What have we learnt from the GFC? From a simplistic view point, is it that the ‘low/no doc’ applicants should never have applied for mortgage loans, knowing that they could not afford them? What about big business? Does the blame lay squarely with the architects and purveyors of the ‘untapped new profits sources’ structured finance instruments, mortgage backed securities and collateralised debt obligations? Surely the regulators and governments should have seen it coming?

What we learnt is that safety in numbers, corporate and professional herding, happens. Secondly, hopefully, is that in an ever increasingly connected world, the effects of corporate and professional herd instincts will have ever more significant global implications, negative and/or positive.

What is ‘Big Data’, by definition? Is there a standard definition? No. According to Wikipedia, it is the collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

Data on the other hand, has a relatively more accepted definition, is defined by Oxford dictionary as facts and statics collected together for reference or analysis.

‘Me too’ strategy

According to the International Data Corporation (IDC), the number of business transactions on the internet – between firms and firms to consumers will reach 450 Billion per day by 2020 (Wikibon).

Google and Amazon, are among the most commonly referenced businesses when it comes to executive and management justification of ‘Big Data’ as the next ‘untapped new profit sources’. Yes, these two companies have successfully demonstrated, and continue to do so, that business in this digital age is still about “Knowing and understanding your clients”. Reminder lesson from the young – both of these companies are still finding their way when it comes to the big business club membership.

The demise of previously, titanic, solid leading global businesses seems to be an influencing factor on executives’ minds. And ‘Big Data’ as a panacea seems to be in fashion. Evidenced by the regular mentions and announcements regarding big data projects at the big end of business, no one wants to be left out. The message being communicated, on one hand, is that some big businesses have somewhere along the lines lost touch/contact with their clients and are now embarking on getting to ‘know them better’. Worse scenario is that it is simply a matter of corporate herding and that no one knows what is happening.

Back to Google and Amazon, these are first and foremost inherently disruptive businesses. Their DNA, from their founders, and their business models, systems, people and overall culture are all aligned to seek opportunities by providing their clients with as minimum friction points as is possible.  And they do have data whose attributes are at the top end in terms of volume, sources, velocity and complexity of analysis.

Crystal ball gazing

Can the analysis of data be useful in a complex decision making process. Yes. But does data analysis guarantee accurate results. No. Is it crystal ball gazing? Definitely not.

If any executive is still expecting an easier way out with ‘big data’ – as is commonly touted – then it would be prudent to have a look at something closer at hand, ‘minute data’, corporate financial reporting. Could you pickup any set of corporate financial reports and timely sign off on a big business decision based on your analysis of the data presented? If you are a CFO, a strong yes is to be expected.

According to the Australia Government Financial Reporting Council (FRC), the current financial regulatory framework is not optimal. The council further acknowledges that, in Australia as in many other countries, regulators sometime require the general purpose financial reporting for entities or circumstances for which that form of reporting was not created, or else confuse their special purpose needs with those of that reporting (FRC). As such CFOs will tell you that financial reporting, data analysis is a minefield.

In respect to volume, data that was expensive only 5 years ago is now significantly cheaper to capture and/or access. The cost of data storage is also a fraction of what it was only a few years ago.  In respect to velocity, the rate at which new data is created is astronomical. In respect to sources of new data, just think social media to get an idea of the plethora of outlets. On analytics, presently available algorithms and analytics platforms were simply not accessible a few years ago.

What about the data value? There are no illusions, rabbit out of the hat type.

Loud noise

Never in history has there been anywhere near, as much data as is currently being produced. And this trend will continue to grow exponentially, think about the effect of the ubiquitous ‘smart devices’.

Is there value, tangible, in ‘big data’ or is it simply loud noise? Yes, there is significant value, in terms of the insights (locking onto the signal) that can be extrapolated. Insights that coupled with the right resources can be turned to wisdom. This is wisdom that can transform life on earth as we know it. Not simply a matter of short term ‘profit sources’ but positive gains for the whole of society – think privacy for example.

Causality is important and as such the focus should not be simply on looking out for data correlation or seeking to find statistical patterns in the data. Remember businesses do not operate in a vacuum.  And the regulators and governments should see this one coming.