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The Holy Grail of Data Intelligence: The Single Point of Truth


Everyone is searching for it, but very few people find it – at least not in their own system landscape: the Single Point of Truth. But without this Holy Grail, data intelligence has minimal value, because how should the right decisions be made based on data if it always points in different directions?


The Single Point of Truth – not only a Question of Technology

The more data and systems involved, the further away the Holy Grail moves, because with increasing diversity the technical and conceptual integration effort increases. If Marketing, Purchasing and Accounting each have their own understanding of sales, this not only cries out for uniform reporting, but even before this, some basic definition of terms is required: Marketing may care primarily about the “sales” from realized “order”-clicks, Purchasing leaves cancelled orders out of their “sales” and Accounting is only interested in the “sales” that are left after shipment returns? In such a case, the departments may all be talking about completely different numbers and yet they are all using the same terms. This is not a basis for good company decisions!


Key Data & KPIs: create a Common Understanding

Before a technical integration, the point is to first create a common understanding of the relevant key data and KPIs. For this we can recommend the following approach:

The_Holy_Grail_Smart_Paper_Reporting_EN1. All at one table: A common understanding of key data and KPIs requires the inclusion of different opinions. Step 1 is therefore to get all participants at one table. Who should be included in the discussion? For example, all division managers?

2. Collecting: Before rambling discussions about the supposed “correct” definition of key data break out, the goal should be to gather all of the company’s relevant key data and KPIs. How do we want to measure success?

3. Differentiate: Once the key data portfolio has been outlined, it is then about the detailed work. Different definitions of the same key data have to be disentangled and understood. Who has which understanding and why?

4. Define: Where diverging opinions become apparent in the differentiation process, a decision has to be made: Is it possible to get consensus for a common definition? Does it make sense to accept several coexisting definitions? Caution: If the latter is the case, there needs to be a distinct name as well as a clear demarcation among each definition.

5. Document: Once the key data portfolio has been worked through in this way and agreement achieved, the results have to be documented. Which form is most suitable for the documentation?

6. Communicate: After the hard work on definitions, of course they should become the basis for future work, so they have to be communicated. How can we best reach all employees and convey not only the definitions, but also, the importance of the issues related to the definitions? How can the documentation of the results be made centrally accessible in the best way?

7. Reflect: To achieve a common understanding of key data and KPIs is awesome – but it is not necessarily a final result set in stone. The definitions have to be continuously assessed, checked in the work process and, if necessary, adapted. For this process, there needs to be a responsible person assigned so that the ends don’t loosen up again over time. Who can be considered for that and how should the adjustment process be organized?


…and then comes the Technology

Well, unfortunately the trip to the Single Point of Truth is not yet done at this step: After the definition work, there of course follows the technical part of the implementation. With the company IT department or a business intelligence provider of your choice, the systems that need to be integrated are determined and (based on former discussions) the project goals are discussed – and this includes the definition and calculation of the required key data and KPIs. The road to technical integration has now been paved!

Alternatively, the use of a standardized, curated, subject-specific business intelligence solution like minubo is a possibility: Here the complete key data set designed for digital commerce is delivered, the Single Point of Truth is, so to speak, available out of the box. Using minubo eliminates the need for a long preparatory period, the definition efforts, as well as requesting external expertise; and instead, delivers sturdy analysis results from day 1 – however it has its limits in realization of individual requirements.

And maybe even the agreement on definitions is enough to allow you to speak the same reporting language even while using different systems? Why not! This is also a type of Single Point of Truth. Every company should define a solution for themselves that satisfies them best.


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