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.

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.

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.

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.

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.

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.

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.

Despite significant investments in automation and AI, many organizations are still held back by siloed, piecemeal automations that create disconnected and inconsistent data pipelines. These approaches lack the fluidity to fuel AI-driven insights and require too much manual intervention.  Without a unified orchestration layer, efforts to build a scalable, responsive automation fabric hinder competitiveness and complicate transformation.

If your organization is forward-thinking, you’re embracing SAP S/4HANA, cloud analytics platforms and AI modeling to accelerate operations, reduce delays and adapt to rapid shifts in demand. But to extract the most value from these investments, you need more than endless integrations tied together haphazardly. 

You need an enterprise platform orchestrator: a high-fidelity orchestration engine that composes, controls and monitors automations across diverse systems. It enables precision execution of end-to-end processes across hybrid environments. All components of your tech stack operate in concert. 

Your intelligent enterprise automation strategy demands integrated orchestration across systems, data and processes to drive continuous innovation and resilience.

What happens when data moves too slowly — or not at all

Take the example of a global electronics manufacturer producing components for medical devices. Their assembly lines depend on just-in-time delivery of microcontrollers (MCUs), PCBs and specialized sensors. Shipments arrive in mixed formats, such as EDI feeds, CSV files and emailed spreadsheets, often on unpredictable schedules.

Without a coordinated schedule or event-based workflow, planners manually load supplier datasets into SAP S/4HANA or wait for nightly updates from a production database. That delay alone can lead to:

• Incorrect delivery forecasts
• Production runs scheduled based on outdated or incomplete material availability data
• Dashboards that show planned output without factoring in actual part shortages or late supplier updates
• Downtime due to missing or late components
• Costly last-minute procurement changes

If you’ve been there, you know the result: operational inefficiencies, ineffective decision-making and diminished overall equipment effectiveness (OEE).

A hybrid architecture requires a coordinated approach

Manufacturers embracing Industry 4.0 are investing in hybrid architectures and offerings like SAP Business Data Cloud, which unifies SAP Datasphere, SAP Analytics Cloud and Databricks, to combine data and AI for better decision-making and lower total cost of ownership (TCO). These platforms are powerful but only as effective as the pipelines feeding them.

Without reliable data movement, even the most advanced platforms underdeliver. If SAP Datasphere isn’t receiving clean, timely data, your analytics lose context. If Databricks or Azure Synapse don’t have access to the latest inputs, your AI models won’t reflect what’s really happening on the shop floor, hallucinating the output instead. And without orchestration, your planning, scheduling and reporting systems fall out of sync.

An automation fabric coordinates data collection, validation, enrichment, transfer, sharing and action across your manufacturing data landscape in real time. 

What modern, SAP-connected orchestration looks like

With event-driven, orchestrated workflows, your team can:

• Ingest supplier delivery updates instantly into SAP S/4HANA
• Validate and normalize part numbers, revision levels and order quantities
• Reduce production delays and quality issues caused by incorrect part numbers, outdated BOMs or mismatched supplier data — no more manual corrections mid-shift
• Automatically reschedule dependent production orders and notify planners
• Monitor for unexpected data issues and trigger alerts when data masking, formatting or validation fails
• Send production data to SAP Datasphere for modeling and enrichment
• Push cleaned datasets to Azure Synapse, Databricks or your data lake for AI/ML
• Use tools like SAP Analytics Cloud, Power BI or Tableau for real-time dashboards

From static reporting to real-time action

When processes are orchestrated properly, your production planners don’t wait for nightly refreshes. They work from real-time data on inbound logistics, material availability and work-in-progress status. They’re notified instantly when delivery schedules change or sensitive information like product specs don’t match the expected format.

And because data moves securely between systems, including staging in test environments and support for data masking where personally identifiable information is involved, your teams can trust what they’re looking at and make data-driven decisions faster. And when the global picture shifts — due to supply chain disruptions, tariffs or new regulations — orchestrated data pipelines help you reprice, reforecast and realign production schedules with agility.

Your team experiences quicker changeovers and optimized production runs and can access dashboards that reflect actual operational data and an accurate balance of demand vs. capacity rather than assumptions. You need far less manual intervention in both the production and test environments, and you’ll improve data governance across all production datasets. All of this gives you stronger support for audit-readiness and regulatory compliance (including for government agencies).

See it in action: Hear from Energizer’s Business Systems Analyst how they ensured on-time delivery and reduced risk by optimizing their production planning using RunMyJobs by Redwood.

Build your plan-to-produce automation fabric

Building a connected automation fabric means more than just linking systems together. It means designing workflows that support smarter decisions, from material forecasts to machine-level execution, by delivering the right data to the right systems at the right time. This level of control becomes especially critical when the external environment shifts, affecting your sourcing, pricing or production.

Here’s how these orchestrated workflows take shape.

Demand forecasting

1. Export historical ERP data from SAP S/4HANA into SAP Datasphere for enrichment and transformation
2. Analyze demand trends using Azure Synapse, Databricks or your preferred data warehouse
3. Transform and load clean datasets into SAP IBP for demand planning and forecast modeling
4. Trigger workflow steps to notify key teams (e.g., sales, supply chain, production planning)
5. Automatically generate planning orders or proposals based on the updated forecast

Capacity planning

1. Calculate available machine and labor capacity using real-time data from SAP S/4HANA and connected MES and IoT systems
2. Run simulations in SAP Integrated Business Planning (IBP) to evaluate potential bottlenecks
3. Identify constraints and trigger automated alerts for planners to review or allocate resources
4. Push approved capacity plans downstream to support accurate materials and production scheduling

Materials resource planning (MRP)

1. Trigger a real-time inventory check and MRP run in SAP S/4HANA
2. Perform BOM calculations based on demand forecasts and order volumes
3. Launch a planning run that automatically determines material needs and timelines
4. Push results to SAP Datasphere for consolidation and enrichment
5. Feed updated datasets into SAP IBP to optimize production and procurement schedules

Production scheduling

1. Generate and dispatch production work orders in SAP S/4HANA
2. Assign machines, labor and tools based on live capacity data from connected systems
3. Integrate with SAP Manufacturing Execution (ME) or a third-party app for predictive scheduling and performance analysis

Shop floor operations

1. Track production progress and completion status in real time
2. Pull quality control results into centralized logs for data validation and reporting
3. Surface KPIs through SAP Analytics Cloud or Power BI dashboards for immediate insights

Updating stakeholders and systems

1. Automatically email warehouse teams with updated pick/pack instructions
2. Notify sales teams of expected delivery dates and inventory availability via Salesforce
3. Route relevant datasets to the data lake or warehouse for broader analytics or governance initiatives

Ready to orchestrate?

