How to become your company's Chief Data Officer (CDO)

There is simply too much information that tries to advise people of the value of data sitting in IT systems and what they should be doing with it. It's no surprise then that 'Data' has become an important area to work and has attracted lots of people to advance their careers.

Building a successful career in data is actually fairly straight-forward from what I have seen and the benefits can be enormously rewarding both financially and non-financially. In this article I make no distinction between the roles of the modern Chief Data Officer (CDO) and Chief Analytics Officer (CAO) role. For me they are two versions of the same thing. My use of the word 'modern' is deliberate and simply means that a modern CDO covers both offensive and defensive parts of using data. You can read a separate article on this topic here.

Now I must point out that this review is a purely personal one, and in no way objectifies any professional advice, standards or endorsement. I just want to show readers how I empathize with junior, mid-level and senior managers and leaders when it comes to their careers and as an ambassador for data I want to see people progress in the right way for the benefit of this domain. I'm going to build on three good articles that give tips to mid and senior managers working in Data:

#1. DataIQ - How to win your Analytics bid. Five tips to be a successful CAO

1. Provide leadership
2. Create an analytics-oriented culture
3. Use lots of data
4. Use the latest tools
5. Build a team and keep it fresh

#2 Mario Faria: Three steps to becoming a successful Chief Data Officer

1. Create a long term strategy with regular short term deliverables
2. Put together the best team you can find
3. Get executive support

#3 Gartner: Build your career path to the Chief Data Officer role

1. Be the emergent leader for data-driven business
2. Be business-centric, data-oriented, analytically minded and culturally aware
3. Focus on the link between data, analytics, business processes and outcomes

All the above tips are spot-on, but it's mostly geared to mid and upper management. I want to add a few pointers that anyone can use, and trust me even senior leaders sometimes need help in some of these areas:

1. Know how to put together a good business case - Hint: make sure you get a senior sponsor to look over it before its presented
2. Master the art of patience - Hint: Great things take time
3. Be seen as a bridge between back-office, middle-office and the front-office - Hint: It's as important to visibly be seen as it is to actually help
4. Demonstrate you are listening and learning from your projects - Hint: Accept feedback and act on the positives and negatives
5. Work harder than anyone else - Hint: Data is a problem and opportunity area for every organisation in all areas. Be seen as an open, helpful and friendly business partner
6. Don't just focus on the fun / sexy stuff - Hint: Get yourself busy with helping Finance with forecasts, Treasury with liquidity, Operations with invoicing, Governance with breach identification, etc. Help these areas in your early mornings/ evenings if you can.
7. If you start losing the love, pass the ladder down - Hint: If you are not enjoying it, pass your knowledge to a more junior member of your team and think about speaking to people you trust about the right area to move into. Because you have a background in data, you are worth a great deal to your organisation
8. Support your manager and know when to move on - Hint: How talented and recognised your manager is will be a top deciding factor for your own career's success. Help them where you can and don't show them up. Carefully move on to a bigger team or for more responsibility. Don't select on remuneration alone. Money will always follow the right job. Sideways moves aren't the norm in data as the market growth is outstripping the supply of talent. Learn what you need in the job

The good news is that many of the tips aren't exclusive to the area of data, which is reassuring. I wrote this article because I am continuously asked for such advice and the above collection is just enough that I can fit into reasonable article, but add your own tips in the below comments section. You don't have to directly work in data to provide a tip below. Such observations (excuse the data pun) are hugely invaluable to help your own data experts become superstars and help you more.