The secret to great analytics (tip - itís not the analytics)
By Janet Brimson Information Management Practice Lead, Business Aspect
I recently attended the Gartner Symposium on Data and Analytics. My core interest being the sessions on data strategy and governance. Hearing what others are thinking and saying always gets me thinking and planning. I also like to see how others present this abstract data world to their stakeholders and it was good to get some time with one of my clients looking for similar insights in higher management education and communication and share our thinking on the topic.
The conference opening talked a lot about ‘digital abundance’ dropping the words ‘empirical’, ‘empiricism’ and several other synonyms for measuring business phenomena and its relationship to quantitative analysis, finally positioning analytics at the epi-centre of the business eco-system. They even had a nice Gartner graphic to promote that view.
In contrast, in every session I attended, the case studies concluded that the customers who had shown the most maturity and success in the analytics field were the ones who embraced deep questioning. The ones who used storytelling, ethnographic research and qualitative enquiry – understanding the broader phenomena and behaviours of those related to their outcomes rather than those with the biggest data sets, their own private Hadoop POC studio, the most heavily worn data dictionary or fleet of data scientist to crunch the numbers.
The secret to great analytical outcomes was allowing people to be human and explore their questions and failed answers. Real maturity and learning came from blended business and analytical teams allowed to conduct small experiments and fail. Real insights came from those teams using “scenario thinking” to better conceptualise the outcome and then model the intelligence around that scenario. Real outcome realisation came from those organisations who allowed a culture that was self-reflective and open for change (“Data and Analytics Strategy Explorations: Linking Information to Tangible Business Outcomes”, Frank Buytendijk).
These were the organisations who were able to position their insights more strategically. And with each exploration of industry, insight and application in the field, the ones that succeeded were those who had taken the time to build a change hardened workforce, trained in innovative and creative questioning and able to process agility into the organisation as the norm, operationalising insights at speed.
Now I love my information management and I love my business cultural transformation, but even more I love to see holistic business strategies bringing everyone together in best practice in their area to deliver on the strategic outcome.
So my ‘take away’ was that you can spend all the money on all the systems in the world but the true value of your analytics spend is in your strategy, in the unification of people, process, analytics and outcomes, and this is not likely to occur until you let deep contextual questioning take place. Deep questioning requires subject matter experts who understand their processes and the relationship of those processes to customer, staff and business outcomes and innovation. It involves finding the right triggers to make those people question their own beliefs about these customers, staff and business outcomes in the safety of an open and agile culture.
So whether we are talking Big Data, small data, Data Lakes, business intelligence or predictive analytics and machine learning, it is still not about the size of your petabytes, it is totally about the relationship of the information asset to the outcome and how prepared the business is to bring everyone together to realise the insight about that outcome in near real-time.
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