CEOs and their teams have access to a wider pool of data than ever imagined even 10 years ago. The problem is not enough information, but getting to the right information to support sound decision-making. Many executives intuitively understand the value of master data in that process. They sense that highly accurate customer, vendor, product, and transaction data can help companies comprehend and react to paradigm shifts, and maximize profit or minimize loss. Where executives struggle, however, is creating a strategic organizational transformation that gets master data to work in a sustainable way, at scale.
Our experience indicates that a new operating model for master data—not just a new technology project—is the key to unleashing the insight-to-action power trapped in vast quantities of enterprise data.
Silos can’t handle volatility, but MDM can
In a recent survey of almost 1,000 executives from large companies in developed markets,1 we found that—quite surprisingly—master data management (MDM) was seen as a very important weapon against the key challenges affecting enterprises. Some striking examples: 55% of finance executives, as well as the same percentage of marketing executives, and 48% of procurement executives see MDM improvements as one of the “top 3” initiatives for enterprise agility and adaptability. Interestingly, 59% of procurement executives indicate that MDM helps materially reduce costs, 63% say the same about MDM’s impact on compliance (as 49% of finance executives do), and 59% believe that MDM can materially improve risk management. Although these scores are very high, it is interesting to identify who does not rate MDM as so important. The answer is: those who have more basic issues to grapple with. In a separate study,2 we observed that 48% of Finance Planning & Analysis (FP&A) leaders in mature FP&A organizations consider MDM and governance a very high priority—compared to only 25% of those in less mature FP&A functions.
So useful, yet not trivial to harness
Master data encompasses all key information such as customer profiles, product portfolios and performance, production capacities, inventory levels, supplier information, and host of other data that, in their own right, is required to process crucial operations across the business. Viewed independently, these bits of information deliver insights into the key parameters of sales, profit, and growth. However, viewed collectively, the data provides insights global enterprises use to build real-time scenarios that can have far-reaching implications in helping companies maximize profits and grow at a greater pace. For that reason alone, MDM should be near the top of any CXO’s to-do list for improvement.
Although senior executives seldom look at raw master data, their decisions are often drawn from insights provided by it, which is why accuracy and timeliness in collecting and integrating data are so critical to business success.
Better MDM can have a significant positive impact on managing market volatility. Systems that take months to update a record simply cannot support fast, decisive responses to market changes. Conversely, well-integrated data systems with analytical capabilities can quickly spot spikes in sales, production cuts, or changes in consumption across geographic or product sectors. Amazon, for instance, uses dynamic pricing based on MDM output by region to drive sales. Even banks, which traditionally have not emphasized MDM, are now using it to understand individual customer behavior and preferences in order to manage risk and selectively market products based on customer profiles. Consistent processes and systems across geographies and business lines are therefore essential for quality data and timely reporting.
Unfortunately, MDM is hampered not only by the sheer volume of information but also that the data is usually held in multiple business silos on disparate legacy systems and processed by separate teams that handle only one aspect (product, procurement, billing, etc.). In short, there is no single source of truth across countries or business lines, or any way to link the data to arrive at integrated reporting and analysis that would provide a clear and holistic view of operations. For bank executives looking to spot fraud or accurately assess a customer’s creditworthiness or retailers looking to understand consumer interests and product costs in various regions, this lack of coherent MDM and related analytics cripples the company’s ability to lower risk or to react quickly to trends and market changes.