How to turn the Predictive Analytics Revolution into a Transformation Evolution

Recently, whilst listening to a presentation on the fast-approaching predictive analytics revolution to how we deliver large scale transformation, I was reminded of what my old history teacher used to say about revolutions. That its linguistic roots are from the latin ‘revolvere’ – to turn, or roll back – which is also where we get the word revolve from. And like the revolving of a wheel a revolution often takes a lot of effort, turns the world upside-down and once you’ve finished revolving you’re back where you started…

I was reminded of this in the context of predictive analytics because so often the analytics ‘pitch’ -with all its talk of artificial intelligence, machine-learning and predicting the future - sounds like the call of the fired-up revolutionary. And, as excited as we should be about the potential for machine-learning and advanced analytics to radically improve our ability to deliver successful complex change to time, cost and quality, this concerns me as without large scale take-up predictive analytics will never reach its potential and this way of promoting it fundamentally stunts the chances of achieving that large-scale take-up.

Too often the tone taken when promoting this powerful new discipline tends to sway between:

a)     the technologist in love with the fancy tool, ignorant of the business questions that need solving, to 

b) the evangelist preaching the promised land after an intense struggle in the wilderness (‘spend two years cleaning and standardising your data and you’ll be able to use my epic new algorithm that will predict the future, reduce your resource costs and cook dinner’). To

c)     the disappointed headmaster baffled by the stupidity of everyone else (‘when will industry realise that if we all just standardised and pooled our information we’d change the world’).

Although I always agree with the pure logic of the approaches, and love and share the excitemment of the presenters, the idea that the busy Transformation Director or CFO will happily allocate considerable resources to begin a massively waterfall data-cleanse activity in order to try out a new-fangled tool or that industry will spontaneously self-organise to standardise and pool data is simply not on the agenda.

To bring predictive analytics into the change management mainstream we must accept that what the industry needs is not a predictive analytics nirvana based on a single methodology and intense data-cleanse and standardisation activity to support that method but support in mapping out an achievable predictive-analytics evolution for the organisation that is both incremental and sustainable:  

·      Incremental – the journey is not all or nothing – small improvements in data quality and standardisation should lead to measurable value in terms of accessible analytics techniques at every stage which in turn leads to greater pressure to improve data quality. The scope of data preparation and migration projects can appear huge at the outset, however, with an agile/adaptive approach, which rallies stakeholders from business and technical domains to work in a series of sprints and defines the quick wins to answer some of the businesses key questions, it is possible to release value earlier and in parallel to longer-term data preparation tasks.

·      Sustainable – the journey needs to fundamentally improve the organisation’s ability to support its own analysis rather than increasing their reliance on external tools, support and databases. Any predictive analytics journey needs to build the capability of the BaU project management teams, as well as improving data and standards, in order to unlock a continuous improvement mentality that drives forward the data quality whilst allowing everyone to draw valuable insights from the tools and techniques implemented.

By continually preaching a predictive-analytics revolution, with all its implications of cost and disruption, we massively reduce the appeal of what should be a game-changing capability that rewards small improvements in data quality for all organisations undergoing change. Far better to preach the incremental and sustainable predictive analytics evolution that is within the grasp of all organisations with some data, some open-source analytics tools and some bright and energised change professionals. After all – evolution may be slower but there’s far less danger of us revolving back to where we started.

About P2 Consulting:

If you’d like to talk more about predictive analytics or building your organisations’ predictive-analytics journey then please visit www.p2consulting.com or get in touch with Adam or any of the P2 Consulting team here on Linkedin. You can also follow P2 Consulting on Linkedin here. 

P2 Consulting is a market leading transformation company, and second fastest growing company in the Virgin FastTrack 100. We work in partnership with our clients to turn their business ambitions into reality, bringing a unique blend of leading-edge thinking and hands-on delivery. We bring the drive, the passion and the courage to act leaving your business stronger, fitter and more profitable for having worked with us.