Why is it we get out the bed in the morning, ICT-wise? Is it to, in that dreaded phrase, just "keep the lights on"? Is it to loaf around waiting for suppliers to take us out to lunch, avoiding the beady eye of the CFO? Is it to be a 24×7 laptop-fixing resource for the Chairman?

Answer yes to any of the above and we’ll have to drum you out of the CIO Regiment. Joking aside, the real reason, surely, any of us drive to work in the morning is to add value to our organisations – to deliver business advantage through technology?

Such stories are rare enough at the best of times but in the last few years with the relentless emphasis on overhead-paring and making bricks with less and less (virtual, perhaps?) straws, the only note we hear struck is cost-cost-cost/down-down-down. So it’s great to hear cool case studies like that of Yongli Ge, senior logistics analyst at a company called Brammer.

Yongli’s company is in a far from fashionable market – it’s a £426m manufacturing outfit, more specifically, it claims to be leading pan-European distributor of such fab and wholly necessary things as bearings, belts and pulleys, clutches and couplings, health and safety products – you get the picture.

Industrial spare parts, it turns out, come in many, many forms – he told us he has an SKU table of 2.5 million inventory items, no less. And while business is good, that’s a lot of inventory sitting around that he and his team don’t know if likely to be sold, no longer in demand, and so on.

Why is that a problem? A part that sits on the shelf for years and only ever really gets bought by one customer is less profitable than items that have more chance of sale. If you have stock to hand that people want and in the right quantities to service the need, you improve the range of products and their yield. Simples.

So the business problem was clear: better inventory management. And for once, it looks like technology really has helped solve it – and convincingly. Yongli Ge says his use of predictive analytics software to analyse his customer data and better predict demand has helped reduce stock by 22%, the equivalent of £31m in bottom line cost savings in 2009 alone.

How? Basically, the firm had no BI. Some of Brammer’s 2,000 employees in at least some parts of the business were carrying out manual calculations and making decisions about inventory levels based on gut feeling rather than real data.

In response, Yongli has been using the SPSS Modeller tool from IBM to re-organise that big SKU catalogue, working on data-sets of five years’ stretch at all its European locations so as to help rationalise the warehousing and so make customers and suppliers much happier. He’s eliminating such problems as duplication of names for the same product in different countries, better managing his data growth problems, making his finance team much happier and all in all making Brammer a much better firm to buy from or work with.

Surely a case study like this is what IT should be all about? Using computers to make the business run better?

More like this, please. Will make us all feel much more inspired about what it is we do… even if the lights do have to stay on and silly jobs get done. Maybe being in charge of IT is about being able to do all of the above and more?

You’re a big guy. You can handle it.