‘Data by itself is useless. Data is only useful if you apply it.’
– Todd Park, former Chief Technology Officer of the United States
Data is all around us. We collect it, see it and contribute to it every day. But how many of us actually go beyond surface-level browsing and apply the knowledge we get from data to fundamentally impact things. It happens fairly rarely and yet, when people and industries commit to data, big change, innovation and positive development often results. Here are just three examples of large scale change that came about because people sat up and took notice of the data that was all around them.
1953 – Taiichi Ohno revolutionises the factory floor
Ohno was an industrial engineer for Toyota when he realised that it was possible to implement a process for manufacturing called Kanban, similar to the Just In Time (JIT) stock-keeping systems seen in supermarkets. After all, everybody within the manufacturing system knew, more or less, when something was needed. It was just that no one was doing anything with that data, or making it available to others, meaning the entire production line could be halted or delayed if one person ran out of the materials they required. Ohno’s relatively simple Kanban system allowed engineers a simple way of flagging that they needed new stock, thus reducing manufacturing hold ups and allowing Toyota to press ahead in the speedy manufacture of cars, reducing production time and cost. Similar, highly advanced systems are now employed worldwide.
2002 – Billy Beane changes the game
Whilst baseball may remain a mystery to many of us in the UK, it doesn’t take a vast understanding of the game to realise that Billy Beane’s tiny Oakland Athletics team, with a payroll of $44 million, should probably not have been beating the New York Yankees in the 2002 season, with their payroll of $145 million. But beat them they did, thanks to Beane’s approach which distrusted the opinions of scouts and instead looked only at data. If a player was good on paper then he was good, no matter what the scouts who saw him might think of his appearance and ‘makeup’. Beane’s philosophy changed the game and helped to popularise a whole new field of sports data analysis, known as sabermetrics.
1987 – J.D. Power attempt to derisk buying a car
The J.D. Power Initial Quality Study (IQS) looks at popular car manufacturers and assesses the number of defects or ‘Things Gone Wrong (TGW)’ they show. It’s a simple approach, with a meticulous view on data collection (73,000 people responded to the 228-question 2011 survey), yet it has the potential to cut through marketing ‘noise’ and long held opinions. Thanks to years of advertisements focused on safety and reliability, Volvo has long been the brand of choice for the diligent driver. Yet the J.D. Power data put nine manufacturers above them in 2010 and fourteen in 2011. Should your next choice of car be based on colour, prestige, brand loyalty… or the data available?
The financial services industry and particularly financial advisers are arguably on the cusp of having an entry in this blog post! We have an incredible amount of data available to us, from all sorts of sources, but is it really being used in the best possible way? Are we not still reliant on a level of opinion and imperfect interpretation. Can’t we do more with data?
We think that we can and we invite you to find out more, give us a call here!
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