The automation talent shift: Building teams that thrive in the SOAP era

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After years of working with SAP customers, partners and internal teams, one thing has become clear to me: automation has outgrown its roots as a technical initiative tucked inside IT. Today, automation is the connective tissue of modern digital infrastructure and, increasingly, of the teams that run it.

What doesn’t get talked about enough is that this shift isn’t primarily about tools. It’s about us as humans.

That’s why I find the 2025 Gartner® Magic Quadrant™ for Service Orchestration and Automation Platforms (SOAPs) so relevant as both a technology lens and a talent and operating-model conversation.

SOAPs aren’t simply better schedulers. They orchestrate end-to-end business services with precision, context and intelligence. And when an organization adopts one, it doesn’t just modernize its automation stack, but reshapes how teams work together, learn and create value.

From my perspective, this isn’t a skills gap problem. It’s about how roles are naturally evolving. With the right guidance, encouragement and space to grow, people can thrive in change rather than just adapting to it.

The shift from task execution to service ownership

SOAPs dramatically expand the surface area that automation touches. We’ve moved from “run this job” to “run this entire business service — with events, conditions, dependencies and real consequences.” 

That evolution changes the nature of the work. You’re no longer optimizing isolated workflows inside a single system. You’re orchestrating processes that span ERP, SaaS applications, cloud platforms and external services. That requires broader thinking and deeper collaboration. The work itself becomes more strategic.

People are still central, but they’re now enabling resilience, business agility and real-time orchestration, not just maintaining automation.

What high-performing automation teams think differently about

The first real shift has to happen in how teams think about automation. Over time, I’ve seen successful teams move from:

• “Automate the task” → “Orchestrate the service”
• Siloed responsibility → Shared, cross-functional enablement
• Versioned scripts → Reusable templates and modular components
• Maintenance thinking → Platform thinking
• Support role → Strategic enabler
  

This mindset shift is subtle, but it changes everything from design decisions to how people collaborate across SAP and non-SAP landscapes.

How automation responsibilities are being redistributed

As SOAPs reshape operational models, new roles naturally emerge. Many organizations already have the talent; they just haven’t named or empowered these roles yet.

Some patterns I’m seeing more often:

• Process architect/Orchestration designer: Connects workflows across business services, APIs and cloud-based environments
• Automation data translator: Bridges operational logic with analytics, logs and business context
• Workflow monitoring and exception manager: Manages signals, dependencies and upstream/downstream impact
• Adoption lead or Change champion: Drives orchestration consistency across business ops, IT operations and development teams
• Automation culture steward: Shapes shared norms around reusable assets, platform thinking and feedback loops

Revisiting how automation work is distributed can unlock capacity you didn’t realize you had.

The conditions that make orchestration stick

Technology expands what’s possible. Culture determines what actually sticks. As automation spans more of the business, shared ownership becomes essential.

That starts with a shared vocabulary. If one team calls it “dependency mapping” and another says “event chaining,” you’ll end up with silos — not orchestration.

It continues with a learning loop that goes beyond training. People and teams need space to experiment, compare patterns and refine their instincts. As a leader, your job isn’t to prescribe every step but to create the conditions for repeatable learning that scales naturally.

And all of the above depend on clear ownership. Without visible leaders accountable for process optimization, templates and tooling standards, automation efforts remain reactive.

How to help your team thrive

If SOAPs unlock new levels of human potential, your team’s job is to take that and run. The environment you create — and the initiatives you choose to prioritize — will bring the shift to life.

At a minimum, I’d focus on the following.

1. Build capability with intention

Capability building can’t be accidental. It should be purposeful. Help teams build fluency in event-driven automation, API integration, cloud orchestration and monitoring patterns. Give legacy automation specialists room to evolve into orchestration designers or platform operators.

The goal isn’t to turn everyone into a developer. But everyone should understand how services fit together and how dependencies behave. You’ll be designing for resilience when your teams understand the “why” behind SOAP-driven workflows.

2. Create a structure that supports orchestration

Orchestration doesn’t thrive without structure. Establish an automation Center of Excellence as a guide for standard workflow patterns, exception handling and reuse. Make ownership explicit for templates, connectors and observability.

Most importantly, bring your practitioners into governance conversations. That’s how you remove friction between process design and automation design.

3. Equip teams with tools that let them excel

People do their best work when technology reduces complexity instead of adding to it. Choose platforms that make dependencies visible and support both low-code and advanced design approaches. Each persona should be able to contribute at their level.

I often ask one simple question: Will this tool make it easier for my team to design, understand and maintain end-to-end processes? If the answer is yes, the value shows up quickly.

4. Avoid the usual traps

Automation stalls when it’s treated as an IT-only scripting exercise, when adoption is an afterthought or when success is measured by output instead of outcomes. You can avoid these traps by formalizing enablement, designing for orchestration — not tasks — and tying KPIs to reliability and business impact.

Your people = your differentiator

SOAPs raise expectations for how work flows across the enterprise. But it’s your people who turn those expectations into outcomes.

When you make space for teams to think bigger about how data, work and ideas move across the business, you unlock something far more powerful than automation alone.

If you’re building that kind of culture, it helps to understand where the market is headed. The 2025 Gartner® Magic Quadrant™ for SOAPs report offers a grounded view of the Leaders and orchestration capabilities shaping the next chapter of enterprise automation — and the teams that will thrive in it.

Payments modernization depends on orchestration — not just the core

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There’s a particular kind of risk that only exists in systems that “work.” It’s not the flashy kind, or the kind that triggers emergency funding or board-level interventions. This is a quieter risk, embedded deep in the background of day-to-day operations. 

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.

The reconciliation is done … or is it?

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Reconciliation checkboxes aren’t a close, especially when “reconciliation” really means transactional matching.

