If companies spent on Master Data Management training and technology what they now spend on chasing down and fixing data errors, they would be on their way to a longer term solution.
Inconsistent data is not merely an inconvenience. In most enterprises, the problem has reached crisis levels. Organizations know their applications and information systems contain indispensable value. Unfortunately, discovering and monetizing that value is too tough given the multitude of data lineages and existing definitions of master data. What's worse, users don't know which version of "the truth" they can trust. Even if IT swears by the data, many on the business side aren't willing to take IT's word for it.
With both business and IT leaders increasingly putting a high priority on establishing data quality and defining subjects, processes and metrics consistently, we're going to hear more about master data management (MDM) in the coming year. In a recent survey of 515 companies, Ventana Research found that executives have a strong desire to improve master data about customers, products, locations, employees and metrics, as well as other subjects.
Master data is nothing less than the language of doing business. It consists of business objects, definitions, classifications and terminology that describe business information; it gives an organizational context to transactional data. MDM enables businesses to speak internally and externally in a single language understood across all informational and transactional systems. Half the organizations responding to our survey have some form of data governance initiative under way. MDM is central to these governance processes and policies, which are critical to giving businesses confidence in their data.
Our survey found that companies spend more time reconciling data than analyzing it. This result speaks to the economic issues driving MDM. Money wasted in dealing with data errors is sizable and still growing. If companies spent on MDM training and technology what they now spend on chasing down and fixing data errors, they would be on their way toward a longer term solution. And decision-making would improve: Forty-two percent of survey respondents cited accuracy of information for making business decisions as the most important MDM benefit.
Yet, MDM implementation is immature; 70 percent of our surveyed organizations are in the early stages of technology deployment, while only 37 percent have initiated an MDM project and just 4 percent have completed one. These numbers will change in 2007 as MDM moves up on the agenda and IT budgets allocate funds for MDM projects.
Large organizations have complex networks of ERP, CRM, SCM and other applications and systems. More than a quarter of those we surveyed have at least two and as many as 50 instances of their applications, and 31 percent have more than one data warehouse. MDM must address every one of these instances and multiple vendors' application frameworks. A single version of the truth must arise from the many master data definitions stored in disparate locations--and in personal computer spreadsheets.
Technology is critical, but MDM is not the kind of thing where companies can just throw technology at the problem. Business and IT stakeholders and data stewards must work together on MDM. Many organizations are already flirting with the mistaken idea that a single technology from a single supplier will solve the MDM dilemma. Vendors are quite willing to let companies draw this conclusion, but in fact, an MDM solution involves the assembly of components on top of a more neutral architecture and technology framework.
Complicating the situation is the fact that there's more than one kind of MDM. Informational and analytical MDM requirements to support decision-making differ from those for operational and transactional MDM. Informational requirements are being addressed by IBM, Kalido and Stratature, among other providers. Customer data integration is another MDM specialty, though vendors that have made names for themselves in this space (such as Purisma and Siperian) are looking to move into the broader MDM market.
With your company's performance in the balance, MDM belongs in the 2007 budget. However, relying on a single view of MDM from one BI, ERP or information infrastructure provider will not help you take charge of all your enterprise's data. Start by defining your organization's business and technology MDM requirements. Don't lose sight of those requirements amid the noise of the vendor marketplace.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.