The business world has been talking about the ascendency of big data for some time now and it is hard to deny that big data is a ‘big deal’ – its proper use can drive profits, not just deep insights. Netflix is a prime example of a company that has turned the data at its disposal to its advantage – collecting data about when and what customers watch, as well as when they pause or use playback to predict viewing habits and create a deeply personalised recommendation service, leading to happier and more loyal customers and an increase in revenue for the company. Supermarkets have become more savvy about using big data in innovative ways and arguably Dunhumby is a world expert in predicting buying behaviour. In the US, Starbucks uses the customer loyalty scheme to drive data-capture not only in store, but by offering reward points for grocery purchase, across a segment of their market that was previously unknown to them.
While these examples illustrate the significant benefits big data can bring, harnessing the data created by millions of customer
interactions is both a technical and organisational challenge, and success is far from guaranteed. When overwhelmed by
data, decision-makers tend to make quick, impulsive decisions that use their intuitions or experience to shape the data
at hand, selecting what they need to confirm their own biases or failing to view data in the correct context.
It undoubtedly helps to have a clear purpose and business case for developing a big data analytical capability or application,
whether that is about identifying and addressing the drivers of customer churn, uncovering pricing opportunities, or
discovering ways to optimise the supply chain. But a business case alone is clearly not enough – the right people in
the right roles will be critical. So what can businesses do from a human capital point of view to increase the chance
It is obvious that a database on its own is worthless without the right skills in the business to analyse, draw conclusions and translate that data into concrete, actionable plans, or to develop the appropriate big data application. The key is to accept that getting the most out of the data will require an investment in technological, data mining, and commercial skills. The biggest challenge, in our experience, is to identify and hire the individuals who can unite an understanding of the business’s commercial needs with an understanding of how data could address those needs.
As with many complex (and to some, completely unfathomable) areas of business and life, it is incredibly tempting to stick a Chief Data Scientist into the business and leave them to get on with it. However talented this individual is, they are likely to be doomed to failure – if a business is serious about using data to aid the business, the job is bigger than one person. Businesses that have used big data most effectively have built out the function from that start. This doesn’t mean creating a large army of data analysts, merely equipping the Chief Data Scientist with a few people with distinct expert skill sets who can help turn data into valuable insight.
Frontline employees are key in turning insight into action, so businesses will get the most out of their data by developing applications that help these employees in their day to day jobs (for example, by flagging a customer that is likely to churn to an account manager so that they can reach out with a courtesy call, offer a discount, etc.). Empowering these employees to make data-driven decisions in real time, whether these are decisions about how they allocate their time, about the level of discount to give a customer, or the packages to offer, is key to securing the business benefits from big data. It involves a great deal of trust that the business has hired high quality staff and trained them we
It’s a well-known anecdote that the average tenure of a CMO is short – just under two years in fact – but little…
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