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Big Data

The value of Data Science

Some of my favourite examples of the value hidden in data come from Netflix – a company famous for its highly data-driven operation.

Take for example its hugely successful series “House of Cards”. Netflix’s data scientists determined that people who watched the original 1990 BBC series correlated highly with people who watched films starring Kevin Spacey, as well as those who enjoyed David Fincher-directed films. When an American remake went up for sale, Netflix had the confidence to snap it up with Spacey cast as lead actor and Fincher directing.  It’s been a huge success.

Of course I don’t want to imply the Netflix explosion is driven solely by House of Cards, but I know it was a big driver in making me sign up, and their use of data science on production decisions for in-house TV programs has been a fundamental cause of growth, seeing their share price rise from $12.76 to $125.44 over only three years.

The art of applying data science in industry is to draw business value and improve decision making based on the computational analysis of data. With the recent boom in Big Data technology, more and more businesses are catching on to the adoption of data-driven decision-making to guide their business strategy, rather than purely rely on experience and intuition. So, what value can data science bring to your business?

Back to Netflix. When the opportunity to commission a motoring series starring the “Top Gear” trio James May, Richard Hammond, and Jeremy Clarkson presented itself, they passed on account of the data not supporting the asking price. Top Gear attracted an estimated 350 million viewers worldwide, so this is a great example of using intelligence locked within data instead of human intuition. With a rival picking up the show, time will tell if it was a good decision or not. If it is, then the value of data science from this one decision alone could be worth millions in saved costs.

Data science’s key role, in my mind, is allowing for automated decision making based on prediction. What advert to show a particular customer to get the best buyer response, what products an etailer recommends you to get additional sales, what movies you should watch next to keep you enjoying a service? That’s just at the front that a customer can directly feel. Behind the scenes, data science is used extensively. Demand planning, route and supply chain optimisation are among many use cases. Famously, the UPS route planner only plans right turns the majority of the time. This may sound ridiculous, but it saves them $40 million a year in fuel costs alone. Data science can help you work out which customers are likely to leave you and when, and what offer they will find appealing enough to stay. It can help you work out who is going to claim their insurance premium, and who is higher-risk.

The question isn’t whether data science will add value for you, but rather how quickly your business can be positioned so that it adds value. At Waitrose, within the space of six weeks BJSS created a proof of concept solution to identify empty shelves in near-real time by simply referring to point of sale data. By analysing years of historical data, trends could be identified and compared with current sales to locate unexpected sales lulls. This information was used to raise an alert to in store staff mobile devices prompting them to stock a particular item as soon as (or even before) shelf stock ran out. Waitrose estimate that correctly identifying these instances could increase overall in-store sales by up to one percent.

This is just one example of how BJSS can help. Our Big Data Lab service is designed to quickly (often within weeks) prove the business value locked within data.

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