Part 6 in the 6-part Data-Driven Enterprise” series, which examines the challenges, leadership requirements, measurement models, and best practices to become a data-driven enterprise 

Earlier in this series, we stressed the importance of aligning strategy, structures, processes, and technology as key to a successful digital transformation. The data strategy determines which data domains are most critical for the enterprise to fix. Once that has been determined, then it would be rather straightforward to determine:

  • What is required to obtain the necessary data insights?
  • What is required to connect the insights to the enterprise systems?
  • What is required for operationalizing the insights at scale?

Which of the three areas presents the biggest challenge is enterprise-specific, but some pointers are worth considering in all situations.

Data insight

  • Is a platform for advanced insights enterprise-ready?
  • Are the insights explainable to business? Can the results be replicated?
  • Are the insights ethical (e.g., no unfair preferences to certain groups)?
  • Is there a data trail of the business data, so records stored are available for future inquiries and documentation?
  • When and how is data archived or deleted?
  • Is the technology sustainable to manage for a decade or more? Will the vendor, partner, or in-house personnel be available to ensure that it can be scaled, upgraded, maintained, and extended reliably to serve the enterprise without excessive risk or costs?

Information management

  • Is the information management platform able to interlink most of the different data platforms with lineage, metadata, hierarchy, and governance?
  • Are the new insights fully interlinked with related enterprise data? (For instance, is the online sales platform also linked with other sales channels to avoid any cannibalization and ensure that true new revenue is realized?)
  • Are data hierarchies normalized for correct interpretation of results? (For example, are the costs for producing a new widget included as a share of the fixed production costs to represent the true margin?)

Execution systems

  • Are the systems able to re-plan and re-synchronize across many areas in near real-time as new insights are streamed to the execution platform?
  • Are most of the business rules, priorities, allocations, decision matrices, compliance rules, dependencies, and other decision factors codified, so a semi-autonomous re-optimizing of materials, resources, and equipment can occur digitally?
  • Will the analytics represent the status of the enterprise?
  • Can managers make the right decisions based on the data in the execution system?
Blog 6 fig Unlocking The Data Challenge: Where To Start? Best Practices (Part 6)

Summary

In a world of exponentially growing data, our goal is to ensure that our customers remain best-run enterprises, even as much more data resides in platforms outside SAP systems. Our mission is clear: to connect the value chain of data. Where does the road ahead lead?

While every journey may be unique, what we see is an increasingly intelligent enterprise. In the intelligent enterprise, a modern business technology platform and integrated execution systems are a powerful gateway enabling people to interlink, manage, and decide with confidence on their data. SAP is always evolving to meet customer needs, and it will continue to incubate, innovate, standardize, and consolidate its systems to meet the needs of enterprises to be best-run businesses.

Intelligent enterprises use the latest technologies to turn insight into action across the business – in real time. Download the brochure to learn more.