Infrastructure monitoring tools can confirm degradation, and application performance monitoring can show response times. But neither explains how orchestrated workflows behaved under pressure: how dependencies interacted, where contention formed or why service-level agreement (SLA) risk accumulated.

As orchestration expands across SAP landscapes, cloud-native services, data pipelines and external APIs, that blind spot becomes harder to ignore. Automation platforms generate telemetry continuously, so the challenge isn’t collecting data, but preserving its context.

Without that context, your teams may find themselves working backwards, which often means piecing together timelines, comparing dashboards and explaining outcomes after the fact. With it, they gain something closer to a panoramic view that makes risk visible earlier and turns automation data into a feedback loop they can actually use.

Redwood Software addresses this directly with Redwood Insights for RunMyJobs, embedding observability into the orchestration layer itself — not bolting it on.

Evolving from system signals to orchestration intelligence

Observability platforms were built around applications and infrastructure. They excel at collecting distributed telemetry and tracking system performance.

Enterprise orchestration introduces a different dimension of complexity:

• Cross-platform workflows with layered dependencies
• SLA-bound business processes such as financial close or order-to-cash
• High-volume batch and event-driven workloads
• Deep SAP integration across ERP and SAP Business Technology Platform (BTP)

When an issue emerges, teams often pivot between different monitoring tools, logs and dashboards to reconstruct the sequence of events. The signals are there, but the intent is missing. Correlation must be manual. Thus, mean time to resolution (MTTR) grows because the orchestration logic — how workflows were designed to behave — lives somewhere else (e.g., in RunMyJobs by Redwood).

Redwood Insights closes that gap by keeping execution data tied to workflow relationships, orchestration intent and historical context. Instead of reviewing isolated metrics, you can see how workflows behaved as connected systems.

What changes first is the quality of investigation. Rather than chasing symptoms across tools, engineers start with the workflow itself. Root causes can surface faster and patterns are easier to spot. Less energy has to be expended for reacting and preventing the same issues from repeating.

Native operational visibility in RunMyJobs

Redwood Insights is available to every RunMyJobs SaaS customer, offering:

• Pre-built dashboards that surface execution trends, runtime variance and failure clustering across environments
• Bottleneck visibility that prevents escalation into SLA breaches 
• Immutable audit visibility and summarized execution history for administrators — without exporting data to external tools
• A high-level dashboard for engineers to move directly into specific workflow executions, eliminating platform switching or manual correlation

The views above create a shared operational baseline. Your automation health becomes easier to understand, explain and improve upon, no matter if your goal is faster triage, cleaner audits or shorter processing windows.

The impact shows up in measurable ways:

• Root causes take less time to uncover
• Mean time to repair drops
• Recurring bottlenecks surface earlier
• System behavior becomes more predictable across distributed environments

Orchestration gets its own observable voice.

Redwood Insights Premium: Extending visibility to enterprise scale

With automation becoming increasingly central to business operations, observability needs to support more than incident response.

Redwood Insights Premium, introduced in RunMyJobs 2026.1, builds on the native foundation with:

• A no-code dashboard designer for customized views
• Easy sharing of custom dashboards across the business
• 15 months of historical data retention

For many organizations, this marks a shift from short-term visibility to longer-term performance management, moving from “what just happened” to “what keeps happening, and why.” 

Custom dashboards and KPI alignment

Different stakeholders require different perspectives. For example, auditors look for records of changes made to automation environments. And Finance leaders care about SLA adherence and process completion risk.

Redwood Insights Premium allows IT to define custom dashboards for tracking KPIs tied directly to orchestrated workflows. Automation performance can then be measured against declared business objectives rather than generic system metrics.

Secure sharing gives process owners and domain leaders self-service access to their own views, while governance remains centralized. This ultimately changes how insights flow through the organization, because IT is no longer the default intermediary. Business teams can have direct visibility into the processes they depend on, too.

Long-term telemetry for planning and governance

Short monitoring windows are useful for resolving today’s incidents, but they don’t help much with planning.

With 15 months of historical data retention, it’s possible to:

• Benchmark year-over-year workload performance
• Identify seasonal execution patterns
• Evaluate the impact of architectural changes
• Support audit and compliance preparation with a continuous execution history

For CIOs and transformation leaders, this longer view supports more grounded ROI conversations. Decisions about scaling orchestration, modernizing SAP landscapes or optimizing cloud consumption can be based on how systems actually behave over time. Observability, therefore, becomes a planning instrument instead of merely a diagnostic tool.

Correlating automation across the broader observability ecosystem

Many enterprises already rely on multiple observability platforms. Infrastructure and application telemetry continue to flow into tools such as Splunk, Dynatrace, New Relic and AppDynamics. RunMyJobs integrates automation telemetry with these platforms, enabling teams to correlate workflow behavior with application and infrastructure performance.

For SAP-centric organizations, the out-of-the-box SAP Cloud ALM connector synchronizes RunMyJobs execution data, including status, start delays and runtime, directly into SAP Job and Automation Monitoring. Automation health becomes visible in the operational interface that SAP teams already use.

Instead of losing orchestration context as data moves between systems, it’s easy to retain a clear picture of how workflow behavior contributes to business risk.

Observability as an architectural decision

Observability is often framed as a DevOps concern. But in distributed enterprises, it’s an architectural one.

As orchestration spans SAP, cloud-native services, hybrid infrastructure and external APIs, leaders need confidence that critical workflows will remain predictable and transparent. Modernization initiatives, from SAP Cloud ERP transformations to multi-cloud adoption, depend on reliable execution.

By embedding observability, RunMyJobs creates a continuous feedback loop:

• Telemetry highlights friction
• Teams optimize workflows
• Reliability improves
• Business outcomes follow

Automation already underpins your most critical processes. With Redwood Insights and Redwood Insights Premium, it becomes fully observable — not only at the system level, but at the orchestration level where business risk actually resides.

Already a Redwood Software customer? Review all the features released in 2026.1.

Ready to democratize your data? Request a demo of RunMyJobs, including Redwood Insights Premium, and see how tailored observability changes how your teams work.

That’s understandable. Revenue growth, AI innovation, cloud agility and customer experience dominate modernization conversations because they’re visible to boards and clients. But inside most financial institutions, the systems coordinating settlement, cutoffs, retries and reporting were designed long before real-time expectations became standard.

We’ve seen this pattern before. During cloud migrations and earlier digital transformation cycles, front-end capability advanced quickly while the operational foundation evolved more cautiously. Payments modernization is now encountering the same imbalance.

In many institutions, particularly large banks and card issuers, the orchestration model was built 25 or 35 years ago for batch windows and predictable cycles. It still works, but layering real-time controls, in-line fraud scoring and API-driven flows onto a clock-driven coordination model introduces complexity that accumulates.

For CIOs, CTOs and enterprise architects, this creates a growing tension. Legacy workload automation and batch orchestration remain deeply embedded in revenue flows, reporting cycles, regulatory controls and settlement processes. Touch them carelessly, and you risk disruption. Ignore them, and modernization efforts stall under their own weight.

The biggest risk in payments modernization today isn’t moving too slowly. It’s assuming the orchestration model you’ve relied on for decades will keep working while everything around it changes.

How modernization unfolds in the industry

Payments modernization rarely arrives as a single, declared program. It unfolds through a series of cautious, tightly scoped decisions, each designed to limit operational and regulatory risk.

• A new payment rail is introduced, requiring ISO 20022 translation, prefunding and intraday liquidity controls
• A real-time fraud check or anti-money laundering (AML) engine is deployed to score transactions in-line in milliseconds rather than overnight
• An API gateway is implemented to expose payment initiation, status and routing to fintech partners or corporate clients

Each change is reviewed carefully, implemented incrementally and monitored closely. Individually, these decisions make sense. Collectively, they change how payments move through the organization. And what often goes unexamined is the execution layer coordinating that work. 

Legacy systems remain in place because they’re stable, familiar and deeply intertwined with settlement, reconciliation, governance and reporting. Modernization rarely centers on replacement. It progresses through selective isolation of functions and the introduction of new capabilities at the edges of the system. The architecture that emerges is layered, as each addition addresses a defined requirement. 

New payment rails change the rules of execution

What’s surfacing now isn’t confusion about how new payment rails work. It’s a growing mismatch between those rails and the execution models many financial institutions still rely on to run them.

Instant payment rails like FedNow and Real-Time Payments (RTP) remove timing buffers that legacy batch coordination quietly depended on. When funds move immediately from the issuing bank to the recipient’s bank, recovery paths narrow and accountability shifts upstream into the orchestration layer itself.

At the same time, payments workflows are becoming more asynchronous and distributed. Tokenization introduces lifecycle events that don’t align neatly with batch windows. Open banking APIs and embedded payments extend payment journeys across third-party providers, payment processors, fintech platforms and institutional counterparties. Cross-border payments introduce dynamic routing, intermediaries and real-time compliance checks across payment networks like SWIFT, SEPA and card rails.

Legacy orchestration models were designed for stability in predictable environments. New payment workloads demand adaptability across hybrid ones.

The “new workload” strategy

A more pragmatic approach is emerging. Instead of forcing legacy workloads into modern patterns, leading teams are deploying modern orchestration only where it’s required:

• New payment rails and faster payments services
• New customer-facing payment options
• New API-driven and data-intensive payment flows

Existing batch workloads — ACH payments, recurring payments, settlement cycles, reporting — continue running where they are. They’re stable, governed and understood. They don’t need reinvention to support innovation elsewhere. Modernization expands outward from new payment capabilities, rather than backward into stable legacy flows.

What qualifies as a “new payment workload”?

Not every payment flow is created equal. Across banks, card networks and payment platforms, the workloads that demand modern orchestration share one trait: they can’t wait.

Examples include:

• Real-time payments and instant settlement
• Token lifecycle management
• API-driven payment initiation and partner ecosystem orchestration
• In-line fraud and risk decisioning tied to live transaction events
• Cross-border payments with dynamic routing and compliance logic

These flows run on live signals, not schedules. Recovery has to be automatic and context-aware, because there’s no safe pause button in the middle of a real-time payment.

The foundation for disciplined modernization

Modernizing forward only works if your orchestration layer evolves alongside those new workloads. Payment rails, fraud engines and APIs introduce speed and distribution, and orchestration determines whether you can safely gain speed without losing control. If your logic remains tied to clock-driven execution, your new capabilities will just inherit old constraints. Deliberate, modern orchestration helps them operate in real time without destabilizing your existing systems.

Why this reduces risk instead of increasing it

The instinctive fear is understandable: introducing new orchestration alongside legacy systems feels like adding complexity. In practice, it does the opposite.

Running modern orchestration in parallel:

• Avoids disruption to revenue-generating payment systems
• Eliminates forced migration of fragile legacy logic
• Creates a clear separation between systems of record and systems of innovation

Instead of turning every change into a platform-wide event, you contain the impact to the new flow. A FedNow exception doesn’t have to spill into ACH payments, and a routing issue doesn’t necessitate a war room just to understand what broke.

Just as importantly, this containment model prevents modernization costs from compounding, so there are fewer emergency fixes, one-off integrations and expensive upgrade projects designed solely to keep the lights on. 

Hybrid orchestration isn’t a compromise

Payments modernization will remain hybrid for the foreseeable future. Cloud-native payment platforms, SaaS services, on-premises systems and external payment networks will continue to coexist.

Chasing a perfectly unified architecture is a distraction; what matters is whether the work moves cleanly across boundaries — cloud to on-premises, internal systems to payment processors, batch to event-driven paths — without creating new failure points.

Modern orchestration becomes the connective tissue across cloud, SaaS and on-premises environments, aligning payment instruction flows, routing decisions and downstream processing without forcing everything into a single model. This is how organizations escape orchestration technical debt without risking operational stability.

Over time, this approach changes the economics of modernization by shrinking upgrade cycles, lowering operational overhead and freeing capacity for new initiatives instead of constant maintenance.

A quieter form of transformation and why it works

The most effective payments modernization programs rarely announce themselves loudly. They don’t arrive as sweeping transformation initiatives or architectural resets. Instead, they introduce new capabilities deliberately, with clear operational boundaries and a strong bias toward stability.

This approach aligns with how regulated financial institutions actually manage risk. Change is evaluated in context, scoped tightly and introduced where it delivers clear value without increasing operational exposure. 

“Boring” is often the point. It means exceptions are handled predictably, and investigations start with answers instead of guesswork. Teams can explain what happened in a payment flow without reconstructing the story after the fact. It also means audits and regulatory reviews are routine rather than disruptive, because the execution trail is clear and defensible from the start.

Change the cost curve of modernization

When new payment capabilities are introduced without reworking what already runs, modernization stops drawing from the same operational budget year after year. In that environment, digital transformation becomes more cost-effective by design. Your teams can spend less time maintaining orchestration debt and more time delivering new value.

Explore how modern orchestration supports new payment workloads without disrupting legacy operations or allowing excess costs to accumulate.

It’s the infrastructure everyone depends on, but almost no one revisits, because it hasn’t failed loudly enough.

Banks have spent years modernizing what customers can see: digital experiences, mobile apps, real-time payment rails, cloud-native cores. Those investments were necessary. In many cases, they were overdue. And on paper, they delivered exactly what executives asked for.

So, why does it still feel harder than it should be to move money safely, quickly and predictably?

When “good enough” stops being defensible

Most enterprise architects and IT operations leaders know this feeling well. The environment works. Payments clear, and fraud is caught. Reconciliation eventually balances. When something breaks, teams step in, fix it and move on. The system absorbs stress, and people compensate. And because the compensation works, the underlying issue stays invisible.

But “good enough” becomes much harder to defend when three pressures converge at once:

1. Payments volumes accelerate
2. Time-to-decision collapses
3. Accountability increases

That convergence is happening now, and it’s visible to regulators and customers.

Real-time rails like FedNow and real-time payments (RTP) aren’t just faster versions of existing processes. They eliminate the buffer zones — overnight windows, batch retries, manual intervention points — that legacy schedulers took advantage of for decades. At the same time, regulatory scrutiny and customer expectations have converged around one assumption: you know exactly where a payment is, why it failed and what you’re doing about it.

That assumption exposes a structural weakness many banks and financial institutions have learned to work around — but not fix.

The invisible complexity behind every transaction

A modern payment doesn’t move through a straight line. It fans out across fraud detection, compliance checks, routing decisions, settlement systems, reconciliation workflows, notification services and reporting pipelines. Many of those components have been modernized individually. Few have been modernized together.

Orchestration fills the gap.

Many teams still rely on a combination of legacy schedulers, custom scripts and tribal knowledge. It’s not elegant, but it’s familiar. And familiarity is powerful, especially when budgets are tight and priorities are visible elsewhere.

The problem is that technical debt compounds fast, and it’s sticky.

Outages that weren’t supposed to matter

In May 2025, a major outage at Fiserv disrupted payment services across multiple United States banks and credit unions. Zelle transfers stalled, and online banking features and ACH processing were affected. For customers, the experience was confusing. And for banks, it was clarifying. It was a failure of coordination, not innovation.

Similar stories have played out across industries. 

• Airlines grounded by systems that couldn’t reconcile real-time data flows: Hundreds of flights were canceled in 2022 when key IT systems went offline, revealing how critical poorly coordinated back-end layers can be.
• Cloud providers experiencing cascading outages because dependency logic behaved differently under load: A major AWS outage in 2025 rippled across global services when internal automation triggers weren’t sufficiently orchestrated, showing how even modern platforms can fail without resilient control layers. 

In each case, the visible platform was modern, but the control layer beneath it was not. These incidents are foreshocks, signaling the risk of a greater problem in the near future. They indicate architectural lag — that the desire for execution speed outpaced application and data orchestration maturity.

The operational resilience question no one wants to ask

Over the past several years, operational resilience has stopped being something IT teams manage behind the scenes and started becoming something boards are directly accountable for. Regulators now expect banks to demonstrate not just recovery plans but clear tolerance for disruption, while customers and markets punish even short-lived outages with lost trust. As a result, resilience is now a governance issue.

Here’s the uncomfortable question many organizations avoid: If a critical payment flow failed right now, could you trace its path end to end quickly enough to meet your obligations without assembling a war room?

Not in theory. Not eventually. But immediately, in real time.

Could you see which system made the last decision, which dependency stalled and which downstream processes were affected? Or would your teams jump between dashboards, logs and scripts to reconstruct the story after the fact?

If the answer feels uncertain, don’t blame capability. The failure is architectural. Operational resilience is proven in the moment of impact: when systems strain, dependencies collide and decisions must be made immediately. It depends on understanding how work actually flows and how systems behave together under stress, so breaks can be proactively identified and addressed in real time, not explained after the fact.

