"It might sound scary to some but, if companies approach this the right way, it is not a scary thing at all. It's about providing the right information far more quickly to help CEOs make key decisions; it's about revealing the unknown about the unknown."
He says it is possible these futuristic business tools will replace a proportion of an executive's job: "We will have to see how that plays out."
Facciano says the driver behind the shift in decision-making is the sheer amount of business data now available.
"The International Data Corporation (IDC) estimates the amount of global data doubles every two years and will reach 40 trillion gigabytes by 2020. New Zealand companies only have access to a tiny fraction of that data, but it is more than enough to transform their decision-making."
Facciano says New Zealand companies are "behind the curve" when it comes to making data-led decisions but this is about to change; Kiwi businesses will need to adapt or risk being left behind by data-led market leaders reaching our shores.
Internationally many companies are hiring staff called data scientists. An opinion published in the New York-based MIT Technology Review, a magazine published by the Massachusetts Institute of Technology, says data science is the "sexiest job" of the 21st century because of the power of making decisions.
"These highly trained people will create databases, build the models and reveal the trends," the article says. "Their influence is growing as the speed and volume of transactions required in business is too much for human decision-makers alone.
"Smart companies," it says, "will have teams constantly probing the world trying to learn its shifting rules and deciding on strategies to adopt."
Datafloq, a data provider based at The Hague in The Netherlands, says the more data a company collects and analyses, the more information it has to go on when making major decisions.
"Companies are no longer flying blind or having to guesstimate," it says. "They have exact measurements for parameters that once couldn't be measured at all."
Facciano says one of the challenges for CEOs is to trust the findings automated data gives them: "This trust is hard to develop and takes time, so the change we will see by 2020 isn't just about data - it will also be a psychological shift.
"The best data analysis in the world will be useless if a CEO ignores it because they don't feel they can trust the findings- but in the long run it is far more reliable than making choices from the gut."
Facciano says artificial intelligence tools are necessary to overcome problems of the sheer scale of data: "The amount of data might be doubling every two years but our capacity to understand it isn't. This is a huge challenge and will be the driving factor behind the growth of more advanced artificial intelligence capability."
He says companies have operated over many decades with people making gut decisions, right or wrong: "Now the tolerance for that is reducing. The 'legacy' approach to decision support isn't working for the 21st century business, especially as the number, size and complexity of decisions business leaders have to make will increase."
Facciano says data-led decisions will not replace the human element. It simply creates more speed and reliability in information gathering so CEOs can make good decisions.
"Analytics is a powerful weapon; it must be pointed at the right target.
"The role of the gut helps form the direction the analytics practitioners will take - so it is intuition and data working together. We say intuition forms the hypothesis, analytics provides the evidence."
He says New Zealand companies fall into three categories. One group don't recognise the value at all; another is aware of the value but have yet to invest while a third group recognise the value and are actively investing.
PwC works with many companies to source and advise on data, says Facciano: "We start by identifying the theme of the analysis, mapping out the process behind it, identifying key moments of truth and then identifying key drivers that influence those moments.
Only at this point do we consider the data we may need, a process we call 'human centred analytics'."
