Over the last few months, I’ve noticed a shift in conversations with sales compensation and IT leaders. A question that many of us thought was settled is quietly resurfacing:
Should we build our own Sales Performance Management (SPM) platform?
Having spent 20+ years in the SPM ecosystem—and the last 15 implementing platforms like Xactly, Varicent, and SAP—I’ll admit this caught me off guard. For a long time, the direction seemed clear: SaaS had won. But the conversations I’m having now suggest something more nuanced is emerging.
Why SaaS Became the Default for SPM
SPM wasn’t just another system that moved to SaaS—it was one of the hardest to build internally.
- Compensation Logic Isn’t Just “Rules” — It’s Constantly Evolving – Unlike many enterprise systems, SPM is never truly “done.” Plans change every year (sometimes every quarter), exceptions creep in, overlays get introduced, and territories shift. Maintaining this level of dynamism in a homegrown system was historically incredibly difficult.
- Trust Is Everything – If sales reps don’t trust their numbers, nothing else matters. One major advantage of packaged SPM platforms was the perception of standardized processes and industry best practices. Sales teams were often more confident in payouts coming from an established SPM platform versus custom internal tools or spreadsheets. Replicating this same level of governance and credibility internally was a major challenge for IT teams.
- The Monthly Crunch Is Non-Negotiable – Commission cycles are unforgiving. Delays or errors directly impact payroll, morale, and sales behavior. Historically, IT teams struggled to support these recurring high-pressure processing windows because homegrown systems couldn’t easily scale during commission runs. When SaaS vendors introduced elastic infrastructure and reliable processing for these time-bound workloads, many IT organizations were happy to step aside and let business teams work directly with specialized SPM vendors.
- SPM Is Cross-Functional and Complex – SPM sits at the intersection of Sales, Finance, HR, and IT, making it one of the more complex enterprise functions to understand and operationalize. Many IT teams found it challenging not only to master the nuances of compensation management, but also to coordinate the cross-functional alignment required to successfully build and sustain a custom solution. Given all this, it’s no surprise that SaaS became the default. For many organizations, it de-risked one of the most sensitive operational processes.
So Why Is “Build” Back in the Conversation?
Despite all of the above, more teams are revisiting the question. Here’s what’s coming up specifically in an SPM context:
- Cost vs. Perceived Value – As compensation plans grow in complexity—multiple crediting rules, SPIFFs, clawbacks, and accelerators—customers often find themselves investing heavily in both licensing and ongoing support. Some are starting to question whether the cost curve aligns with the value they’re getting.
- “Last Mile” Complexity – All SPM platforms handle standard compensation scenarios quite effectively. However, the real complexity often emerges in the last 10–15%: exception handling, retroactive adjustments, complex splits, territory realignments, and other edge cases. Because these scenarios must ultimately fit within the framework of packaged software, they often lead to convoluted configurations, custom workarounds, and manual interventions. Some customers ask: At what point does the complexity outweigh the value of staying within the platform?
- Dependency During Critical Cycles – When something breaks during a commission run, the stakes are immediate. Several customers have expressed discomfort with relying on external vendors during these high-pressure windows.
- Admin Bottlenecks – Comp admins often become the gatekeepers and bottlenecks for making changes to SPM programs. Because these changes frequently require specialized platform expertise, even simple updates can become time-consuming and expensive. Several organizations mentioned that dependency on niche SPM skill sets increases both the cost of administration and the challenge of hiring and retaining administrators.
- Sales Experience Expectations – Today’s sales reps expect real-time visibility: “Where do I stand against quota right now?” “What happens if I close this deal?” Some customers feel that current SPM platforms do not support this level of immediacy and interactivity.
Enter AI: A New Angle on an Old Problem
What’s different this time around is the influence of AI-driven development. Several leaders I spoke with are not necessarily committing to build—but they are re-evaluating feasibility because of tools like Cursor and Claude.
In the SPM world, this is particularly interesting because much of the complexity lies in:
- Translating compensation plans into logic
- Managing frequent changes
- Explaining calculations clearly
These are areas where AI-assisted development and iteration could, in theory, make a meaningful difference.
What the “Build” Advocates Are Saying (in an SPM Context)
Here’s how some teams are framing the opportunity:
- Faster Translation of Plans into Logic – Unlike traditional waterfall SDLC, AI enables rapid prototyping, allowing teams to quickly deliver working MVPs. This helps reduce the risks of a full-scale build by validating ideas early and refining them through iteration before committing to a complete implementation.
- Purpose-Built for Their Needs – Every organization tends to view its compensation plans as unique-and in many cases, they’re not wrong. Custom builds make it possible to accurately model specific crediting logic, distinctive hierarchy structures, and, most importantly, numerous exceptions without being constrained by predefined frameworks. Beyond functionality, custom solutions also provide flexibility in choosing the underlying technology stack based on specific needs and available in-house skill sets-ranging from robust n-tier architectures with in-memory computing to simple spreadsheet-based solutions. Sometimes, it simply comes down to fit-for-purpose simplicity: Why invest in a “car” when a “bicycle” is all that’s required?
- Real-Time Earnings & Simulation – Real-Time Earnings & Simulation – A common theme is: “What if reps could see their earnings update in near real time?” Some teams see custom solutions as a way to tightly integrate with CRM data and enable continuous calculation and simulation.
- A High-Impact AI Use Case – SPM is highly visible but not as deeply embedded as ERP, making it a strong candidate for IT leaders to showcase AI-driven innovation- especially when leadership teams are looking for tangible outcomes. If IT leaders can reduce SaaS spend while delivering a well-fitting custom solution, they position themselves as clear value creators. It’s exactly the kind of move that signals leadership – not just participation in the AI transformation journey.
Why This Requires Careful Consideration
Even with all this interest, very few organizations are jumping in blindly. Common concerns include:
- Existing SaaS investments: If an organization is already on a SaaS platform, moving away introduces disruption and migration risk—so IT needs to have a solid partnership with business stakeholders.
- Cybersecurity responsibility: With a custom solution, IT must assume full responsibility for cybersecurity. Hosting the home-grown software in an industry standard cloud such as AWS or GCP, may eliminate most of these concerns, but still require IT to stay engaged.
- Limited domain expertise: Most IT teams may not have in-house expertise in Sales Performance Management (SPM). This can lead to longer build cycles, design inefficiencies, and solutions that don’t fully capture business nuances.
- Long-term ownership: A custom build requires a clear plan for ongoing support, including bug fixes, enhancements, and scalability-without which it can quickly become difficult to maintain.
Is There a Hybrid Path?
One pattern I’m seeing more frequently is that teams are not immediately replacing their SPM platforms, but instead building around them:
- Custom forecasting tools
- Analytical dashboards and data pipelines layered on top of existing SPM platforms
- AI-assisted dispute analysis
This allows organizations to test their “build muscle” in lower-risk areas before making larger strategic decisions.
What Are You Seeing?
I’d love to hear how others are approaching this—particularly IT leaders looking to demonstrate AI-driven innovation. If this is a topic you’re actively thinking about, feel free to DM me with the phrase “SPM Future.” I’d be happy to exchange perspectives on the build vs. buy decision and what it could mean for your specific landscape.