Why this matters now

For years, banks could afford to defer this problem. Latency masked fragility, and lots of manual effort absorbed uncertainty. Institutional knowledge filled the gaps, but that tolerance is disappearing.

Real-time payments have reduced recovery windows to seconds. AI-driven fraud models are introducing asynchronous decision points. And each new payment method and provider increases the number of routing paths. Customers, retail and corporate alike expect transparency when something goes wrong. In that environment, orchestration is a strategic capability rather than background plumbing.

Orchestration as the control plane

Being successful at modern payments orchestration means establishing a control plane that understands how payment flows behave across systems.

That includes:

• Event-driven execution instead of clock-based scheduling
• Dependency awareness that prevents cascade failures
• End-to-end visibility across payment journeys
• Governance and auditability built into execution, not layered on afterward

When orchestration evolves, your ecosystem behaves differently. Failures isolate instead of spread, and recovery is not some heroic moment. You regain your margins quicker than you would’ve thought possible in the worst-of-the-worst scenarios.

Modernizing your orchestration approach is also going to prepare your organization for executing on the AI use cases you’ll need to keep up in tomorrow’s financial services world. Learn how.

The risk (and opportunity) of waiting

The greatest risk in payments modernization today isn’t choosing the wrong platform. It’s assuming the operational foundation will keep holding. Most organizations don’t modernize orchestration because something breaks. They do it because the cost of not knowing what’s happening in their payment flows —and not being able to change them quickly — eventually exceeds the cost of change itself. When competitors can launch new payment experiences in weeks and you’re stuck doing it in quarters, the limitation isn’t strategy but orchestration.

Payments modernization is already a recognized growth lever. What’s often missed is where that growth actually comes from. It doesn’t come from new payment types alone, but from the ability to operationalize, deploy and scale them into production quickly and reliably. That capability lives in the underlying application and data pipeline orchestration. When plumbing is rigid, modernization becomes cosmetic rather than transformational.

This is why payments modernization succeeds or fails long before a new rail or service goes live. Real-time processing and richer payment data enable request-to-pay, embedded finance, merchant insights and cross-border optimization. None of these are possible without orchestration that can adapt payment flows quickly, route intelligently across providers and expose consistent data across the ecosystem. Modernization creates growth only when the plumbing underneath is built to move.

The banks that act now won’t be the ones chasing outages but the ones making payments boring again. And in financial services, boring is often the highest compliment. Find out more about how to modernize your payments processes.

Few organizations achieve that kind of orchestration consistently, because their automation is fragmented. One team might manage batch jobs, and another might script data pipelines. A third could rely on manual interventions and shared inboxes to keep business processes moving.

The value of a Service Orchestration and Automation Platform (SOAP) lies in its ability to unify these silos and support the workflows that actually run the business. In its 2025 Critical Capabilities for SOAPs report, Gartner® outlines five Use Cases that demonstrate this value in action. Here’s how, in my interpretation, those capabilities show up in real operations across industries.

IT workload automation: Still essential

No matter how much technology evolves, the reliance on routine workloads never really goes away. Nightly ERP updates, hourly job chains and critical data movements between systems are fundamental processes that keep your business running.

But those workloads aren’t confined to a single mainframe or on-premises scheduler anymore. They span hybrid environments, connect to cloud-based APIs and carry tighter service-level agreement (SLA) expectations than ever before. The hard part isn’t the workload itself but the web of dependencies and recovery paths that stretch across different systems.

A robust SOAP solution lets you orchestrate all these elements in one place: SAP jobs, custom scripts, data movements and file transfers, for instance. You gain centralized control with distributed execution — the perfect balance for hybrid IT environments. I feel Gartner points to this as a foundational Use Case because it tests how well a platform performs under enterprise pressure — securely, reliably and with minimal manual intervention.

What this unlocks: With dependable workload automation, your IT teams can start each day with confidence that core batch processes ran cleanly and dependencies resolved in the right order. Not to mention, any failures were isolated and didn’t cause unwanted ripple effects. Your operational tone can shift from checking for surprises to reviewing a clean audit trail and planning ahead.

Workflow orchestration: Running the business, not just jobs

Behind every business outcome is a complex chain of tasks, approvals and exceptions that span multiple systems and departments. Take the month-end financial close: it happens thanks to finance systems, spreadsheets, validations and cross-departmental collaboration. Or consider onboarding a new hire. Beyond provisioning accounts, it requires scheduling training, initiating background checks and activating access across multiple systems.

With a SOAP platform, these workflows can be orchestrated end to end. Instead of managing each step separately, you create a unified process that flows across boundaries. You get steadier execution and cleaner handoffs, which cuts down on the small errors that tend to compound over time.

It seems Gartner emphasizes this Use Case as a marker of maturity: it’s not about more automation, but using the right automation to move the business forward. By linking actions into cohesive workflows with decision points and exception handling, you transform fragmented activities into streamlined business processes.

What this unlocks: If your workflows run end to end, you’ll feel the difference immediately. Approvals and handoffs will happen without manual nudges, and any exceptions will surface early. The work is to oversee processes instead of managing dozens of micro tasks.

Data orchestration: Automating movement and storage

Analytics live or die on the reliability of the pipeline behind the dashboard. At 3 AM, your retail data might need to move from SAP to Snowflake, be validated, then trigger an update to executive dashboards before the morning meeting. That kind of flow can’t rely on spreadsheets, email notifications or ad hoc scripts — it requires systematic orchestration.

SOAPs plug into managed file transfer (MFT) solutions, ETL tools and data lakes to manage the full lifecycle of data movement: ingestion, transformation, validation and delivery. You can build flows that validate data quality, handle exceptions and ensure downstream systems receive accurate, timely information.

I believe Gartner calls out data orchestration because the stakes are high. Poor data hygiene slows decisions, introduces risk and devalues analytics investments. With proper orchestration, your data pipeline becomes a strategic asset rather than a constant challenge.

What this unlocks: Reliable data flows remove the daily uncertainty that slows decision-making. Your analysts don’t have to wonder whether today’s numbers are safe to use. And by the time business users open a dashboard, the underlying pipeline has already done the hard work.

DevOps: Coordinating pipelines across teams

It’s relatively easy to automate a deployment, but it’s much harder to orchestrate everything that comes before and after. When your infrastructure team needs to provision environments, QA needs to run tests and compliance needs to log every step, a simple webhook or CI/CD pipeline isn’t sufficient.

SOAPs can coordinate across your entire development lifecycle, trigger event-based actions and integrate with ITSM and monitoring tools. This coordination is especially valuable when different teams use different tools but need to work together seamlessly.

In my view, Gartner includes this as a distinct Use Case because orchestration here is a force multiplier: it aligns developers, operations and compliance without slowing velocity. By automating handoffs between teams and tools, you reduce waiting time, eliminate manual coordination and maintain an audit trail of all activities.

What this unlocks: Orchestration that supports the DevOps lifecycle ensures your release cadence reflects your engineering velocity. Your dev team doesn’t have to worry whether upstream tasks are complete, and your operations team gets predictable workflows they can trust.

Citizen automation: Putting control in the right hands

Not every routine workflow warrants an IT ticket. An HR manager initiating onboarding or a supply chain planner adjusting inventory levels need their workflows to be accessible without sacrificing governance. As your organization scales, the ability to distribute automation capabilities becomes crucial.

SOAPs support low-code interaction, reusable templates and full audit trails. Users get what they need when they need it, and IT maintains oversight of the entire automation ecosystem. Gartner likely highlights this Use Case because it balances empowerment and control: you reduce shadow IT while still enabling business agility.

What this unlocks: Governed self-service changes how work gets done. You can move faster without losing control because every action runs through the same orchestrated backbone with full visibility.

Your SOAP unifies it all

Every Use Case in the Gartner report points back to a simple truth: orchestration is how you scale automation without multiplying complexity. The best SOAP platforms make that orchestration real across jobs, data, workflows and teams, providing the connective tissue that binds your digital ecosystem together.

As you evaluate your options, look for platforms that support all five Use Cases with equal strength. Your business doesn’t operate in silos, and your orchestration platform shouldn’t either. The right solution will grow with your needs, adapt to new technologies and continuously deliver value as your organization evolves.

RunMyJobs by Redwood offers comprehensive, enterprise-wide orchestration, with deep integration into SAP environments and support for hybrid cloud architectures. Download the full Critical Capabilities report to see an extended analysis of the Gartner Magic Quadrant™ and learn why Redwood was recognized as a SOAP Leader two years in a row.

This year, we have proudly welcomed over 100 new customers to Redwood. Our partnerships span the globe, as we collectively now serve over 7,600 customers in more than 150 countries. This growth highlights how organizations are embracing true end-to-end automation, and we believe the success our customers have achieved has played a significant part in this growth. 

We’re inspired by the commitment our customers show in helping others realize the power of full stack automation. Filled with numerous speaking engagements, webinars and insightful conversations that made our shared vision a worldwide reality, this year has been exceptional.

Let’s take a look back at some of the most memorable moments of 2025.

Center stage: Event speakers

Sharing your success stories at major industry events provides invaluable, authentic insight. The customer sessions this year detailing the real-world business impact achieved with Redwood were truly inspiring.

Eugene Water & Electric Board

At the SAP for Utilities event in Denver, Leif Utterstrom and Prita Mani from Eugene Water & Electric Board (EWEB) detailed how RunMyJobs is enabling autonomous execution of complex processes like meter-to-cash while strengthening their core operations. They explained how they transformed resource-intensive work into faster execution and better business outcomes. 

RS Group

Dharmesh Patel spoke at SAP Sapphire Madrid about how RS Group now manages over one million global customers using RunMyJobs by Redwood for supply chain optimization on SAP via Amazon Web Services (AWS). The company runs approximately 150,000 executions per day to cater to its key SAP business processes.

Schneider Electric

Schneider Electric showed us how to reshape the financial close and what an 80% reduction in manual effort looks like. Stefano Oliveri hosted a workshop at Shared Services and Outsourcing Week (SSOW) Europe, where he shared how the company moved from fragmented record-to-report (R2R) processes to integrated automation strategies. With Finance Automation by Redwood at the center, they saw 86% faster close tasks and increased compliance without increasing workload.

On the air: Winning webinars

Redwood customers brought their expertise straight to the community this year through enlightening webinars and user group sessions. The major takeaway for 2025? It’s all about cost reduction and shifting focus from manual tasks to high-value strategy.

Sabari Swaminathan of Energy Transfer detailed how Finance Automation saved their accountants 45,000 hours annually, freeing them up for strategic analysis instead of time-consuming data entry. Watch the on-demand webinar here. 

In a similar vein, Mary Shiena Johnson from Siemens Global Business Services showed exactly how Finance Automation cuts labor costs and accelerates the R2R close, proving the tangible financial impact for Siemens.

Our user groups were filled with practical insights from the true experts — the people using Redwood products every day. We saw great contributions from Srikanth Nellutla (CONA Services), Srinivas Udata (Corebridge Financial) and Sumit Sinha (HHS Technology Group) at the RunMyJobs and JSCAPE by Redwood sessions, helping the community learn best practices and accelerate their own automation journeys. 

Don’t miss out on this collective wisdom — learn more about joining a user group. 

A special thanks to our most engaged advocates

While every advocate’s effort makes a difference, we want to give a special nod to those who participated in an exceptional number of activities this year.

🏆Top advocates of 2025

• Charles Sheefel from International Paper: Charles was deeply engaged this year, participating in multiple Customer Advisory Board meetings, speaking at our global kick-off and offering his insight in numerous conversations with customers and industry experts alike. Thank you!
• Daniel Sivar from American Water: Daniel engaged in Customer Advisory Board meetings, spoke on the panel at our global kick-off, recorded a video testimonial and even took last-minute reference calls. We can’t thank you enough for the time and effort you’ve put in, thank you!
• Darrin Ward from Energizer: Darrin has graciously lent his time and expertise for multiple reference calls and industry analyst conversations, plus internal feedback meetings that will help shape the future of Redwood. Thank you!

We are so grateful to all of our advocates for sharing their expertise and automation journeys this year. A heartfelt thank-you to all!

Join the movement in 2026

Your incredible efforts directly help other organizations see how Redwood’s automation fabric solutions can empower them to orchestrate, manage and monitor their mission-critical workflows.

We’re already planning for 2026, and we want you to be a part of it. Whether it’s in the form of a brief reference call, a quick case study interview or speaking on stage, every contribution makes a difference.

Interested in sharing your Redwood success in 2026? Visit the Customer Advocacy Program page to learn more.

As soon as teams began trying to extend AI beyond isolated tasks — past the browser tab, outside the development environment or into workflows that cross departments — progress stalled. The models were perfectly capable, but in most cases, the enterprise wasn’t ready to support them.

AI today largely operates in silos:

• Summarizing a document in one tool
• Generating a draft in another
• Answering a question inside a chat window

Those applications are useful, yes. But transformational? No. And certainly not autonomous.

The next phase of AI will operate very differently. Agentic AI promises to reason, plan and participate in the work, not just advise on it. For any AI system to influence real business processes, the organization must first create the environment to support it.

It’s critical to build a foundation for the next decade of AI to operate with clarity, coordination and control.

Why leaders often think they’re ready

When AI experiments stall, the reflex is to look at the model.

• Should the prompt be rewritten?
• Should the model be retrained? 
• Should the team switch providers?

In fact, most AI slowdowns have nothing to do with model quality. They’re caused by the operational surface the model enters. Across enterprises, the same foundational gaps appear again and again, regardless of industry or scale.

1. Work happens in silos. AI has no shared control layer. Automations, scripts, SaaS workflows and departmental tools all run independently. This fragmentation increases the likelihood of “shadow AI” — and the blind spots in security and cost that come with it.
2. Every department uses different guardrails. Access, approvals and policies vary wildly across teams. AI simply can’t follow rules that don’t exist consistently.
3. Workflows assume predictability, but reality doesn’t. Static, rule-based logic breaks the moment conditions change. AI becomes another exception handler instead of a force multiplier.
4. Leaders lack cross-system visibility. Throughput, failures, bottlenecks and downstream impacts are scattered across tools. You can’t operationalize intelligence you can’t see.

These gaps don’t make agentic AI unrealistic, but they reveal what’s missing. To safely give AI the ability to plan and act, enterprises need coordination, governance, adaptability and visibility working together under a unified orchestration approach.

Before autonomy: The architectural fundamentals

Across enterprises making real progress toward AI readiness, one theme is clear: they’ve perfected the architecture underneath the model. These organizations are doing more than just experimenting with clever tools. They’re building the conditions for intelligent systems to operate safely and consistently.

Unification: One orchestration layer to coordinate the work

Imagine an AI system evaluating a delivery delay. It checks order data in one application, inventory in another, customer records in a third and workflow timing in a fourth. Without orchestration, those steps become disconnected guesses. With it, they become a single, synchronized, visible and aligned action path governed by business rules.

A unified layer provides the control plane that keeps all forms of work — human, automated or AI-assisted — moving in the same direction.

Boundaries: Guardrails for scaling intelligence — not risk

Guardrails vary in format, but they all answer the same question: What is safe for this system to do? Instead of a long list, the most effective enterprises keep it simple with:

• Actions that are always permitted
• Actions that require verification or approval
• Actions that are never allowed

When these rules are applied consistently across departments, intelligent behavior becomes predictable. AI stops guessing how decisions should work and starts following the same standards everyone else does.

Transparency: Governance that keeps humans in control

As soon as automation can influence workflows, visibility becomes non-negotiable. Leaders need to see how a decision unfolded, what it touched and why it behaved the way it did. That requires:

• Observability into processes
• Clear documentation of decision paths
• Audit trails that withstand scrutiny
• The ability to unwind or adjust actions when needed

Governance turns autonomy into something accountable, rather than opaque.

Coexistence: A blended environment of deterministic and dynamic automation

Enterprise leaders sometimes assume they must choose between traditional automation and AI-driven adaptability, but the highest performers do the opposite. They preserve their deterministic backbone: the scheduled workflows, validations and rule-based logic that keep operations steady. Then, they layer adaptability where variability actually occurs.

In other words, it’s reinforcement, not replacement. Rule-based processes handle what is predictable, adaptive decision loops handle what isn’t and orchestration brings the two together.

How experimentation becomes an operating model

AI experimentation is happening everywhere at once. Marketing might test a summarization tool, Finance could be exploring anomaly detection and Operations may pilot an automation assistant. The activity is high, but the impact is uneven. Some pilots work, others stall and many echo work already happening elsewhere in the organization.

What’s missing is structure. Modern AI only becomes meaningful when it’s connected, governed and repeatable. That requires shifting from scattered experimentation to an operating model that gives every team the same foundation to build upon.

