Master data management can no longer be an afterthought in today’s data-reliant world. Making it a top priority can be an efficient way for business leaders to gain insights from business processes and operations to increase business value. However, implementing a successful data management strategy is easier said than done. Deloitte’s data management and architecture study revealed that about 86 percent of companies find leveraging data for new products and services challenging. Given this, about 36 percent still favor manual data management processes. But there are several ways to turn things around. This article can be a great guide to help you implement your master data management strategy.
Identify the business problem.
Several challenges account for inefficient results from your master data management strategy. One of such is the imbalance between MDM strategy as a tech project and MDM strategy as a revenue opportunity. A master data management strategy can have several business implications for your entire organization. Understanding your business’s unique demands for an effective MDM solution can be a great first step to the entire process.
Start by listing your business objectives, linking them to unique business challenges your business seeks to solve. It can be data quality issues, operational efficiency, or supply chain optimization. The more you understand your business’s demands for MDM, the better your chances of setting the right context to guide your strategy’s implementation.
Ensure stakeholders are on the same page.
Strategic implementation requires an all-inclusive approach, and many businesses are tempted to leave the entire responsibility to an IT department. But master data strategies may demand significant changes in organizational behaviors, and users may have to adopt best practices in ensuring MDM plans actualize in the real world. Therefore, providing business stakeholders with periodic progress reports can be crucial in garnering maximum support for your data strategy.
You can segregate business stakeholders into multiple groups based on their influence, subject areas, product lines, and other factors. Customers may not be on the same level as your company’s financiers, but including your customers in your MDM plans can be a great way to carve sustainable customer relationships in the long run. That said, your customers may not need the same information as higher-level executives. Therefore, defining stakeholder groups and their data needs can be a good idea.
Consider multiple MDM implementation style options.
A good MDM strategy affords companies unparalleled access to accurate data, and companies with high-quality master data can ensure data consistency across multiple data sources, making it easier to leverage master data for revenue growth and a competitive advantage. That notwithstanding, several implementation styles exist, and each one may have different implications for your MDM strategy outputs. Gartner Inc. outlines four implementation styles to execute your MDM initiative. They include consolidation, registry, centralization, and coexistence.
Making a choice between the styles can be daunting; however, businesses can consider several factors, including the specific master data to be selected for storage, data governance, and regulatory compliance issues, among others.
Establish prioritized business outcomes.
It’s only right to prioritize your business outcomes after setting your corporate objectives, engaging key stakeholders, and choosing the implementation best fitting for your business goals. Generally, master data management has many use case benefits, but your business has a better chance at scalability by focusing on a number of benefits rather than leaving things to chance. Businesses can prioritize their outcomes by assessing key performance indicators to measure and communicate different phases of the strategy’s progress.
All in all, setting your strategy’s direction can facilitate its implementation in several ways. For instance, you can rally support from stakeholders across the entire organization by focusing on specific outcomes. Also, it helps to see master data management as a never-ending process rather than a one-off project. That way, you can evaluate success metrics, identify weaknesses, and streamline implementation efforts for improved results.
