SOURCE-TO-PAY MEASURED BY REAL BUSINESS VALUE

Stewart Monk, Chief Revenue Officer, and Chris Rauch, Chief Operating Officer at Proactis, discuss why Source-to-Pay success depends on measurable outcomes, customer adoption and strong foundations for AI.

VALUE BEYOND GO-LIVE

Organisations want faster value with manageable disruption. Proactis’s modular approach helps them address pressing challenges first and build from proven results. Monk and Rauch explain why clear success criteria, customer adoption and sustained engagement are essential to turning implementation into lasting operational improvement.

BUILD THE FOUNDATIONS FOR AI

AI can accelerate invoice processing and improve data extraction, but its effectiveness depends on the processes beneath it. The conversation explores why reliable data, consistent adoption and sound governance provide the foundation for more intelligent spend management and better business decisions.

Stewart Monk brings more than 30 years of experience building and scaling commercial organisations across ERP, HCM and enterprise technology. Drawing on roles at Oracle, Certinia and PowerSchool, he emphasises the importance of customer relationships, faster time to value and sustained engagement beyond implementation.

Chris Rauch’s background spans Customer Success, Support and Professional Services. His perspective centres on connecting customer expectations with implementation plans, maintaining a personal service as operations scale and measuring success through adoption, process consistency and lasting business outcomes.

The organisations getting the most from Source-to-Pay are the ones that have built strong adoption, consistent processes and reliable data.

Q: You’re both joining Proactis at a point when Source-to-Pay is moving beyond process digitisation toward more intelligent and increasingly automated spend management. From your respective perspectives, what do you see as the biggest change taking place in the market right now?

Stewart Monk: The conversation has fundamentally changed. A few years ago, we were talking to finance and procurement teams about whether to digitise. Today, the question is how far, how fast and how to make sure the foundations are solid enough to get real value from what comes next.

What I find genuinely exciting is that we’re at the point where the technology has caught up with the ambition. AI in Source-to-Pay is no longer theoretical, it’s live, it’s measurable and it’s already delivering results for customers like Betfred, who achieved a 47% AP efficiency improvement through our Invoice Capture AI Accelerator. That kind of proof point changes the conversation entirely.

The organisations that will pull ahead are the ones who treat the underlying process and data foundation as a strategic asset, not a precondition to tick off. That’s where the real opportunity is and that’s what drew me to Proactis.

Chris Rauch: From an operational standpoint, the shift I find most significant is the move from output-based measurement to outcome-based accountability. For years, the question was ‘did the system go live’. The question now is ‘is it actually changing how the business operates and delivering the outcomes customers expect’.

That requires a different kind of engagement from software providers, one that extends well beyond implementation and into how customers use the platform over time. The organisations getting the most from Source-to-Pay are the ones that have built strong adoption, consistent processes and reliable data. Those are the foundations that make everything else work.

Q: Proactis has built its position around modular Source-to-Pay. As organisations look for faster time to value and less disruption, are you seeing a shift away from large-scale transformation programmes toward more incremental, outcome-led modernisation?

Stewart Monk: Absolutely, and honestly, it’s one of the things that makes Proactis a compelling proposition right now. The era of the multi-year, big-bang ERP transformation is not dead, but it’s losing ground to a more pragmatic approach: start where the pain is greatest, prove the value, and build from there.

That plays directly to the way Proactis is built. Our modular architecture lets organisations address a specific challenge, invoice processing, supplier management, spend visibility, and deliver measurable results quickly without needing to overhaul everything at once. Time to value has become a genuine differentiator, and we have the case study portfolio to prove it.

Chris Rauch: The shift is real and it’s driven by experience as much as preference. Many organisations have been through large-scale technology programmes that took longer, cost more and delivered less than expected. There is understandable caution as a result.

What we see working consistently is a focused starting point with clear success criteria, a defined process, a committed customer team to partner with, a baseline measurement and an agreed target. When that’s in place, the case for the next phase practically makes itself. Modular implementation is not a compromise; done well, it’s a more reliable path to value than trying to change everything at once.

Q: Stewart, you’ve spent more than 30 years building and scaling go-to-market organisations across ERP, HCM and other enterprise technology markets. What have those experiences taught you about what customers now expect from enterprise software providers beyond the technology itself?

Stewart Monk: The honest answer is that technology has become the price of entry. When I started in this industry, having a great product was genuinely differentiated. Today, there are excellent products across almost every category. What separates the best providers is everything around the technology.

Customers want a partner who understands their business problem before they understand the software. They want speed, not just in implementation, but in the time it takes to feel confident that the investment is working. And they want to feel like the relationship gets better over time, not just maintained.

The experiences that have shaped me most, from Oracle to Certinia to PowerSchool, consistently showed that customer retention and expansion are won or lost in the post-sale relationship. That’s where trust is built, and trust is what drives everything else: renewals, referrals, upsell, advocacy. It’s not complicated, but it requires deliberate, sustained effort.

