Comment: How big data can solve Britain鈥檚 productivity crisis Published on: 18 February 2016 Writing for The Conversation, Professor Paul Watson argues that we need to get cracking now if Big Data is to solve Britain鈥檚 productivity crisis. , Britain has a serious productivity problem 鈥� levels have not risen since 2008, and are now . The gap with our competitors in Europe and further afield is estimated to , and addressing this problem has been a source of angst for politicians for decades. The problem has been that the proposed solutions are often rooted in a 20th century view of the economy, such as adopting Japanese approaches to reducing defects (鈥渢otal quality management鈥�), replacing outdated machinery, and improving transport infrastructure. But a more 21st century solution is already at hand: using big data could be a game-changing approach that could tilt the scales back in Britain鈥檚 favour. At least, that鈥檚 what a recent parliamentary has suggested, by extracting more value from the vast amounts of data generated across all areas of industry and society. Computing has always been focused on processing data, so why is this now talked of as being 鈥渞evolutionary鈥�? The change comes from how increasingly dependent we are on software for all aspects of our lives. Most businesses depend on computers, public services are increasingly administered electronically using online platforms, our health is monitored by risk-detection algorithms, and even our social lives are now filled with the social media we use on smartphones 鈥� the computers in our pockets. All this software generates vast amounts of data 鈥� and this is where the new opportunities arise. Consider an e-commerce website. Every time a customer accesses the site, information on what they viewed and bought is captured. Over time, this builds a pool of data with huge potential value. The company can discover whether an advertising campaign is effective by analysing changes in customer purchasing. It can build a picture of each customer鈥檚 interests so that adverts can be personalised, and help predict in advance what stock levels are needed for different products at different times of the year. The data need not just be used to optimise the sale of existing products: analysing what people search can reveal opportunities for new services and products to fill gaps in what鈥檚 available. The potential to exploit data isn鈥檛 restricted to retail alone, but to any industry or field that has been computerised, either internally or in the way it interacts with its customers. Some of this data has already been . For example, vast quantities of data on chemical properties are now freely available to anyone on the web, waiting for an innovative company to use it to design an effective new drug, or for a clever researcher to make a Nobel-prize winning discovery. Big data: everyone鈥檚 talking about it. What are we doing with it? ,
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