The Analytics Breakthrough
I recently watched a short presentation of ideas from Microsoft’s Corporate Vice President of Business Solutions Marketing, Mr. Wayne Morris in which he spelled out a couple of points for the future of “Big Data” and especially “Big Data Analytics” that I believe to be vital to seizing the opportunities on offer:
- By 2020 there will be 25 Billion Connected devices.
- Data generation will reach the 44 Zettabytes by the same year.
- The opportunity is “how do you make sense of it” with the machine learning of small insights to build a more accurate “bigger picture” being vital.
This is something I agree with wholeheartedly and in my own small way I have tried to contribute to, both in my posts to forums such as Pulse on LinkedIn and in my working life for eConnect.
Big Data is going to be so unimaginably big that, when looked at as a whole, there are unlikely to be huge insights possible; as the time taken to find them, or to recognise them for what they are, is likely to be prohibitive and our ability to do it without complex AI systems is likely to be similarly constrained. Some of these limits are contained and explained within the limits to our own biology. It simply isn’t that likely that a brain that evolved in the African savannah, within the limited complexity of a hunter-gatherer way of life, can handle the deluge of potential information available to it in a high tech society of the Twenty-First century.
This is where the small insights are so important.
It has long been known that a powerful way to look at a big problem or situation is to break it down into smaller, more “digestible”, lumps that can be understood. This is where the real power of data analytics will change the world. By taking the unimaginable deluge of facts and figures and reports about what is going on from all of these connected devices and data bases and put them together in a pattern that the human mind can comprehend.
There have been a number of successes in this area already such as the eConnect eCounter system for queue analysis in bars, cafes and fast Food Restaurants; or the eConnect Casino Connect Ratings Module with Table Games Analytics. These systems exist now and can give genuine business insights for their users. This is a very powerful development and one where eConnect leads the way in our chosen field. These systems use the concepts presented, of the Big Data – Small Insights model, along with machine learning to provide the tools that are increasingly coming to be seen not as luxuries, but as absolute business necessities.
But there will have to be many, many more, both from eConnect and from others, to take advantage of the different ecologies in which the data that we wish to mine, in the everyday business world, resides. Data about patron flows and queuing (subjects that I have written about before) when tied in with information from Point-of-Sale, Staff Rostering and Stock Systems can paint a very vivid picture of how a business is operating; where the money is coming from, are their periods when there should be more staff available and periods where there can be less? All of these insights allow more flexibility in operations and more bottom line profitability.
None of these can be described as a “Big Insight”
But rather as a number of smaller insights put together in a form that illuminates the business, and exposes areas of weakness.
But suppose we go further and tie in additional “connected devices”, the device that is so ubiquitous world-wide now that it comes as a physical shock when you encounter a person who does not have one, I mean of course the mobile phone: what if we use geo-location, by means of an opt-in and a suitable app, to track people not just in the defined area of a queue but throughout a property or premises and use that technology to consider purchase habits and dwell times.
Again these would be a number of smaller insights that would build up into a much bigger picture that is actionable. This gives decision makers actual data driven insights on which to base their decisions and a way to continually measure what they are doing right and what they are doing wrong.
To quote from Mr Morris again:
“Predictive analytics empowers people to transform”
This is the power that we have to be ready to give to business.
This is the power that we have to be ready to take from the technology providers who can give us it.
Because these are the technologies that is going to reshape the future.
The amounts of data aren’t going to decline and go away and our ability to deal with them and derive insights from huge chunks of it is unlikely to really, significantly, develop. So we need the machine learning for the small insights, and lots of them, to give us the big-picture vision which will enable success.
That will be the Analytic Breakthrough, and it is happening already.
 You can watch the whole thing at: http://empoweringbusiness.economist.com/article/technology-and-the-future-of-work/