Today we’re talking about business analytics and the interesting questions that lead to big data exploration. But first, what exactly is business analytics and how is it different from business intelligence?
I define it as just the systematic use of data and quantitative analysis to make decisions. business intelligence was mostly about reporting whether it is a standard report run every month or ad hoc reports or queries. Business analytics is more about prediction, optimization, and more sophisticated uses of mathematics and statistics.
Put another way, business intelligence is about gaining the hindsight and insight into what’s happening in my business and what do I do about it. Examples of business analytics include looking into the future to understand my customer interaction, and figuring out how can I improve it. Anotehr example is understanding the profitability of a product line and how will I continue to extend that. A third example is understanding risk in the market and how I respond to reputational risk or any other components that might jeopardize my success.
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Frontier of Business Analytics
What’s going on at the frontier of business analytics? It’s a very popular topic today. At every client we talk to, from the boardroom down to the front lines, everyone wants to understand how they should apply business analytics to all the information we have gathered from all the different sources over the years in a way that it really makes a difference in their business. So they’re looking at that information asset frontier and trying to apply business analytics to everyday decision making and get better results.
The vanguard is really industries that historically not been analytical at all are really starting to change. You see it all over the place. Education, where you have student performance data, healthcare, where the US government is spending literally billions to try to get every hospital and physician to use electronic medical records, which is going to create massive amounts of analysis even to the point of identifying patients who may be coming down with a particular disease like diabetes so you can head it off quickly.
In manufacturing you see areas like green manufacturing that were never using analytics before but are now putting sensors on things like windmills so you know when is the time that we should really service this windmill. Many of them are offshore. It’s very expensive to go out on the water and service them so if the sensor is telling you the failure pattern, it can save you a huge amount of money in terms of your maintenance expense.
There are three basic components to business analytics. First is information management. What facts do I need to track, and what value does that data actually provide to the business? Performance optimization is the second. That’s around looking at history and how I perform against my metrics and measures. Business analytics insight is the third, and that is really looking to the future and asking those unclear questions that I need to understand such what opportunities I can take advantage of and what risk I need to avoid.
To me the most important thing of it is that all three of those steps are targeted to particular business problems and issues. Analytics is a really broad activity. We can’t analyze everything so I think it’s very critical to identify what are the real business questions that matter and focus the performance optimization and the forward looking insights on the business questions that really count.
What are the steps for applying analytics, and how do they help an organization master the discipline of analytics and adopt an analytics culture? The first thing is to start from where you are. Assess your maturity and analytics and how you might be applying analytics across the different business functions in your organization. Those functions could be merchandizing or supply chain or workforce or whatever.