Determining data value by measuring return on effort

3 min read

I’m always very encouraged when professionals from different architectural disciplines can converge on common ground. This can be rare event, so when it does happen, I like to call it out.

Such an event has happened recently with a contact coming from the business architecture discipline, namely Robert DuWors, with us both trying to put some metrics around the measurement of data value in our respective areas of expertise.

I believe that business architecture and information architecture are the two core pillars of the architecture of an enterprise. But practitioners of these interconnected disciplines can frequently rub badly against each other, each side devaluing the other’s methods and approaches. So, to reach agreement across the two on what constitutes enterprise value of our efforts is a happy place to be.

What came out of those discussions was this equation…

…and together, we agreed that this represents the value of a specific item of data to the enterprise from both information and business perspectives. Now, of course, this may be refined over time, but it already contains most of the aspects that together, Robert and I believe are key to this metric…

So, what does this equation gives us? It’s in 3 major sections, which I will call ‘Horizons.’

The numeric value these generate (you can chose your own scale as long as they are applied consistently and with lack of bias for any particular horizon) can then be used as a point of decision where values under an agreed limit are deemed as not able to return sufficient value to the enterprise in respect to the specific effort required to achieve that value.

A subjective judgement call will need to be made on a case by case basis…but it means that general low cost effort can be applied to the majority and focus placed on the big ticket items, regardless of what makes them a big ticket item…priorities can be set, but the idea is you get everywhere eventually.

Robert DuWors originally stated this as a function FrameOfReference(), however this subsequent version we agreed was expanded to enable the concept of consensus….or a frame of reference that can be agreed across all interested parties across the entire enterprise. This could also include external parties key to the enterprise.

The four elements are:

The consensus horizon is critical in establishing where value can be recognised as worth the effort of increased data or business management attention, the product of the four consensus aspects creates the consensus horizon metric.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.