by Angela Guess
Johann van der Walt of Thought Bubble recently set forth his argument for why Master Data Management should begin with analytics rather than operations. He begins, “With any enterprise project, it makes sense to follow a phased approach, pick the low-hanging fruit, deliver some business benefits early on, gain buy-in and support, then continue along the chain. It highlights the considerations of complexity and cost. No company wants to tackle projects that are highly complex and very costly. The opportunity for failure is just too high and the cost can be extreme. Businesses want to get stuck into projects that are low-cost and which have low complexity to give themselves the best opportunity for success and to get the most immediate and cost-effective benefits possible, says Johann van der Walt, MDM Practice Manager at Knowledge Integration Dynamics.”
van der Walt continues, “That’s why I believe there is still a great deal of education to be conducted around master data management (MDM). In many cases, South African businesses are going directly to the high-complexity, high-cost end of the scale, and it’s not because they’re suckers for punishment; it’s because they lack the fundamental understanding of the animal that is MDM. Overall, MDM aims to provide quality information that business executives can use to devise strategies and make operational business decisions. The need usually stems from segmentation of business lines that results in poor understanding of customers, products, materials and a host of similar business components. There are multiple, overlapping and duplicated data entities, and that clouds the view executives have of the business, disabling them from making sound decisions about the organisation’s future.”
While the premise of starting small and expanding is sound, I find that starting with analytics is how clients tend to boil the ocean on MDM, loose focus, and become overwhelmed eventually abandoning the project in data discovery. It is seemingly a logical point to start as analytics is more closely associated to getting data value, you speak the same language, and you are tightly working with data. Nice IT comfort zone. But, it is business process (operations) that created data, changes data, and consumes data in a more structured and bite-size manner. Business process allows you to better focus on data that matters and more clearly defines master data. It is also how to more easily get the business speaking about what is important in terms that are understood and relate very specifically to their urgent needs. Business performance measures business process/operational through put and a good starting point to analytics. Analytics lends itself to discovery making MDM about managing all over managing what matters. Even if you start by analyzing data within a process, that is highly useful to developing MDM that supports Analytics. I don’t think you should pit operations against analytics. They need to support each other.