Master data management (MDM) is a data management discipline to actively “manage” master data enterprise-wide rather than “maintaining” it in each transactional system. There is heightened attention on MDM recently due to the pervasiveness of business intelligence (BI) applications. MDM unlocks the true value of BI by providing a consistent view of business performance measured or analyzed through the key master entities of an organization.
Integrating master data can be perceived as an IT-related issue, and, hence, business stakeholders may be reluctant to engage in these initiatives. But MDM is a cross-functional, technically complex, process-oriented discipline affecting data governance of master entities, which requires acceptance and wide organizational support. MDM initiatives resonate well with each business function when a rationale, viability and applicability are unambiguously articulated and a credible business case is presented.
In this article, I will cover three dimensions of laying out a business case: master entity, technology landscape, and process and industry vertical. A scenario covering a specific master data entity – products, a specific industry and functionality – a distributor, a specific technology (tool agnostic) landscape and their organizational pervasiveness is explored.
Justifying MDM
Errors in master data across multiple sources/applications can cost an enterprise significantly in terms of missing business opportunities or creating dissatisfied customers. MDM helps in reducing such costs and also potentially helps business growth.
Technology initiatives such as enterprise resource planning (ERP), customer relationship management (CRM) and business performance management (BPM) offer an immediate, material impact on business performance and visibility upon implementation. Benefits such as increased revenues, increased productivity or reduced cost for these initiatives could be established, quantified and tracked. Developing a business justification of MDM is challenging because the benefits are often indirect and intangible, as MDM is essentially a technology stack lying between the transactional and analytical systems. There is also inadequate precedence of quantified business benefits due to limited implementations.
Each master entity has its own significance and unique applicability in each situation (size, scale of operations, IT landscape and requirements related to the master entities). For example, managing customer data will yield more benefits on the demand side when compared to products data, which may result in supply chain efficiencies. Hence, an effective business case should be built for each significant master entity and analyze the potential value in stewardship of that data. The following aspects help build a case for MDM:
- Current challenges in the operations and transactional systems (scenario)
- Business benefits in each functional areas (drivers)
- Opportunities yet to be realized (analytics).
A persuasive case should showcase benefits that are achievable and quantify those using models such as ROI, total cost of ownership (TCO), return on assets (RoA) or total value of opportunity (TVO).
Scenario
Let us consider a fictional distributor for electrical and datacom parts called Axal Inc. This distributor has a network of 300 warehouses/branches supplying 1.2 million products with seven major product families and processes 10 million orders a month. This distributor has more than 23 legacy systems, including ERP and CRM systems that support the core functional areas of warehouse, logistics and distribution, sales and marketing and finance.
Axal follows a stringent availability promise of 30,000 (delivered within a day), 9,000 (on-the-shelf availability at its branches) to its customers. Axal grows inorganically through mergers and acquisitions to achieve a larger market share and economies of scale. The sales channels for this distributor are bulk sales to retailers, retail outlets and e-business. The supply side involves thecoordination of many vendors and manufacturers. Because, Axal is in a commodity market, cost levers (margins, profitability of product portfolio and efficiencies) take far more precedence than the demand-side market dynamics (volumes).