Read more about building the best foundation for agentic orchestration.

A platform-first evolution in automation

The transformation underway resembles the moment when analytics matured from isolated dashboards into full data platforms. AI is undergoing a similar transition. What begins as a collection of tools eventually becomes an operational discipline shaped by shared infrastructure, shared controls and shared context.

In practice, this means we have to start thinking differently about how AI gets introduced and supported. Investment decisions move away from individual tools and toward foundational capabilities that every team can rely on, like interoperability and visibility. Talent evolves as well, with roles focused on designing supervised automation, not just building models in isolation.

Metrics also expand. Instead of measuring AI success through cost savings alone, executives are beginning to track the health of end-to-end processes: throughput, order delivery rate, consistency, service quality and customer satisfaction, for example. These are the signals that show whether the enterprise is truly becoming more adaptive.

Risk posture changes, too. Rather than waiting for AI to cause a problem, leaders establish guardrails and safety patterns before AI touches a core workflow. True autonomy starts with boundaries.

This evolution marks a larger shift: the move from experimenting with AI to preparing the enterprise for it. When you treat orchestration and governance as shared capabilities instead of departmental add-ons, innovation becomes faster, safer and easier to scale. AI moves from being something scattered teams try out to something the entire organization can trust.

What agentic orchestration will unlock (when the foundation is ready)

Agentic AI at scale remains a future capability, but the directional value is already clear. Once you have orchestration, governance and interoperability in place, you can unlock an entirely new class of capabilities:

• Systems that adapt faster than conditions can destabilize them
• Cross-system decision-making that reflects real business context
• Self-service interactions where users request outcomes, not workflows
• Operations that continue running even when inputs, timing and exceptions change
• Insight that spans applications, dependencies and data in motion

Your teams can gain a level of clarity, context and control that may be elusive today.

The advantage will go to those preparing now

Organizations making progress toward autonomous operations share a common pattern. They’re not racing toward agentic AI, but building the scaffolding that will support it.

That means they’re:

• Consolidating automation under a unified orchestration layer
• Strengthening governance to define how decisions and actions occur
• Insisting on interoperability across systems and tools
• Using AI assistance to improve deterministic workflows
• Piloting new AI patterns in controlled, low-risk environments
• Defining KPIs that reflect throughput, delivery, consistency and service quality

Preparation accelerates innovation, creating an environment where AI can be introduced safely, evaluated clearly and scaled confidently. Enterprises that begin now won’t just be ready for agentic AI. They’ll be structurally positioned to benefit from whatever comes next.

To explore the now, next and beyond of AI, read “The autonomous enterprise” and get a deeper look at how orchestration, governance and preparation shape the path to more intelligent operations.

It’s a fair question. And the answer isn’t just focused on why you should add another automation tool. Instead, considering a Service Orchestration and Automation Platform (SOAP) means you’re ready to think about the operational model behind how work moves across your organization.

A scheduler triggers tasks, an iPaaS connects applications, but a modern SOAP coordinates end-to-end business processes across systems, teams and environments in a way that maintains reliability at enterprise scale. That difference shows up directly in operational resilience, business agility and cost control.

The 2025 Gartner® Critical Capabilities for SOAP report is the clearest framework I’ve seen for tying platform strengths to financial outcomes. Here’s how I help leaders like you use that framework to build a credible business case.

The framework: Mapping Use Cases to your P&L

The Critical Capabilities report doesn’t start with architecture diagrams or methodology. It starts with how platforms perform against five operational Use Cases, each representing a measurable part of your business. I find these especially useful because they line up almost perfectly with the major categories of cost, risk and productivity that executives care about:

• Operational resilience
• Business agility
• Cost optimization
• Risk management
• Speed to insight

Instead of thinking of them as technical buckets, think of them as the five pillars that determine whether your automation investments actually return value. A SOAP that scores well across all five transforms automation from a technical initiative into an engine for enterprise performance.

Pillar 1: IT workload automation and the ROI of unbreakable operations

The business challenge:
A pervasive pattern I see is IT teams stuck in a reactive mode. Excessive time is spent on firefighting and manual monitoring, which draws focus away from strategic process improvement. This reactive posture results in costly consequences, including missed service-level agreements (SLAs), silent failures in critical overnight processes and a constant backlog of expensive incidents.

What this Use Case measures:

Gartner considers this the foundation of SOAPs: Can the platform run critical workloads reliably across hybrid and multi-cloud environments? Think financial close, inventory syncs, regulatory reporting — with real-time awareness and automated recovery. This means it must offer dependency management that understands system context, recovery paths that prevent cascading failures and observability that lets operators diagnose and resolve issues quickly.

Where the ROI shows up:

• Reduced downtime costs: Preventing failures before they hit the business
• Lower operational overhead: Fewer hours spent monitoring or intervening
• Strategic consolidation: Eliminating multiple schedulers, licenses and skillsets

This is the first place most organizations find real cost savings, because reliability is expensive when you’re compensating for it manually.

Pillar 2: IT workflow orchestration and the value of cross-team agility

The business challenge:
Most delays don’t come from individual tasks. They come from the handoffs: the approvals that get stuck in someone’s inbox, the data that wasn’t validated, the system that didn’t trigger the next step. Teams often automate inside their own domains but leave the gaps between them unmanaged.

What this Use Case measures:
Gartner looks at how well a SOAP can coordinate entire processes, not just tasks:

• Cross-application workflows (ERP + ITSM + SaaS + custom apps)
• Conditional logic and exception handling
• Orchestration spanning on-premises and cloud environments

Where organizations see ROI:

• Shorter cycle times: End-to-end processes move without waiting on human intervention
• Higher throughput: Fewer restarts, errors or duplicate work
• Greater adaptability: Workflows that adjust as business requirements change

The payoff is simple: people get hours back. Not to mention, change doesn’t feel risky anymore.

Pillar 3: Data orchestration and the payoff of faster, smarter decisions

The business challenge:
Analytics teams can only move as fast as the data feeding them. Many organizations are still juggling multiple disjointed ETL solutions, insecure file transfers or inconsistent handoffs between systems. The result is predictable: delays, inconsistent data and missed windows for decision-making.

What this Use Case measures:

Gartner evaluates a SOAP’s ability to orchestrate reliable, governed data pipelines:

• Event-driven movement from systems like SAP to data warehouses like Snowflake
• Managed file transfers with dependency tracking
• Data validation, reconciliation and exception handling
• Automated triggers to BI, AI or other downstream applications

Where organizations see ROI:

• Faster time-to-insight: Data arrives validated and on time
• Improved compliance: Centralized audit trails remove the risks of custom scripts with no single source of truth
• Eliminated bottlenecks: Analytics teams spend less time waiting and more time analyzing

This is where organizations often unlock value they didn’t realize they were losing.

Pillar 4: Citizen automation and the advantage of empowered teams

The business challenge:
IT teams become bottlenecks when every routine request — from report generation to onboarding steps — has to be manually actioned. The backlog grows and the business slows.

Yet handing automation directly to business users without governance isn’t an option.

What this Use Case measures:
Gartner evaluates this capability by looking at how well a platform can distribute automation safely without losing control. It’s essentially a test of whether your Operations team can create guardrails that let business users trigger approved workflows on demand without introducing risk. A strong score here reflects a platform that supports low-code execution, reusable templates and full auditability, so non-technical users can initiate routine actions while IT retains oversight. This Use Case ultimately measures how effectively a SOAP can push automation closer to the edge of the business without allowing fragmentation or shadow IT to creep back in.

Where organizations see ROI:

• Faster turnaround: Teams get what they need without waiting days or weeks
• Reduced IT ticket volume: Freeing technical staff to focus on higher-value work
• Fewer errors: Standardized workflows eliminate risky and error-prone manual steps

When done right, citizen automation is not “shadow IT.” It’s a controlled extension of enterprise automation.

Pillar 5: DevOps automation and the competitive edge of continuous delivery

The business challenge:
Software teams often automate their CI/CD pipelines but leave the surrounding processes — environment provisioning, test data setup, dependency coordination — untouched. Those manual steps are what slow releases and introduce inconsistencies.

What this Use Case measures:
For DevOps automation, Gartner focuses on how deeply the platform can integrate into modern delivery pipelines and how reliably it can coordinate the steps surrounding deployment. It’s about assessing whether automation can move at the same pace as engineering, from provisioning and testing to promotion and release. High-performing platforms demonstrate support for automation-as-code practices, event-based triggers and consistent orchestration across environments. Use these parameters to gauge a provider’s ability to remove bottlenecks from the software lifecycle so teams can deliver changes quickly without compromising reliability or governance.

Where organizations see ROI:

• Shorter release cycles: Faster, safer path from commit to production
• Higher developer productivity: Fewer manual tasks around the deployment lifecycle
• More reliable deployments: Consistency enforced across environments

This is increasingly a strategic differentiator for teams moving toward cloud-native delivery models.

An undeniable case for a strategic investment

A scheduler reduces manual effort, whereas a SOAP reduces friction across your entire operating model. When a single platform delivers across all five Gartner Use Cases, you’re not just buying automation capabilities — you’re buying:

• Fewer outages
• Faster decisions
• Higher team velocity
• Lower integration costs
• Stronger risk posture
• A future-proof automation foundation

This is the business case every CFO wants: clear outcomes tied to operational, financial and strategic value. The next time you evaluate platforms, don’t ask, “What does it automate?” Ask, “Where does it impact my P&L?”

That’s the difference between a tool and a transformation partner.

Evaluate SOAP vendors with our scorecard, and download the full Gartner Critical Capabilities report to compare how leading platforms perform against these five essential Use Cases.

As teams shift toward hybrid and cloud technologies, workload automation (WLA) needs to evolve, too. Not because your current solution is broken, but because cloud-first tools are better equipped to support growth, change and resilience. The right strategy allows you to extend what you have on-premises while taking advantage of cloud-based solutions where they make sense.

Cloud-first doesn’t mean cloud-only

Some processes still belong on-prem, and many organizations will remain hybrid or multi-cloud for the long haul. That’s normal. Automation has to meet your business where it is, not force a complete replatforming.

Cloud-first means choosing SaaS-native automation tools when expanding capabilities or modernizing parts of your environment. It gives your teams the flexibility to automate across ERP, data platforms, DevOps and more, so you can integrate quickly and reduce manual maintenance.

The goal isn’t to rip and replace. It’s to simplify what’s complex and make your WLA platform future-ready.

Why workload automation works better in the cloud

Legacy systems were built for a different era. They do the job, but they require tuning, patching and on-prem support that doesn’t scale easily. As automation becomes more central to digital operations, these limits start to matter.

Cloud-first WLA removes the infrastructure burden and adapts to shifting demand without manual overhead.

Automation goals haven’t changed — the delivery model has

The reason to automate hasn’t changed: reduce errors, speed up processes and free up people for higher-value work. What’s changed is how quickly your automation platform needs to adapt to business needs.

A cloud-first approach helps you respond to business demands without waiting on infrastructure. New processes can be built and deployed faster. New systems can be connected in less time. And your teams can focus on building value, not maintaining tools.

You don’t lose control. You gain capacity.

It also reduces technical debt. Instead of holding on to legacy schedulers that require custom scripts and tribal knowledge, you get a system that evolves with you. One that enables better governance, compliance and transparency across IT and business operations.

Respecting the value of existing systems

If you’re already using a WLA solution on-prem, you’ve laid a strong foundation. You know the value of automation, the importance of visibility and the impact of reliable scheduling.

But if you’re finding it harder to scale, integrate or support new initiatives, it may be time to extend your automation with a cloud-first option. That means giving your team a platform that’s built for what’s next.

Many teams continue to use their on-prem automation alongside cloud-first orchestration. It’s not all or nothing. The benefit is having the freedom to move at your own pace, modernizing high-impact workflows first and expanding as needed.

RunMyJobs by Redwood: Cloud-native automation that grows with you

RunMyJobs is Redwood Software’s SaaS-native WLA platform. It’s built for hybrid and cloud environments from the start and used by enterprises worldwide to orchestrate complex workflows across SAP, DevOps, data platforms, finance and more.

What makes it different:

• True cloud-native: No agents, no patching, no servers to manage
• Built-in support for SAP: S/4HANA, RISE with SAP and more
• Integration-ready: Prebuilt connectors for cloud services, ERP, file transfer, containers and CI/CD pipelines
• Always-on performance: High availability with 24/7 global support
• Transparent pricing: Value-based licensing that scales with your automation maturity

RunMyJobs is ideal for teams that want to reduce manual scheduling, eliminate job failures and improve SLA performance. It brings together business-critical workloads in one view, so you can monitor, control and scale without complexity.

Many Redwood customers use RunMyJobs alongside their existing automation tools to orchestrate end-to-end processes. It allows them to modernize at their own pace, starting with the processes that benefit most from agility, visibility and scale.

Thinking about your next move?

If automation is a critical part of your business, your platform shouldn’t be a limiting factor. Cloud-first WLA gives you a way to move faster without taking on more infrastructure, risk or overhead. Use it to extend your automation strategy — not upend it. 

Read more about Redwood’s unique approach to WLA migration and how our teams prepare you for a smooth transition from legacy to cloud.

If your IT automation is running well but you’re finding it harder to scale or innovate, it may be the right moment to consider a jump in WLA technology. And modernization doesn’t have to mean all cloud, all at once; many teams keep key processes on-premises while adopting cloud-based orchestration where it adds value.

Here are nine signs that your organization is ready for a change and how doing so will prepare you for scalability and long-term resilience.

✅ Your team is ready to move beyond daily upkeep

On-premises WLA solutions can fall multiple versions behind because upgrades compete with other IT priorities. Adding hardware to expand capacity feels clunky, and even routine maintenance can put critical workflows at risk. When your IT team is spending more energy on patching and firefighting than planning new initiatives, it’s often a signal you’ve outgrown the old model. Upgrading to a SaaS-based platform is less about replacing what you have and more about celebrating that your automation maturity has reached a point where you’re ready for the next level. 

✅ Manual fixes are crowding out higher-value work

If your operators are babysitting workflows or writing scripts just to keep processes running, you’re not realizing the full ROI of automation. Time is money, and when you spend hours on workarounds instead of optimizing processes, your total cost of ownership (TCO) rises and strategic value shrinks. 

Modern WLA software reduces that manual intervention with event-based triggers, self-service options and automated recovery. Freeing your people from constant fixes means more time spent improving processes and less time chasing failures.

✅ Automation needs to follow workloads into the cloud

Most enterprises are already moving workloads to the cloud, whether it’s data analytics, ERP modules or customer-facing apps. If your WLA doesn’t connect to cloud platforms natively, you’re forced into brittle workarounds that waste time and limit scalability. 

Modernization means orchestrating flawlessly across on-prem, hybrid and multi-cloud environments — AWS, Azure, Google Cloud and SaaS applications — with equal reliability. Modern WLA adapts dynamically to wherever the workload runs.

✅ Visibility gaps are slowing decisions

When leaders don’t have a real-time view of workflows, they’re forced to make decisions based on lagging reports or gut instinct. Outdated WLA tools often lack centralized dashboards or predictive analytics. That leaves IT blind to bottlenecks, failed jobs or SLA risks until it’s too late. 

Modern platforms deliver observability with centralized dashboards, SLA projections and proactive alerts so you can fix issues before they disrupt the business.

✅ Scaling feels harder than it should

Every business faces periods where job volumes soar: end-of-month closings, holiday traffic, product launches. Traditional WLA models can hit limits under pressure, leading to delays and downtime. Some organizations work around this by adding servers and hardware that they only need a few times a year. 

A modern SaaS platforms scales with your business, growing and shrinking with demand, so you only pay for the value you get. That means no scrambling or overbuying.

✅ Maintenance is draining resources

Traditional job scheduling tools can come with hidden costs in the form of specialized staff or consultants and downtime during upgrades. None of that creates business value.

In contrast, a SaaS-based automation platform rolls out updates automatically to minimize downtime and ensure you don’t have to rely on niche expertise. You get true financial headroom, even beyond IT operations.

✅ Security expectations have surpassed your tools

When automation runs financials, healthcare data, customer transactions and other key processes that handle sensitive data, security isn’t optional. Many systems still in use struggle to keep pace with modern cybersecurity expectations.

Today’s automation platforms include role-based access control (RBAC), encryption, continuous patching and audit-ready trails by default. So instead of hoping your system is secure, you can prove it.

✅ AI isn’t part of the equation

If your platform is stuck in reactive mode, you’re missing opportunities to get ahead of issues and continuously improve. Automation isn’t static anymore — it’s intelligent. AI isn’t hype in this space. It’s becoming the standard for enterprises that want reliable, efficient and proactive automation.

