Data Governance Interview with Miles Reah by Nicola Askham, The Data Governance Coach

Data Governance Interview with Miles Reah by Nicola Askham, The Data Governance Coach

My name is Miles Reah and I have worked as a data governance consultant predominately in investment banking but more recently in insurance and healthcare. I am currently working as a Data and AI Consulting Manager for Avanade helping our clients discover the value of effective data governance and data management can bring to their organisations.

How long have you been working in Data Governance?

I’ve been working in data governance in various forms for nearly 6 years now.

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

I’d always been interested in the financial services sector but when I started working for a financial services consulting company after university, I didn’t know what specialism I might move into or where it would take me. I made sure I was open-minded to interesting opportunities that came across my desk, particularly when they would offer me the chance to develop valuable skills. With that in mind, in September 2016 I took a role in a large-scale data regulation program for a major investment bank.

I initially thought this role would tide me over until the New Year and I would then re-evaluate but during this 3-month period helping the bank implement a range of data governance principles I came to understand how vitally important data is. Understanding data, how it’s used, and the challenges that can surround it helped me understand how major organisations operate. From what was only supposed to be a 3-month stop-gap, I ended up staying with the client for over 2 years as I enjoyed helping them so much on their data journey.

What characteristics do you have that make you successful at Data Governance and why?

• Communication skills: Being able to explain complex data principles in a simple and concise way to business stakeholders can be invaluable in implementing enterprise-wide data governance. This can be in meetings, in presentations or by developing simple diagrams or metaphors that everyone can relate to. One of my favourite simple data diagrams is the picture below that explains the difference between data and metadata.

·       Influencing skills: the ability to get senior stakeholders or sponsors onside and see the benefits of data governance can go a long way. Implementing data governance can often be a long, hard process with a lot of manual effort and a few dead ends, and it can often take a while before you see the dividends it pays. It is imperative to keep stakeholders engaged and enthused during this time and reminder them of the potential benefits ahead. It is good practice to get a couple of quick wins in early that can serve as use cases for the rest of the business. Fixing a couple of data issues with good data governance practice will show people the tangible benefits of the process.

·       Relationship Building: data governance might be the number one item on your list of priorities, but it won’t be top of everyone else’s. Being flexible and patient will help you to build relationships across the organisation and in turn bring data governance benefits to fruition. Try to make asks on your client as clear and reasonable as possible- there is no quicker way to sour a relationship than by giving a stakeholder a huge spreadsheet to fill in, or by wasting their time in pointless meetings.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

I have found “Navigating the Labyrinth” by Laura Sebastian-Coleman really helpful. The book is aimed at executives, so it gives a high-level view of the key principles of data management and governance. Sometimes its good to zoom out of the detail, think about the bigger picture and simultaneously understand how senior stakeholders might think about the issue at hand.

I also believe one of the best ways to learn is from others. Most of the knowledge I have now has been passed down from mentors, with concepts often explained to me via diagrams drawn on scrap pieces of paper or napkins!

What is the biggest challenge you have ever faced in a Data Governance implementation?

I was involved in planning, coordinating, and delivering a very tough large-scale data lineage project. We had tight timelines and a short agile sprint delivery method that kept the team on our toes! Our stakeholders were spread right across the globe (Korea, India, Israel, Czech Republic, Brazil, US, Canada to name just a few) so juggling meetings was a challenge in itself.

To add to that, people who have conducted data lineage work in an investment banking know what a difficult process this can be due to the sheer number of systems and the complicated calculations they work off. This becomes a lot more challenging when you have hold workshops and gather information about data flows through an interpreter!

Is there a company or industry you would particularly like to help implement Data Governance for and why?

Government. I think there are huge opportunities and benefits that are yet to be realized from data sharing between UK government departments. Large scale data sharing programmes have been attempted in the past with minimal success, and some have even been abandoned due to sheer complexity. Success in this space will rely on a huge culture shift to increase trust between departments but the potential benefits of getting this right could be huge (both for the taxpayer in efficiencies and for the civil servants who use the data to inform improvements to the services they deliver for the public).

What piece of advice would you give someone just starting out in Data Governance?

Be curious! Don’t be afraid to ask the obvious questions.

Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?

 I remember once talking to a stakeholder about their data quality. They were adamant that they had no issues because they had a team of 10 people offshore who cleaned up their data. Once I had relayed back to him that he had 10 people working full time fixing data quality issues (costing them hundreds of thousands of pounds a year) the penny dropped: “oh yeah, I’ve never thought of it like that… I actually have a huge data quality problem…”.

Originally published on

Have Your Say: