Insight. The ‘eureka’ or ‘aha’ moment, the moment when the penny drops. However you wish to define it, we can all agree it is a euphoric experience as a result of a sudden realisation. But waiting for these moments can be like waiting for lightning to strike. In a world where there is an abundance of data from an endless supply of sources, it can sometimes be hard to know where to start. It can also be hard to separate fact from fiction.Hidden inside every data set that you find are two important subsets, similar to a Russian doll, which exist inside each other. These two subsets are information and insight. The trick to turning this data into a strategic advantage is being able to hunt between these two to find key points which can then be applied strategically to your work.
To bring the concept to life, think of all the wearable tech we have today. Consider what a top end Fitbit can do (available in detail on their website https://www.fitbit.com/global/uk/technology), and how much data it can give you; the obvious steps taken and miles covered, but then it goes deeper to amount of floors climbed, calories burnt and then again further to time sedentary and hours slept. The amount of information available is extensive at the best of times but you can’t look at these statistics and make a snap decision to ‘eat less’ or ‘walk more’. You need to understand the information at more than just face value, more than just because your expensive watch says so. You need to take the time to understand what it is telling you overall.
Going back to the concept of two subsets, we start with information. I want to stress that this is different from data. Put simply, information tells us what to do. If we think of our Fitbit again, if I’m wearing one 24 hours a day and enter all the required information, I will have access to an excess of data. Only when I strip the data back and look closely will I find valuable information. Knowing my BMI, resting and peak pulse rate is interesting but not really useful. If I want to achieve my objective of losing weight, for example, then I need more than just information.
Which leads into the second subset, insight. Armed with our relevant information, we can use insight to guide how to apply what we now know. If we look at the Fitbit once again, the information gained could be finding our individual fat burning pulse rate but applying insight would be discovering the best exercise to achieve that rate in order to reach our objective of, for example, losing weight. So next time you’re trying to interpret your data, consider the information of said data and then apply insight through understanding actions based on the two combined.
The quest for true insight is not easy on your own and there is no shame in calling in the experts to help you open those Russian dolls. It can be difficult to know if all the data you have is actually useful. But ask yourself, are there products in the past that have been through what we are now? Are there insights we can add from that? Or even, what is the benefit of the areas I’m focusing on? How can I use this to quantify my value proposition? For more than 5 years, our NeoSypher team has been at the forefront of helping clients find true insight in their data. So, if you want to know what’s hidden inside your data, and how this can be used to maximise your product, brand or business success, get in touch.