If your instincts tell you to trust the data, listen. If not, then don’t trust your instincts

The C-suite should check its instincts at the door and focus on the data. Ironically, for many senior executives trusting to the science of data analysis actually amounts to a leap of faith and means averring a self belief common among many successful managers – that they can bend the world their way by the sheer force of will.

But the research is clear that for those who successfully recalibrate their thinking the commercial outcome is better productivity and higher profits – and we know this because the data tells us so.


(Image: Andrew McAfee. Source: andrewmcafee.org) 

The extent to which a company describes itself as being data-driven is strongly associated with performance,” says Andrew McAfee, principal research scientist at the MIT Centre for Digital Business, and co-author of a new study examining the impact of data driven decision-making.

The study  encompassing 330 leading US businesses, found that the organisations most strongly focused on data-driven decision making had four per cent higher productivity overall and six per cent higher profits – in other words, a quantifiable, significant edge over the competition.

Rather than relying on the flawed compass of experience plus intuition, business leaders can now base their decision-making on hard, data driven, analytically robust, quantitative fact.

Shifting from ‘decision making’ to ‘decision science’, from gut instinct to quantified proof, requires a significant shift in business thinking. As well as finding and keeping the smartest quants, business leaders need to develop the skills to translate and operationalize data driven insights within their organisation.

A 2012 survey conducted by MIT Sloan Management Review and SAS Institute found that although 67 per cent of business leaders said that analytics had helped the create a competitive advantage, only 35 per cent always or frequently had access to data to make decisions.


(Source: MIT Sloan – Sloan Review)

However, as they move into era of more quantified decision-making, business leaders face two adjacent challenges. Firstly, finding a way to locate and resource analytics teams within the organisation to optimise their effectiveness. And secondly, building analytic vision and advocacy at executive level, where business strategies are set.

Analytics is good for your bottom line

In ‘Keep up with your quants’ (HBR July-August 2013), Thomas Davenport highlights a telling example of an analytics/ business disconnect in a major US financial institution.

“I don’t know why we didn’t get the mortgages off our books,” a senior quantitative analyst at a large U.S. bank told me a few years ago. “I had a model strongly indicating that a lot of them wouldn’t be repaid, and I sent it to the head of our mortgage business.” 
When I asked the leader of the mortgage business why he’d ignored the advice, he said, “If the analyst showed me a model, it wasn’t in terms I could make sense of. I didn’t even know his group was working on repayment probabilities.” The bank ended up losing billions in bad loans.

While this is an extreme outcome, the disconnect between quants and leaders is endemic in business, particularly in industries that are not traditionally data centric. But whilst it can be tricky to bridge this gap there are a growing number of businesses showing just what is possible – and that the business benefits can be huge.

Drive value from analytics

The first commonality across analytic innovators, from eBay to Bank of America, is consolidation. A centralised analytic function working as one group is more efficient than having numerous teams with multiple data warehouses and disparate tools. Centralised analytic teams can report to business units through a matrix structure, but are able to bring a broader skill set and greater business knowledge to bear on a problem, as well as ensuring consistency in how key performance metrics are defined across the organisation.

The second success factor is strong advocacy and understanding at senior level. Great analytic insights are little use if key decision makers don’t see or understand them. The sub-prime example illustrates this perfectly – an inability to translate analytic insight to business meaning prevented corrective action.

A senior executive who can promote analytic findings and use them to drive business decisions enables the company to truly operationalize analytics and drive value through quantified decisions.

Checklist for building an analytic culture

  • Centralise analytic functions and matrix out to business lines
  • Find a C-level advocate
  • Hire ‘translators’ as well as technical specialists
  • Invest in the necessary tools
  • Create a culture of curiosity throughout the organisation
  • Commit to front line action to operationalize insights

Beyond structuring teams and ensuring senior level advocacy, there is one additional consideration – the type of analytic skills in the organisation. Great quants are immensely valuable, but deep analytic skills don’t tend to come hand in hand with the extroversion and entrepreneurial thinking needed to translate analytics to time poor executives.

Where possible, resourcing your team with ‘translators’ who can interpret and explain the business implications of complex analytics is a powerful way to embed analytics in corporate culture. Analysts with personality can teach your organisation how to consume analytics, in a meaningful way. Find them, care for them – and keep them.

Anna Russell is a director at Polynomial, a Sydney based analytics and strategy consultancy. Polynomial works with businesses to drive value from technology investment and develop effective data driven strategies for marketing and customer engagement. 

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