Not all information is created equal
Saving all your data all the time is not always smart. The Naked CIO explains how to turn your organisation's information into knowledge.
Over the last few years the amount of my annual budget that deals with data and the management of this colossal aspect of every business has increased significantly. The ability to apply tools to analyse data is now not a luxury for a company but a necessity.
The thirst for data has also increased. Any piece of what appears to be insignificant data must now be stored in databases just in case a company might want to someday use it for one reason or another.
The biggest problem with data is that it is becoming more important than the ability for it to mean something. What I am referring to is the difference between knowledge and information and the significance of knowing why data is important rather than just believing it could be.
As we purchase more and more applications and hardware to support this data obsession, we can no longer see the woods through the proverbial trees.
My complaint is that little or no thought is put into the meaning and relevance of data as justification of whether we should store it within the data model of an organisation.
This is irresponsible and also creates other problems in terms of how that data relates to the rest of the organisation's data franchise.
Additionally, volume and manageability become significant issues for applications and analysis. Performance, knowledge and effectiveness are inevitably impacted by needless hording of non-relevant data that becomes an IT issue when it does not work as departments want it to.
The complexity of business intelligence environments that create dimensional cubes is compromised and enterprise data warehouse models become extraordinarily bulky because of the old 'what if I need it' mentality.
Business users believe these tools are so intuitive that it does not matter how much data exists or how ill-defined data relationships are - but this is the biggest mistake an organisation can make. Tools become exception-based or even worse they have no primary key and invariably impact the deliverable that the business expects. And once again the perceived blame is passed on to the IT arena.
As CIOs we need to coach our organisations to define and understand data first. Look at what it does and more importantly doesn't do. Deal with source-related inaccuracies as a basic founding principle and structure relationships between data that allow for the best decisions to be made.
In short turn the raw data in your organisation into meaningful and valuable knowledge - knowledge that can allow people to make informed decisions as opposed to regurgitate reports that only ever say what everyone already knows anyway.
We must also encourage people to be less concerned about the quantity of data and more concerned about the quality. I am strong believer that this is the most effective way to get the best out of your data systems and also out of the users that rely on it.
Fishing expeditions often end without a fish being caught.