Every executive has experienced dueling spreadsheets. Rival business advocates present compelling spreadsheets. The arguments are clear and persuasive, backed by an impressive array of quantitative data.
On closer inspection, however, the dueling spreadsheets reveal disturbing inconsistencies in the data. Overall 3Q sales for Region 2 are significantly different; customer data in one points in a different direction than the other. Even data about the company’s products are different. How can that be?
Enterprises struggle to gain a consistent, shareable and accurate single version of data across their enterprises—a single version of the truth—according to Gartner’s latest Magic Quadrants for Master Data Management. Yet, achieving and maintaining a single, semantically consistent version of master data is a critical capability that supports many business drivers, from sales to compliance.
Master data management (MDM) is the process that tries to—you pick the word—(enforce), (impose), (enable), (manage) consistent data throughout your organization. Its goal is a single version of the truth in data terms.
This is not easy. There are technological, organizational, cultural, and procedural challenges involved. Any of these can undermine the effort. Further complicating the effort are the staff, including executives and managers who have a vested interest in ensuring their particular version of the truth prevails regardless of the actual data.
IBM, a leader in MDM along with Oracle, defines master data as common data about customers, suppliers, partners, products, materials, accounts and other critical entities that is commonly stored and replicated across IT systems. Master data is high-value, core information used to support critical business processes. It sits at the heart of every business transaction, application, report, and decision. IBM provides a good overview of MDM here.
From a technical standpoint, there are numerous challenges to MDM, starting with the sheer multitude of applications and systems that create and store data in their own ways. And then the data often is incomplete or missing. It may be incorrectly copied and distributed. Sometimes human errors produce inaccurate data and those mistakes ripple through the system uncorrected. Integration always is a challenge. With data growing exponentially and organizations riddled with non-integrated application silos, it is not surprising that a single version of the truth is so hard to come by.
Or organizations will have diverse application and information management portfolios, with fragments of often inaccurate, incomplete, and inconsistent data residing in various applications or different databases. There usually is no comprehensive system to maintain the single view or to manage the complete life cycle of the master data as it continually changes.
The result: executives make decisions based on inaccurate or inconsistent data. Often they may not even be aware the data is problematic. Or, they may feel there is nothing they can do about it. Yet, the ability to create, maintain, and leverage a single, trusted, shareable version of master data, notes Gartner, is an essential requirement for business processes and meaningful business intelligence (BI), not to mention the accompanying risk of noncompliance with whatever regulatory mandates apply to a particular piece of data.
This is where MDM comes in. MDM is a technology-enabled discipline in which business and the IT organization work together to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise’s official, shared master data assets.
Advanced automated technology is essential to avoid the inconsistencies and inaccuracies that plague corporate data today. Gartner identifies 12 players in its report on MDM for product data and nine players in its MDM for customer data report. IBM and Oracle are the clear Gartner leaders in each group. Earlier this week IBM introduced InfoSphere MDM v10 here. View Oracle’s MDM products here.
To put an end to dueling spreadsheets and inconsistent data you need MDM. And even then, it isn’t easy although IBM insists it has been able to lower the skill set required to implement MDM, accelerate the overall time to value, reduce risk by decreasing the time to go live with an MDM project, and lower the overall cost. That’s as good a start as any.