Understanding the eight levels of analytics

SAS executive says there's more to analytics than meets the eye

Analytics is "the most used and abused term in the marketplace right now", according to Jim Davis, senior vice-president and chief marketing officer of SAS Institute. Speaking at SAS's Premier Business Leadership Series in Las Vegas, Davis questioned whether there is "a vendor or supplier out there today that doesn't have analytics". "Everybody has analytics," he said. But what they are actually offering in terms of analytic capacity in support of solving business problems remains in question. "So you bring all the data together and you put it in some form in which the end user can gain access to it, but what are you doing with it?" he asked. There are eight levels of analytics, according to Davis. The first four encompass what he considers "the classic definition of business intelligence" and what the majority of organisations are actually doing. What the first four levels all have in common is they look at past activity, Davis pointed out. "They support reactive decision-making ... understanding the facts after things occurred and are now reacting too," he said. The remaining four levels support pro-active decision-making and keep innovation and optimisation on track. These are predictive in nature and keep things "headed in the right direction." It is the last four that "are really going to help change the future" for business, said Davis said. But analytics alone doesn't guarantee success for an organisation. To actually solve business problems, companies must address areas of data integration, analytics, report the results and put it all in the context of a business solution, according to Davis. While this requires a framework to capture data and allow people to gain access to that data on a consistent basis, "it's not about simply building a data warehouse and putting a BI front end on it", he said. "It's not about going out and buying the fastest database or the coolest interface or the best piece of hardware. It's about solving a very focused business problem," he said. 1) Standard reports Standard reports provide summary statistics and answer questions like, What happened? and When did it happen? said Davis. "That's analytics, but not enough." 2) Ad hoc reports Ad hoc reports answer questions like, How many? How often? Where? he said. They provide a level of independence on desktops that allow an individual, for example, to see sales in a particular region or at a particular point in time, without needing to go to an IT governance counsel and wait three months for the result. 3) Query drill-downs Query drill-downs answer questions like, Where exactly is the problem? and How do I find the answers? said Davis. This is for when an organisation wants to see not only the results, but what the results mean and what backs it up, he explained. 4) Alerts Alerts answer question like, When should I react? and What actions are needed now? said Davis. "This is when you reach a particular threshold ... something changes from green to red, so you do something about it." 5) Statistical analysis Statistical analysis answers the questions, Why is this happening? and What opportunities am I missing? he said. "You begin to take the data ... and you begin to understand why things are happening." 6) Forecasting A popular level, forecasting answers questions like, What if these trends continue? How much is needed? When will it be needed? 7) Predictive modelling Predictive modelling tells users what will happen next and how it will affect the business. 8) Optimisation Optimisation answers the questions, How do we do things better? and What is the best decision for a complex problem? This includes areas such as price optimisation, markdown optimisation and size optimisation. This isn't just about cost-cutting and can be the difference between success and failure for an organisation, Davis noted.

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