Why big data analytics needs huge talent

As the volume of data grows, organisations will need to democratise the use of analytics and make data-driven decision making intrinsic to their culture.

Over the last decade, businesses have undergone a transformation. The dynamic landscape has given rise to ill-defined and continuously shifting business problems. For example: how are my customer preferences changing? Who should I target? What is the right pricing model for different products?

In order to address such problems, organisations across industries are shifting from a knowledge-based to a learning-based approach. They can no longer rely on gut or past experience. They have to rely on the latest available information to infer and learn from, before making decisions.

This trend has been enhanced by the data age, where organisations are progressively looking to leverage data and institutionalise data driven decision making.

It is for this reason that many have gone on to term data as the economys new oil. However, as the volume of data grows, organisations will need to democratise the use of analytics and make data driven decision making intrinsic to their culture.

Ironically, even with so much data available, its true value has not been fully unleashed. One reason for this could be the severe talent shortage in the analytics realm. Research Organisation Gartner predicts that by 2015, Big Data will create 4.4 million jobs globally. Another alarming projection suggests only one-third of these positions will be filled. Make no mistake; we are not referring to people who at the core possess just one kind of skill. Rather, we are referring to people who are able to cull meaningful insights and findings from chunks of disparate data and information sources to enable better decisions.

Potent skills

Decisions is the operative word here. Although there is a lot of hype and talk around Big Data, organisations need to focus on the journey from Big Data to Big Decisions.

What is imperative for companies to understand is that as they embark on the journey of making data-driven decisions even the typical skills associated with the now popular term Data scientist may not be sufficient.

While a lot has been written about data scientists, we believe that the skills that they bring to the table need to be augmented. Just data, math and technology skills are not sufficient. One needs to take an interdisciplinary approach comprising a potent combination of skills such as applied math, business acumen, technology, design thinking, behavioural sciences as well as the ability to work with people. In this regard, what organisations really need is professionals from Decision Sciences.

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Why big data analytics needs huge talent