The most advanced WLA platforms now layer in AI and machine learning. These capabilities don’t just predict job failures but also recommend optimizations and analyze patterns across thousands of runs. It’s the difference between automation that simply works and automation that amplifies ROI by proactively driving efficiency. 

✅ Users want more control without more risk

When automation tools are too complex, IT becomes the bottleneck. Business users resort to shadow IT, running critical business processes outside governance because the official system is too hard to use. 

Modern WLA turns this on its head with intuitive interfaces, drag-and-drop workflow builders and delegated self-service. When users are empowered, automation becomes a force multiplier instead of a source of friction.

Why readiness matters now — no matter your use case

Every organization is under pressure to do more with less. Outdated workload automation slows you down, increases risk and adds hidden costs. Modernization isn’t about chasing a trend; it’s about putting your business in a position to scale, innovate and compete.

A modern SaaS WLA solution gives you:

• Scalability without infrastructure sprawl
• Deep integrations not only with SAP and other enterprise systems, but also for hybrid and multi-cloud workloads
• Observability for centralized visibility and predictive monitoring
• AI-driven optimization and self-service
• Built-in security and control
• Lower cost of ownership and fewer upgrade headaches

If these signs sound familiar, it may be because your business success has outgrown traditional approaches. That’s a good thing — it means you’re ready to modernize. Acting now lets you turn that momentum into a more scalable, flexible and resilient automation strategy, just as many leading enterprises are already doing.

What happens when you don’t modernize in time? Find out what the aviation industry learned the hard way.

Partner with the leader in WLA

Redwood Software has been helping enterprises modernize automation for decades, across both on-premises and cloud environments. Redwood was also named a Leader two years in a row in the Gartner® Magic Quadrant™ for Service Orchestration and Automation Platforms (SOAPs).

With RunMyJobs by Redwood, we offer the only SaaS-native WLA platform purpose-built for hybrid IT, designed to support SAP and business-critical processes at scale. Because we’ve led in both on-prem and SaaS, we’re uniquely positioned to guide your transition and help you modernize at your own pace.

Talk with a Redwood expert to see how a modern workload automation solution can reduce costs, boost operational efficiency and support your cloud journey.

Together, the two reports give a comprehensive view of the SOAP market landscape, but they remain market-level research, not an assessment of your specific business priorities.

Here, we offer a practical framework for how to translate Gartner’s approach into your own scorecard to evaluate SOAP platforms against your organization’s needs and goals.

Why capability-based evaluation matters

The Magic Quadrant™ is invaluable for seeing which vendors are positioned strongly in the market. It shows who’s executing effectively today and who has the vision and roadmap to meet tomorrow’s demands. But it’s not a detailed interrogation of product features or a guarantee of fit for your particular requirements.

That’s why the Gartner Critical Capabilities companion report is so useful. It zooms in on differentiators — why the SOAP software providers were recognized in particular areas. It asks: How well does this platform execute real-world tasks? How usable is it? What outcomes does it enable?

In the report, Gartner recommends, “When selecting a SOAP vendor, conduct thorough due diligence to understand their specific strengths in innovation, integration and responsiveness to emerging trends, rather than assuming parity in a mature market.”

Inspired by this approach, we’ve built a scorecard you can use to evaluate vendors for your particular purposes, for both functionality and fit,  based on the five SOAP Use Cases.

Key capability domains to score

Each domain aligns with a Use Case from the Gartner report. Below, you’ll find:

• What the domain measures
• Traits to look for
• A 1–5 scoring rubric

1. Operational resilience and IT workload execution 

Inspired by the IT Workload Automation Use Case

Can the platform orchestrate and safeguard large volumes of complex, time-sensitive IT workloads?

What to evaluate:

• SLA monitoring and escalation dashboards
• Automated failover, retry and recovery mechanisms
• Volume throughput and performance under stress
• System auditability and job history tracking

How to score:

2. Hybrid orchestration and workflow flexibility 

Inspired by the IT Workflow Orchestration Use Case

How well does the platform support both business and technical workflows across hybrid environments (on-prem, multi- cloud, SaaS)?

What to evaluate:

• Breadth of pre-built integrations across legacy and modern systems
• Ease of orchestration across teams and technologies (e.g., low-code)
• Flexibility to design, trigger and adapt complex workflows
• Support for both technical and non-technical users

How to score:

3. Data movement and pipeline governance

Inspired by the Data Orchestration Use Case

Can the platform reliably orchestrate large-scale, rule-based data flows across warehouses, lakes and BI systems?

What to evaluate: 

• Availability of connectors for major data platforms (e.g., Snowflake, SAP Datasphere)
• Orchestration of rule-based, event-driven data flows
• SLA tracking for data jobs and throughput performance
• Guardrails like validations, retries and logging

How to score:

4. Empowering business users

Inspired by the Citizen Automation Use Case

Can non-technical users safely create, edit and trigger automations with the right controls?

What to evaluate:

• Guided self-service tools for workflow design and execution
• Guardrails and governance features (e.g., approval workflows, role-based access)
• Training resources and onboarding ease
• Audit logs and rollback capabilities for business-created workflows

How to score:

5. DevOps readiness and automation agility

Inspired by the DevOps Automation Use Case

Does the platform integrate with DevOps toolchains and support agile release cycles? 

What to evaluate:

• Native plugin availability for CI/CD tools
• API maturity and extensibility
• Support for version control, branching, rollback and parallel pipeline execution
• Ability to deploy and manage automation as code

How to score:

Constructing your SOAP scorecard

You don’t need a complex spreadsheet to evaluate SOAPs. Just build a simple table:

Adjust weights based on your priorities. If you’re focused on business agility, you might weigh citizen automation more heavily. If uptime is paramount, prioritize IT workload execution.

This approach doesn’t just tell you which provider offers what you want but the depth to which that capability goes.

Interpreting your results

• 4.5–5.0: Top-tier platform fit, capabilities with depth
• 3.5–4.4: Strong candidate, likely meets core needs with some tradeoffs
• 2.5–3.4: Mid-tier and may require customization or compromise
• <2.5: Unlikely to meet enterprise orchestration needs

Where Redwood leads — and what that signals for you

Redwood Software ranked #1 in all five Use Cases in the 2025 Gartner Critical Capabilities for SOAP report. We believe that reflects more than just functional breadth and confirms Redwood’s ability to deliver real-world orchestration across IT workloads, business workflows, citizen development, data movement and DevOps. This aligns with our mission to unleash human potential through automation fabric solutions.

A SOAP platform is not just a feature set but an enabler of better business outcomes. Use the scorecard above, and download the full Gartner Critical Capabilities report to optimize your search for the right SOAP.

Intelligent orchestration ensures business processes execute reliably, securely and without unnecessary manual intervention. As hybrid environments expand, data pipelines multiply and digital initiatives accelerate, unified orchestration platforms have become mission-critical.

This leap is reflected in the 2025 Gartner® Magic Quadrant™ for SOAP. Vendors are being evaluated on execution in addition to how well they support end-to-end processes, hybrid environments and governance at scale.

If you’re in the process of selecting a SOAP solution, use this practical guide to evaluating your options, with insights inspired by Gartner’s criteria and industry trends.

What is a SOAP — and why does it matter more than ever?

According to Gartner, “SOAPs unify workflow orchestration, workload automation and resource provisioning, extending across data pipelines and cloud-native architectures.”

SOAPs represent the evolution of traditional workload automation beyond job scheduling. These platforms are crucial for bringing order to complex IT environments that span on-premises, multi-cloud and hybrid environments. They matter because they provide a centralized hub to coordinate workflows across diverse systems — both within an organization and across an ecosystem for suppliers and distributors. They reduce risk by providing end-to-end visibility and control and improve business agility by reducing manual intervention.

A modern SOAP coordinates dependencies, enforces service-level agreements (SLAs) and triggers workflows based on events, making it essential for:

• Digital transformation in finance, supply chain and IT operations
• Cloud modernization initiatives
• AI and machine learning (ML) adoption that requires governed data movement
• Compliance with security and regulatory frameworks

The “right” SOAP solution should reduce human error, free up IT to focus strategic priorities and streamline how automation is designed, maintained and governed. It should support faster response to business and market shifts, break down silos by connecting legacy systems and cloud services and enable seamless coordination across your technology ecosystem. Most importantly, it should enhance visibility, control and auditability with a unified view of every process, so your automation is as trustworthy as it is efficient.

Key evaluation criteria when choosing a SOAP solution

Here are six areas to include in your evaluation, inspired by trends surfaced in the Gartner report and common attributes among SOAP Leaders.

Scalability and performance

The platform should be able to handle high volumes of automated tasks without performance degradation. Ask whether it can support millions of jobs per day and how it performs under peak loads. A SOAP must be resilient and elastic enough to accommodate sudden surges in workload without compromising execution times or reliability. Scalability is about sustained performance, not just capacity.

Cloud-native architecture and SaaS delivery

When evaluating a SOAP solution, start with how the platform itself is built and delivered. A truly SaaS-native platform doesn’t just “run in the cloud;” it’s designed for elastic scale, multi-tenant performance and frictionless updates. Look for characteristics like agentless architecture, stateless services, zero-maintenance provisioning and high availability built into the core. These reduce operational overhead and speed up onboarding.

Deployment flexibility and hybrid orchestration support

It’s not just how the platform is built but also how it operates. A SOAP platform must support orchestration across your entire environment, from legacy mainframes to modern SaaS apps, cloud services, containers and DevOps pipelines. Seek flexible endpoint support, native connectors and the ability to run across multiple clouds, regions or tenants without custom scripting or duplicate workflows.

Ease of use and low-code accessibility

Automation should be democratized. Your SOAP platform should provide a low-code interface that enables IT operators, developers and even power users on the business side to design and modify workflows. Features like drag-and-drop workflow designers and reusable templates make it easier to build, test and share workflows. Integrated documentation and governance reduce training time and increase adoption. 

Observability and monitoring

It’s not enough to execute a job. You need to know what happened, why, and what could go wrong next time. Real-time dashboards, job dependency maps, SLA monitors and predictive alerting help teams quickly isolate failures and understand upstream/downstream impact. A strong observability layer turns the SOAP into a diagnostic tool, not just a transaction engine.

AI-powered productivity

It’s key to empower your teams with specific and valuable assistance for using the product and operating the platform to deliver efficient, reliable and observable automation fabrics. AI is now embedded into how automation platforms help users work faster, smarter and with greater confidence. AI features can significantly reduce time-to-value and operational risk. Whether you’re troubleshooting a failed job or optimizing a business-critical process, AI-powered diagnostics accelerate root-cause analysis, helping your teams resolve issues before they cause downstream delays. Equally important is AI’s role in design-time productivity. Context-aware configurations and AI-optimized change management can reduce the friction involved in building new workflows.

Security and governance

Security and compliance should be built in, not bolted on. SOAPs must support enterprise-grade authentication and authorization, including single sign-on (SSO), multi-factor authentication (MFA) and role-based access control (RBAC). They should also be able to encrypt data in transit and at rest and offer detailed audit logs. Look for support for compliance frameworks like SOC 2, ISO 27001 or HIPAA, depending on your industry. Governance features should also enable fine-grained control over who can modify, execute or monitor workflows.

Extensibility and ecosystem

No SOAP platform operates in a vacuum; it must integrate cleanly with your existing infrastructure, applications and cloud services. Look for out-of-the-box connectors, a rich library of APIs and support for event-driven triggers. The more extensible the platform, the more value it will deliver as your tech stack evolves.

Trends shaping the SOAP landscape in 2025

“By 2029, 90% of organizations currently delivering workload automation will be using service orchestration and automation platforms (SOAPs) to orchestrate workloads and data pipelines in hybrid environments across IT and business domains.”

2025 Gartner® Magic Quadrant™ for SOAP report

SOAP solutions are evolving rapidly. Let’s examine a few trends shaping enterprise automation strategies this year.

• Convergence with adjacent tools: Modern SOAPs increasingly overlap with iPaaS, managed file transfer (MFT) and IT Service Management (ITSM) platforms. Expect tighter ecosystems and fewer isolated tools.
• AI-enhanced observability: Predictive analytics, anomaly detection and proactive SLA risk insights are fast becoming differentiators, especially in high-volume scenarios. The report notes that, “By 2029, 75% of SOAP workflows will leverage generative AI (GenAI) to increase troubleshooting efficiency by 50% — up from less than 10% in 2025.”
• Orchestration for analytics workloads: Data must flow faster and more reliably. As AI becomes operationalized, orchestrating data is just as important as model performance.
• Citizen automation: Business users want self-service tools without compromising governance, and IT needs to enforce guardrails. SOAPs now must deliver both to enable scalable citizen automation.
• Centralized control across domains: Fragmented platforms are falling behind. SOAPs that serve as a control plane for hybrid IT, cloud, data and business workflows are rising to the top.

What sets Leaders apart in the Gartner® Magic Quadrant™

According to Gartner Magic Quadrant™ research methodology, “Leaders execute well against their current vision and are well-positioned for tomorrow.” Choosing a Leader as your SOAP vendor doesn’t guarantee success, but it does reduce risk, accelerate ROI and align you with those invested in long-term innovation.

Why organizations are turning to RunMyJobs by Redwood

When enterprises outgrow reactive automation, they turn to RunMyJobs. It’s purpose-built for orchestrating complex, enterprise-wide workloads.

RunMyJobs helps global organizations automate with confidence through:

• SAP Endorsed App, Premium certification — SAP’s highest standard for performance, security and integration
• Robust hybrid connectivity to seamlessly connect on-premises systems (e.g., ERP, WMS, MES) with multiple public cloud services
• Event-based triggers and integrated data management
• SaaS-native, agentless architecture built for scale, with no infrastructure maintenance
• Built-in observability via Redwood Insights with pre-built dashboards and the ability to customize
• AI-powered productivity enhancements that range from knowledge access to troubleshooting to actual design and development of automation workflows
• Low-code workflow design for both IT and business users
• Enterprise-grade security and compliance
• Decades of automation expertise and two consecutive years of being named a Leader in the Gartner Magic Quadrant™ for SOAP

Choosing the right SOAP solution means choosing the foundation for your automation future. Make the investment count — for what your business needs today and what it will demand tomorrow. Read the full analyst report today.

Forecasting and replenishment (F&R) works the same way. To the customer, it’s simple: the product they want is available where and when they want it. But what got it there was a full production involving forecasting systems, ERP, POS, purchase orders, distribution centers — each with their own scripts. 

Take the case of Target Canada. They had ambitious plans, shiny stores and plenty of product in stock. But backstage, systems weren’t talking to each other. Some shelves stayed empty while others were overstocked, and many customers walked out or didn’t show up at all. The two-year production bombed big-time, resulting in a multi-billion-dollar loss. “Ticket sales” didn’t even cover the cost of performances in this scenario.

Opening night: The performance customers see

F&R is the entire performance from the moment you draw the curtain back. It’s what the audience (your customers) experiences when they shop. Your forecasting engine is the lead actor, but it can’t carry the whole show alone. It depends on a cast:

• ERP systems handling orders and procurement
• POS systems sending daily sales signals
• Warehousing and logistics making sure the right props (products) land on stage
• Replenishment planning and allocation tools managing cues

If these players don’t work together well, the audience will see the mistakes: empty shelves, markdown bins and lost orders, to name a few.

Missed cues: Why supply chains go off script

Even seasoned companies misstep when the backstage crew isn’t in sync. In supply chain terms, that means F&R falls apart when the systems behind them aren’t connected or coordinated.

Take siloed systems, for example. ERP, POS and warehouse management each follow their own script, and none of them talk to each other. That disconnect means planners may not see when a promotion is running, when seasonality is driving spikes in demand or when external events disrupt supply. Without those inputs flowing cleanly into the forecast, replenishment planning quickly goes off track. It’s like three actors reciting different versions of the same play — it’s confusing, messy and painful to watch.

Manual workarounds are another sign of a shaky production. When planners resort to spreadsheets to patch gaps or re-sequence orders, it’s like stagehands rushing onto the set with duct tape mid-performance. The show goes on, but the cracks are obvious.

Rigid, batch-driven processes add another layer of risk. Imagine trying to run a live play using only rehearsed recordings. The story would fall flat the moment something unexpected happened. And the same goes for replenishment runs that can’t adapt when demand shifts suddenly, such as when there’s an unforeseen weather event.

Then there’s the lack of visibility. Without clear lines of sight into whether a job has started, finished or failed, supply chain leaders are left waiting to see if the actor will make their entrance. By the time they realize the cue was missed, the audience already knows.

The outcome of all these broken scenes? Outdated forecasts, replenishment delays, high carrying costs and frustrated customers who don’t come back after intermission.

