I am endlessly fascinated by data: how and why we accumulate it, what we do (and don’t do) with it, and—perhaps most intriguingly of all—how organizations are adapting to incorporate data as a business priority, rather than a computing by-product.
In my role, I’m fortunate enough to be able to follow the data journeys of organizations across a variety of industries and what strikes me is that, while one size does not fit all when it comes to managing data, there are some universal data truths that seem to come up time and again.
Recently, I was debating with some of my colleagues on alternative approaches to Master Data Management (MDM) – a wider topic we have been talking about for some time, now. One colleague told me that his banking clients know well the importance of leveraging data but had questioned whether it’s really necessary to deploy a specific MDM tool in order to run a robust and fruitful analytics program. In essence, to MDM or not to MDM?
I’ve argued before now that MDM is a must, but it turns out that there are exceptions. My colleagues were able to point me to a small number of organizations which have, since the very beginning, organized their data clearly, assigning owners, leveraging CRM tools and maintaining good data governance. Given that mastering data is really all about cross-reference between data sets, we could say that, despite the lack of an MDM tool or program in place, it’s still a form of MDM. And for some, it works. (Data truth number 1: there’s more than one way to do it).
But there’s a flipside: the second those organizations acquire a new company, merge divisions or encounter market disruption, their quietly effective non-automated way of managing data is likely to rupture, as processes, people and data sources inevitably change. The moment that diverse data sets are treated differently, it challenges the ability to cross-reference and create relationships between data from different sources. Suddenly the rules are no longer the same, and if no MDM tool or program in place to manage this, there’s a danger that things can go downhill pretty fast. (Data truth number 2: data is now business-critical, whichever way you look at it).
That’s because robust MDM brings together governance, processes, standards and tools under one roof and sets unshakeable foundations for collecting, analyzing and leveraging data into a single view. So I’d argue that it’s still the key to making data invaluable. (Data truth number 3: MDM pretty much cannot fail to bring value).
So to bring us back to the question—to MDM or not to MDM? Ultimately, the better the data, the better the insights—and the better the insights, the better the business decisions. That’s the most basic case for setting your MDM course and leaning on the necessary process and tools to make it work. For many organizations working without a specific MDM system, their alternative data approach will be enough for the foreseeable future. But is it enough for the unforeseen future? Maybe that is the question.
This article was written by Murat Aksu from CapGemini: Insights & Data Blog and was legally licensed through the NewsCred publisher network.