Already using RunMyJobs for your critical manufacturing processes? Download this convenient plan-to-produce workflow template to optimize further. 

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

That control translated into speed, agility and accuracy — attributes retail supply chains desperately need, especially today. Apple had end-to-end visibility over its production pipeline, and the result was a supply chain that could handle demand spikes and disruptions alike, without compromising quality.

What if you could apply the same mindset Cook used to optimize Apple’s supply chain to your data? Instead of waiting and reacting, you could respond to change as it happens.

If your data sources are fragmented, refresh on schedules that don’t take current or relevant events into account or depend on manual intervention, you’re not able to resolve problems or confidently make decisions, and the shift to proactive methods won’t be possible. But with continuous orchestration of your most valuable digital asset, you can win in an industry where most companies are merely fighting to uphold razor-thin margins by avoiding spoilage, waste and lost revenue.

Perishable profits

Consider the most direct example of waste potential in the retail space: grocery. Fresh retail items don’t just sell quickly; they expire quickly. Between the farm and the fridge, there’s a complex, fragile chain of vendors, distribution centers and stores.

The smallest delay in your data pipeline is a chance for product to go unsold, unstocked or wasted. The shelf life of perishable goods is short, and demand can shift hourly. If your inventory forecasts are built on delayed or inconsistent data, the results can swing in either direction: Overorder and waste inventory or understock and miss sales. Either direction is costly. 

To prevent these outcomes, you need real-time visibility into what’s arriving and what’s already on your shelves. Plus, what’s moving fastest. Since you have to stitch together a view of field data, supplier inputs, distribution center updates and data from POS and other systems, you must have orchestrated, intelligent data pipelines.

That’s why more retailers are adopting modern data management architectures via offerings like SAP Business Data Cloud, which brings together SAP Datasphere, SAP Analytics Cloud and Databricks to unify data and AI-driven insights. But these platforms can’t work in isolation. They require clean, orchestrated tasks, steps, activities and transfer across an IT landscape to generate the relevant, quality data necessary to inform daily decisions.

Why retail data spoils

Unfortunately, it’s common in retail to know what needs to happen but be stuck in reactivity mode because your data is stale or simply late.

You might have a perfectly calibrated model in SAP Integrated Business Planning (IBP), but if it’s pulling incomplete or old data, there’s no chance it reflects your real replenishment needs. You may receive vendor data in flat files, but if they have to be manually validated and uploaded, your cycle slows down. Or maybe you have all the right tools, but your pricing team and planners aren’t seeing the same information in the same format at the same time.

This is the hidden challenge of retail: achieving consistency and speed at scale. When your supply chain spans multiple regions and partners, minor data issues amplify quickly. 

See how global retail collective Centric Brands achieved end-to-end visibility and control across its complex SAP environment and a variety of non-SAP systems.

Keep your data flows from expiring: The automation fabric way

A resilient supply chain for fresh goods runs on fresh data across your SAP and non-SAP systems. You must continuously collect, transform, enrich and act on it without delay. A mere technical upgrade won’t do, either. You have to build a foundation for repeatable execution.

On a high level, that might look like:

• Ingesting real-time inventory and shipment data directly into your SAP S/4HANA systems from farms, warehouses and distribution centers
• Using tools like Informatica Cloud to extract and transform data from external sources, including environmental sensors for temperature, humidity and shelf life
• Feeding POS data to SAP IBP to do short-term forecasting using recent demand patterns
• Normalizing data formats and units across suppliers and geographies automatically
• Triggering dynamic adjustments in SAP, like store delivery windows or pricing recommendations, based on updated transit times, spoilage risk or demand spikes
• Alerting supply chain planners the moment a shipment is delayed or a product batch falls below freshness thresholds
• Routing enriched data into SAP Datasphere, then feed it to Microsoft Power BI or SAP Analytics Cloud for real-time inventory and margin analysis

How do you bring all of this together in a way that’s scalable and automated? 

Build your forecasting-and-replenishment (F&R) automation fabric

An automation fabric is a cohesive framework that connects and monitors your applications, processes and data sources with zero friction. What sets this approach apart from individually integrated point solutions is its ability to control data movement with a high degree of autonomy. Instead of waiting on rigid schedules or scrambling to react to delays, you can operate with precision. 

Think of it as air traffic control for your data. It monitors every source and route to make sure nothing arrives late, out of order or without clearance. That level of control gives you agility that’s unmatched in retail.

Processing incoming data

• Load daily sales data from SAP POSDM or your POS platform into SAP IBP
• Validate and post documents in SAP S/4HANA for reconciliation and further processing
• Import promotional updates and sales uplift data from SAP IBP or third-party campaign tools
• Trigger structured data exports to SAP Datasphere for enrichment and modeling

Nightly forecasting and replenishment cycles

• Full forecasting and replenishment
  • Stage datasets from SAP S/4HANA and external systems (e.g., supplier APIs) and validate readiness 
  • Generate promotional impact estimates using SAP F&R, enriched with Databricks or Azure ML
  • Wait for inbound shipment confirmations, trigger replenishment calculations and create and dispatch pick orders to warehouses or store distribution systems
• Processing negative stock
  • Identify and count negative inventory positions from SAP S/4HANA and store systems
  • Create physical inventory documents (PIDs) to trigger reconciliation and downstream updates

Planning and reporting system updates

• Push refreshed stock and forecast data into SAP IBP for next-day planning
• Enrich and route datasets to SAP Datasphere and Microsoft Power BI or SAP Analytics Cloud for visualization
• Notify supply chain teams and store planners of updates via email or workflow triggers
• Log and monitor every job to meet SLAs for stock updates, pick orders and forecast refreshes 

Your competitive advantage: Orchestration that delivers

Already using RunMyJobs in your retail environment? Download this forecasting-and-replenishment workflow template to move faster while maintaining accuracy and quality.

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

SAP environments are more powerful than ever, but they’re also more flexible and open to work with the latest technologies. This inherently adds complexity. Many organizations are operating hybrid landscapes with SAP S/4HANA on-premises or in the cloud, SAP Business Technology Platform (BTP) connected to non-SAP apps and tools, external data lakes or warehouses, third-party analytics platforms and a growing number of integration points and APIs. 

Yet, many enterprises are discovering the hard way that it’s not the limitations of integration holding them back; it’s a lack of true orchestration.

Managing data movement across this ecosystem is no longer a task for isolated scripts or point-to-point integrations. It requires an automation fabric that ensures your data flows securely and reliably.

Luckily, much of what you need to achieve this already exists — within your environment, your tech stack and your team. But it needs to come together to run autonomously across all your applications, processes and data. That’s where a purpose-built orchestration layer adds transformative value to SAP data ecosystems.

Where data pipelines break down

Modern SAP landscapes are hybrid by design. You might be running S/4HANA on-prem with SAP BTP extensions in the cloud. You might be feeding into Snowflake for advanced analytics or using Microsoft Power BI for dashboards. You may even leverage tools like Azure Synapse, Databricks or Informatica Cloud. This sprawl creates complexity, and complexity creates friction.

Let’s walk through some common data-related challenges you could be experiencing.

Fragmented scheduling leads to inconsistent data

Without centralized orchestration, teams use whatever’s available: cron jobs, external schedulers, hand-written scripts, etc. This leads to mismatched timing and unreliable dependencies. For example, your sales numbers in Power BI don’t align with your inventory figures in SAP S/4HANA because the data pipelines refresh on different cadences — or worse, silently fail.

Disparate systems often mean data stays siloed, which causes reporting to be inconsistent. That’s a consequence of not having a single pane of glass from which to manage and monitor your data flows. Without a centralized scheduler that acts as an orchestration engine, systems can’t depend on one another effectively, leading to gaps and overlaps. 

Manual processes contribute to high error rates

Manual data entry and transfers are still too common, especially when you’re bridging SAP with non-SAP systems like partner portals, pricing tools or local data repositories. Each touchpoint adds risk. 

If a pricing update comes in from an external vendor and someone delays or incorrectly inputs it manually into files that update SAP Business Warehouse (BW), your customers might see the wrong price and your support lines could light up.

Lack of timely visibility forces reactivity

Outdated data is almost worse than no data. If dashboards and reports pull from systems that haven’t been synced properly, your leadership team will make calls based on stale information. 

Let’s say SAP Analytics Cloud shows margin erosion in one product line, but you don’t have up-to-date access to supply chain or POS data. The root cause will remain unclear, delaying response and ballooning the impact of negative outcomes. 

Difficulty tracking data lineage

When something goes wrong, how fast can you trace it back to the source? In many cases, it takes hours or days of manual investigation across teams and tools. 

When a financial report in SAP Analytics Cloud flags missing revenue, but the issue started in a data ingestion workflow running through Azure Synapse or SAP Datasphere, you’re stuck chasing ghosts if you have no orchestration layer.

Missing automation, missed opportunities

This is perhaps the most widespread and costly issue: systems and teams doing the right things but in isolation. It causes pipelines to stall and dependencies to be overlooked. In other words, you get stuck in a reactive loop.

Your data may be moving on rigid schedules instead of when it’s actually available. Critical workloads like Databricks clusters or EC2 instances might stay running long after they need to. Or, your Power BI might be refreshing every hour instead of being triggered by actual data loads. All of these have the potential to create both lag and waste.

A real picture of end-to-end orchestration across your data ecosystem

What does a centralized, intelligent workload automation (WLA) platform that unifies and orchestrates data movement across SAP and non-SAP systems look like?

• Fluid integration with everything from SAP S/4HANA to cloud-native tools like Snowflake, Databricks, Azure and Google Cloud
• Automated data flow — no more relying on email alerts or batch jobs
• Real-time alerting and proactive error handling to prevent pipeline issues before they impact the business
• Centralized observability so you can see and track data lineage and process status across the entire landscape

With these capabilities, you’re not just fixing technical issues. You’re enabling business agility. You’re giving your teams trustworthy data to act on and reducing the cost and risk of digital operations. Essentially, you’re building a future-ready enterprise.

This automation fabric is powered by a secure, cloud-native job scheduling solution that runs completely outside your SAP environment but is deeply integrated with it. That means no additional load on SAP systems, no lost visibility and no vendor lock-in.

Why this matters for you now as an SAP user

Whether you’re deep into a RISE with SAP transformation or just beginning to connect SAP to cloud analytics and data platforms, orchestrating your data movement must be a strategic priority. SAP Business Data Cloud (BDC) offers incredible promise for unifying enterprise data and applying AI and analytics at scale.  But like any system, BDC is only as good as the data pipelines feeding into it.

And for most enterprises, those pipelines touch systems far beyond SAP: Snowflake, Databricks, Power BI, Azure Data Factory, ServiceNow, Kubernetes, even legacy platforms. And this isn’t just an IT issue. Your Finance team needs timely close processes and readily available data that supports compliance. Your Operations team has to keep processes flowing without waste. Your Customer Support team needs a 360-degree customer view to ensure service and satisfaction.

Even your future initiatives, like training and implementing AI models, depend on clean, accurate and complete data that’s reliable and doesn’t cause hallucinations.

What’s at stake? Cost, trust and transformation

End-to-end data pipeline automation is more than just convenient. RunMyJobs by Redwood customers know firsthand how critical advanced WLA via an SAP-partnered solution can be. It helps them handle the real-world complexities of data operations that arise daily for fast-moving enterprises. 

RunMyJobs’ event-driven workflows, conditional logic, alerting, retries, visual no-code design, AI/ML predictive analysis and alerting and other automation fabric-focused features enable:

• Cost savings: Customers have reduced cloud spend by auto-scaling Databricks clusters or shutting down idle EC2 instances via RunMyJobs.
• Faster reporting: Orchestrating SAP-to-Snowflake-to-Power BI flows, for example, keeps you meeting tight SLAs for daily or hourly dashboards without running refreshes that burn compute unnecessarily.
• Better governance: With audit trails, centralized logs and controlled access (e.g., via ServiceNow), RunMyJobs customers meet compliance requirements more easily.
• Reliability for AI: As AI becomes more crucial to drive productivity and efficiency, you need to know that the data it uses is accurate. RunMyJobs uses best-in-class automation practices to secure the data feeding your AI models, orchestrating continuous data flows so their outputs are reliable, unbiased and meet quality standards.

