The importance and significance of big data in this digitalized business world has been generally agreed upon by business leaders and strategists. We are now in a new phase of big data life cycle which is what I call the shaking off stage.
The big data shaking off stage is the phase where the multitude of businesses that joined the bandwagon of enterprises that deployed facilities and tools to allow them tap into the benefits of big data needs to reassess their stand.
The big question is, are processes lean enough to meet the agility that modern enterprises now require to remain competitive? If the principles of lean processes cannot perfectly be upheld while developing procedures to collate, organise, analyse and then benefit from investing in big data projects, then, there is no point venturing into it.
Cisco has predicted that more than 20 billion devices will be connected to the internet by the year 2020. If this prediction happens to be realised, then more and more unstructured personal data will be generated by users of these over 20bn devices. You already know what huge opportunity this development will present to businesses as far as data mining is concerned.
At this stage, the all-important questions of ‘is big data driving our business forward? Did we invest too much or perhaps too little in implementing the big data philosophy? Are processes more complex as a result of buying into big data philosophy? Are so important that every company have to answer these questions or face the inevitable- which is, having too many resources wasted before they realise it.
I recently read an article on CIMA website where the writer, Neil Amato writes that although companies that leverage on the power of data are more likely to succeed, most big decisions that are made by top management are not based on data but on pure guts.
This finding is a bit worrying for one very important reason- a lot of investment has gone into developing and deploying big data infrastructure. And that points to a long cliché of ‘analysis paralysis’ The finding of CIMA is in direct contrast with the finding of IT research companies like Gartner, Ovum and IDC.
Social, Mobile, Analytics and Cloud (SMAC) technologies according to the findings of the above three mentioned companies are the future of how business is done. This gives an indication that harnessing the potentials that big data presents is a venture that is worth giving a go after all.
The question of whether big data is driving businesses forward or just causing unwanted distractions lies in the company’s ability to keep up with the pace of opportunities presented by big data that comes in different volume, velocity and of course variety.
For big data to deliver value to a business, it must bring all the benefits discussed in this article and more. This article will not go into details of what a company needs to do in order to take advantage of all the data mining effort that is properly channelled can bring. But, I will quickly point out in bullet form features and ability of what a big data can do.
- Must give companies competitive advantage to understand their customers
- Allow companies to reasonably predict the future
- Data analysis must be done on a real-time basis
- The company must have the ability to monetise the information that are generated through big data
- The data must be managed carefully- privacy should be the key word.
- The cost of implementing big data must not outweigh the benefits
I recently ran a simple regression on 12 companies that are well known for their interest in pursuing opportunities that are presented by the advent of big data and found no conclusive evidence of improved profitability in these companies. The investments made now might be reaped in the future but who has time nowadays to wait 5 to 6 years for investment to start yielding dividend?
Big data can theoretically benefit a company but only if they can be gainfully harnessed. Profit trends in the profits of selected companies that heavily rely on big data haven’t reflected any noticeable change that can be attributed to the collection, analysis and use of big data. This could be due to the fact that any benefit of big data will be largely offset by the cost involved in implementing big data.