Q: In a mature enterprise software market, what does sustainable growth look like today? How much of that opportunity comes from winning new customers versus creating greater value and deeper engagement within the existing customer base?

Stewart Monk: Sustainable growth in this market has to be dual-engine: you need both, and you need them working together. But I’d probably push back gently on the framing that they’re separate opportunities.

Your existing customers are your best acquisition channel. A customer who has seen real value from a Proactis implementation and has a strong relationship with the team is also your most credible advocate to a prospect. The organisations that try to separate new logo activity from customer success tend to underperform on both.

That said, and I think it is important to be direct about this, the biggest lever for sustainable growth right now is ensuring every existing customer is getting the value they signed up for. If we do that well, the growth follows. Proactis has a strong, long-standing customer base and a product that keeps improving. That’s a genuinely good position I will be building upon.

CONNECTING CUSTOMER EXPECTATIONS WITH REAL RESULTS

Q: Mid-market organisations often face enterprise-level procurement complexity but have fewer resources and less tolerance for lengthy transformation programmes. How should Source-to-Pay providers adapt their go-to-market approach to better serve that part of the market?

Stewart Monk: The mid-market is where I think the biggest opportunity in Source-to-Pay sits right now, and it’s also where providers most often get the approach wrong.

The mistake is treating mid-market customers as smaller enterprise customers. They’re not. They have different constraints, different decision-making structures and a much lower tolerance for complexity. They need a clear answer to three questions: what will this do for my organisation, how quickly, and what will it actually take from us to get there.

The go-to-market response has to match that. Shorter sales cycles, faster onboarding, more opinionated implementation guidance and commercial models that don’t require a business case the size of a small dissertation. Proactis’s modular approach is well suited to this, the challenge, and the opportunity, is making sure how we take it to market reflects that.

Q: Chris, your background spans Customer Success, Support and Professional Services. Where do you most often see a disconnect between what customers expect when they buy enterprise software and what they experience after implementation?

Chris Rauch: The most common disconnect is not about the software itself, it’s about what success was defined to mean before the contract was signed. Sales processes are, by their nature, focused on possibility: what the platform can do, what other customers have achieved, what the future state looks like. Implementation reality requires specificity: this process, these users, this configuration, in this timeframe.

When that translation doesn’t happen clearly, when the customer’s vision of transformation hasn’t been connected to a concrete implementation plan with measurable milestones, you see disappointment even from technically successful deployments. The software is working. But the customer doesn’t feel the value they expected.

The fix requires alignment early: agreed success criteria before go-live, realistic timelines, prioritised business requirements and a shared understanding of what the customer’s team needs to bring to make the implementation work. There is a saying that “customers buy on hope and renew on experience.”

Q: As SaaS businesses scale, there can be tension between operational efficiency and maintaining a high level of customer service. How do you create more scalable operations without making the customer experience feel increasingly standardised or distant?

Chris Rauch: The main thing is making sure customers don’t have to keep repeating themselves. Most customers are fine with process. What annoys them is speaking to someone who doesn’t know their history, and that happens more as a business grows and work gets passed between teams.

The handover from sales to onboarding is a good example. A customer might spend weeks with the sales team explaining what they’re trying to achieve and how their business works. Then on the first onboarding call they get asked the same questions again. That’s a poor start, and it makes us look disorganised. If everything the customer told sales is properly written up and handed over, the onboarding team can start from what they already know, and the customer just feels like they’re dealing with one company.

I’d apply that thinking more broadly too. Standardise the routine work so it’s quick and consistent, make sure the team can see a customer’s history before they speak to them, and give them enough freedom to make sensible exceptions without needing sign-off every time. Small things help as well. Our support agents sign their emails with their own name rather than a generic “Support”, so customers know who they’re dealing with.

I don’t think scale and a personal service are opposites. Good processes are what let you stay personal as you grow, because the team spends less time chasing information and more time with the customer. That’s something I’ll be keeping a close eye on in this role.

Q: Procurement and finance leaders are increasingly expected to demonstrate measurable outcomes from technology investments. Beyond cost savings and process efficiency, which measures do you think provide the clearest indication that a Source-to-Pay transformation is actually working?

Chris Rauch: Cost savings and process efficiency are necessary measures, but they are lagging indicators, they tell you what happened, not whether the change will last. The measures that give me the clearest signal are adoption and adherence metrics.

If the people who are supposed to be using the system are using it, consistently, in the way it was designed, that tells me the process has actually changed, not just the technology. Conversely, a system with strong automation metrics and low adoption is a system waiting to regress.

