Good decisions are based on knowledge rather than numbers.
Plato, one of the great Greek philosophers made this statement almost 2,500 years ago. Actually, this is a great and wise statement. And probably a quote that perfectly describes why I think that data – in its rawest form – is useless.
Decisions are the essence of our everyday’s life. And I’m not only talking about the big decisions a CxO has to made. I’m talking about that everybody – from the flight attendant to back office staff, the manager and ground handler has to make hundreds of decisions every day.
And I do presume that, despite Plato’s wise words 2,500 years ago, most of the decision are based on numbers and not on knowledge.
So, when Plato was talking about numbers, we’d call it data today. We talk so much about data. The importance of data. Big data, small data. And every airline, every airport, every company possesses a vast amount of data today. Data about clients, about processes, about products.
The thing is, as initially stated, that data in its purest form is useless. Data has to undergo a certain refinement process in order to create knowledge out of it.
So what do we have to do? What I would like to show in this blog article are four steps about how to create knowledge out of data.
Let’s start simple. This is data:
Step 1 — Give a context
What we have to do in a first step is to give data a context. This is nothing disruptive — but giving data a context means, creating information out of data.
Data + Context = Information.
So in our example, we put the context of on-time performance to our data.
Now these numbers make much more sense. Still this is very basic, but we converted data into information. Great job.
But as you can imagine, in order to create knowledge, there are some more steps to take.
Step 2 — Make it easy to digest
On-time performance, as shown in our example, is a very easy to digest information — but we all know, we have to deal with much more complex information in our daily business. So it is important, to make information as easy as possible to understand. And what’s easier to understand then a perfectly visualized information.
We now have the information and we found a way to visualize it, to enable the person who looks at it to understand it in a blink of an eye. Nonetheless, you remember Plato’s quote, he said decisions should be based on knowledge.
Step 3 — Apply Rules
Knowledge is created, when rules are applied to information.
Information + Rules = Knowledge
In our on-time performance example the average or the target value create that knowledge. And of course a corresponding visualization.
Step 4 — Predict
However, there’s one last step — actually, the ultimate knowledge level. Not only knowing how the situation is right know but also to predict how the situation will be in the future.
A summarized overview
Let’s take this example a step further and assume you are the operations manager of an airline. Having knowledge about your on-time performance is already a good start, but of course you’d need a lot more.
Information on delays, the planned flights, passenger information, airport information, you name it.
A comprehensive overview of all relevant information, in a context, perfectly visualized, applied rules and predictions – could finally look like this:
Benjamin Walther, CEO, Information Design
Get in touch with Benjamin directly: firstname.lastname@example.org or connect with him on LinkedIn