Dealing with Data
Most of us would like to believe that we’re open-minded. No-one wishes to paint themselves as being closed off to new ideas. Yet people often actually struggle to take on new concepts and new ways of working, even if they are hugely beneficial and could absolutely transform the success of a business.
If an argument is so transformative that it completely challenges our fundamental beliefs then we can experience cognitive dissonance; a psychological condition, in which we experience an unwillingness or inability to adapt our beliefs to a radically new reality.
The Brick Wall
But more common is that we make a conscious decision that we just don’t want to face up to the new reality that has been presented to us. Indeed, some people in an organization will never actually acknowledge the problems that you point out to them, no matter how thoroughly and accurately you attempt to do this! Unfortunately, this is part of human nature. They either don’t want to be involved, or don’t want to deal with the reality of changing their business practices. Yes, they’d rather continue with lousy business practices and underperform, than be willing to face the music!
This means that there is always the possibility that you will find yourself bashing your head against someone else’s beliefs when trying to implement something new, even if it isn’t particularly radical. From your perspective it could be completely straightforward, perhaps even mind-numbingly obvious, yet from the perspective of the business it can be a reality that they can’t stomach, can’t accept, can’t understand…or they just don’t want to!
Knocking Down the Wall
This is a problem that plagues a vast range of industrial fields. Thankfully, there is a way around this troublesome issue, using data. It’s very difficult to argue with facts and figures, particularly when a raft of information inherently pushes you in a certain direction. No matter how much cognitive dissonance you may experience, no matter how resistant you may be to the conclusions being presented and no matter how unwilling you may be to jettison your previous beliefs, at a certain point it just becomes impossible to ignore compelling data.
So in one particular case, we were having problems convincing a client of a particular conclusion that we had drawn. So we assembled a huge collection of testing data and after collating all of this information, we went back to the client and showed them our results.
And when you have a group of people, as many as 10 or 15 in number, all effectively saying the same thing, at the same time and these are evidence-based, data-based conclusions, it starts to become very convincing. And we’re then also able to actually map out, not just the feedback confirming what we are saying, but the whole process of determining what was correct and incorrect. And this can be highly intuitive and convincing.
From this we were able to go back to the client, and say…”Look this was our initial assumption, here are three interviews that prove our assumption is wrong, here are three further interviews that assessed a different assumption, and here are five of us testing the new assumption and proving it to be correct.” It is taking the client on this journey, from point A to point B, that can be particularly important and illustrative for them.
It’s also important and valuable to be able to tell a story with data. When we were working with the aforementioned client, not everyone wanted to be involved. For example, the CEO, whose idea it was in the first place for us to assist with the issue, he didn’t really want to be involved with this element. But other members of the team who were involved in that process with us could see the data and the way that we were mapping it out and consequently were all on board with our conclusions from day one.
And this illustrates the transformative potential of data and the way that it can be used to convince people working within a business of conclusions and viewpoints that they would otherwise reject out of hand. Data simply illustrates a particular perspective and way of working in a profound way that cannot really be equalled by any other method, at least in our experience.
Moneyball and Experts
It’s also important to remember that you’re often dealing with experts in their field, or at the very least people that have been deeply ensconced with a certain way of working or thinking for quite some time. So you’re faced with something of a ‘Moneyball’ problem, where you think you know something that they don’t, whereas inherently they think that they know better than you, because they’ve been working in that area for a long time!
In the case of Moneyball, one professional baseball club, with one team of analysts, took on many of the assumptions of baseball insiders that they believed to be flawed and subjective. And they did this using data analysis. And now barely a week goes by in baseball without someone mentioning Moneyball and of course, the book that explained this concept was made into a successful film featuring Brad Pitt.
This baseball example also exemplifies another truism…quality of data is more important than quantity. While there is a lot of hype about big data, and this phenomenon can be useful in some contexts, we have been able to completely prove and disprove theories with merely a handful of one-hour interviews.
Importance of Structure
Structure is all important. As long as you address an issue with a blank slate and aren’t going into it with the intention of ‘proving your theory’, then you can constantly refine this process. It’s not about how much data you have, it’s about asking the right questions and thus deriving the right information.
An example of this which came up in our work involved an AI system, which worked with solicitors, scanning contracts for certain recognizable clauses, in an attempt to reduce the time taken to deal with contracts.
So when dealing with this client, the first thing I asked him was…”who do you sell to?” The answer was “attorneys.” So I explained that what he should do is find three different types of attorneys – for example, specialists in property law, criminal law and family law – and ask them what problems they experience with contracts, their different features, and so on.
Once you have this information, you can very quickly establish that one will derive more value from your product than others. Then you can refine this. Look at another variable, such as company size and assess again how this impacts on usage. Then refine again. Who’s pushing this internally?
Top to Bottom Analysis
By implementing this process, you can quite rapidly assess an organization from top to bottom, understanding buyers, users, challenges, likes, dislikes and you have a very viable structure for your product before you’ve written a single line of code. From this, you can then map out the features needed from this ideal structure.
This is a highly effective, yet easy and not particularly time-consuming or resource-intensive way, of ensuring that the market is interested in what you do. And you can then be very specific in terms of what you’re building. This example demonstrates the immense value of data with regard to understanding your market and your audience, and how profoundly this can impact your whole operation.