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HPC 2017 Part 1: Public Sector Analytics Adoption Priority

In my first of a three-part series, I’ll be sharing my views on some of the latest technologies and political developments that will affect the market in 2017. HPC managers, suppliers and big data experts – take note!     

It’s going to be really interesting to see which industries will lead the big data analytics charge in 2017. In my opinion, from a commercial perspective, it will be industries like retail, which have historically made good use of big data anyway, for example, by analysing data collected through loyalty schemes and cards. Making greater use of analytics will come naturally to retail.

There are also lots of newer commercial industries and technologies popping up that will present an analytics opportunity too, for example, driverless cars. In the recent Autumn Statement, the Government pledged £100 million to fund a testing infrastructure for connected and autonomous vehicles. Once road-worthy, they will generate a lot of data, but what do you do with that kind of data? I’m sure there will be lots of businesses keen to access it. It will be an intriguing journey to watch [pardon the pun].

The public sector, as a priority, will need to take up the baton of data analytics in 2017. Only last week innovation charity Nesta called on The Government Digital Service (GDS) and the Department for Communities and Local Government to embed data analysts alongside local government workers around the country. Personally, I can really see it making a difference to the health service – for example, by looking at ways to reduce treatment times, speeding up the movement of patients through the system and removing bed-blockers. Most NHS trusts can already make intelligent decisions, but it’s increasingly obvious that the more complex challenges they face cannot be fixed without data and analytics. Fortunately, there is now a mass of data and tools to work with.

From our own perspective, we have now launched a new company – OCF DATA – to help people with common analytics challenges. Up to now, a lot of companies have tried analytics on their own, but have been disappointed by the results – however, they tend not to start from the correct place. We’ll be aiming to correct that next year.

 

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