The director’s chair: Keeping every scene in sync

An orchestration solution like RunMyJobs by Redwood acts as the director behind the curtain, ensuring every system, transaction and dependency plays its part. Think about the challenge of planning a holiday promotion: Forecasting modules may generate a strong demand forecast, but if order proposals don’t trigger on time or distribution centers can’t see accurate inventory levels, the campaign won’t be successful.

With RunMyJobs, order forecasts, replenishment planning, purchase orders and automatic replenishment proposals are kept in sync with demand planning and forecasting algorithms. That means safety stock calculations adjust automatically when seasonality spikes, promotions launch or future demand signals arrive from POS sales data. It also means master data issues are flagged and corrected before they cascade downstream.

This is true whether you’re running SAP F&R, IBP, Retail and Distribution Industry Solutions, MM, APO or connecting to non-SAP systems — RunMyJobs keeps the performance on track no matter the complexity of your tech stack. You’ll be able to respond faster to factors influencing demand, like promotions, pricing changes or unexpected stockouts, while reducing manual interventions. 

Orchestration transforms F&R from a fragile balancing act into a resilient, repeatable process that adapts to real-world conditions.

Standing ovation: Course-correcting with orchestration 

The value of orchestration in F&R shows up in the KPIs that matter most: gross margins, order fill rates and customer satisfaction.

Treat F&R like the production it is

In retail and distribution, forecasting and replenishment is mission-critical. It’s not a solo performance but an ensemble production that needs perfect timing, cues and orchestration. 

RunMyJobs provides the automation fabric that keeps your show running. Global retailers and distributors trust it to bring order to complexity and deliver consistent, applause-worthy results. 

Book a demo to see how RunMyJobs can optimize your F&R process end to end.

The problem is, “just working” isn’t the same as being ready for what’s coming next, especially if you care about SAP’s evolution and the massive role AI is playing. In a world where digital transformation now means becoming an intelligent enterprise built on real-time data, you can’t afford not to make use of the “best of the best” solutions.

Luckily, SAP gives us an easy way to determine which compatible solutions the company most strongly stands behind: SAP Endorsed App Premium certification.

SAP Endorsed App: More than just a badge

SAP Endorsed Apps aren’t ordinary partner solutions. This invitation-only program highlights solutions that help you with strategic business challenges not directly addressed by core SAP functionality. 

SAP Endorsed App status is the highest level of certification SAP offers, and it isn’t handed out lightly. It signals to customers that the solution has been extensively tested and validated to meet SAP’s highest standards for performance, security and integration.

Being an Endorsed App means a solution has been rigorously evaluated and passed SAP’s most demanding Premium certification standards. Every angle is tested to ensure the solution truly stands up to real-world enterprise demands, even in the most complex hybrid environments. Only solutions that are widely used by SAP customers, future-aligned and proven to deliver outstanding customer value earn this highest level of SAP trust.

SAP Endorsed App for workload automation

Taking advantage of SAP’s next-generation capabilities is particularly important when it comes to workload automation, the backbone of your mission-critical processes. SAP CEO Christian Klein envisions a world in which ERP, automation, data and AI all work together in one cohesive ecosystem. Your processes should run end to end, intelligently orchestrated rather than stitched together. If your automation layer isn’t deeply integrated and future-ready, it becomes an anchor dragging you down. And if your workload automation partner isn’t deeply aligned with SAP, you’re going to hit bottlenecks sooner than you think.

That’s why RunMyJobs by Redwood becoming a Premium certified SAP Endorsed App matters so much. You know your automation will be not just compatible but optimal, now and into the future.

Certified vs. optimal integration

Many job scheduling solutions are certified to connect to SAP systems, even RISE with SAP. And that’s good, but it’s only the first step. Basic certification means a scheduler has been tested to connect and perform standard tasks, but it doesn’t tell you how it integrates, what extra infrastructure you need or whether it supports a clean core without workarounds and fragile custom code.

It’s kind of like giving your teenager a learner’s permit. Sure, they’re legally allowed to drive, but would you hand them the keys and say, “Go ahead, take your friends to the basketball game tonight … and use the freeway”? Probably not. You know that true readiness involves more than basic certification. It’s about trust, experience and minimizing risk — for the driver and everyone else on the road.

RunMyJobs is the experienced, fully licensed driver: the only workload automation solution that is an SAP Endorsed App, Premium certified. Thus, it’s optimized to run in complex SAP landscapes, including RISE with SAP, Business Technology Platform (BTP) and Business Data Cloud (BDC). 

It’s not about whether your automation connects to SAP. It’s whether it truly unlocks SAP’s full value, without compromise.

True future-proofing: Not just a fancy marketing slogan

We all see “future-proof” plastered across marketing materials. But real future-proofing isn’t a tagline. It means what’s being offered is designed to evolve, not just function today.

With SAP Endorsed App status, RunMyJobs is verified to keep pace with SAP’s roadmap. There is a regular cadence for SAP and Redwood Software to collaborate and align product roadmaps. What you get from this: reduced risk, faster time-to-value and confidence that your automation engine won’t become the bottleneck when it’s time to embed AI into your core business processes. So when we talk about RunMyJobs being “future-proof,” we’re not throwing around empty words. 

Don’t run your business on a learner’s permit. You need a solution that’s been trained, tested and trusted to navigate the entire journey confidently, even if the road ahead is uncertain.

Watch the video below to learn more about what RunMyJobs’ SAP Endorsed App status means for your business.

See more about RunMyJobs in the SAP Store.

Earlier this year, radar failures at Newark Liberty International Airport grounded flights across the United States, not because the aircraft failed but because coordination broke down. A combination of aging systems, staff shortages and manual overrides created a chain reaction that left passengers stranded and schedules in chaos.

Enterprise IT isn’t so different. Cloud systems, data platforms, ERP modernizations and AI pilots are all taking off, but the control layer that’s supposed to orchestrate them is often still stuck on the ground.

When the automation “tower” fails, everything stops.

Who’s guiding your IT traffic?

CIOs and CTOs are moving fast. They’re focused on cloud-first, generative and agentic AI and workflow automation. Under all that progress is a quiet problem: The automation architecture powering it all hasn’t kept up.

Companies are building smarter systems but still relying on old job schedulers and hard-coded scripts to orchestrate between them. That creates delays, disconnects and blind spots. The sky might look clear now, but storms are coming.

The more systems you modernize, the more complex your operations become. And as this modernization goes faster and faster over time, the harder it is to coordinate workloads with high fidelity, especially across legacy systems that require custom-coded connectors, manual refactoring for continuous integration and automation designed for a different era. While it feels like you’re accelerating, legacy systems beneath the surface are quietly pulling the brakes.

Modernization without orchestration is like asking your control tower to manage new aircraft using equipment they’ve never trained on. The sky is getting more crowded, but the systems guiding the traffic are stuck in the past.

The illusion of progress

The problem with mainframes didn’t begin and end in the early 2000s. It lingered for decades. Even as businesses moved to the cloud in the 2010s, their most critical workloads and data remained locked inside monolithic, closed mainframe applications with no APIs, no agility and shrinking pools of technical talent.

During the COVID-19 crisis in 2020, the issue broke into public view when multiple U.S. states issued emergency calls for COBOL programmers to stabilize aging unemployment systems. Rather than isolated IT issues, these were architectural bottlenecks that made rapid response impossible. No DevOps, no iterative improvement, no access to real-time data. Just batch cycles, manual updates and fragile processes buried under decades of technical debt.

Today, many enterprises are facing the same limitations, just in a different disguise. Legacy job schedulers and automation tools are the modern mainframe, standing in the way of AI adoption, API-driven integration and autonomous orchestration across cloud-native ecosystems.

These schedulers were designed for predictable workflows and tightly coupled environments, not for hybrid cloud, continuous delivery and interconnected platforms like SAP Business Technology Platform (BTP), Salesforce and Snowflake. As a result, they can’t scale, they can’t adapt and they certainly can’t keep pace with AI-driven transformation.

Static scheduling vs. intelligent orchestration

Orchestration requires controlling systems with precision and context, rather than just connecting them. That’s where event-based architecture becomes critical.

Unlike traditional scheduling, which runs on fixed times or batch jobs, event-driven orchestration allows your processes to respond dynamically to business and system events. You react to what’s happening now, not just what’s scheduled. Orders get fulfilled the moment inventory updates. Reports run the second data hits the warehouse. Downtime shrinks. You meet service-level agreements (SLAs).

At Redwood Software, we call this architecture an automation fabric: a unified layer that weaves together cloud and on-premises systems and AI innovation with full visibility, scalability and control. What makes it different?

• Built for hybrid: Connect SAP, Oracle, cloud services and custom apps across environments.
• Agentless integration: Connect systems without installing or maintaining local agents, so no need for custom scripts. Reduce risk, friction and security vulnerabilities.
• AI-powered observability: Identify SLA risks and optimize performance before problems arise.
• Unified monitoring: View everything through a single pane of glass.

Why would you custom-code or patch together manual workflows when intelligent orchestration can adapt autonomously?

Avoid a Newark moment: Your flight plan

Let’s say your global energy company is modernizing for sustainability and scale. You’re juggling regulatory demands, transitioning to RISE with SAP, piloting AI in financial planning and managing dozens of custom systems. But your core automation is still dependent on a legacy scheduler designed for batch processing and nightly jobs.

You’re not alone.

This is where modernization breaks down. It’s not in the cloud migration or the AI launch, but in what keeps it all together. By upgrading to a modern orchestration platform, your company could retire fragile custom scripts, slash risk across compliance-heavy processes and move faster with fewer people.

Rather than just picking a tool, it’s essential to choose a partner with a forward-looking vision. RunMyJobs by Redwood is designed to be air traffic control for the modern enterprise. Even if you’re not feeling the turbulence yet, the future is coming faster than you think. 

Don’t wait until delays, outages or compliance gaps force your hand. Modern orchestration isn’t optional — it’s foundational.

See it in practice: Read our guide to learn how automation fabrics are helping teams orchestrate SAP and non-SAP data across industries.

But what happens after the fire is out? This is where you make real, lasting improvements. This is the world of problem management: the forensic investigation into the root cause of an incident to ensure it never happens again.

Redwood Insights is the essential tool for this investigation in RunMyJobs, enabling you to identify trends that are critical for long-term problem resolution. With persona-based dashboards that visualize near-time historical execution data, Redwood Insights allows you to move beyond guesswork and find the root cause of your most complex operational problems.

This post explores how you can use Redwood Insights to transition from a reactive operational posture to a proactive one, using data to solve complex issues and optimize your automation landscape.

Core challenges of effective problem management

Without the right analytical tools, it’s difficult for you to move from a “hunch” to a data-driven conclusion about the root cause of an issue. Teams often lack the aggregated historical data needed for a proper investigation. This leads to two common, frustrating scenarios:

• The major incident post-mortem: A critical production process failed last night, causing significant disruption. The incident team resolved it, but the question remains: Was it a one-time anomaly, or is it a symptom of a deeper flaw that will cause another major outage soon?
• The “death by a thousand cuts:” A seemingly minor job fails intermittently, causing small disruptions. You log it as a low-priority incident every time and manually fix it. No single incident is big enough to warrant a major investigation, but the cumulative impact on team resources and user confidence is significant.

Real-world problem management scenarios with Redwood Insights

Let’s look at how Redwood Insights helps teams move from putting out fires to preventing them through data-driven investigations into both major incidents and recurring annoyances.

1. The major incident post-mortem – anomaly or systemic flaw?

The process: Following a major outage of a critical data warehousing job that was resolved by the on-call team, you’re tasked with conducting a root-cause analysis to prevent recurrence.

The investigation with Redwood Insights:

1. You open the Job Insights report for the failed job to get a complete historical view.
2. You use heat maps to see if failures have ever correlated with this specific date or time of month before, trying to identify patterns.
3. To determine if this was an infrastructure issue, you switch to the Job Server Analysis dashboard. This allows you to quickly rule out a systemic problem by comparing performance across your environment. 
4. Confident that the infrastructure is sound, you return to the job’s execution data. As you analyze the widgets, you clarify the situation using a smart narrative, powered by AI: a simple, natural-language summary of the data.

The business outcome and ROI:

• Action taken: Based on this clear, data-driven context, you can confidently classify the issue. You document the anomaly and close the problem record, avoiding an unnecessary and costly investigation into a one-off event.
• Business outcome: This data-driven approach avoids wasting resources chasing ghost issues while ensuring that genuine systemic risks get the attention they deserve.
• ROI: This leads to improved long-term service stability, more efficient use of skilled engineering resources (who now solve real problems) and increased business confidence in the automation platform.

2. Solving the recurring problem with data

The process: An end-of-day reporting workflow has been failing intermittently for weeks, creating a backlog of low-priority incidents.

The investigation with Redwood Insights:

1. You begin your investigation on the Operator Overview dashboard. Your eyes are immediately drawn to a widget highlighting the “top ten jobs with most frequent failures,” which confirms this reporting job is a chronic offender that needs attention.
2. You analyze the job’s history and use heat maps to discover a clear pattern: The failures almost always occur on weekday afternoons. 
3. To understand why, you pivot to the Queue Analysis dashboard to drill down into the systems involved. Here, the data clearly shows that when the reporting job fails, queue wait times are consistently high, indicating resource contention is the likely culprit.

The business outcome and ROI:

• Action taken: With definitive proof of the root cause, you submit a change request to create a dedicated queue for the reporting workflow, a targeted improvement based on historical data.
• Business outcome: The recurring incidents stop completely. The business service becomes reliable, and the stream of low-priority tickets ceases.
• ROI: This eliminates the hidden operational cost of repeatedly fixing the same small issue, frees up your Operations team from repetitive tasks and improves the reliability and timeliness of service delivery.

Your toolkit for proactive problem management

These tools give you the operational visibility and historical context to take IT operations from reactive troubleshooting to a data-driven, intelligent function.

• Identify recurring issues: Use the Operator dashboards to prioritize the most impactful, systemic problems by highlighting key metrics, such as the top ten failing jobs.
• Correlate failures to find patterns: Use interactive widgets like heat maps to uncover underlying triggers for recurring problems by correlating failures to specific dates or other factors.
• Isolate system-specific problems: Use the Job Server Analysis and Queue Analysis dashboards to understand if failures are application-specific or tied to a particular component, which is crucial for problem management.
• Drive data-driven improvements: Use the detailed Job Insights and Workflow Insights dashboards to perform targeted analysis, enhancing processes through redesign or resource reallocation based on historical performance data.

From reactive firefighting to strategic reliability

Redwood Insights provides the essential tools for a mature problem management practice. It allows you to move beyond the immediate incident and analyze historical trends to find and permanently eliminate the underlying causes.

The result is a more stable, reliable and optimized automation environment. This leads to fewer outages, more efficient use of IT resources and consistently more timely and reliable service management.

Watch this video preview of Redwood Insights to learn more.

Ready to move beyond firefighting and start solving problems for good? Discover how Redwood Insights can power your problem management process. Book a demo of RunMyJobs today.

It’s a disconnect that’s quickly becoming unsustainable. While the pace of AI adoption is moving faster than other disruptive innovations, it simply won’t work if the rest of IT doesn’t catch up. And as SAP made clear at SAP Sapphire 2025, there’s no value in building AI on a shaky foundation.

The new mandate: Modernization beyond ERP

SAP’s strategy has evolved beyond ERP. SAP CEO Christian Klein says true transformation is now about incorporating the “flywheel” of applications, data and intelligence. The implication is that SAP Business Technology Platform (BTP), embedded AI and unified data models aren’t peripheral to the core — they are the core.

The explosion of SaaS tools hasn’t produced better outcomes. In his SAP Sapphire Orlando 2025 keynote, Klein noted that global productivity growth has slowed rather than accelerated because too many businesses are duct-taping together apps and automations without the foundation to make them work together.

The implication is clear: You can’t just modernize your ERP and call it a day. Supporting systems, especially those running behind the scenes, such as workload automation (WLA), must evolve in lockstep. Otherwise, you’re introducing friction into every cross-system process (and therefore, AI model) you run.

Old schedulers, new risks

Traditional job scheduling tools were built for a different era. They rely on locally installed software, custom scripts and fragile connections to coordinate batch jobs in static environments. They were never designed for real-time, intelligent processes across cloud-native applications and rapidly evolving AI models.

Sticking with these tools introduces unacceptable risks:

• Operational complexity from maintaining brittle, outdated architecture
• Technical debt from endless scripting and patchwork connectors
• Challenges with maintaining clean core principles
• Fragmented automation across SAP and non-SAP systems
• Inability to leverage SAP’s AI roadmap due to data silos and latency  
• Delayed time-to-value from SAP innovations

You can’t derive reliability and maximum value from AI if your job scheduler is stuck in the past.

