Intro

At a CDO Hub event in London earlier this year, we caught up with Peter Eckley, CDO at The Bank of England, on his own data journey.

Name
Peter Eckley

Job Title
Chief Data Officer

Company
The Bank of England

How long have you been a data leader?

Short answer: somewhere between 2 and 16 years.

As with many of the hard-to-define roles in our space, that depends what you count as a “data leader”. 16 years ago I started my career as a strategy consultant; the work was based heavily on data analytics to understand business models and regulatory questions. I led teams doing that work, and provided data-driven thought leadership to clients on their questions.

More obviously, I wrote my first data strategy around four years ago, alongside my main job in regulatory policy and research at the Bank of England. One thing led to another and two years ago I became the Deputy CDO, which is probably my first role in which no-one would contest the label of “data leader”!

How did your own personal data journey start, and how did you get to this point?

With my first job out of university. As a strategy consultant in the telecoms industry, in a firm that was strongly quantitative, and used a fair amount of data in its business and economic modelling work.

But it really stepped up in sophistication when I left consulting to pursue applied empirical economic research. Or in other CDAO language: data acquisition, data management, data quality assurance, analytics, visualisation. It was that combination of skillsets that got me conscripted to write the data strategy for the prudential policy function in the Bank of England, and sit on the first Bank-wide Data Council. There I gained experience and made connections that subsequently led to becoming Deputy CDO and then CDO.

What is the data related achievement that you are most proud of?

If I could choose an ongoing achievement: Being able to straddle between the worlds of business, data, analytics, and technology, and translate between them.

For a one-off achievement? Managing to plausibly identify causal relationships between banking regulation and lending. Sounds esoteric, but identifying causality is such an incredibly hard thing to do in economics that I and my co-authors were pretty chuffed.

Tell us about a lesson learned along your journey?

As a newly minted Deputy CDO, with a huge learning curve to climb in good practice regarding data governance and data management, I let myself and my team become too focussed on trying to understand industry good practice and data management capabilities. We ended up relatively neglecting the business outcomes lens. (Ironically, I was given the role partly because I was from the ‘business’ and thus well placed to understand the data needs and the related business outcomes.)

I suspect this is pretty common because good practice can be standardised into frameworks and textbooks that you can read, and capability maturity frameworks you can assess against. Whereas business outcomes, priorities, and how these translate to data management/analytics capabilities, are different in each organisation, so hard to codify, and hard to transfer as knowledge that a new data leader could quickly internalise.

With the benefit of this hindsight, I now always work hard to make sure we start from – and trace all our activities back to – prioritised business outcomes.

What are your 3 top tips for others looking to make a career in data?

1. Be relentlessly curious and opportunistic in your learning – you need at least a basic understanding of several areas, from data management, to analytics methods, strategy, business models, people management, leadership, communication, governance, etc. etc.. Different roles offer opportunities to learn different areas, so exploit whatever learning opportunities your current role affords, and consider what learning opportunities future roles offer (but don’t worry too much about how you sequence your learning).

2. Know the business, and strategy – I suspect that at the timescales relevant for career planning, the supply of technical data/analytics specialist roles such as data scientists, data engineers, data governance experts will rise up to meet demand (though it doesn’t feel like it now, and may take a while!), and the scarcity premium for those skills will erode. Plus the roles will become increasingly specialised, and therefore (unless that’s what you want) potentially less fun and creative. But the scarcity of people who can straddle the business and technical will be more persistent.

And by the time I’m retired, everyone in the workforce will be literate in data and analytics, data and analytics strategy will ‘just’ another standard and integrated a facet of business strategy; much as talent strategy is today, and CDOs will have become Chief Strategy Officers.

3. Connect with other people who work in the same space both to learn and to be known when future opportunities arise – e.g. come to CDO Hub!

Best advice you were given?

I have twin two-year old boys. I’ve been told by so many times, some variant of “When you have young children the time just flies by, so treasure it”, that I keep phone off until after I’ve had breakfast with them, and schedule my work so that I can often get home and spend time with them before bed.

Anything else we should know?

I wrote a song that has sold approaching half a million copies. No data or analytics involved.

 

Well now we all want to know what the song was?! [I’ll try to find out and will report back. Tor]

And we couldn’t agree more on the CDO Hub – we have some really great data leaders all learning from each other and sharing their experience.

Written by Tor Park

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