Most transactional reconciliation tools rely on dashboards and checklists to show progress across the financial close. Once data matching flags items as “matched,” the system often marks the task complete. From the surface, the close process appears controlled. Dashboards turn green. Workflows advance. The reconciliation looks finished.

But checklists are driven by task completion, not data movement or financial accuracy, and a “complete” status in the reconciliation tool doesn’t mean the data has been updated or validated. It only means someone flagged a match. In the financial close process, completion should mean corrected account balances in the general ledger instead of a visual signal in a reconciliation solution. This distinction matters during the month-end close, when manual processes and unresolved discrepancies can quietly accumulate.

That gap misleads CFOs into thinking issues are resolved when they are not. One healthcare controller learned this the hard way. Their team believed reconciliations were complete across bank reconciliation, sub-ledger activity and accruals. The dashboards showed no open items. Yet during an audit, $2.6 million in accrual-related journal entry corrections were still sitting in email threads, never posted to ERP systems. The financial statements looked clean on paper, but the underlying financial records told a different story.

Finance Automation by Redwood prevents this false confidence by tying reconciliation status to execution. The platform does not allow the close process to advance until required journals are created, approved and posted inside SAP to align transactional reconciliation with real financial outcomes.

“Matched” doesn’t mean corrected

In transactional reconciliation, data matching is detection, not correction. Auto-match logic highlights discrepancies between bank statements, bank feeds, bank transactions, credit cards and bank accounts, but it doesn’t fix them. Many reconciliation tools stop once discrepancies are identified, which forces finance teams to resolve issues elsewhere.

That “elsewhere” is typically spreadsheets or Excel templates used to calculate correction journals. These manual processes introduce human error, increase manual effort and slow the account reconciliation process, especially in high-volume environments handling large volumes of transactions across multi-currency entities. This time-consuming workaround introduces risks that include:

• Added burden on finance and accounting teams already stretched thin
• Late-cycle changes that disrupt the month-end close
• Lower reliability in financial reporting and audit trails
• More exposure to error-prone, manual processes

Validation functionality inside transaction-level reconciliation tools rarely touches the actual SAP posting layer. As a result, the system cannot reconcile accounts end to end. In the healthcare example, unmatched accruals required correction journals before depreciation could run. Because those journals were not posted, downstream close management tasks stalled, consolidation was delayed and financial reporting timelines slipped. The reconciliation tool checked the box, but the close process broke.

Finance Automation closes this gap by linking transaction matching directly to journal execution. When reconciliation logic is satisfied, the platform can automatically create, route and post journals based on configured rules and approvals to eliminate spreadsheet dependency.

Resolution depends on actual journal execution

A reconciliation is only complete when correcting entries are posted to the general ledger. Visual confirmation without execution is meaningless. Yet many reconciliation tools cannot natively see whether journals tied to reconciliation items are even in flight, let alone posted.

Auditors know this weakness well. During the healthcare audit, the team was asked to prove when corrections posted, with timestamps, audit trails and supporting documentation. Without proof of posting, the team couldn’t explain how those corrections affected the broader financial data or when adjustments were reflected in reporting. The reconciliation system showed completion. The ERP showed nothing. Internal controls existed on paper but not in execution.

Finance Automation enforces reconciliation completeness by embedding the entire discrepancy resolution process into ERP-native execution. It tracks discrepancy detection, journal creation, approval workflows, posting and reversal where needed. As a result, teams get audit-ready financial records with full traceability that reduce risk management exposure and support accurate decision-making.

Why most tools create journal gaps instead of closing them

Most tools separate anomaly detection from journal processing. That architectural split forces accounting processes to span multiple systems and modules, which creates manual work outside the platform. Corrections are calculated in Excel, routed through email and posted manually through ERP interfaces or APIs that break audit trails and slow down downstream SAP jobs. Even when teams try to fill the gaps manually, the process remains error-prone because they’re relying on disconnected handoffs between people and systems.

This fragmentation impacts cash flow visibility, forecasting accuracy and consolidation timing. When account balances are corrected late, pricing assumptions shift and financial management becomes reactive. The reconciliation solution reports completion, but the financial close continues behind the scenes.

Finance Automation addresses this structurally. Built as a cloud-based orchestration layer, it unifies reconciliation, journal entry and close management in a single platform. It integrates directly with data sources, bank feeds and ERP systems and removes the journal entry automation gaps that reconciliation tools leave behind by streamlining the entire close process.

Use reconciliation to trigger real action

Finance Automation transforms transactional reconciliation from passive review into active resolution. Where traditional account reconciliation software promotes visibility and certification as its key features, Finance Automation embeds execution directly into the ERP layer so reconciliation actually results in posted journal entries. Finance Automation is the leading record-to-report (R2R) orchestration platform and is designed to execute the financial close rather than monitor it.

When reconciliation logic confirms discrepancies, Finance Automation automatically generates correcting journal entries, applies approval workflows, validates posting rules and posts directly to SAP. The reconciliation process becomes a trigger for real action instead of a reporting exercise. Account reconciliation tools no longer stop at visibility. They drive execution.

In the healthcare controller’s case, this would have changed the outcome entirely. The $2.6 million in accruals would have been posted in real time, depreciation would have run on schedule and audit questions would have been answered with system-backed evidence. Finance and accounting teams would have spent less time chasing emails and more time closing with confidence.

By orchestrating close management, automated reconciliation and journal execution across ERP systems, Finance Automation reduces manual processes, improves scalability for enterprise organizations and delivers real-time insights through a user-friendly platform.

If your dashboards look clean but your journals live in email, your reconciliation is not done, and your journal entry close is not really automated. Test your journal automation maturity and see how your reconciliation breaks down into manual journals.