Why AI fails without clean, timely data

It’s easy to think AI fails because the models are wrong. But in enterprise environments, the more common culprit is something far less glamorous: bad data. When job scheduling is not modernized, it can quickly become unreliable or disconnected and fail to feed AI systems with what they need to produce in-depth, accurate insights. When they deliver irrelevant or dated insights or hallucinations, it undermines trust in the intelligence you’re trying to deploy.

AI can’t magic its way past old and brittle plumbing that was already on the brink of needing replacement. Trying to update your kitchen or bathroom with fancy new showerheads and faucets with all kinds of bells and whistles may make it look nice, but the water that’s critical to its functioning may struggle to get there at the right time and temperature. A remodel will always require a certified inspection of the pipes and supporting foundation to ensure they work safely and reliably with the upgraded fixtures.

No workaround necessary: The modern approach to WLA

SAP has been loud and clear about the clean core mandate. What was once a push to keep ERP extensibility under control is now a requirement for AI readiness. SAP’s vision of a “fit-to-suite” architecture, where apps, data and automation are in harmony, can’t happen if your WLA layer brings discord into the mix.

Trying to keep your legacy scheduler working is like bringing a VHS tape to a Netflix pitch meeting. Sure, you might find a dusty adapter somewhere in the back closet, but you’ll be miles behind before you even press play. No amount of workarounds will make outdated technology compatible with a world that’s already streaming ahead.

Modernizing WLA for SAP and non-SAP processes means orchestrating every part of your business to be faster and more intelligent. It means having:

• Cloud-native SaaS that orchestrates processes across hybrid environments without additional infrastructure
• Frictionless architecture that provides a singular secure gateway to connect with every SAP and non-SAP application, reduces maintenance and eliminates failure points 
• Deep SAP integration that aligns with SAP product roadmaps and innovation strategies
• Pre-built templates and connectors to accelerate time-to-value without violating clean core
• Centralized orchestration for SAP and non-SAP processes from a single interface

Automation purpose-built for an SAP cloud and AI future

Redwood Software and SAP share a trusted partnership built on over 20 years of co-development, innovation and roadmap alignment, making RunMyJobs by Redwood a strategic extension that maximizes the ROI of your SAP investments.

What sets it apart?

• SAP Endorsed App, Premium certified: RunMyJobs reduces risk, accelerates time-to-value and offers long-term reliability to SAP customers. It’s certified across a broad range of SAP technologies, meeting SAP’s highest standards for performance, security and integration. It delivers native functionality and deep integration across complex hybrid and cloud deployments, with built-in, SAP-specific templates and connectors that eliminate custom code and scripting. This supports clean core strategies and helps customers solve critical business challenges more efficiently.
• The only WLA solution included in the RISE with SAP reference architecture: RunMyJobs is included in the RISE reference architecture through managed services offered and delivered by SAP Enterprise Cloud Services (ECS). ECS handles the direct installation and maintenance of the RunMyJobs’ secure gateway connection within your RISE landscape, eliminating the need for extra infrastructure, custom workarounds and friction in the RISE journey. You can also opt into additional ECS-managed services for enhanced monitoring of SAP processes automated with RunMyJobs, improving visibility and enabling proactive issue resolution.
• Co-innovation with SAP BTP and Business Data Cloud (BDC): Get the latest connectors for SAP Analytics Cloud, SAP Datasphere, SAP Integration Suite, Databricks and more.

Proof that AI-ready automation works

What defines AI-ready in the context of WLA? It’s more than speed and scale. 

Your processes are orchestrated, not just scheduled. You’re connecting tasks and dependencies across SAP and non-SAP environments using event-driven automation.

Governance is built in. You have visibility and control over every job and data flow, from development to execution to exception handling.

Business value is clear. Automation is no longer a backend utility but a strategic driver of innovation, efficiency and competitive advantage.

These elements have already been realized by companies that have modernized with RunMyJobs.

• RS Group, a global industrial distributor, modernized its legacy job scheduler as part of its digital transformation and supply chain operations improvement programs. The company now runs business operations across 26 global markets daily, maintaining job reliability above 99%, and have eliminated Priority 1 and Priority 2 incidents in critical operations for over a year.
• UBS, one of the world’s largest financial institutions, relied on RunMyJobs to replace a legacy scheduling solution that couldn’t scale with the complexity of its SAP environment. UBS transitioned to RunMyJobs for its cloud-native architecture and reliability. The company built a cleaner automation landscape, achieving faster recovery from exceptions and future-proofing its foundation to support advanced analytics and AI-powered compliance.
• Centric Brands, a leading lifestyle brand collective with a complex ecosystem of SAP and non-SAP systems, used RunMyJobs to consolidate multiple legacy scheduling tools and modernize its WLA. By eliminating manual job chains and replacing legacy scripts with standardized, centralized automation, Centric increased visibility across end-to-end processes and significantly reduced errors. Unifying orchestration improved operational efficiency and positioned Centric to adopt AI-driven forecasting and planning tools without needing to overhaul its backend infrastructure.

Rather than being a bolt-on scheduler, RunMyJobs builds automation fabrics that prepare your SAP environment for embedded AI and intelligent processes.

AI-ready businesses don’t wait

SAP’s future is already unfolding, and AI is at the center. But its effectiveness depends on the quality and timing of your automation. If your job scheduling can’t keep up, neither will your strategy. The decisions you make now will determine whether your organization will be ready to act on AI opportunities or stay stuck reacting due to technical limitations.

Modernizing your ERP isn’t enough. You need an orchestration layer that aligns with SAP’s direction, accelerates transformation and eliminates risk. RunMyJobs gives you that edge.

When your automation is fit-to-suite, your business is fit for the AI future. Explore how RunMyJobs future-proofs your SAP ecosystem.

The business case was clear for moving to a cloud-native WLA solution. But the clock was ticking. With just three months before their existing contract expired, the company needed to evaluate new platforms, prepare for migration and go live in that tight timeframe without disrupting critical business operations.

That’s when they turned to Redwood.

Our team of migration experts quickly mobilized, leaning on Redwood’s proven methodology, cloud-native platform and proprietary migration tools. We helped this company not only meet their deadline, migrating from a legacy platform in just 14 weeks, but also use the migration as a strategic opportunity to improve automation processes, retire technical debt and set the stage for long-term success in the cloud.

This isn’t an edge case. Whether you’re facing similar licensing deadlines, preparing for a RISE with SAP transformation or simply looking to modernize a fragmented automation landscape, you’re not alone — and you don’t have to start from scratch.

At Redwood, we understand that migration isn’t just a technical change. It’s your chance to rethink how automation supports your business and make sure you’re ready for what the future brings.

Speed is essential — but so is strategy

Time constraints are common in these scenarios. Redwood frequently works with organizations facing license renewals that force a go/no-go decision, RISE with SAP transitions that require cloud-readiness and/or internal mandates for tool consolidation and legacy system modernization.

These deadlines create urgency, but a rushed migration without strategy leads to risk. It can carry over inefficiencies and complications into your next-generation platform. Too often, we see companies fall into the trap of replatforming without rethinking.

In our experience, there are two primary mindsets when it comes to WLA migration:

1. Lift-and-shift first, optimize later: Move jobs as-is to meet tight deadlines, with plans to modernize after go-live.
2. Modernize as you move: Take the opportunity to streamline architecture, remove redundancies and improve process logic as you migrate.

Most organizations fall somewhere in between, and that’s exactly why Redwood approaches migration by tailoring it to your environment, not a one-size-fits-all script.

Migration as momentum: Essential considerations

• What kind of change are you driving? Are you simply replicating jobs or using this transition to streamline, modernize and reduce complexity?
• How will you optimize the new platform? Are you planning for better performance and improved reliability from the start?
• Is your automation strategy aligned with broader goals? Will the migration support larger initiatives like cloud adoption, tool consolidation or SAP transformation?
• Who needs to be involved: Are departments, service providers or external teams part of the process, and are they looped in early?

Redwood evaluates your:

• Source platform and job volume
• Critical business processes and dependencies
• Timeline flexibility and go-live constraints
• Appetite for technical debt cleanup

This ensures we don’t just recreate your existing environment but deliver a better one.

Specialized migration expertise = smarter, faster results

Rather than thinking of migration as a one-time event, consider it the start of a smarter operating model. Redwood’s Professional Services team brings decades of experience helping enterprises like yours transition from legacy WLA platforms to our modern, cloud-native solution, RunMyJobs by Redwood. Here’s what that means for your business.

IT infrastructure savings

Migrating off legacy systems sooner lets you decommission outdated infrastructure, eliminate those redundant support contracts and reduce operational overhead. This is especially important if you’re heading toward hybrid or full cloud adoption.

Business process improvements

We don’t just move your jobs; we evaluate them. During migration, we help you identify inefficiencies, unnecessary handoffs and outdated dependencies. This is your chance to streamline.

Operational efficiencies

Redwood provides pre-built templates, connectors and industry best practices to fast-track implementation. These accelerators and our unique testing frameworks help you get to production faster.

Modernize on your terms

Migrating to a new WLA solution involves much more than moving scripts or job chains. Your goal should be to enable a new level of orchestration across your enterprise. That’s why it pays to work with a partner who specializes in this exact domain.

Redwood’s Professional Services team is focused solely on successful automation implementations. We offer:

• Proven methodologies for assessment, migration and rollout
• Proprietary tools to streamline job mapping, testing and cutover
• Flexibility to adjust your scope in real time
• Risk mitigation with detailed validation and go-live readiness
• Post-migration services to keep advancing your automation maturity
• Training and enablement via Redwood University

At Redwood, we don’t just bring technology. We also offer unmatched focus, tools and experience. Organizations across industries have trusted Redwood to help them leave behind legacy WLA platforms. 

If you’re feeling the pressure of an expiring contract, a cloud deadline or a business that’s outgrown your current WLA solution, Redwood’s proven migration approach is here to move you forward with a clear vision. 

Hear directly from Daniel Sivar, Technologist at American Water, about how Redwood guided the largest regulated water and wastewater utility company in the United States through “managed waves” to ensure a successful migration.

AI was simply everywhere at this year’s events. From Christian Klein’s keynote to the show floor demos, it was the foundation of nearly every conversation. But beneath the buzzwords and bold visions, I noticed one question kept surfacing: How do you actually do it? How do you make AI actionable inside the day-to-day workings of an enterprise?

That’s the question we were thinking about at the Redwood Software booth and in our customer sessions and roundtables. It was fantastic to see the energy this year: standing-room-only demos, deep discussions with IT and business leaders and a steady stream of customers stopping by to share what they’re already doing with job scheduling, orchestration and workload automation (WLA). The excitement was real, but the deeper story was about who’s already rolling up their sleeves instead of just dreaming about digital transformation that actually realizes the value of AI.

Redwood was proud to be recognized for the second year in a row with the SAP Pinnacle Award in a category honoring innovative partners that provide economically relevant solutions, validating our ability to consistently drive high adoption and ROI for SAP customers. We also announced that RunMyJobs by Redwood is now an SAP Endorsed App, Premium certified — the highest level of SAP verification, indicating outstanding customer value. 

The best part? We’re not talking in hypotheticals. These milestones are a testament to the real-world outcomes our customers achieve when integrating with the latest SAP technologies, maximizing the value of their SAP investment. We saw that in full color in sessions and roundtable discussions with RS Group and others, whose teams shared striking results they’ve achieved using RunMyJobs. They haven’t been waiting for the AI wave. Instead, they’ve been preparing for it by modernizing their WLA. And it’s paying off.

We’re making business AI real as we drive digital transformations that help customers thrive in an increasingly unpredictable world. 

Christian Klein, CEO of SAP

Klein’s sentiment rang true throughout the event, especially his keynote theme: To thrive in an AI-powered world, it’s not enough to modernize ERP. Foundational processes, especially the ones running behind the scenes, must be intelligent, agile and orchestrated. WLA platforms like RunMyJobs are already doing the work of preparing SAP landscapes for AI by coordinating processes end to end, orchestrating the tasks that drive efficient data pipelines and ensuring the reliability that AI output depends on.

Redwood customers leading the charge

SAP made it clear: the future isn’t about cobbling together best-of-breed tools. It’s about building a smart, cohesive suite. That suite extends beyond core ERP to include the applications and automation fabrics that make an entire business run. Redwood customers are already there.

RunMyJobs isn’t a standalone job scheduler. It’s the connective tissue for automation fabrics across SAP and non-SAP systems, delivering the kind of real-time orchestration that complex, data-intensive environments demand. Redwood’s shared product vision with SAP is helping customers optimize operations to scale with AI. That alignment is also what earned RunMyJobs its SAP Endorsed App status.

We spotlighted compelling Redwood customer stories at SAP Sapphire this year, including the following.

RS Group: Transforming global supply chain operations for a demanding market

As a global industrial distributor, RS Group faces an unforgiving supply chain environment. Before RunMyJobs, they couldn’t even run business operations processing (BOP) daily for all 26 markets they serve. The complexity was enormous. They had to stagger market runs, which put customer promises, such as delivery timelines, at risk.

Using RunMyJobs to re-engineer processes and workstreams and optimize job logic, they now run BOP for all 26 markets daily. 

We now meet our promise to our business and customers. 

Dharmesh Patel, Head of SAP Development & Services, RS Group

But that was only the beginning. Previously, RS Group faced issues with poor monitoring, alerting and visibility, leading to frequent Priority 1 (P1) and Priority 2 (P2) incidents in critical operations like order processing and warehouse management. With RunMyJobs, they introduced custom alerting, rebuilt job frameworks and created a governance model for continuous improvement.

This isn’t just operational success. It’s setting the stage for AI readiness, because AI needs more than just access to data. It needs reliable, actionable data at the right time, integrated into the processes that power the business. RS Group is ready. When you run a global supply chain, “ready” isn’t a luxury.

Ready on day 1: How fit-to-suite automation prepares you for the AI future

The real takeaway from SAP Sapphire wasn’t that AI is coming. It’s that AI is already here, and the companies reaping the benefits are the ones that did the foundational work early. Redwood customers like RS Group have already modernized their WLA. They’re not bolting on AI. They’re ready for what’s happening now and what’s to come because their automation is fit-to-suite: deeply integrated, spanning SAP and non-SAP systems and built for scale and AI innovation.

RunMyJobs provides the automation fabrics enterprises need to orchestrate complex, cross-system workflows and support the data pipelines AI depends on. It connects SAP S/4HANA to the hybrid architectures, business process layers and related data AI needs to drive better, faster decisions and more efficient attainment of business outcomes.

When your business runs on well-managed, intelligent processes, you don’t just hope your AI strategy will work — you know it can.

An obvious and undeniable message of SAP Sapphire 2025? WLA modernization isn’t a side project. It’s a prerequisite. See how Redwood supports SAP customers in future-proofing their ecosystems.

This is apparent in recent headlines. For example, JPMorgan Chase has ambitiously invested in AI, building a team of over 2,000 AI experts and developing proprietary models to improve everything from fraud detection to investment advice. But the story underneath the surface is just as important. 

Bold bets can only be made from a solid foundation. Before any AI, analytics or digital transformation initiative can succeed, the data behind it must be clean, connected and controlled. Leading financial services firms recognize these initiatives can only deliver value when the data feeding them is complete, synchronized and auditable. 

In an environment where transactions span mainframes, SAP systems, cloud platforms and best-of-breed specialty tools, orchestrating data flows rather than just integrating endpoints becomes the competitive differentiator. Instead of adding more tools, you need to build better pipelines. Your filings, financial statements and liquidity metrics are too critical to allow stale, inconsistent and siloed data to inform them. 

The more orchestrated your data movement, the faster and safer your institution can move. Whether you manage $5 billion or $500 billion, orchestration supports financial close acceleration, real-time risk aggregation and ongoing compliance with evolving regulations.

And it’s achievable now.

The stakes are higher in finance

Whereas it would be a mere efficiency problem in some industries, data friction in financial services is a major business risk. When your systems operate in silos or on rigid schedules, you open the door to fines, missed cutoffs, extended close cycles, customer dissatisfaction and other negative outcomes.

Meanwhile, the AI and analytics platforms you’re investing in, from SAP Business Technology Platform (BTP) to Azure, Databricks and beyond, can’t deliver value if the pipelines feeding them are delayed, error-prone or unverifiable. Precision and timing are non-negotiable when you’re dealing with the precious numbers that impact the lives and livelihoods of your valued stakeholders.

From static pipelines to dynamic orchestration

Despite years of modernization efforts, many financial institutions have invested heavily in connecting systems via APIs, ETL pipelines or middleware. These integrations were a necessary step, as they enabled data movement between SAP S/4HANA, legacy mainframes, cloud data warehouses, CRMs and more. But whether data moves isn’t the question; it’s whether it moves correctly, completely and in sync with the events that drive your business.

