Is the future written in the data? Five steps for effective predictive analysis
Predictive analysis can help organisations predict opportunities that may lie ahead, Stephen Pritchard explains.
Organisations are always looking for more sophisticated ways to predict the outcomes of the decisions they make or the impact of external events on their businesses. Predictive analysis helps companies peer into the future by crunching data to make a forecast on the likely outcome of a strategy.
Whereas other methodologies for finding out what could happen in the future centre around identifying risk, predictive analysis is used more for identifying opportunities, and so is more often used to help decision making in sales and marketing.
Using data to predict the future
The larger the volume of data the more accurate the forecast, and often predictive analysis is used to identify which segments in a group (of products, or customers for instance) will behave in a certain way.
This analysis is dependent on the construction of complex mathematical formulas, based on the variables considered most influential to the outcome: for example if a retailer wants to know where a certain brand of jeans will sell well in a particular month, variables could be population density, disposable income and the weather.
"If the past couple of years have taught us anything it is that a lot of people could have made much better decisions," says Jeanne Harris, executive research fellow at the Accenture Institute for High Performance in Chicago, and co-author of Analytics at Work: Smarter Decisions, Better Results.
"People were using data and models but they were using models the wrong way, or the models didn't identify the right things. They used it to support what they were going to do anyway. So people are now looking to use predictive analysis more thoughtfully."
Businesses have continued to build up larger and larger volumes of data, even during the economic downturn. A big factor in this trend is increasing regulation forcing companies to collect and hold more data to meet regulations or for financial controls.
But companies are also gathering more data for sales and marketing purposes, in order to improve customer retention and to reduce the cost of sales by allowing more targeted campaigns.
The Royal Shakespeare Company (RSC), for example, used seven years' data, and a sample of two million theatre goers, to identify the customers who were most likely to visit its venues again in the future. This has allowed the theatre company to cut the cost of its promotions - by focusing campaigns on people more likely to visit its venues - but still increase ticket sales at its main Stratford-upon-Avon venue by 50 per cent.
Above all though, businesses are being driven by competition to be smarter in the way they predict the future, and the data...