Data literacy is important, everyone must understand the data if we want to make it to the next level. I also agree with that, but I think how most organisations go about it is all wrong. Let me explain.
Who needs to be more fluent in data?
“The business needs to understand the data” – would someone in IT say. The business knows they have some things to learn, so they sort of agree that they are the subject of this exercise.
The business does not know exactly what the state of their data is. They need IT and tools to help them. They often even need IT to tell them what they should want. The business feels that they have something to learn and this is true. They need to understand the importance of strings, dates, numerics, querying, filtering, speed and memory, all the fun things for IT.
In fact, it is the next step in computer literacy and that is a good approach.
It is however not the complete picture …
IT needs to learn ‘business data’
It is crucial that IT talk about data in business terms. Instead of talking about data tables and fields, values, reference data, they also need to talk about the meaning of data in business term. Very often IT do not understand the meaning of certain data, the importance or the impact for the business. It is like talking to someone who only understands bricks and mortar and you want to explain what you do with houses, offices, factories and roads.
IT need to get literacy on business data and concepts to have a better understanding and then being able to help.
What are we missing?
We are still missing the best party on the table. When IT and business understand data in the other’s terms and can work out how to work together, there is still 1 party that also needs to get better at understanding the data. Correct, the computer needs to understand the data in IT terms and in business terms. If we fail to do that, then IT and the business will keep reacting on data, having to define every rule and exception, do trial and error, do manual analyses to find out if there is some pattern in the data.
We also need to get the computer in on our data literacy efforts. These 3 parties together need to be educated on the other’s view on the data to work more effectively towards a data-driven and automated future.
Are you wary of artificial intelligence (AI) and machine learning (ML)? Me too, because here the computer is taught about our world, or our business. Too often this is done by IT alone, with mixed results.
An approach that could backfire, is one where the short term and long term goals are set and now people are trained towards these goals. That is leaving very little space for the business to find out how data can help them. It also forgets the steps in data quality and reconciliation that are necessary.