Governance is Not Maintenance: Solving the Human Side of SAP IBP Master Data

Master Data is the language of planning. However, even the most eloquent language can fall apart if the speakers don’t follow the rules. In the second part of SAPinsider’s interview with Nikki Sheridan, Functional Lead for the SupplyChainPaths practice at CloudPaths, she shared insights on the most critical yet overlooked aspect of success in an SAP Integrated Business Planning (IBP) implementation—Governance.

“When we talk to clients about governance, they often think about IT tickets, help desks, and fixing errors,” Sheridan said. “But that is reactive. True governance isn’t about cleaning up a mess; it is about preventing the mess from entering the model in the first place.”

Urgency Trap

However, why does bad data enter an SAP IBP system in the first place? According to Sheridan, this is usually because a user is acting out of urgency or impatience.

“Mature governance is preventing bad data from getting into the model in the first place,” Sheridan explained. “If the users have an understanding of who owns that piece of data and they know the consequences of bad data, those are good signs of a mature data governance framework.”

Additionally, if process clarity is missing, users will create their own workarounds to get the job done. They need to know specifically how and when master data should be created, and, more importantly, what happens if it isn’t done right. “When users understand the consequence—how a bad location-product combination affects planning levels, calculations, and system performance—governance becomes behavioral rather than bureaucratic,” Sheridan noted.

The Lift and Shift Pitfall

One of the most significant drawbacks of reactive governance that Sheridan identified is the tendency for integrators to build a model that matches the client’s current process instead of their desired one.

She noted that implementation partners often look at the source system and replicate what they see. This results in the implementation partner unwittingly designing the data model around the business’s current pain points, essentially digitizing their existing problems.

Sheridan recalled a recent customer where planning teams were operating on different grains because the master data wasn’t harmonized. The easy path would have been to patch the data. Instead, the team paused. They pulled the business back into design conversations to rebuild the data grain to match how the business ran, not how their legacy system was configured.

“The result was immediate. Within a month, users dropped Excel and moved into SAP IBP because the system finally aligned with their reality. Adoption sped up significantly because trust was restored,” Sheridan said.

Designing for the Future

Finally, if there is one piece of advice Sheridan gives to business leaders, it is this: “Do not start by asking, ‘What data do we have right now?’ Instead, ask: ‘What decisions do we want the system to drive in the future?’”

She added, “We’d rather slow things down to make sure that we capture all of the requirements for the future state rather than trying to fall into that situation where we’ve got slow adoption.”

Therefore, a fast go-live means nothing if it’s followed by years of retrofitting. “Slow down, define your language, and build a governance model based on human behavior, not just system configuration,” Sheridan concluded.

What This Means for SAPinsiders

Choose behavioral governance over bureaucracy. This creates a culture of ownership. When users understand why, they stop looking for workarounds. This leads to cleaner data entry at the source, reducing the overhead cost of IT support and data cleansing teams.

It is better to pause than have a flawed process. SAP partners like CloudPaths actively advise clients to pause implementation if the data model mirrors an inconsistent current process. By slowing down to capture future-state requirements, it ensures the final build is robust. Even though it may seem counterintuitive, this pause accelerates adoption. As seen in Sheridan’s example, aligning the data grain with actual business needs enabled users to drop Excel and fully adopt SAP IBP within just one month of the fix.

Cloudpaths recommends a diagnostic loop to ensure a governance model is scalable and resilient. This includes identifying why users are exporting to Excel instead of using SAP IBP, creating an accountability map that assigns a clear owner to every data point, and interviewing planners to identify system blocks and where they circumvent the process to move faster. According to Sheridan, these friction points provide a roadmap for master data optimization and governance of SAP IBP processes.