Beyond adoption, I look at supplier engagement rates, first-time invoice match rates, purchase order compliance and the ratio of exceptions to total transactions. These are operational measures, but they are also leading indicators of data quality, and data quality is what determines how much further value the organisation can unlock, including from AI. The organisations that focus only on cost savings often find they have to rebuild the foundation later. The ones that measure adoption and compliance from the start tend to compound their results over time.

“Good processes are what let you stay personal as you grow, because the team spends less time chasing information and more time with the customer.”

STRONG FOUNDATIONS FOR MEANINGFUL AI

Q: AI is becoming increasingly prominent across procurement and finance. Where do you believe it can create meaningful value in Source-to-Pay today, and where should organisations be cautious about introducing AI before their data, processes or governance are ready?

Stewart Monk: The short answer on where AI can create value today is: anywhere the data is structured, the process is understood and the performance baseline is clear. For many organisations, accounts payable is the right place to start with AI, because the data is relatively well structured and the performance gains are measurable from day one.

For example, our Invoice Capture with AI Accelerator uses machine learning to improve the accuracy and speed of invoice data extraction. The result is faster processing, fewer exceptions, less manual intervention and a cleaner data foundation for everything that follows.

The caution I would offer is this: AI is not a shortcut past the hard work of getting your Source-to-Pay foundation right. The organisations that see the best results are not the ones who moved fastest, they are the ones who got their processes, adoption and data into good shape first. AI amplifies what’s already there. If what’s already there is fragmented, it will amplify that too.

Chris Rauch: From an operational perspective, the clearest signal that an organisation is ready to benefit from AI is the quality of the data that already flows through its Source-to-Pay processes. Clean, consistent, complete data, with high adoption and low exception rates, gives AI the best possible foundation to work from.

Where I would urge caution is in applying AI to processes that are not yet well understood or well managed. AI needs to be trained on something accurate and representative. If the underlying process is inconsistent, if people are routinely working around it, or if the data has significant gaps, you will not get reliable outputs. In those situations, the priority should be fixing the process first. AI then becomes a meaningful accelerator rather than a mask for underlying problems.

Q: Looking three to five years ahead, how do you expect Source-to-Pay to evolve? Will it remain a distinct category of procurement technology, or become more deeply embedded as an intelligent layer connecting ERP, suppliers, financial data and enterprise decision-making?

Stewart Monk: I think both things are true, and the tension between them is what makes this such an interesting moment to be in this market. Source-to-Pay as a distinct operational discipline will remain. The underlying challenges of supplier management, contract compliance, spend control and invoice automation do not disappear because ERP vendors add AI features to their roadmaps.

But the most valuable Source-to-Pay platforms will increasingly feel less like standalone applications and more like intelligent connective tissue between the ERP, the supplier network and the financial decision-making layer of the business. The data generated across the Source-to-Pay lifecycle, when it is clean, connected and accessible, becomes genuinely strategic. That is the direction of travel, and it is one that Proactis is well placed to be part of.

Chris Rauch: My perspective is that the distinction between Source-to-Pay as a category and ERP as a system will become less meaningful to end users, even as it remains meaningful to the market. What finance and procurement leaders will care about is whether the right information reaches the right person at the right time to support a better decision. Whether that comes from a dedicated Source-to-Pay platform, an ERP extension or an AI agent is increasingly secondary.

What that means operationally is that integration, data quality and adoption become even more critical over the next three to five years than they are today. Organisations that build strong Source-to-Pay foundations now will be in a significantly better position to benefit from whatever the intelligence layer looks like in 2029. Those that defer the foundational work in the hope that a future AI deployment will do it for them are, I suspect, going to find that assumption expensive.

ERP NEWS EDITORIAL TAKEAWAY

The conversation with Stewart Monk and Chris Rauch places lasting business value at the centre of Source-to-Pay modernisation. A successful deployment begins the journey; sustained improvements in how people work demonstrate its value.

Modular implementation offers a practical starting point, particularly for mid-market organisations. Addressing a pressing challenge, agreeing clear success criteria and measuring progress can establish the confidence needed for the next phase.

Customer relationships are equally important. Clear handovers, shared expectations and accessible customer history help providers maintain a personal service as operations scale, while keeping delivery connected to the outcomes originally promised.

Adoption and process adherence reveal whether transformation is taking hold. Supplier engagement, invoice matching and purchase order compliance provide further evidence that improvements can endure beyond the initial implementation.

AI adds another opportunity, but its effectiveness depends on these foundations. Reliable data and consistent processes allow automation to accelerate performance; unresolved fragmentation limits the quality of its results.

As Source-to-Pay becomes more closely connected with ERP, suppliers and financial decision-making, those foundations gain strategic importance. Organisations that strengthen them today will be better positioned to turn emerging capabilities into sustained operational value.

LASTING SOURCE-TO-PAY VALUE STARTS WITH STRONG PROCESSES, RELIABLE DATA AND CUSTOMER ADOPTION.