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How Big Data Analysis Is Driving Business Transformation

March 2, 2016 at 8:28 AM

Corporate silos may have been necessary in a burgeoning industrial era some decades ago, but times have changed. The era of social, mobile, analytics and cloud (SMAC) technologies has been fuelling a new wave of business transformation. Virtually every industry is being affected by the SMAC phenomenon and we’re currently only scraping the surface of what is possible.

By tapping into new sources of value, transformation is occurring on many fronts: not only is the customer/business dynamic enjoying a new balance of power in what Forrester Research calls “The Age of the Customer”, but organisations are also forced to re-imagine internal relationships, structures and pervading cultures that may do more harm than good.

Read: Is your IT Department ready for the Age of the Customer?

Big data analysis is making businesses more agile

According to this Forbes article, by 2020, businesses will rely on data to, "…reinvent, digitalize or eliminate 80% of business processes and products from a decade earlier.” It is not surprising then that many companies are already turning the lens inward to better understand hurdles in efficiency. McKinsey reports that manufacturing companies are using historical process-data to “identify patterns and relationships among discrete process steps and inputs, and then optimize the factors that prove to have the greatest effect on yield.” Big data is also helping organisations reduce energy consumption,making the oil industry more efficient and safer and even aiding researchers in the fight against cancer. And, considering the steady evolution of computing power and increasing software intelligence, big data analytics is set to expand its already pervasive influence.

Getting your business ready for big data analytics

None of these far reaching achievements would be possible without an openness to the “cultural shift” that comes with big data. And little benefit can be derived from data if organisations aren’t prepared for it, which makes top-down adoption strategies paramount in driving change toward data-centricity. As C-level employees realise the need for closer collaboration amongst themselves, their staff and other key players, careful thought must be given to where data resides, both inside and outside the walls of the business. Once this is clear, its potential uses and how to mine, manage and, ultimately, monetise it will be much more straight-forward. But, since industries differ and businesses have their own unique structures, objectives and cultures, bridging what Gartner terms the “analytical divide” requires organisations to map clear paths to reach data-centric objectives.

Can organisations afford to ignore big data for much longer?

The digital era appears to have an oversupply of “next big things” and this might make it seem excusable to write big data off as more hype than reality. But developments on the ground involving real-world applications of big data analytics have shown overwhelmingly positive results. With this said, the question isn’t whether big data should be ignored, but for how much longer companies can afford to do so at their peril.

Using machine learning in business - download guide

Blog post originally published 6 October 2015.

Julian Diaz
Julian Diaz
Julian Diaz was Head of Marketing for Principa until 2017, after which he became Head of Marketing for Honeybee CRM. American born and raised, Julian has worked in the IT industry for over 20 years. Having begun his career at a major software company in Germany, Julian made the move to South Africa in 1998 when he joined Dimension Data and later MWEB (leading South African ISP). Since then, Julian has helped launch various South African technology brands into international markets, including Principa.

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