Machine Learnable Data Management - the Circle of Influence!

Let's throw in some acronyms - CDO, CDO (yeah there are two of them!) DG, DQ, DS, CXOs and let us limit ourselves here. Vantage Point was a great movie. The director shows us one incident from six different vantage points. Different people viewing the same incident - the attempted assassination of the US president - at the same point in time from their own perspective. Rings a bell? Quaid plays the quintessential secret service guy who saves the day. On a same note, how have these different vantage points of a Chief Digital Officer, Chief Data office, Data Governance Leader, Data Quality leader, Data Steward and many of the CxO's hampered or is hampering a digital revolution within your business? Doing average or a roaring business - are you? Quite the question. For businesses wanting to have a 'x'-degree view of customers and a great personalized CEM (customer experience management), you need to know the 'circle of influence', as we call it, that MLDM can have in today's digital business.

Master Data Management (MDM) for long has been a bad and neglected child at that. Reprimanded, loved and still being used to solve business issues as we speak. The digital era not-withstanding. Technologies will get hyped and mature but the core reason for such strategies are everlasting. If you are writing a piece of Machine Learnable Data Management (MLDM) - machine learnable code for MDM or trying to create a private blockchain within your bank for an immutable master copy of your most valuable business asset, the concept of MDM is at its core. The technology space is experiencing a revolution of sorts and MDM - MLDM has long arrived. When the Chief-digital/data-Officer (CDO) is looking to create an impact, it has to be through the betterment of services to their customers. That shall only come when the underlying data - assets/equipment, facilities/locations, chart of accounts, customers, products - influence and impact is known. Processes cannot exist w/o data and data exist because of processes. Hence, MLDM becomes more relevant in these Digital times.

IoT/IoE and the influence of these on businesses is staring at us. Banking institutions, healthcare companies, insurance companies, utilities, manufactures and the rest will get impacted by AI and IoT. They will also rely heavily on data, master data and analytics. Hence the circle of influence of MLDM is far and wide. Chief Digital Officer, Chief Data office, Data Governance Leader, Data Quality leader, Data Steward and many of the CXOs - each of them will rely on how quickly, efficiently will accurate master data will be created and dispensed across the enterprise. Scale is not an issue and so is the human intervention. This is a huge business advantage to focus on process improvement and adds on to the operational efficiency. Over a period of time it will also bring down costs of implementing this very strategic MDM program in enterprises.

This is in continuation of our previous blog on MLDM which can be found here. That piece introduced the concept and the relevance in these digital times. While the above provides you with a circular view of the influence that MLDM creates. We have taken the CDO role to be more relevant to the businesses of today. Hence a CDO by implementing MLDM stands to benefit from speed, more accuracy, quicker access and better utilization or an optimized use of his current technology landscape. If you are in the manufacturing or healthcare business and IoT/E is driving your next billion dollars, then the underlying tech used to power them, could be statistically programming or machine learning or deep learning methods, can also further the development of MLDM. Hence the CDO does not need to look beyond what he/she has.

What have been your learnings and 'circle of influence' that you have seen? Do you think the digital era of business can make use of this circle and benefit from that? Share your bouquets and brickbats with us and let us further this discussion to mutually benefit.

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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