IBM’s SMART Approach to Analytics

Came across this 5 point methodology for applying analytics in a business… very similar to the 3 I’s that I use in my training. I’ll start using both going forward.

S=Start with Strategy
What problems do you need big data to help you solve? If you’re running a business you might think it’s as simple as “How do I increase my profits?” But a question like that is inevitably going to lead you to more questions.
How do you generate more sales? How do you increase visitors to your site or store? How do you make your customers happier?

In this first step you need to be clear about your strategic objectives as well as the key strategic questions you want to have an answer to. You need to have this nailed down before you worry about collecting your first kilobyte of data.

M = Measure metrics and data
Once you know what data you need to answer your most strategic business questions, you can work out how you are going to capture it. Everything we do, online and, increasingly, in the real world, is capable of being recorded and stored. If we visit a website, records are kept of how long we browse for and where we head off to next. GPS systems in our phones as well as CCTV surveillance keep track of our physical movements.

Of course much of it is (hopefully) anonymized. Big data collection isn’t about tracking individuals, it’s about tracking the masses, so patterns can be spotted giving clues to overall trends. This part of the process involves designing the actual systems that will collect what your strategy tells you is needed.

A = Apply analytics
Increasingly, we are finding that the sort of data which contains really valuable insights is very messy. The slightly more technical term we use for this is that it is unstructured data. The sort of neat and tidy data you get when, for example, you ask someone to fill in a form giving you their age, height, weight and data of birth, is structured. The sort of messy, disjoined data you get when you analyze the contents of an email exchange or CCTV recording is unstructured.

The hidden value in this unstructured data is where most big data divers are finding the real sunken treasures. If you’re a business, being able to spot trends affecting your industry before your competitors is what will give you your edge. In order to implement this part of the process you will need to get to grips with the ever-growing range of tools and methods becoming available for making sense of messy, complex data sets.

R = Report results
The most insightful insight ever is useless if you can’t explain what it means to the key decision-makers in your business. Presenting the information necessary to drive change in a clear and digestible format is as vital as any other step of the operation. This part of the process has analogies to storytelling. There will be a beginning, a middle and an end, detailing why you need the insights, what you did to find them, and how they will result in everyone living happily ever after.

If you use data visualization and narratives to tell that story in a focused and interesting way, it’s far more likely people will understand what you are trying to do, and be as motivated as you are yourself about implementing data-driven change.

T = Transform your business
Change—specifically positive change—is the ultimate aim. Transformations you make to your products, service, marketing strategies or internal processes, guided by insights from your Smart Big Data analysis, is the catalyst which will drive that change.



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