Big data: Think Smarter, not bigger
Big data is changing the world, and will continue to do so—I’m sure you’ve heard this, whatever industry you happen to work in. The ability to digitally measure and record everything we do, and analyze it for improvements, is providing new answers to everything from curing cancer to the fight against international terrorism. And in business, too, it’s a game changer like nothing we’ve seen before. No matter what size a company is, if it isn’t leveraging data for a competitive edge (as 70 percent are, or are planning to) it is in danger of being left behind.
It’s not about the size of your data
The problem is, people get confused by the name: big data. I’ve been saying for a while that the name is misleading—the truth is, it isn’t how big your data is, it’s what you do with it that matters!
You see, the value isn’t in the size of your data. That’s the mistake that a lot have already made, and, sadly, due to the hype the term “big data” is receiving, many are continuing to do so. By simply focusing on the size of your data you run the risk of becoming “data rich and insight poor.” You have huge volumes of information at your fingertips, but no idea what it all means or what to do with it.
The real value comes from the analysis of that data. While data has undoubtedly grown much larger in recent years, equally strident advances have been made with the methods and technology we have to query, interrogate and report that data. This is the key to unlocking the valuable, change-driving insights locked inside.
I work with a lot of companies of all shapes and sizes to help implement data strategies, and I see this all the time, which is why I’ve developed the Smart Data Framework. It’s a step-by-step guide to planning and implementing a data-led operation with the emphasis on Smart Data.
The aim is to build an efficient, streamlined data operation designed to provide you with the answers you need to generate positive results, and, vitally, also make sure you are asking the right questions.
A quick view of my five-step Smart Data Framework:
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.
How to generate valuable predictions
Despite all the hype that has been generated (and the predictions such as the one I mentioned above about the number of companies that are planning to use big data), reports have found that relatively few companies (less than one in three) have actually completed the process to the point of generating predictions with commercial value. Follow the steps of my Smart Data framework, and you will be among them.
I explain each step of the Smart Data Framework in detail in my new book Big Data: Using Smart Big Data Analytics and Metrics to Make Better Decisions and Improve Performance. Learn more about Smart Big Data and sample a free chapter today, preorder anytime.