I’m back at summer school! It’s been 230 days since I started at the Department for International Development as Head of Data for Effective Development. Last week ended 6 months of assessing the organisation’s data maturity. Let’s pause and reflect together.
Taking the temperature
On a long journey, how do you decide if you’re going the right way? One thing I learnt from far too much time with the excellent NHS is to take the temperature — also known as observations. Blood pressure, pulse, and other measurements that help track what’s happening with your body and get baseline readings. On a long journey, you might wish to stop and check you’re still going in the right direction and perhaps, adjust, adapt to overcome barriers.
A data journey is little different. When I joined the Department for International Development (DFID), one of my first major work was a data maturity assessment with Carruthers & Jackson to do just that — find out where we are right now and decide the next steps, using evidence not assumptions. The goals was not to form a new strategy straight away but decide next steps to build a stronger foundation, release capacity and build the evidence for a sustainable strategy. With Spending Reviews, the UK government 3-year budgeting decisions, round the corner, the timing has been ideal.
Last week marked the end of this work as we presented our findings and recommendations. I supplemented the excellent report and presentation with what’s being referred to as a ‘bingo card’ — my equivalent of a roadmap. The ‘bingo card’ shows the delivery and infrastructure steps we need to take over the next 6 months linked to a timeline that outlines our potential for delivery over the next 3 and a half years. I find a roadmap with timelines can be easily seen as a commitment to timings or Gantt chart, the ‘bingo card’ is my antidote .
So what did I learn from the process? Aside from being invaluable in engaging with people across DFID, in the UK and overseas, at all levels, I learned so much more nuance about the key blockers people face and the grassroots data leadership we should champion.
My advice to anyone considering a data maturity assessment is to remember that like NHS observations, you have to do them frequently enough to give you an idea of where you are and help you steer your organisation towards better data. You must then act. Make use of the signals the results give you. If you don’t? Change becomes lip service and adds to the perception and perhaps reality of good data being too difficult, messy, expensive and hard to bother doing well.
Back to school
This week I went back to school and I’m living my best life. I was ridiculously pleased I completed the Chief Data Officer Summer School homework before it started. You can find out more in my recap: Which Generation Chief Data Officer are you? I ask: Are you evangelising or delivering value from data at pace? Are you making change or adding value? How do you build a better Chief Data Officer?
Language matters when you lead
It’s been a pretty busy week at work, so space to think about my threads has been fairly limited. For folks joining my journey, I’m weaving these threads together:
- The designed organisation: How might we design an organisation that is resilient to change, keeps learning together and is a great place to work?
- Data governance as a service: How might we make data governance part and parcel of our organisation, built into everything we do with data?
- Design patterns for data and analytics: How might we make use patterns to speed up making data useful, usable and putting it to use?
Leadership fits into each of these threads, it ties them nicely together as does data. So this week I’ve been thinking and acting on my language of leadership. Last week, I mentioned the qualities I believe are important in a leader. This week, I’ve been working on making my language (and actions) reflect those qualities.
Reading Dan Barrett’s Weeknotes s07e07 he mentions “I had a neat thought about shifting our language so that people in the team are responsible for data, rather than responsible for reporting. I reckon that would be a useful tweak to our language, and implies greater ownership.” This resonated with me a lot, tying in with the work I’ve been doing this week.
I spoke (on the phone!) on a similar vein about what we call things and why they matter with Mor Rubinstein, Data Labs manager at 360giving. We discussed the tangle of interchangeable use of taxonomies, vocabularies, dictionaries and code lists in open standards and why it causes confusion. You should read the guide I authored for the Open Data Institute — The Open Standards for Data Guidebook — and please do contribute if you can make things clearer and easier for others.
Best of all, I got to discuss “What we say here and what we don’t” as one way to build and lead teams. This gives everyone clear guidance on what’s expected of them. We discussed the excellent book, How to make sense of any mess by Abby Covert which is designed to introduce information architecture discipline to people who don’t do information architecture. I find it invaluable for practical advice on how to untangle data messes because data and information are cut from very similar cloth. It goes even further, the language we use, what we say, how we organise are all parts of our organisation’s culture, so I was able to offer my most powerful incentive to better data to leadership this week as DFID merges with the Foreign and Commonwealth Office:
Data reflects and supports our culture. By building a data culture you can build an organisation culture that is reflected in the tools, systems and processes we use and supports the behaviour we want to see. In essence, good data culture is good organisation culture. The two go and grow together.
This week’s photo is by Stanley Morales from Pexels and it is gorgeous. Thanks to my wife and therapist (both called Alex!) for supporting me over the last 230 days and for countless days before. Thanks to my friends who really are the best bunch of folks I know and my family, because we rock together.