In your world

No two SAP landscapes look alike, but whether you’re producing goods, delivering power or moving financial assets, your success depends on frictionless data movement between SAP and non-SAP systems.

Consider manufacturing, where orchestration is fast becoming the backbone of Industry 4.0. Production planners must align real-time inputs from MES platforms, IoT sensors, logistics networks and supplier portals with demand forecasts and capacity models in SAP S/4HANA and SAP Integrated Business Planning (IBP). In practice, that means more than connecting systems. It means using an orchestration layer to ensure delivery schedules, machine assignments and work orders always reflect the most up-to-date data. When all systems operate in concert, manufacturers gain agility and protect margins, even as supply chain conditions change.

Or take retail, where every hour of inventory delay risks spoilage, stockouts or missed sales. Leading retailers are using data orchestration to keep forecasting and replenishment, logistics and pricing synchronized across SAP S/4HANA, SAP IBP and SAP Datasphere environments. Retailers are using automation fabrics to move data faster while maintaining accuracy, maximizing their margins in highly volatile markets.

In utilities, orchestrating data across smart meters, SAP IS-U, cloud analytics tools and CRM systems helps ensure billing is accurate and customer service teams are always working from the latest information. Intelligent data orchestration validates and properly sequences handoffs, no matter how many systems are involved.

Life sciences is another area in which data orchestration connects key functions, in this case, discovery and delivery. Research teams rely on orchestrated data movement between SAP R&D Management, ML modeling platforms and analytics tools to screen compounds and predict efficacy, while clinical teams use the same orchestration fabric to forecast site-level inventory and synchronize replenishment. Intelligent automation drives accuracy and timeliness across the research-to-treatment lifecycle.

Global banks, insurers and others in financial services also need to orchestrate thousands of interdependent workflows, from early-morning FX position updates and bank statement reconciliations to intraday liquidity forecasts and payment batches. Orchestrating end-to-end processes, such as start-of-day, eliminate manual interventions and greatly reduce operational risk.

That same level of orchestration is possible across other industries, too. As you explore how to extend automation in your organization, take inspiration from how others are rethinking their SAP-connected processes. With RunMyJobs, SAP customers across industries are unifying their SAP and non-SAP systems into one intelligent, automated, business-aware fabric. In turn, they’re reducing risk, lowering costs and dramatically improving reporting accuracy and timeliness.

Stop thinking in terms of single integrations and start thinking in terms of coordination. Learn how to develop resilient value-chain processes and get the most from your SAP solutions with end-to-end automation.

This drive to harness AI to deliver targeted information more efficiently is precisely what inspired the Redwood Software Education and Documentation teams to create a similar experience for Redwood users. As Director of these teams, I’ve seen firsthand how AI-powered solutions can transform user experiences. We’re bringing that innovation to our product documentation with a new AI assistant designed to help you navigate our products with unprecedented ease. 

Let’s explore how we’re leveraging AI to evolve product documentation into a dynamic and seamless experience.

Transforming a search into a conversation

Getting answers in the form of accurate and timely information is crucial. That’s why we’ve integrated an AI-powered feature directly into our documentation portals. Consider it your personal assistant, ready and eager to answer your questions right now.

Our AI assistant understands natural language queries, allowing you to ask questions conversationally. This launch is one of the many steps Redwood is taking toward leveraging AI to enhance your automation journey. Whether you’re navigating configurations, troubleshooting issues or seeking best practices, our assistant provides the support you need.

Benefits of generative AI

Generative AI has the capability to produce and synthesize a wide array of content, transforming how we enhance productivity on a daily basis. This technology empowers the AI assistant to parse through complex technical questions and provide you with exactly what you’re looking for. And, like all Redwood products, it’s built with robust security measures in mind. Any data you upload or the assistant interacts with is not used to train external models, so you get a secure and reliable experience.

We’ve been leveraging AI at Redwood for quite some time, focusing on making things more efficient and enhancing our product offerings. It’s not just about moving faster; it’s about working smarter. From cutting down on manual errors in finance operations to predicting and preventing service disruptions, AI is a key part of our strategy. Now, we’re putting that intelligence directly into our documentation with this conversational assistant. We’re excited to keep improving it to better serve you.

How Redwood’s AI assistant empowers your automation strategy

There are many tangible advantages to engaging with this new assistant, including:

• Instant answers: Enhance productivity and efficiency through a personalized search assistant, providing you with relevant information in seconds.
• Enhanced navigation: Redwood’s AI assistant understands natural language, making it easy to pinpoint specific details within our comprehensive documentation.
• Streamlined troubleshooting: Resolve issues faster with quick access to relevant troubleshooting information.
• Increased productivity: Spend less time searching and more time building automations for your mission-critical business processes.

Getting started

We’re launching this AI assistant across our workload automation and JSCAPE by Redwood documentation portals as part of our beta program, and we value your input in shaping its future. Simply initiate a conversation by selecting the Redwood logo on the bottom right-hand side of the page. Start typing your question and let our AI assistant do the rest. 

Your feedback is valuable to us and will help us make this tool even better!

Looking ahead: The future of automation support

From crafting travel plans to navigating complex automation solutions, AI’s potential is undeniable. Redwood is excited to see how AI empowers you as you build an automation fabric, and we’re committed to pushing the boundaries of what’s possible. As AI evolves, so will our ability to provide increasingly intelligent and personalized experiences to all users.

Some companies end up in a frustrating position, having invested heavily in advanced software solutions but failing to realize their full ROI. Coupled with challenges like skilled personnel shortages and high turnover, the cumulative effects leave them struggling to fill resource gaps. 

New data highlights an additional strain: Only 36% of CIOs expect IT headcount growth in 2025. This stark reality underscores the urgency for organizations to make the most of the resources they already have.

