Q&A: Why Data Integration Is the Foundation of a Successful SAP Analytics Strategy 

Many organizations struggle to translate their data ambitions into measurable outcomes as they accelerate investments in analytics, AI, and cloud platforms. According to Ingo Hilgefort, Senior Director of SAP Business Data Cloud, SimpleFi Solutions, success requires more than modern tools. It demands alignment between business and IT, executive sponsorship, trusted data, and an architecture designed to support real decisions. 

Ahead of his session at SAPinsider Las Vegas, Hilgefort shared practical insights on what separates effective data strategies from aspirational ones, why integration is critical across complex SAP landscapes, and how leaders can avoid common pitfalls that cause initiatives to stall before delivering value. 

SAPinsider: How has your experience across product management, engineering, and enterprise BI implementations shaped the way you think about data and analytics strategy today? 

Ingo Hilgefort: In terms of the different roles that I’ve had, one of the key things I learned is that business strategy and IT strategy play a very important role. From product management, you learn to focus on business value and outcomes. From an engineering perspective, you learn about architecture and scalability. And from an implementation and consulting standpoint, it’s about feasibility.  

Thus, data strategy isn’t about technology, a product, or an interface. It’s really about business and IT coming together. 

SAPinsider: Why do many organizations still struggle to translate data and analytics investments into tangible business outcomes? 

Hilgefort: Many organizations don’t take the time to clearly define the expected outcome. I’ve seen data strategies written across hundreds of pages that ultimately ended up in a drawer and were never implemented. 

There are often great conversations about business outcomes, but the practical aspect is missing. Organizations must be realistic while defining their goals. They must ask, what decisions are we trying to support? What scenarios matter most? And What do we expect our data landscape to provide? 

These questions help to identify the right use cases, understand the organization’s stakeholders, and align everyone around where the organization wants to be in the next 12 to 18 months. That early collaboration is often where initiatives fall short. 

Another critical element is executive sponsorship. Even if teams align, without leadership providing airtime, budget, and direction, there is no real starting point. 

SAPinsider: From your perspective, what distinguishes a true data and analytics strategy from a collection of disconnected tools and initiatives? 

Hilgefort: Organizations shouldn’t approach this from a feature-function perspective. Whether you look at BI tools like Power BI, Tableau, SAP, Qlik, or MicroStrategy, comparing features alone misses the point. 

The tool is a vehicle to reach a goal. Leaders should start by asking what they are trying to achieve and what capabilities they need, not which product they should buy. 

More features don’t necessarily create more value. Focus on the use case first, then determine the implementation details that support your business goals. 

SAPinsider: What core components must be in place for a data and analytics strategy to be effective at the enterprise level? 

Hilgefort: Executive sponsorship is essential. I once had a customer ask what to do if the CEO and CIO couldn’t agree on direction. The reality is that both rely on the data strategy, and they need to align on where the organization is going. 

If that sponsorship isn’t there, the chances of success are very low. 

The next step is an honest assessment of where you are today. Are you still running static reports? Are you enabling self-service analytics? Are predictive capabilities or generative AI already part of your landscape? Be realistic, don’t claim predictive maturity if you’re still printing spreadsheets for meetings. 

From there, define where you want to be in one to three years and build a capability roadmap to get there. That may involve new products, updated architecture, or different operating models. 

Two additional areas are often underestimated. First is data literacy. Even the best analytics roadmap fails if users don’t understand the dashboards in front of them. Second is governance. Without trusted information, decision-making slows, or worse, stops entirely. 

When people hear governance, they often see it as an obstacle. It shouldn’t be. Trusted data enables faster and more confident decisions. 

SAPinsider: You mentioned that many organizations come to meetings with different numbers and different reports. In landscapes where tool sprawl is common, how should leaders think about addressing it? 

Hilgefort: I’ve been in the industry long enough to see this pattern come and go. There are phases where customers want to consolidate everything with a single vendor, followed by phases where best-of-breed tools dominate, and then a return to consolidation again. 

The mistake is approaching the decision from a feature-function perspective. If you compare BI tools purely on features — how many charts they offer or what capabilities appear on a checklist —  you miss the bigger picture. 

Leaders should start with the use case. What are they actually trying to achieve? What capability do they truly need? More features don’t automatically create more value. 

Instead of asking which product to buy, organizations should define the capability required to support their business goals. Only then should they look at the implementation details. 

SAPinsider: What role does data integration play in supporting analytics across complex SAP landscapes, and where do organizations typically underestimate its importance? 

Hilgefort: Integration is crucial because you can’t make a decision if you only have half of the information. No user wants to open ten different dashboards to gather insights from finance, procurement, HR, and operations. 

Integration is about accessing data and harmonizing it. You need consistent master data, aligned KPIs, and shared definitions. For example, an employee should be defined the same way across SAP S/4HANA and SuccessFactors. It’s the same person, and your data should reflect that. 

When organizations get integration right, it often leads to powerful insights. Some discover they are overstocking products because predictions were based on incomplete data flows. 

Leading organizations also look beyond their internal data. By incorporating industry benchmarks, supplier data, or external providers, they gain context – understanding not just how they are performing, but how they compare to the market. 

SAPinsider: What advice would you give to leaders who are just beginning to formalize their data strategy? 

Hilgefort: Don’t reinvent the wheel. There is a significant amount of research, frameworks, and guidance already available to help organizations establish capability models and assess their current state. 

A data strategy is not a document you write once and consider finished – it’s a living document. Communication is often underestimated. Some organizations create a strategy and then go silent for 18 months, leaving stakeholders unsure about progress. 

Leaders should consistently communicate where they are going, why it matters, and what the plan is. Keeping people informed builds alignment and momentum across the organization. 

This Q&A gives SAP leaders, analytics teams, and ERP program stakeholders a practical look at how to build a data and analytics strategy that delivers business value—starting with integration, governance, and executive alignment rather than tool selection. Interested readers can hear Ingo Hilgefort share additional guidance and best practices during his session, “Crafting a Winning Data & Analytics Strategy: Key Elements and Best Practices for Success,” at SAPinsider Las Vegas 2026.