Data Governance Interview with Kohinoor Mukherjee
Kohinoor Mukherjee started his career as a mainframe developer before moving onto business analysis, project and then program management. Kohinoor has been working on various data specific projects, mainly with financial institutions, for the last decade, and is now presently a Data Governance Consultant with an energy company.
Apart from data, he is also an avid reader with a keen interest in financial risk management, behavioural science, history and public speaking.
How long have you been working in Data Governance?
I have been working solely in Data Governance initiatives for the last 3 years. Prior to that, I was primarily involved in Data Quality and Reference & Master Data Management. However, with every passing day I am intrigued and fascinated by the interdependence of these disciplines and how they enrich each other.
Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?
Probably 5-7 years back it was unusual but not anymore. With the tremendous growth of different Data Management disciplines, Data Governance is becoming increasingly relevant. I think it’s a key factor, which integrates the different data management streams, resulting in a synergy for the organization.
My entry into Data Governance was to some extent situation driven and not by choice. While working on a data quality initiative with a bank for a regulatory program, we found that our DQ deliverables were lacking context and failed to rollup to the overall objective of the program; and the missing link was inadequate Data Governance. That’s when I got involved with this topic and eventually found it to be quite interesting.
What characteristics do you have that make you successful at Data Governance and why?
a. Resilience is a must have quality for anyone in this field, as that will be frequently tested during any Data Governance rollout.
b. Ability to see the bigger picture and finding the intersections with other data management areas helps immensely.
c. Having good articulation and negotiation skills are also highly desirable traits to get things moving and create an impact.
Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?
I regularly subscribe to the DAMA and DCAM contents (papers, webinars etc.) to remain updated. LinkedIn forums on similar topics are also enriching. Anyone new in Data Governance can consider having formal training. I took the 2-day training course offered by Nicola and found that quite good.
I found that knowledge on change management techniques and tools come quite handy in Data Governance implementation. So, it would be good to have some exposure in that area.
What is the biggest challenge you have ever faced in a Data Governance implementation?
Challenges are different depending on the industry and their maturity in data disciplines. I will talk about two of them: In one assignment with a financial institution, I found weak data leadership coupled with organizational politics that rendered major data initiatives less effective. In another organization, which was new to Data Governance, getting senior management buy-in and convincing them about the business value of data governance was a big challenge. Without the blessings and active support from senior management, implementing data governance is almost impossible.
Is there a company or industry you would particularly like to help implement Data Governance for and why?
I would love to do Data Governance for organizations where data is not a byproduct of its business processes but the product itself. For example, the financial data vendor companies. And the reason being that probably I don’t have to spend days and months convincing the decisions makers and budget approvers, the importance and value of data governance before getting into the real work.
What single piece of advice would you give someone just starting out in Data Governance?
It is of course important to have a sound framework and operating model but don’t wait for them to be perfect before you start. Start implementation sooner and they will evolve and get better. Most of the time we can’t envisage the practical problems lying ahead. So, let them come and make the necessary changes to your op model and framework etc.
Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?
I am still looking for that humorous side of Data Governance. Every discussion and meeting on this topic get so serious at times that it won’t be a bad idea to introduce a ‘Joke of this quarter’ slide in the SteerCos. Jokes apart, I don’t have any one memorable event to share. Rather, almost every interaction with so many different stakeholders have been enriching in different ways and has helped me to develop both personally and professionally.