Automation software can help bridge these gaps, but it doesn’t operate in isolation. It requires skilled, confident users who can apply it wisely to each use case. Targeted, high-quality training is the answer. 

Product education empowers employees to take ownership of their roles in ways that drive growth, efficiency and long-term success. Proper training can turn former resource needs into opportunities to build a more agile and capable workforce.

The transformative power of online learning for automation success

Learning Management System (LMS) tools have revolutionized how companies approach employee training. No longer constrained by the logistical challenges of in-person instruction, companies can offer ongoing training on everything from cybersecurity protocols and software usage to company values. As of 2023, Gartner reported a 52% increase in demand for LMS software, and skill development continues to be a priority.

For automation software in particular, LMS platforms offer significant advantages. They allow for flexible, self-paced learning to accommodate different schedules, locations and learning styles. They also drastically reduce the cost of scaling training programs by keeping materials online and editable. Instead of sending trainers to new locations, it’s possible to deliver consistent interactive instruction across a distributed workforce at a fraction of the cost.

Most importantly, LMS tools help education teams keep their learners up to date. Automation software evolves rapidly, with new features and integrations introduced regularly. Employees need access to the latest information at all times and from anywhere.

Employee education as a competitive advantage

Investing in education sends a clear message: Your company values its employees and is committed to their success. Furthermore, accessible digital training doesn’t just improve skills — it contributes to outcomes that can differentiate your organization from your competitors. A workforce capable of leveraging cutting-edge automation tools can be the defining factor that sets you apart.

Organizations that invest in employee development have 11% greater profitability and are 2x as likely to retain employees. 

Gallup

Training programs can even drive business outcomes due to their impact on retention and internal mobility, as shown in the graph below. Quality software training can build a more resilient workforce, preventing the loss of institutional knowledge and gaps in expertise that arise when good employees leave.

Today’s workforce values growth and development, and businesses that invest in these areas are more likely to attract and retain top talent.

94% of employees would stay at a company longer if it invested in their professional development.

LinkedIn Learning

The benefits are profound in an automation context, where well-trained teams can quickly and effectively integrate new tools into their workflows, reduce time-to-value and enable smoother collaboration across departments. Building capabilities and confidence turns technical solutions into strategic assets.

Bridging the gap between training and performance

Effective training doesn’t stop with imparting the what and how of a new tool or feature. To truly benefit, you must ensure that learning translates into real-world performance. 

Especially in the case of automation software, which could cause employees’ roles to shift as they’re relieved of repetitive tasks, they need guidance to embrace their evolving responsibilities and continue adding value. For example, training might focus on how automation software can generate actionable insights from data or facilitate better decisions. Automation benefits become more real with these relatable applications, so people feel engaged rather than worried about job security.

Continuous access to learning resources is also a must. A robust library of on-demand resources provides relevant knowledge right when users need it. They can revisit concepts, explore new features and upskill over time.

When training is done right, employees feel inspired, and businesses see tangible improvements in efficiency and decision-making.

How Redwood University sets a new standard

In addition to 24/7 global support, Redwood Software product users get access to Redwood University with no prerequisites. Redwood University was created with the mission of equipping users with everything they need to extract maximum value from their experience with the software. 

Here’s what makes it unique:

• Users first: We are passionate about our learners’ success and strive every day to find new ways to empower and delight them.
• Evidence-based instructional design: Our materials are developed using proven methods that maximize retention.
• Role-based curricula: We tailor content to specific job functions to ensure relevance and make learning paths immediately useful.
• Hands-on learning: Practical simulations, exercises and quizzes created by product experts help learners apply skills in realistic scenarios.
• Flexible structure: Modular training courses allow users to learn at their own pace and focus on specific topics as needed.
• Certifications: We offer formal assessments that validate knowledge and demonstrate capability within the software. These credentials can be uploaded to LinkedIn to further celebrate learners’ achievements.

Automation software is only as valuable as its users’ ability to leverage its power. Redwood University is a dynamic learning resource that goes above and beyond typical training manuals to help you drive real change.

Develop a culture of continuous learning

For companies that have successfully cultivated a continuous learning culture, there’s a case to be made for encouraging the development of active learning opportunities. Such opportunities ensure the learners engage with their trainers and are an effective way to bolster innovation.

TrainingMag

Training isn’t a one-time event. Education should be embedded into the fabric of your organization — and, certainly, the automation fabric you’re developing using Redwood products.

A culture of learning starts with leadership. To cultivate this culture, higher-ups should:

• Encourage active learning opportunities in which employees can interact with peers and those with more advanced skills.
• Promote innovation by opening blocks of time for creative brainstorming and building pathways for new ideas to reach leadership.
• Make learning a seamless, integrated part of work life rather than something your team has to struggle to fit into their schedule.

Continuous learning is easier when your automation software provider reflects this value in its approach. When you use a Redwood product, you get the backing you need to make widespread cultural changes stick.

Already a Redwood customer? Empower your team and transform your business even faster: Sign up for Redwood University.

While I do not like our customers experiencing issues with our software, working together with them to find a resolution and listening to their ideas on how to improve our products and Support services is inspiring. And it seems to me that our customers also truly value our support. 

In our recent LinkedIn poll, 60% of respondents stated they value customer experience most when evaluating a Service Orchestration and Automation Platform (SOAP). As a Leader for two consecutive years in the 2025 Gartner Magic Quadrant™ for SOAPs, Redwood delivers the type of support you need to reach your automation goals.

We’ve covered how to engage with Redwood’s Customer Success teams. Here, we’ll dive deeper into what it’s like to interact with our Support team in particular and how your interactions help us level up and continue to provide industry-leading products and customer service.

Your positive outcomes = our mission

One of Redwood’s core values is to obsess over customer success. We treat customers like partners and aim to earn their trust every day. 

Having worked with some of our customers for nearly all 23 years has convinced me that trust is the basis for a good relationship. I may not always tell them what they want to hear, but I’m committed to saying what they need to hear.

A global presence

In the aforementioned Magic Quadrant™ report, Redwood was positioned furthest in Completeness of Vision and highest for Ability to Execute. Gartner heavily weighted geographic strategy in this evaluation.

