What does it mean (WDIM) to be a Chief Data Innovator ? Up until this month (February) I was very uneasy with the label innovator or innovation. Too often you see the term in some corporate vision statement, for example “By being both sustainable and innovative our agile approach will drive blah, blah, blah”, which is often just wishful thinking. It also has become debased with the usual corporate questions of “What would Google/Apple/Uber do?”, implying that we haven’t a clue and our only course of action is to reverse engineer someone else’s success.
In most cases that answer would be not to start form here. Innovation is all too prescriptive and contradictory involving too many mutually exclusive concepts. Now innovation is entangled with digitisation, which itself is really about automation and utilising up to date technology.
Data Innovation needs to be thinking beyond the Agile/SCRUM models of Delivery. Modular thinking augmented with business processes holds key creating data driven innovation
Now I have the grand job title of Chief Data Innovator, perhaps not in the league of Director of Fun but still pretty interesting. The usual reaction is congratulations followed by what on earth do you do? Whilst I am not really sure after 10 days I do feel it is necessary to try to explain what I think I ought to be doing. To try to simplify to one statement it would be:
“Given what we know today how can an enterprise use data to enhance its ability to adapt in a changing market place?”
In my last role I was told by one of the senior management team that “I was disruptive and challenging”. Initially I took this as a compliment until the conversation unfolded and it became clear that it wasn’t and that he wished me to use the “correct channels”.
That is the key in that at the time there were no channels, data is democratising it doesn’t’ care about hierarchy. One element of the role is to ensure enterprises can ensure that all can benefit for new capabilities to place knowledge where it is needed at the a most appropriate time. Partly change management, party role definition and certainly questions the role of the Manager.
Second element is the way in which this work gets done. Today we have to have a way of working which we can all study, be trained and get the certificate. We have methods such as Waterfall, Agile, Safe, Scrum, Lean and Six Sigma, none of which really fit the steps you have to go through when going from raw data to some actionable outcome.
Methods such as Agile are excellent for software development but not for data exploration. Data needs a new set of methods. Added to this is the roles, never mind job titles, of those undertaking this work. All I am certain about is that it needs some business people to be present all all stages, the rest can be fluid depending on what is needed on the day, nonetheless the business people do need to be mentored otherwise every output will be the centre of a discussion about its validity.
Final element, there are probably more but at the moment brain-space is limited, relates to the technology involved, ranging from statistical models to quantum computing. Trends here to be pursued are ‘Serverless’ architecture and use of ‘AI’ to prepare data and create models and algorithms. Open standards and open source are a key driver here for this stack, especially as more and more services are moved off premise.