“Of all areas of the business, yours must be changing fastest John. How do you see things?”
I was enjoying a coffee in a rather comfy reclining chair that seemed a bit out of place in the IT office. Saying that, the cushions were in the style of social media sharing icons. Nice.
“Well, you could look at two aspects of IT, the information, and the technology. Sounds obvious right?
“Looking at technology first, the way I see it, the biggest change is the level of abstraction the IT departments in firms like ours deal with.
“Back in the day, the technology was all about centralized computing power and spinning disk drives. We bought stuff. We put it in its own room. We configured it. We installed some software. We ran it.
“Then the boxes we put on people’s desks got more powerful, with capable software running directly on them, and the stuff back in the room became more dedicated to storing different kinds of data to serve up as needed.
“Then the local network got more capable so the powerful applications could be re-centralized for ease of maintenance and enhanced security without affecting the user-experience.
“And then the wider Internet infrastructure got more capable and some-one said, “hey, this stuff isn’t your core competence, but it is mine, so why not let me run that for you?” and this thing called the cloud emerged. So now, Attenzi doesn’t need to power its own computing, just like it doesn’t need to generate its own electricity, or pump its own water.
“And so to information.
“Now the words information and data are often used synonymously, yet incorrectly. Data of itself is just discrete, objective facts. Take an example from our production facilities – an item number with a particular serial number achieved a particular status at a particular time.
“Item no. 00256, serial no. 005693432, achieved status 4, 110903032010.
“We mere humans do not readily digest or understand data. Rather, we deal in information; that is data made useful, made relevant. A collection of data is not information – for that it also requires context and understanding. In my example here, in transforming the data to information in the context of Attenzi’s production facilities we find out that the item was a cooker, and all but one of the 52 made on 3rd March passed testing first time.