As a global company, Redwood understands the technical requirements, cultural benefits and challenges of both asynchronous and in-person work. We know that supporting modern businesses means being available anywhere and everywhere. Interactions with people all over the world strongly influence how we enhance our customer support strategy on an ongoing basis.

Our team is distributed across time zones, and while our communication language is English, some of our Support team members can switch to several other languages when necessary.

We’re available via portal, email and phone to give you a range of communication options that best fit your needs. 

The goal: Synergistic relationships

Collaborating with you to solve problems is just as advantageous for us as it is for you.

Whether we’re working on an issue, reviewing an enhancement or simply having an introductory meeting, we prioritize listening above all. We want to know what works for you and, perhaps more importantly, what doesn’t.

Your feedback is always valuable and welcome — about product functionality, our work as a Support team or Redwood as a whole.

Your voice helps us develop, and we amplify that voice by representing you in internal meetings and strategy discussions. We are proud to share your thoughts and feelings with the whole company.

Don’t hesitate to ask for support

The thing I find myself saying to customers the most is: “If we don’t know about your issue, we can’t help you.”

We don’t want you to worry about the validity of any question! We would rather have you ask us than be confused or frustrated.

Reach out any time, from anywhere, when:

• You can’t access your environment
• You’re unable to perform an action you could previously do in your Redwood solution.
• You’ve encountered an error or what appears to be a bug.
• You’d like to suggest a product enhancement.

Here’s everything you need to know about how to reach us and how to escalate a ticket.

Understand how we handle critical incidents.

You’ll never have to ask that question when you take advantage of our robust Customer Success programs and services. As a Success and Support team member at Redwood for almost 10 years, I can confidently say you’ll have a first-rate experience as we strive to be a valued partner in your success.

To start, it can be helpful to understand how our team is organized. Here, I’ll share the various functions of Redwood Customer Success and when to contact each team.

Pillars of Customer Success at Redwood

Redwood’s vision is to unleash human potential by giving you the freedom to focus on more than repetitive tasks. To support you in using our products to drive strategic efforts, we’ve set up Redwood Customer Success to be multifunctional and partner with you throughout your entire journey. From implementation to troubleshooting to learning how to get the most from our automation solutions, our team is here for you.

We provide comprehensive assistance across four pillars of Customer Success.

Customer Success

For standard onboarding, you’ll interact with our Customer Success team. Along with applying proven implementation methodologies, this team provides guidance and helps you optimize time-to-value. In every interaction, we offer guidance for your use cases and best practices for your automation solution to help you maximize the return on your investment. 

As you progress and your users become more comfortable using Redwood products, we continue to engage by performing periodic health checks, advising on upgrades, informing you about best practices, sharing how other customers have tackled similar challenges and being a starting point for navigating Redwood products.

When to contact Customer Success

• You have a question about product functionality, e.g., “How do I …”
• You’d like us to review your configurations to ensure you’re following best practices and mitigating risks.
• You want to upgrade or use case guidance.

Professional Services 

If you are implementing new Redwood products and need help with configuring, installing or integrating, engage with our Professional Services team. They’re the ones who create a custom implementation plan for your initial launch and, if necessary, migration or when you request specific deliverables.

This team can also act as functional consultants, freeing up your staff for key automation initiatives and maximizing your ROI.

When you may need Professional Services

• You’re starting a new automation project and want to plan for success with qualified Redwood experts. 
• You want personalized enablement or on-the-job coaching for your existing team or after a significant business change such as a merger or acquisition.

Support 

Once you’re up and running, you need to know you have quick, reliable answers at your fingertips when you encounter problems or have a question. Redwood’s Support team can be available 24/7/365 for technical fixes and peace of mind. In our support portal, you’ll be able to track the real-time progress of your tickets.

When to contact Redwood Support

• You can’t access the platform, but you have verified your own network status.
• You’re unable to perform an action you could previously do in your Redwood solution.
• You’ve encountered an error or what appears to be a bug.
• You’d like to suggest a product enhancement.

Education 

In addition to our initial product training, we offer easy-to-access product documentation and learning tools for you to drive outcomes with Redwood’s automation solutions.

How to access Redwood learning opportunities

• Visit our documentation portal to learn more about the product(s) you use.
• Explore Redwood University for on-demand training and certification programs. Redwood customers can register here.

Got feedback or suggestions for the Redwood University team? Let us know what you think by completing this suggestion form. Your feedback helps us improve Redwood University for all customers.

TIP: Not sure where to begin? Email the Customer Success team for guidance.

Learn more from fellow customers

One of the best ways to improve your outcomes with new technology is to learn how others are using it. There are a few easy ways to get inspired by fellow Redwood customers:

➡️ Read our blog series, The Automationist.

➡️ Watch customer webinar replays to learn about use cases.

Have a question? Reach out via email to success@redwood.com.

When we travel around the holidays, most of us expect a certain amount of stress, and there’s always a risk of weather-related delays. With the impending “bomb cyclone,” Winter Storm Elliot, this period of 2022 was fraught with uncertainty for people on the move.

Weathering two storms

Starting on December 23, the powerful cyclone grounded more than 17,000 flights nationwide. Many airlines, including Delta, American and United, faced bottlenecks, an all-too-familiar story. Despite heavy investment in systems and careful orchestration by leading IT experts, technology failed to perform under extreme pressure.

Southwest Airlines, for one, found itself in a dire situation. Even after the storm cleared, its systems were still struggling. Between December 26 and 31, the popular airline had to cancel up to 70% of its flights every day — largely due to its inability to assign crews to the flights that were still scheduled. Millions of passengers were stuck.

Southwest expressed sincere apologies: “Our employees and crews scheduled to work this holiday season are showing up in every single way. We are beyond grateful for that. Our shared goal is to take care of every single customer with the hospitality and heart for which we’re known.”

Despite these sentiments and round-the-clock efforts to correct the problem, operational disruptions continued beyond that week, making many travelers hesitant to book future trips. The debacle cost Southwest nearly a billion dollars in net outlay and lost revenue. Compounded by viral negative stories circulating on social media, the financial repercussions dealt a considerable blow.

Runway to ruin: Origins of an industry predicament

The cause of the storm after this storm wasn’t the snow and ice blanketing the runways. It was invisible — embedded in the legacy infrastructure underpinning many airlines’ operations.