Without considering this connectivity and complexity, you’ll lack event-driven control, data validation checkpoints, dependency management and real-time recovery, among other key capabilities. An intelligent orchestration layer addresses these gaps, especially if, like most financial operations, yours operates across a hybrid mix:

• SAP S/4HANA or SAP Central Finance
• Legacy mainframes for core banking or policy systems
• Cloud data warehouses and analytics platforms
• CRMs like Salesforce 
• Risk engines, actuarial systems, customer applications and partner ecosystems

It’s important to have a living nervous system connecting it all. A foundation that can monitor, react and adapt automatically across SAP and non-SAP systems will help you meet ballooning expectations brought about by AI, evolving regulations and more industry-specific factors.

True data pipeline enablement requires the ability to:

• Trigger workloads across SAP, cloud and legacy systems based on real events instead of static schedules
• Validate and sequence data automatically — delaying or rerouting jobs until quality gates are cleared
• Coordinate ML model execution tied directly to upstream data pipelines, whether scoring loans, recalculating provisions or updating liquidity forecasts
• Automatically log, track and retry processes to maintain auditability and meet SLA commitments
• Push structured, enriched datasets to SAP Analytics Cloud, Microsoft Power BI and other downstream consumers

Orchestration makes this possible. It doesn’t replace your SAP platforms, APIs, data lakes or CRM systems. It connects and governs the financial data flowing between them, automatically and intelligently. And AI and compliance-readiness depend on this very orchestration.

Building an efficient automation fabric around everyday financial processes

Your organization lives and dies by its ability to respond to change, and it all begins with having every dataset, account and rate positioned correctly from the outset. An automation fabric is the layer that connects and synchronizes your tools, data sources and processes across your IT environment, no matter how complex it is.

Setting your entire organization up for resilience begins with the first transaction of the day. Here’s what orchestrated start-of-day financial operations can look like with a secure, advanced workload automation platform as your control layer.

Ledger updates and overnight postings

• Finalize overnight processes — interest accruals, FX revaluations, journal entries — using SAP Financial Accounting (FI) and SAP Treasury and Risk Management (TRM)
• Validate completion of all wrap-up jobs
• Check dependencies and prevent downstream jobs if failures are detected

Balance reconciliation

• Trigger FF_5 to import bank statements
• Run matching logic and update general ledger balances
• Launch ML cash application processes in SAP Cash Application (Cash App)
• Automatically alert stakeholders about missing files and manage escalation workflows

Opening balances and cash positioning

• Refresh One Exposure hub with new data
• Load memo records and run liquidity forecasts in SAP Cash Management
• Pull FX rates, payment maturities and treasury forecasts from SAP TRM

Data loading for exchange rates and market data

• Import daily FX rates and market indices into SAP tables
• Validate values against prior-day data
• Alert treasury and risk teams of major discrepancies that could impact valuations or cash forecasts

Risk checks and exposure updates

• Run FX valuation jobs
• Generate treasury dashboards in SAP Analytics Cloud (SAC)
• Monitor for trading limit exceptions and notify teams automatically

System readiness and transaction processing enablement

• Execute standing instructions and direct debits in SAP Banking Services
• Generate payment proposals (e.g., F110, APM)
• Route for approvals via SAP Bank Communication Management (BCM) and transmit to banks
• Monitor acknowledgments and update One Exposure with outgoing flows

Every step is timestamped, validated and fully auditable, so you’re ready to operate at full speed from the first minute of the business day. Your firm can create resilient, auditable pipelines, reduce risk, enable AI and advanced analytics and scale cross-system processes without adding complexity or risk.

RunMyJobs ensures readiness across SAP FI, TRM, BCM and external systems while automatically triggering ETL pipelines once jobs complete and feeding analytics platforms like Databricks, SAC, Tableau or Power BI.

Harnessing the orchestrated advantage for hybrid environments

Financial institutions have long recognized the importance of data. However, the sheer volume, velocity and variety of financial data are exploding. Fueled by real-time event streams, the proliferation of APIs and embedded finance, plus an increasing reliance on AI-driven insights, the data landscape is becoming exponentially more complex.

The future demands a fundamentally different approach to managing this ever-growing tide. Intelligent automation and orchestration are essential for building a resilient foundation capable of handling the dynamic and interconnected nature of tomorrow’s financial operations. 

To navigate an expanding hybrid data landscape effectively, you must build a robust orchestration layer that ensures data integrity, auditability and observability across all systems.

Read more about how to get your data out of the modern-day maze.

Despite an optimized IT infrastructure and cloud environment, the simulation doesn’t start because the latest compound batch data hasn’t been validated in SAP. The experiment metadata is still siloed in spreadsheets, and the model can’t ingest incomplete or inconsistent values. In other words, the fluid connection required between systems isn’t there.

As you may well know if you work in this industry, this isn’t a hypothetical delay. Data readiness can’t be treated as a side task, although it too often is. In which case, it doesn’t matter how advanced an AI model you have. With regulatory pressures high, the cost of a subtle misalignment is steep.

Because this applies whether you’re simulating compounds, ensuring patient records are anonymized and audit-ready or forecasting inventory, critical processes break down when data stays disconnected. Leading healthcare and pharmaceutical organizations are attempting to solve this common problem by rethinking how data moves from SAP to ML platforms to analytics and back.

Life science’s parallel pipelines: Innovation and execution

In life sciences organizations like yours, innovation happens on two fronts. On one side, your R&D teams use AI and massive datasets to accelerate discovery. ML models in AWS SageMaker or Schrödinger Suite predict promising compound structures, while simulation platforms test toxicity and efficacy before running a single experiment.

On the other side, your clinical and supply chain teams ensure those discoveries reach patients safely and cost-effectively while following all compliance regulations. They manage everything from patient enrollment to cold chain logistics to regulatory filing, with each process powered by SAP supply chain and life sciences solutions and custom platforms.

These processes live in very different domains, but they share a common dependency: structured, timely, accurate data. And in too many organizations, that data still moves manually or asynchronously between systems.

Where the cracks appear 

When SAP data isn’t orchestrated, critical handoffs break down and molecular data must be manually pulled from SAP R&D Management to feed AI pipelines. Trial operations build forecasts on outdated enrollment data. Lab results live in one system and regulatory documentation in another, with no feedback loop. Business users wait on IT to reconcile siloed datasets and generate reports.

Drug discovery is increasingly computational, but that doesn’t mean the work is fully automated. Whether you’re managing experiments or kits, the pain is the same: unreliable flow, lost time and elevated risk. Without intelligent orchestration, pipelines either fall apart or deliver fragmented, stale information. This directly undermines the performance of AI models and introduces bias or neglects to provide key correlations. Essentially, you end up making decisions with outdated datasets — or worse, hallucinations. Predictive models built to accelerate discovery or optimize trial logistics can quickly fall out of compliance with data lineage and validation requirements.

Meanwhile, if you cling to these fragmented or manually stitched data pipelines, you face another growing disadvantage: You can’t match the speed of your competitors. Those who are investing in intelligent, adaptive data orchestration are moving faster while proving the trustworthiness of their AI-driven insights.

High-fidelity orchestration is the foundation of competitive agility and relevance in your industry.

Research, meet orchestration

Orchestration is what makes AI scale in R&D. Your SAP environment becomes the launchpad for faster, smarter research, enabling you to:

• Continuously extract experimental and batch data from SAP R&D Management and SAP Analytics Cloud 
• Send compound specs to AWS SageMaker or Schrödinger Suite for modeling
• Coordinate modeling jobs and return results to Databricks for consolidation
• Push insight summaries about ranked candiddates back into SAP
• Trigger alerts for research leads of successful outcomes or red flags and send validated results to SAP Datasphere

Clinical delivery, intelligently aligned

On the delivery side, timing is everything. Clinical trial operations depend on up-to-date patient enrollment data, trial protocols and inventory levels across distributed trial sites. If systems aren’t aligned, sites risk running out of supplies or holding expired stock.

With proper orchestration:

• Enrollment data from SAP Intelligent Clinical Supply Management flows into forecasting tools
• ML models in Azure ML or Databricks predict site-specific demand
• Stock levels in SAP Integrated Business Planning (IBP) or S/4HANA Materials Management (MM) are cross-checked automatically
• If risk is flagged, replenishment is triggered and stakeholders are notified
• Trial performance metrics update automatically in SAP Analytics Cloud
• All data is centralized in SAP Business Data Cloud (BDC) for regulatory compliance and real-time insight

A research-to-treatment automation fabric

True transformation comes when discovery and delivery are both orchestrated from end to end. Here’s what a real automation fabric looks like.

Forecasting clinical and manufacturing needs

• Export enrollment or order data from SAP S/4HANA
• Clean and enrich using SAP Datasphere
• Run predictive models via Databricks, Azure ML or SageMaker
• Feed outputs into SAP IBP for dynamic planning

Managing research and validation 

• Extract compound data from SAP R&D Management
• Coordinate modeling jobs in Schrödinger Suite
• Score and validate candidates in Databricks
• Trigger SAP updates and notify research teams automatically

Controlling inventory and site logistics

• Pull inventory positions from S/4HANA
• Reconcile with forecasted site needs from SAP IBP and ML pipelines
• Generate and dispatch replenishment orders
• Publish everything in SAP Analytics Cloud for transparency

Keeping teams informed and aligned

• Push alerts to supply, clinical or research leads based on process outcomes
• Route structured datasets to reporting dashboards and compliance archives
• Automate audit trails, approvals and next-step triggers

With every step validated, timestamped and secure thanks to RunMyJobs by Redwood, your data flows continuously, allowing you to be proactive instead of reactive.

Audit-ready AI depends on orchestrated data

The rise of AI in life sciences is helping to optimize molecule screening and clinical trial site selection and even personalize patient communications. With that power comes increasing scrutiny.

Regulators are watching closely. Health authorities in the United States, European Union and beyond are issuing new guidelines around AI in clinical decision-making, digital therapeutics and research applications. They want to know: Where did the data come from? Was it anonymized? Who validated it? And can you prove it?

If your data pipelines are fragmented, those answers may simply not exist. But orchestration changes that. When you automate your data moving from SAP modules to Azure ML or from SAP Datasphere to regulatory systems, you also create a system of record. Every dataset has a timestamp, and every transformation is traceable. This strategically enables AI innovation.

The next wave of advancement will hinge on more than modeling accuracy; you’ll need to be able to explain how your model was built or prove the integrity of the data behind it. With the right orchestration solution, you don’t have to choose between speed and control. You can stay audit-ready and future-ready.

Develop a resilient nervous system

Think of your systems like organs. Each one serves a distinct purpose, but they communicate via signals that travel through connective tissue. These signals are orchestration in action!

Want to know more about orchestrating SAP data with RunMyJobs? Read more about using the SAP Analytics Cloud connector.

Analytics power nearly every strategic business decision, but only when they’re delivered in context, on time and aligned with the end-to-end processes and stakeholders they’re meant to inform. That’s why forward-looking insights are no longer optional.

Whether you need to spot cash flow risks before they affect liquidity, adjust production plans before disruptions ripple downstream or re-forecast inventory before you notice a sales dip, your ability to predict and respond depends on analytics that move with your operations.

SAP Analytics Cloud (SAC) was built for exactly this kind of intelligent analysis, forecasting and agile planning. It brings together business intelligence, planning and predictive analytics in one place so you can always know where you stand and model future scenarios to be ready for what’s coming instead of what has just occurred.

But insights alone don’t create outcomes. Unless they’re integrated into an operational process, even the most advanced insights can’t drive impact. Worst case, they could guide you to wrong decisions and negative consequences.

The hidden liability of siloed analytics

Even in a powerful, cloud-based platform, analytics can still fall out of step with the business. Your systems might be automatically refreshing and publishing dashboards or verifying outputs, but if they’re doing so while disconnected from your end-to-end processes, you won’t be able to apply these outputs meaningfully to your role.

You shouldn’t have to wonder whether your numbers reflect just a small snapshot of what’s happening or the full sequence of updates across systems. That uncertainty chips away at trust, and it’s more than frustrating. It’s costly.

Take a high-stakes industry like manufacturing, in which a day-old production forecast can misalign plant operations with actual demand. Or healthcare, where even brief gaps in staffing or patient volume data can impact care and compliance. Siloed analytics workflows aren’t useful or timely in supporting complex, mission-critical processes that need to run continuously.

SAP Analytics Cloud: Built for insights, ready for orchestration

SAC is already a strategic hub for business insights. It connects natively to SAP S/4HANA, SAP Datasphere, SAP BusinessObjects and Databricks. It helps unify planning and analysis across departments and roles. But what transforms SAC from a great tool into an essential one is where it fits in the big picture of your business.

Think about it this way: SAC tells you what’s happening or what’s about to happen. It can publish dashboards and refresh models on a schedule, but to act on those insights in time, you need analytics to match the continuous rhythm of your operations instead of sitting still. 

Orchestration with an advanced workload automation platform can embed those steps inside complex, multi-step job chains that include dozens of tasks, from ETL and ERP updates to file transfers, reconciliations, condition checks or even alert triggers. Reports can be triggered by events, conditions or thresholds from within SAP or external systems, then distributed, published or escalated based on logic.

Instead of standalone data, you get analytics in motion. What does this look like in the real world?

• A multi-step financial close process automatically refreshes and publishes the appropriate dashboards at each stage as part of the normal process chain of the closing cycle — without needing to be managed in a separate analytics workstream
• A disruption in supply chain data from SAP S/4HANA or SAP Datasphere triggers a refresh of demand forecast models in SAC as part of your continuous supply chain processes
• Executive dashboards are scheduled within a larger workstream to update nightly and adjust to special schedules around holidays, peak seasons or system maintenance windows

These reports don’t stay isolated. They’re embedded in your broader business workflows and reacting to real-world conditions. In other words, they align with your operational priorities.

What full automation delivers

With SAC jobs built into your end-to-end business processes, you see the value compound across your organization.

There won’t be a need for separate analytics workstreams anymore. Dashboards and models, connected to your end-to-end processes, will update based on the logic you define at the cadence your business needs.

Analytics will follow the pace of your business, not the other way around. That means your leadership team can get ahead of issues and make proactive decisions. Everyone will see the same numbers, which are built on the same trusted foundation.

Instead of ad-hoc report refreshes or support tickets, your analytics will run as part of a monitored, auditable job chain, giving your key stakeholders insights as they happen in the everyday flow of business.

Ultimately, you’ll be automating business readiness — not just accurate or timely reporting.

Making insights flow: SAP Analytics Cloud + RunMyJobs by Redwood

The new RunMyJobs connector for SAP Analytics Cloud makes it easy to orchestrate your analytics processes within broader, mission-critical job chains without adding complexity or rework.

With the connector, you can:

• Include SAC alongside ETL jobs, S/4HANA transactions, file transfers or external alerts
• Monitor your analytics within each complete job chain from a single pane of glass
• Refresh and publish reports automatically as tasks in end-to-end process rather than siloed triggers
• Tie analytics tasks to business events, conditions or schedules from SAP and non-SAP systems

There’s no need to replace SAC’s native scheduling functionality. With RunMyJobs, you elevate its capabilities by embedding them into more complex and interdependent processes. SAC gives you top-notch insight, and RunMyJobs makes sure it’s delivered at the tempo you need and as part of the complete picture.

Know what’s happening and be ready to act on it. Explore more about how to orchestrate your SAP data pipelines with RunMyJobs.

It means usage is spiking across the grid. Smart meters are flooding in data every 15 minutes, or faster. Restoration events from a recent storm haven’t fully cleared, and your billing engine is about to get overloaded. You know that if even one upstream dataset is missing or incorrect, your rates won’t calculate properly. And if you don’t hit billing SLAs, your call centers will be overwhelmed due to frustrated customers, cash flow will take a hit and revenue recognition will fall days or weeks behind.

In this moment, what matters isn’t just the data you’re collecting but how efficiently and cleanly it moves through your systems, from AMI and CRM to SAP Industry Solution for Utilities (IS-U) and billing. That’s why data orchestration isn’t a luxury. When the weather shifts, your systems have to shift with it automatically.

