I would not consider “Information” to be useless or not giving good answers. If sense making could answer all the problems why would new technologies be invented (concept of variety is important here: http://www.techrust.com/humane/us-and-machines ). Also, if being close to customer was the answer, smaller businesses would have flourished at faster pace. In fact I would disagree to the fact that Zara's logic of supplying material at fast pace can keep customers satisfied too long, as Customer themselves are very well informed about the products (so many market comparison sites have popped up in the internet space)! It's a classical situation in which DATA vaccum is working fine for NOW.

One of the most slanderous argument made by Analysts: “Over-analysis leads to paralyses and sometimes information overload can be painful”. I would counter-argue these statements by asking again- WHAT was analysed, WHY was it analysed, WHEN was it analysed and HOW was it analysed. If the process design let the DATA pass all these filters, useful INFOMRATION was translated to higher levels, else, it was meaningless DATA (not Information). That's why I disagreed with the name of your post. I believe you, like other analysts, confused Information with data.

Also, I would like to draw your attention towards “Concept of Strategy” at different levels. Zobaggy has pointed out what happens at different levels (http://www.hcss.nl/en/download/176/file/Militai...). When it is difficult to achieve Ends by the Means (available), different behaviours are observed at different levels, with increased level of complexities. What worked as 'simple rule' is again one of the states called “Strategy as Rules”, but there are even harder points, edges of Chaos, which needs a wider perception of understanding and deeper logic of problem solving.

Arie de Geus, MD of Shell, talked about importance of Memory of future in his book- The Living Company. He said, “Managers can see the signals for change in time.” But I would add that managers also need “powerful tools” to SEE these signals from future and logically change it to meaningful information to act proactively in a pacefully changing environment. Pragmatic thinkers like DeBono, explained Seeing-Exploring-Judging as an important tool for decision making and I would say that information helps to take step1 and technology enables to store this information as memory of future. In the end it's the people of the organisation, who can make decisions and trade off before eliminating the options I have explained.

It reinforces one of the critical elements missing from most initiatives (where they 'do' make sense) = the real-world research to validate the assumptions.

As to “classic market data” — that's a whole 'nuther can'o-worms. We've been having several in-depth conversations about most of the key metrics being used not being relevant to the specific business model (http://twurl.nl/2txzo0).

Again, assessing the relevance is a matter of 'design' and the related research of what makes sense for the business to best preserve their lifeblood — connection to their customers.

I do think there are ways to harness this “specific” data, share it and even make collaborative decisions with it. There's a middle ground between huge objective numbercrunching and improvisational decisions out in the field, and in that middle ground (which is very untended today) is a lot of insight that can help both executives and first-line managers.

I do think there are ways to harness this “specific” data, share it and even make collaborative decisions with it. There's a middle ground between huge objective numbercrunching and improvisational decisions out in the field, and in that middle ground (which is very untended today) is a lot of insight that can help both executives and first-line managers.

So there is a strong trade-off in being a data-driven decision-maker and a strong instinctive decisionmaker. The right way to break this tradeoff is to aim to deliberately present limited information in somewhat disorganized/random ways so that there is room for some creative right-brained pattern-recognition to happen. The disorganization serves to scramble any preconceived models that might be loaded in your RAM.

A simple example is the presentation of a table. Size is not the only variable (depending on the context, you may need 7 or 7 million…). Ordering is important too. Any rational sort on some column biases the mind to think in certain ways. There are advantages to random or otherwise arbitrary (eg. lexical order) presentation (which is why browsing libraries is still more fun than following an Amazon recommendation trail. Libraries sometimes juxtapose things in interesting random ways).