This was not merely an instance of management neglecting to anticipate weather impacts but a fundamental flaw in backend IT setup. Many large corporations continue to use the same technology that drove successful outcomes for years without realizing the magnitude of risk involved, sometimes thinking any system upgrade or migration would be too much. Relying on outmoded systems for critical processes is costly yet common.

Four root causes of the aviation industry’s struggles stand out.

1. Archaic technological architecture

At the heart of operational dysfunction is often a struggling gate check-in and check-out system, which may rely on an outdated job scheduler. Ill-equipped to handle the complexities and rapid changes required in modern air travel logistics, old systems don’t perform well under stress. Any disruption in the schedule could lead to widespread systemic failure.

Just a couple weeks after Elliot passed, the Federal Aviation Administration experienced an outage of its 30-year-old NOTAM system, which is critical for the safety of all US flights. Thus, the effects of obsolete technology aren’t limited to private companies but also regulatory bodies.

2. Increasing enterprise complexity

The complexity of today’s enterprise environment further complicated the 2022 event and presents an ongoing dilemma. Digital transformation has, for many organizations, meant increasing the number of tools used for everyday work. On average, a large enterprise uses 473 SaaS applications. 

If integrations aren’t seamless, this expansiveness breeds information silos and a disjointed system that isn’t equipped for large and intricate workloads. Delayed responses in critical times are, therefore, not surprising.

3. No true workflow orchestration system

Many airlines also lack effective workflow orchestration, depending on custom-scripted automations that weren’t designed for rapid adaptability or scalability. The absence of a robust, integrated workflow system means they’re not prepared to recalibrate in the worst-case scenario.

4. Missed signs of impending breakdown 

Technology crises don’t generally occur without warning. For instance, a smaller system outage occurred two years prior in Southwest’s Atlanta hub, highlighting vulnerabilities that were bound to worsen if not addressed. It’s understandable that this would have been overlooked, as it’s not necessarily obvious that a particular outage across such an intricate system is the one signaling a major problem in the near future. However, more sophisticated systems would be able to predict system issues before they grow to the scale of the 2022 debacle.

The value of seamless data flows in preventing operational chaos

In this tale are priceless lessons for complex enterprises in any industry. It’s a stark reminder of the role of modern, resilient technology in a crisis response strategy.

The most prominent message? Seamless data flows aren’t just part of a secure IT foundation. Implemented correctly, they can be a business advantage and ensure your architecture stands up to pressure when your competitors’ may not. Reliable, powerful technology is instrumental in preventing delayed responses, misinformation and downtime.

Good data is anticipatory — it allows you to predict challenges. Organizations with agile, data-driven processes can see what’s coming and pivot effectively, a significant competitive advantage when external factors like weather impact an entire industry.

Should an unforeseen event occur, continuous data flows are the best form of insurance, as they protect your business in real time. When data moves unhindered across departments and systems, it minimizes downtime and the costs associated with it. In turn, this reduces the indirect costs of lost customer trust and potential market share.

An alternate route

How could things have gone differently for airlines with a more modern IT environment in the midst of this major storm? 

Fewer, newer and more tightly integrated systems would have removed the manual burden of disaster recovery and reduced the scale of the consequences. Specifically, end-to-end automation could have dramatically improved crew scheduling and reassignment to reroute resources where they were most needed. Real-time data inputs from weather services and airport traffic updates could have preemptively adjusted flight schedules. 

The customer experience, while not entirely protected from disruption, could have been far less catastrophic, with automations triggering customer alerts and eliminating the need to stand in long lines for answers.

How to navigate an application-heavy landscape

Still not convinced it’s time for IT infrastructure modernization initiatives at your organization? Let’s look to the future.

Sophisticated technologies are arriving on the business scene at an exponential rate. On top of the immense number of apps you already use, you’ll likely be looking to fully utilize the power of machine learning and AI to transform your business operations and keep up. 

However well-intentioned, these moves increase the chance of system failure if they’re not done well. Stacking more complexity on top of an already overwhelmed mainframe or legacy infrastructure is a sure way to kill any amount of operational efficiency you’ve maintained until now.

Interconnection and interdependence are mandates in today’s (and tomorrow’s) IT operations, and every enterprise must evolve to support them. You need your business processes to run at scale — millions of times per year, across your architecture, uninterrupted. To achieve this and stay competitive, you simply must automate.

A storm-ready modernization strategy

Automating single tasks in silos is not the answer. Instead, aim to implement an automation fabric — a single, integrated framework that unites all of your activities, applications and environments and orchestrates mission-critical business processes. This approach is essential for modernizing your infrastructure and solving for the complexity of the application explosion.

Here’s how to stay ready for the equivalent of a severe winter storm during the holiday travel period in your industry.

• Don’t overlook warning signs. Your systems speak! The longer you ignore a “check engine” light, the bigger and more costly the issue could become. While your backend may not be revenue-generating, it is revenue-protective.

• Choose forward-thinking software providers. Invest in relationships with software providers who prioritize innovation and adaptability while considering your business needs. They’ll offer solutions that are adaptable to changes in technology to ensure your ecosystem doesn’t become obsolete.
• Safeguard your organization with workload automation. Instead of fighting to make monolithic, inflexible systems do what you want, streamline and build efficient end-to-end processes you can rely on.

Clear your organization for takeoff 

Imagine a plane from the 1960s taking off next to one built in 2024. While it could theoretically get off the ground, problems verifying the safety of parts, finding pilots who can fly it and speaking to air traffic control and more would make it impossible to try.

Today’s plane is your competition. They will modernize whether you do or not. Therefore, trouble is inevitable if you fall behind, whether it manifests as a few days, hours or minutes of chaos.

Modern enterprise scheduling can pull you forward from an archaic space to help you level with the best in your market today, tomorrow and beyond. The key is to find a solution that can do the job. Many job schedulers haven’t shifted their architecture or offerings in 15 to 25 years. 

Redwood Software, on the other hand, has been live with SaaS for over 10 years. The full stack automation platform that’s purpose-built to orchestrate your mission-critical business processes, RunMyJobs gives you a single pane of glass to turn your business operations into a business advantage. 

Don’t wait to get off the ground. Demo RunMyJobs today.