Data handoff: The origins of bottlenecks in utility billing pipelines 

The journey from meter to money sounds simple on paper: collect usage data, calculate the bill, send the invoice and match it against incoming customer payments. But anyone working behind the scenes knows it’s far more complex. Between raw data and revenue is a sprawling digital ecosystem that spans:

• Smart meters and AMI platforms 
• Distribution systems that track service status, outages and restoration events
• CRM and customer service tools
• SAP IS-U or SAP S/4HANA environments that handle contracts, rate logic, billing and cash application
• Regulatory platforms and reporting systems

Each system excels at its job, but without frictionless orchestration, the handoffs between them are prone to failure. If meter data arrives late or out of sequence, you’re forced to estimate usage. If a service status update doesn’t land on time, billing logic may misfire. And if downstream systems don’t receive validated, structured consumption data, bills can’t go out.

Common consequences include inaccurate or estimated billing, SLA violations, delayed revenue recognition, failed compliance reporting, cash flow shortfalls and surging call volumes from disgruntled customers. Thus, it’s not just the billing team that feels it. When meter data is delayed or incomplete, every part of your operation experiences the fallout: Customer Service, Finance, Compliance and other departments. 

A system that only works when nothing changes won’t cut it in an industry where change is constant.

Orchestration over integration

To build resilience, many utilities are investing in smarter, more connected data ecosystems. Platforms like SAP Business Data Cloud, which combines the power of SAP Datasphere, SAP Analytics Cloud and Databricks, make it easier to layer analytics and AI on top of operational consumption data. But the value of those platforms depends entirely on the quality, timing, structure and completeness of the data they receive.

Connection alone can’t guarantee this data will always be right and show up when and where it needs to. A modern automation fabric, a high-fidelity method of controlling and monitoring your data across SAP and non-SAP systems, validates each task and activity required to move data through each step of the pipeline and routes it to the right destination. It only triggers the next process when quality and other key thresholds are met.

Build your M2C automation fabric

Your billing pipeline can only move as fast as your data pipeline does. An automation fabric carries your data on an effortless journey from the first smart meter reading to the final bill.

Here’s what a unified, orchestrated utility billing pipeline can look like.

Usage data ingestion and validation

• Ingest raw meter data from AMI systems and IoT platforms
• Estimate consumption where smart meter reads are missing, using SAP IS-U meter reading logic
• Use tools like Databricks or Azure Synapse to pre-process high-volume raw readings and identify anomalies
• Trigger alerts if data doesn’t meet billing quality thresholds
• Send validated readings to SAP Datasphere for context-aware enrichment

Transformation and billing preparation

• Trigger mass activity billing document creation via SAP IS-U
• Trigger SAP IS-U to generate usage records, apply pricing and finalize billing logic with SAP Financial Contract Accounting (FI-CA)
• Ensure all required meter data and service status information is available before SAP billing runs start
• Standardize formats and units across devices, systems and regions
• Load cleaned datasets into SAP IS-U or S/4HANA and apply rate structures and SAP FI-CA contract logic

Bank clearing and revenue processing

• Execute SAP IS-U bank clearing by applying clearing locks, posting incoming payments and cash receipts and processing prepaid invoicing and credit card transactions
• Initiate billing cycles in SAP only after the prerequisite datasets are verified and complete
• Use event-driven orchestration to delay or reroute processes when exceptions are flagged
• Automatically generate audit trails and trigger alerts for missing, duplicated or stale data
• Route usage summaries and cost breakdowns to SAP Analytics Cloud, Power BI or Databricks for reporting and forecasting

Downstream system and stakeholder updates

• Feed final billing and payment data to SAP Analytics Cloud and Databricks for forecasting and reporting
• Feed structured data into SAP Datasphere and cloud storage for compliance reporting and AI model training
• Push finalized consumption and billing data to SAP FI-CA and S/4HANA for cash application
• Notify customer service teams of exceptions or late accounts via CRM updates before customers call in

When your data is orchestrated with this level of fidelity, your utility company becomes more agile and competitive. Faster billing cycles, fewer disputes and more accurate forecasts translate into better customer experiences and stronger financial outcomes.

Bonus: Powering grid modernization

The same orchestration fabric that streamlines your billing operations can also unlock faster, more accurate decision-making for your capital grid projects. Whether you’re expanding substation capacity or reinforcing the grid in anticipation of extreme weather, the ability to ingest and align data from multiple sources is critical.

Grid investments require input from asset condition data, load forecasts, GIS platforms, outage logs, customer growth models and more. Orchestration helps unify those sources and validate data quality in real time, so planning and forecasting are always based on the most current and accurate inputs.

RunMyJobs can coordinate data management across SAP, GIS systems, project management tools and platforms like SAP Datasphere and Databricks to:

• Prioritize capital spend based on risk modeling
• Synchronize rate impact data with financial planning and regulatory reporting tools
• Route updated procurement or contractor schedules to SAP S/4HANA or project accounting and management models
• Feed structured data into dashboards and AI models for stakeholder transparency and “what-if” scenario modeling

As electrification demands surge from new demands like electric vehicles and AI-powered data centers, utilities need more than project plans. They need dynamic data pipelines that drive fast responses and grid resilience.

Your systems, in sync

RunMyJobs isn’t another system you have to bolt on. It’s a full orchestration platform purpose-built for SAP environments and particularly effective in highly regulated industries. Whether you’re using SAP IS-U, S/4HANA or hybrid systems, RunMyJobs can precisely coordinate your end-to-end data pipelines without adding overhead or risk.

Already a RunMyJobs customer? Download our pre-built M2C workflow template to accelerate your billing transformation.

Planning to attend SAP Sapphire Madrid 2025? Stop by booth #10.332 to see how utility providers are making the switch from fragmented data flows to end-to-end orchestration.

Now, imagine you’re only using the basic functions — driving, accelerating, braking. You’re getting where you need to go, but you’re not using cruise control, lane assist or advanced navigation. That’s what it’s like when a team adopts a powerful automation platform without fully investing in training. 

The car (the software) is fantastic, and it’s working, but there’s so much more it can do. A team of admins may have created basic automated tasks, transferred essential files and set up fundamental reports. But are they leveraging all the features that will help them achieve their goals? How much valuable time was spent setting up those rudimentary processes, and how often did they need to reach out to support or success teams to gain even minimal traction? 

This is where a “learning champion” can shift things into high gear.

We’ll explore how becoming a learning champion boosts your individual productivity and career and amplifies that effect across your team and organization, especially if you’re in the process of adopting automation.

Taking control: Why become a learning champion?

According to the Customer Education Trends in 2025 report from Skilljar, the modern learner has been thrown into an “everything, everywhere, all at once” environment, consuming self-paced content, articles, documentation and live support on their own terms and at their own pace.

While the flexibility to find information in the format that makes sense to you and without waiting to be assigned a course can feel empowering, it also adds complexity. When you consider the number of people who must learn a given skillset or platform, you can understand the nth-degree potential for confusion or frustration — an undesirable and non-scalable state.

Individual ownership matters, especially when you’re adopting complex or evolving tools like automation platforms. A learning champion becomes a catalyst for team efficiency and organizational progress.

Elevate personal productivity

Proactive learners make fewer basic errors, reduce support tickets and implement automation faster.  Plus, upskilling a team contributes to business agility. As BytePlus notes, “Employees with diverse, updated skills can adapt more quickly to technological and market changes.”

Quick tip: Gauge your starting point. How long does it take you to complete a process? How often are you asking for help? Once you complete training, measure again. You’ll see tangible signs of your growth, and so will others. Share these insights with your team and manager to make the case for upskilling.

Advance your career with certification

Becoming a learning champion isn’t just about helping your team; it’s a smart career move. Achieving certification, especially in complex automation software, validates your expertise and positions you as a subject matter expert. It signals to your organization (and future employers) that you’re not just using the tool but owning it.

Certifications in automation software demonstrate that you can do more than execute tasks: You can understand workflows, configure processes and lead others. For example, the Automation Developer Specialist Certification from Redwood University challenges your understanding of advanced functions, complex workflow automation and process scheduling best practices. Users with this certification leverage their deep knowledge of the software to drive transformation instead of just reacting to the tool. 

The initiative can start during your onboarding: Learning champions don’t wait for permission to explore new things, and proactiveness is a quality your current leaders and future employers seek.

Quick tip: Ask about learning paths that align with your team and career goals, then dive in and get started. Share feedback with your immediate team on how the material helped you. Post your new credential on LinkedIn for wider reach.

Share what you learn

Knowledge is best when shared widely and in ways that are digestible. As Skilljar puts it, “Educators are curating, not just creating.” Software vendors can offer a full library of content (like what you’ll find in Redwood University), but it’s up to learners to enroll, complete lessons and share their knowledge.

Whether you’re forwarding helpful documentation, recommending training courses or showing a colleague how to fix a recurring issue, you become the go-to person. Don’t stop there. Your goal should be to elevate yourself AND others. A lone learning champion is a great start, but real efficiency comes when your whole team levels up.

Quick tip: Create a “Top 3 takeaways” list after every course you complete and email them to your team. Keep it light, useful and actionable.

The impact of software education on team productivity

A well-trained team is a fast team. When many users understand how to leverage automation software fully, you get better data, fewer bottlenecks and less reliance on external support.

In other words, you’re making the most of your investment. 

According to TSIA, product adoption is a key business metric. Leaders expect returns on software purchases, and ongoing, quality training is how you get there.

The real power of education becomes clear when users go beyond the fundamentals of process automation. Too often, users are taught just enough to complete their tasks. But it’s essential to go deeper: to grasp why a process works the way it does, where automation eliminates inefficiencies and how to extend those benefits across other business processes.

This level of knowledge comes from hands-on experience — working through real use cases, experimenting in a safe environment and applying lessons immediately to daily work. If you discover a faster way to automate a handoff between departments, for example, you’re building consistency and making sure everyone is working from the same playbook.

Build a culture of curiosity

When one person steps up, others follow. A team that values education creates a ripple effect. Questions become learning moments, and continuous improvement becomes the norm.

That kind of culture pays off. 

BytePlus emphasizes an SHRM stat: Replacing a single employee can cost up to 200% of their salary. Investing in learning reduces turnover and keeps your best people engaged and growing.

Bonus: Training builds loyalty. A team that learns together stays together.

Be the spark

Investing time in learning pays off at every level, from your own growth to company-wide productivity.

You gain:

• The confidence to navigate the software
• Mastery of tools that drive automation
• Speed and accuracy in your day-to-day work
• Recognition as a subject matter expert
• Momentum to shape your career path

Your organization gains:

• Stronger product adoption rates
• Greater ROI
• A lesser need for IT intervention and manual workarounds
• Faster onboarding for new team members
• Reduced turnover due to better engagement and support for each role

Become a learning champion for your team’s Redwood Software products by utilizing Redwood University. It’s free and open to all customers and partners. Sign up today.

This is why observability is key. A concept originating from IT monitoring and AIOps, observability goes beyond simply monitoring what you think is important. It’s about being able to ask any question about your systems and understand their internal states based on the data they produce: logs, metrics and traces.

Applying observability principles to workload automation and Service Orchestration and Automation Platforms (SOAPs) can help you handle complexity and orchestrate peak performance in your mission-critical automation fabrics.

Automation is leveling up

Several key trends are driving the need for sophisticated automation. Industry 4.0 adoption, the relentless pursuit of supply chain resilience and the demand for real-time business intelligence all require a new level of powerful and transparent automation. 

This requires a new kind of automation. SOAP solutions play a critical role, enabling real-time coordination of smart devices and systems. They provide centralized control, from production schedules and quality checks to predictive maintenance. Automation platforms are empowering organizations to guarantee the reliability of intricate IT and business services at scale.

What observability really means

Observability is built on three core principles:

1. Telemetry: Gathering rich data from your systems. This means collecting logs, metrics and traces to capture every facet of their behavior.
2. Context: Adding meaningful information to this data. Understanding the relationships and dependencies between different components is crucial.
3. Exploration: Empowering you to ask any question and investigate system behavior, even questions you didn’t anticipate.

Unlike traditional monitoring, which focuses on predefined metrics and alerts, observability allows you to proactively investigate issues, identify root causes faster, improve system performance and enhance agility. It’s about moving from reactive firefighting to proactive optimization.

As the automation industry changes to adapt to new business models and an increase in technical and data complexity that shows no signs of slowing down, focusing on observability as a key concept in the automation space is critical.

Applying observability to workload automation and SOAP

Observability brings significant value to workload automation and SOAPs, turning abstract job chains into fully transparent systems. It gives operators and administrators the tools they need to answer key questions like: Which jobs are running late? Where is the bottleneck? What impact will a failed step have downstream?

Here’s how that looks in practice:

• Integration monitoring: Tracking the health and performance of integrations with other systems and applications, such as ERPs, CRMs and cloud services
• Job-level insights: Monitoring individual jobs or tasks within workflows, analyzing resource utilization, tracking error messages and measuring performance metrics
• Predictive analysis: Leveraging observability data to predict potential issues and optimize automation performance before disruptions occur
• Workflow visibility: Gaining deep insights into the execution of your automated workflows and understanding dependencies, tracking execution times and pinpointing success/failure rates

To effectively leverage observability, your workload automation or SOAP solution needs specific capabilities:

• Alerting and automation: Enable proactive alerting based on observability data and trigger automated actions to address issues.
• Contextualization: Enrich data with context using tags, metadata and workflow IDs for meaningful analysis.
• Data collection: Robustly collect detailed telemetry data (logs, metrics, traces) from all components of the automation platform and its integrations.
• Visualization and analysis: Provide powerful tools for visualizing observability data, creating dashboards and performing root cause analysis.

Consider these real-world examples.

Supply chain optimization 

By applying observability principles, organizations can gain end-to-end visibility into their complex supply chain workflows, tracking the execution of various automated procurement, manufacturing and logistics tasks. This deep insight allows them to pinpoint exactly where bottlenecks are occurring, such as delays in raw material processing or inefficiencies in distribution, ultimately unlocking hidden efficiency and ensuring greater supply chain resilience against disruptions.

Business process assurance

Observability provides the granular detail necessary for troubleshooting failures in critical business processes like order processing or financial transactions, going beyond simple error notifications to reveal the precise step and underlying cause of the issue within the automated workflow. By monitoring individual jobs and integrations involved in these processes, organizations can quickly identify whether a problem stems from a failing application connection, a data validation error or a resource constraint. Thus, it enables faster resolution and minimizes costly disruptions to essential business operations.

Resource efficiency

Through observability, organizations can monitor the resource utilization of individual automated tasks and workflows, gaining a clear understanding of CPU usage, memory consumption and I/O operations. This detail allows them to identify underutilized resources that can be reallocated or optimize the scheduling of resource-intensive jobs to avoid contention. The outcomes of wisely navigating complexity instead of letting it overtake operations? Improved overall efficiency and reduced operational costs.

Properly implemented, observability allows you to predict disruptions instead of reacting to them.

Knowing what’s about to happen: AI in observability and automation

With observability in place, automation becomes more than a set-it-and-forget-it system. AI is allowing businesses to use automation to highlight weak points, adapt to changes and continuously improve. Its integration with observability and automation platforms unlocks new levels of efficiency and intelligence.  

AI enhances observability with smart narratives for data views that enable deeper data exploration and deliver real-time operational insights. This empowers teams to orchestrate workflows in perfect harmony and predict bottlenecks before they happen.

AI-driven automation is also moving beyond simple task execution to more complex, autonomous operations. The near future will include AI that operates autonomously to optimize performance and resolve issues, collaborates with users to automate complex tasks and provides instant information and guidance.

By integrating AI, automation platforms are evolving to provide a seamless experience, taking users from data to insights to action in a single step.

Redwood Insights: Observability built for orchestration

The need for enhanced visibility and control is transforming how enterprises approach automation. It’s no longer enough to simply automate; applying observability principles to orchestrate critical business processes is essential for achieving operational excellence.

To address this, Redwood Software is introducing a new solution that empowers users to visualize every process in motion, predict bottlenecks and turn uncertainty into opportunity. Today, Redwood announced Redwood Insights, first being integrated into RunMyJobs by Redwood, a market-leading automation solution.

Redwood Insights will deliver:

• Role-based dashboards for operators and administrators
• Orchestration analytics that provide actionable intelligence
• AI features with smart narratives for data views and deeper data exploration
• Analytics and visualizations to identify problems and bottlenecks before they impact operations

Redwood Insights, integrated with RunMyJobs, enables users to visualize every process in motion, predict bottlenecks and turn uncertainty into opportunity. 

Applying observability to workload automation and SOAP offers a path from chaos to clarity. It empowers organizations to achieve autonomous transformation, optimize operations and thrive in a complex digital world.

With the launch of Redwood Insights, Redwood aims to transform automation from an opaque process into a transparent, self-healing ecosystem. By embracing observability and AI-driven insights, you can move from simply managing automation to truly orchestrating business harmony. 

Learn more about how Redwood’s automation solutions and Redwood Insights can help you harness the power of observability and AI to achieve precision, synchronization and harmony in your business operations.