Are marketeers simply collecting user data 'just in case'?
If we can, we should. That's been the attitude towards all kinds of data in the business world in the past few years, and after being constantly told that data is the future, it's no wonder. "The majority of activity is more 'just in case' rather than about gaining genuine or additional insight," says Gordon Fletcher from Salford Business School's Centre for Digital Business. "In being confronted with multiple terabytes of data, marketeers – just like everybody else – are more inclined to stumble than fly."
However, marketeers are the furthest ahead in using data to analyse and make decisions. "Take personalisation on e-commerce websites – this functionality is used to sell to us, but it also makes us aware of things that we might want or need," says Pfeil. "Collecting data over time helps make those predictions more accurate, and therefore more useful."
Is this 'spare' data being sat upon to sell later?
If every business has been told that big data has financial value now and in the future, you can be sure that the accountants have cottoned on to the value of so-called 'exhaust data'. "It's unlikely too many businesses would actively admit to this, but this is a real prospect as more and more businesses recognise data as one of their tangible assets," says Fletcher.
Such residual data is fuelling a growth in data aggregation companies, which at the moment is on the edge of the Internet of Data, but much of this data belongs only to those who first generated it – customers – few of whom will look kindly on companies known to sell-on personal data.
"For many companies, the value of big data is the knowledge of the customer that they get, rather than the strict monetary opportunity that could come from the data," thinks Pfeil. "Look at the energy sector – as we bring more smart devices into our homes, the utility provider can build up a better picture of how we live and where services can be updated to save energy over time, which adds up to a far closer relationship than would be possible in the traditional energy provider market," he says, stressing that 'monetising data' should only be about prolonging the customer relationship.
"Selling data would potentially backfire here," says Pfeil, who thinks that clarity is everything. "If people understand how their data may be used beforehand, they will be willing to share data in return for a service that provides value to them."
What's the problem with big data analytics and tools?
Many business intelligence platforms were designed only for data specialists to work with. "People across the business would ask them for reports, and they would generate them and send them back, often times after a period of weeks," says Jones of this now outmoded way of working with data. "The challenge with this is that you have to know what question you want to ask, and if the data you have will support what you want to find out [but] so much was invested in these applications, they could not be touched."
Jones explains that business users responded by bringing in their own tools so they could upload their spreadsheets and create visualisations of their own data, saving a lot of time. But not relying on a centralised team brings a big problem. "When more people are analysing data sets in different ways, you run the risk of getting many different answers to the same question," says Jones.
The answer? The cloud, of course. "It's important to marry both traditional business intelligence skills and ease of use together," says Jones. "Networking the business intelligence infrastructure so that everyone can work from one source of data is one part of this." With the Internet of Data growing every day, developing best practice within organisations – and employing data scientists to manipulate it – will become hugely important.