Integration is a core capability of a Service Orchestration and Automation Platform (SOAP), according to Gartner®. SOAPs are today’s evolved workload automation solutions.

To ensure your infrastructure can evolve is to empower your people and operations. A solution that’s capable of such evolution is one that easily integrates with other essential tools and supports the creation of an automation fabric. 

Together, we’ll explore the features of an extensible automation solution, its benefits over disjointed integrations and how to apply its power to gain a competitive edge.  

What makes an automation solution extensible?

In an automation platform, extensibility refers to the ability to expand its capabilities without the need for excess coding or fundamental changes to existing architecture. Extensible technology maintains relevance longer than restricted software.

Three main elements indicate a platform is extensible.

No-code or low-code environment 

A cornerstone of extensibility is a no-code or low-code setup. Users with varying skill levels should be able to easily design, implement and modify workflows. If anyone can create extensible components, they can get actively involved in the creation of automated processes. This approach also doesn’t rely heavily on specialized IT skills for everyday tasks, so deployment and modification are much easier. 

Code-heavy workflows should be the exception to the rule in design to empower superusers of a platform or language.

Built-in connectors

An extensible automation platform offers pre-designed connectors that make for simple and reliable integration with a wide array of applications, databases and IT systems. Whether you need to pull data from a CRM, integrate with an ERP or connect to a cloud service, connectors eliminate the need for custom code and integration maintenance. Vital to the success of these integrations are strong support and quality assurance, regular updates and minimal to no dependencies; setup should be as simple as a click.

⇨ Learn more about how to elevate your automation experience with connectors.

Open API

Finally, an open API is instrumental in extending an automation platform’s functionality. It enables developers to tailor automations to their industry’s and organization’s requirements. Fine-tuning is often essential for supporting unique business processes. Whether you’re automating business processes and their associated applications or building your automation platform into your existing CI/CD builds, API flexibility is key to ensuring interoperability in the future.

Benefits of an extensible automation platform 

While your organization could gain many advantages from adopting an automation platform with robust extensibility, a few stand out. 

Visibility: Centralizing automation management

One of the primary benefits of having an extensible automation solution is the enhanced visibility it offers across all automated processes. By centralizing the control and monitoring of different automation tasks, you can see them all through a “single pane of glass.” Consolidating helps to identify bottlenecks, streamline operations and improve decision-making efficacy.

Agility: Evolving with new demands

An extensible platform is inherently agile. It can adapt to changing business needs over time without any significant overhauls or replacements. In today’s dynamic markets and technology stacks, agility is crucial. Armed with nimble automation capabilities, you can pivot quickly and integrate new technologies without extensive downtime or resource expenditure.

Scalability: Supporting growth with minimal overhead

Being able to increase the amount of work or number of jobs your automation platform handles is key, as new growth opportunities are not always predictable. Innate extensibility makes a platform less of a burden for your IT department and decreases your reliance on third-party vendors — and, in turn, the time it takes to scale.

Inherent extensibility vs. disjointed integrations

Still tempted to use point solutions that rely on various third parties? Let’s compare true extensibility to a piecemeal approach. 

Gain a competitive advantage with extensible automation

Leveraging the right automation tool that aligns with your larger automation strategy can mean the difference between achieving successful business outcomes and falling behind. As we’ve discussed, extensible automation can equip your organization with plenty of benefits — a collective threat to your competitors.

	Benefit: Extensible automation platforms streamline operations and reduce mundane work, which significantly reduces the need for manual intervention, increasing efficiency and lowering costs. Outcome: The immediate impact is a leaner operation. You’ll be able to reallocate resources from routine tasks to more strategic initiatives, making it faster and easier to go to market with new products and services.
	Benefit: Automated customer support processes, such as ticket sorting and basic query responses, enhance the quality and consistency of your customer service.  Outcome: Consistently excellent service improves customer satisfaction and loyalty, which are key differentiators in a competitive market. It’s also likely to contribute to better customer retention rates and a solid reputation.
	Benefit: Precise data handling and integration improve data accuracy and compliance with regulatory standards. Outcome: Reliably managing data reduces the incidence of costly errors and non-compliance penalties. It also builds a foundation of trust with stakeholders, who value data security and ethical management.
	Benefit: With robust data integration and analytics, you can consolidate real-time data from multiple sources to generate actionable insights into your operations. Outcome: Armed with deep insights, your team can react to market conditions and anticipate future trends to position your business ahead of the competition.
	Benefit: Rapid implementation of new automations gives you the flexibility to explore and innovate within new segments without significant upfront investment. Outcome: Moving quickly without the drag of large-scale IT infrastructure changes offers a major edge. It’s possible to create niches that competitors without end-to-end automation find difficult to challenge.

When the above elements combine, the result is seamless end-to-end automation that runs across multiple business processes and improves various facets of operations, from customer relationships to decision-making to market innovation. Automation, wisely applied, can be a key factor in sustained success and leadership in any industry.

What extensibility looks like in Redwood Software products

• Connector catalog simplifies integration selection • Native API integrations support a clean core for SAP users • Connector Wizard facilitates integration building Most common integrations: SAP, ServiceNow, Databricks and Snowflake	• Job steps library enables workflow orchestration • Super REST adapter allows for rapid API creation • Self-service portal frees up time for your IT team Most common integrations: Informatica, ServiceNow, Azure and SharePoint
• Catalog of pre-built, ready-to-run integrations for both legacy and modern solutions Most common integration: Oracle JD Edwards	• REST API prevents the need for complex workarounds • Cloud connectors and architecture support scalability • Easy integration to partner workload automation solutions drives efficiency Most common integrations: RunMyJobs, ActiveBatch and Tidal

Reap maximum value from an end-to-end automation solution

As has been more evident than ever in the past several years, it’s vital to be poised for market changes and ready to engage in rapid innovation. Automation can serve both purposes, but not all automation solutions are created equal. 

Redwood Software was named a Leader in the 2025 Gartner® Magic Quadrant™ for SOAP report — for the second consecutive year. Download the full analyst report to learn why.

We’ve covered just some of the grounds for using an extensible, end-to-end automation solution. There’s even more latent potential for shifting your organization into the ultimate efficiency and growth mode. Demo Redwood’s solutions to find out how.