A sound analytical strategy encourages activity and embraces a self-service methodology but also provides guidance and oversight from those close to the data. This governance will be instrumental in preventing data quality issues, superfluous analyses and misguided decisions. Enter master data management (MDM). The technologies and processes underlying a typical MDM strategy not only provide oversight and access control, but also enable companies to track the origin and lineage of data to ensure safety and consistency in the decision process.
While data governance may have once been viewed as unnecessary or burdensome red tape, it is now seen as an opportunity to pave the way for effective analytics. The first wave of enterprise business intelligence (BI) was effective in gathering and processing data for better visual rendering via reports or dashboards, insights that would typically be served up to an executive in a position to act on it immediately. Almost exclusively owned and operated by the IT department and those close to the data, this process could be managed and tracked fairly easily but suffered from a lack of agility and breadth of usage. The next wave focused very specifically on agility and self-service usage of analytics. Companies needed a way to enable their most curious and critical decision makers with fact-based insight, whether or not these were technically inclined people. The problem, in some cases, was that this widespread analytical activity created issues like data duplication from different business units, multiple interpretations of the same information, competing analyses, and erroneous decisions as a result.
Recognizing the value of pervasive analytical activity in combination with proper supervision, companies today want to have their cake and eat it too. By marrying analytics with a foundation of governance and oversight through the use of MDM, companies are actually finding a greater level of satisfaction in their users. From the senior executive to the mid-level manager, these non-technical decision makers are more satisfied with data quality, their ability to access and share information, and the overall ease-of-use of their data systems (Figure 1).
Figure 1: A Governed User is a Happy User
Governance and strong oversight isn't just about a check box on a corporate compliance report however. The data above demonstrates how this type of environment helps foster trust among end-users leading to a higher overall level of satisfaction. This foundation of quality and trustworthy data, combined with an active and engaged group of users, is the hallmark of a company using a governed approach to MDM and this approach carries a variety of benefits, such as:
- Track and traceability. Data changes constantly. Even data that is widely considered to be static is only static for a finite period of time. Addresses change, names change, lead times change, product specifications change. The ability to understand the lineage of information as it changes over time is not just about improving the general quality of data, but is critical to a company’s ability to ensure things like product safety or the security of sensitive information. This all stems from having a foundation of high quality and complete data. Companies combining MDM with strong governance policies experience 2.3 times fewer instances of inaccurate or incomplete data.
- Data expediency. With a foundation of quality trusted data, it’s easy to see how organizations can expedite the flow of information within their companies. Fewer instances of corrupted data result in less time spent prepping information, which accelerates the analysis process and helps create insight more quickly. Companies using governance and MDM are 65% more likely to see an accelerated time-to-decision.
- Business growth. Data quality and speed are critical, but at the end of the day business results speak the loudest. Today’s best analytical strategies combine the oversight and guidance of early business intelligence with the user enablement and creativity of more modern analytical environments. This powerful combination enhances the usability and overall value of data, provides users with more confidence in their decisions, and produces results. Companies combining MDM and governance are 2.2 times more likely to see year-over-year revenue growth greater than 20%.
The ability to deliver heightened business performance from MDM and analytics is predicated on far more than just technology usage. Top performing companies are also more likely to have a variety of organizational capabilities in place that help them execute against the promise of their technology strategy. Data governance policies and procedures help produce higher quality data but also provide much-needed visibility into data lineage. Top companies are also more likely to have a strong collaboration between IT leaders and line-of-business decision makers, one that helps connect the most data-driven managers with the right data at the right time. This effective combination of data management, data oversight, and analytics, delivers substantial business results for companies today.