MDM: The Cassandra Conundrum

Greek legend has it that when Apollo fell for the beautiful Cassandra, daughter of the King of Troy (nope, Brad Pitt wasn't in the works then!), she spurned him. An angry Apollo, who had earlier provided her the gift of prophecy, cursed her saying that nobody would ever believe what she foretold. Looks like MDM consultants share the same fate, as of now at least.

Enterprise data continues to be in a state of chaos thanks to data silos and we know that MDM as the foundation is the way out. But for most organizations it just leads to discussions on investments and changes in processes and it is eventually put off. Most often than not, Data Quality and Data Governance are also brought into the picture and the discussion does not proceed further.

We as staunch followers of the MDM discipline consider data as the underlying foundation of any business for managing enterprise information. For us, Data Quality and Data Governance augmented by Profiling and Standards are critical from an execution and strategy perspective, and central to any MDM program. Hence, viewing MDM as a strategy is critical to success.

Here are some "predictions" related to the analogy of Cassandra, steps that an enterprise should take if it has to find success in its MDM program:

Invest and invest well in profiling; then assess and make that a continuous "ingrained" process; set right what is wrong; nurture and monitor the process.
Inculcate business-specific and related rules that help enhance the value and quality of the available data. By making it a continuous process, the key stakeholders start to gain confidence in the system and make fact- based decisions.
Build a Governance framework; an 'Umbrella' to ensure that operational and feedback related aspects are addressed by conscious involvement based on the inputs provided. This again has to be a continuous process with a feedback mechanism in place.
Set up standards for the above. This helps in compliance and enables ease of business operation.

The illustration below summarizes these

Illustration: MDM Framework

'Easy to preach, but not to practice,' the unconvinced Apollo might still snap. So what is the solution? Incorporating the art of selling Data Quality and Data Governance to various stakeholders as part of the overall MDM strategy is the first step. Elucidation of the related opportunity costs is key to selling and making MDM a success for an organization. Pointing out some real issues and business problems caused by misgoverned and bad quality data is the next step.

For instance, the uproar caused in the UK when inaccurate data led the authorities to direct some legal migrants to leave the country¹. An efficient MDM strategy would have saved the government the embarrassment. In another case, again in the UK, the Department of Health had to delay its national Payment by Results tariff for adult mental health services program thanks to a huge data error². Here too, MDM would have guaranteed data integrity and the program could have been introduced as originally scheduled. Last year Gartner said that by 2016, enterprises need to spend five times more on governing information, to be successful³. They also said that by 2014, 66 percent of the Fortune 1000 organizations will have deployed two or more MDM solutions to support their enterprise MDM strategies⁴.

Once the hard work of making converts out of MDM agnostics is done, assist them in implementing strong processes and putting in place best practices that will benefit the enterprise. But this needs to be done real quickly via short tactical wins to help build a case for MDM.

How often have you become a Cassandra? Do share your experiences.?

About the Author

Venkataraman Ramanathan has more than 15 years of experience in the areas of MDM, DQ, Data Governance, CRM, BI and Java. He has been involved in various consulting and engagements across geographies for a variety of Fortune 500 companies. He is involved in the areas of customer re-engineering, machine learning, data quality, data governance, sales and service efficiency, business strategy and business analytics/intelligence.

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