I left University with a degree in a bizarre subject called Actuarial Science and entered the dark world of very grey people who worked every hour god sent and did numbers for breakfast, lunch and dinner. I got into writing algorithms behind insurance company systems to automate manual calculations. After seven years of trying to finish the intolerable exams, I gave up and found I could make a good living working with data. In 1999, I headed to The AA to finish its product data warehouse and lead the exploitation team. After a few years, I was approached to set up an internal marketing analytics team and work with the central function running the customer data warehouse. After three years, I assumed total charge as we headed away from our parent company Centrica. After five changes of AA ownership and reaching data and insight director, I decided to leave for the role of chief data officer at Addison Lee and modernise its data estate. The last few years have seen me write forewords for books, sit on panels and present at conferences (“My life in data” is popular), advise newcomers to data how to short cut progression, and complete many trade interviews.
The stand out must be becoming CDO at Addison Lee (just behind making it into the DataIQ 100, of course!) While Addison Lee isn’t best known for its data approach, it has led the market in service and technology long before others arrived. I just want to put data up there with those market-leading qualities.
I wish I hadn’t spent so long pursuing perfection with my data responsibility and settled for “best it can be for now”. Also, network, network, network and will you never have to apply for the best job, as they will come to you. Join some data professional communities and both receive and contribute.
Yes and no. In the industry, the advent of GDPR and various data scandals highlighted the need for good data practices, while real examples of AI (and not exaggerated rebadging) have become common place. My negative relates to work where it has become harder and harder to retain good data professionals.
More of the same! GDPR fines will gather pace with plenty of big names failing. We may see the dawn of realisation across a broader group of companies that AI and AV, etc, rely on good quality data. I expect to see consolidation in the new data science platforms as the big players move in and look to alleviate skills shortage amongst existing clients for their BI platforms.
Despite being a small organisation, we have dipped our toes in several areas, from grow-your-own to free MSc and PhD students. Equally, investing in training our existing resource pool using a variety of methods, none of which include the now old-fashioned “attend an external training course”. We are also trying to create more resources in the organisation by delivering self-serve data services.
With the continued shortage of certain data skills, we need to optimise what we have, and we will see the resurgence of the insight analyst who can both perform analytics and communicate the actions to take. After all, a few actionable insights are more useful than lots of interesting outputs.