22 October 2008

Getting IT right!

Writing in InfoWorld magazine (6 Jan 2003), Ephraim Schwartz said:

"The goal of IT, since its inception, has been the timely (a relative term) delivery of information to those who need it. Behind this goal is an unspoken belief in technology: If IT could deliver to its internal enterprise customers all of the information all of the time, it would be impossible for them to make a mistake."

Understanding the difference between data and information

More likely than not, many of the folks working in your organization's IT department don't actually know the difference between data and information. To be fair, they are not alone: Many people working as supervisors, managers, and executives probably don't recognize the difference between data and information either.

  • Data are the bits of information your various systems store. The system may be any kind of system -- not necessarily and IT-related system. Those old metal filing cabinets still found around many offices store data, just like that 160 gigabyte hard-drive on your desktop computer stores data.
  • Information is data transformed (e.g., gathered, analyzed, collated, sorted, coded) to allow the user to rapidly digest and comprehend the implications of the underlying data for timely, accurate, and effective decision-making.

For example, a 300-page report printed on green-bar paper, like an old mainframe computer used to spit out for us at a firm I worked at years ago, is data. Make no mistake, the data -- in the 300-page report -- contained everything we needed to know to make an effective decision. However, it its form as a report, it was not readily digested and comprehended for effective decision-making.

At another firm for which I consulted a few years ago, one of the firm's key production managers would take home several reports from their existing system almost every night. Working at home in the evenings, he would comb through these various reports and, using an assortment of colored highlighters, would mark up the reports with various colors to guide his production decisions the following day.

What was he doing? He was transforming data into information.

The data contained in the aforementioned 300-page report could have been more easily digested and decision-making could have been faster and more effective if the data had been presented, perhaps, in a chart, a graph, or even reduced to some form of exception list.

Placing the information in its context

Data content may typically be broken down into three general classes for most organizations:
  • Operational data such as orders, purchases, inventory, and so forth;
  • Process data such as schedules, routings, bills of material, logistics, and similar; and
  • Administrative data including accounting, customer lists, vendor lists, employee lists and more.
The data context, however, must be understood before effective decision-making may be done for any particular organization. The context of the data give the data meaning within the framework where it is to be applied. The context includes such elements as:
  • The organization's purpose,
  • The organization's strategy,
  • The organization's vision and mission,
  • The organization's execution model,
  • The organization's capabilities and competencies,
  • The organization's structure,
  • The organization's policies and procedures, and
  • The organization's values and culture.
Clearly, depending on an organization's purpose or strategy or production model (for example), essentially the same data may drive two different organizations to make equally effective but totally different decisions.
It should be part of every organization's IT strategy to mandate the transformation of the huge volumes of data being collected into information by their IT systems. This transformation, in itself, should be flexible, timely, and subject to ad hoc transformation, as well.

That's what business intelligence is all about. In today's world, this is all about survival, not just improvement or excellence.

"Business, we know, is now so complex and difficult, the survival of firms so hazardous in an environment increasingly unpredictable, competitive, and fraught with danger, that their continued existence depends on the day-to-day mobilization of every ounce of intelligence."
-- Konosuke Matsushita, founder of Matsushita Electric (Panasonic) as quoted in Managing on the Edge: How Successful Companies Use Conflict for Competitive Advantage by Richard Pascale (New York: Simon and Schuster, 1990), p. 51.

17 October 2008

Information Is Not Knowledge

"Information is not knowledge. Knowledge comes from theory."
-- W. Edwards Deming

When Sir Isaac Newton was conked on his head by the falling apple (as the story goes), he had information. The information was, "apples fall from trees" or, put more generically, "things fall to the earth."

However, Newton still had no "knowledge."

Newton's comprehension of the facts did not provide "knowledge" that would be useful in any significant way. After all, people had known for centuries that things fall to the earth and, if one didn't want them falling to the earth, one must be certain that the objects are held securely in their present location.

Once, however, Newton began to construct "theory" around the fact that things fell to the earth, valuable "knowledge" began to spring from the "information" at hand.

For example, based on the "theory" that gravity was a force that always acted in precisely the same way, experiments could be set up to measure just how gravity functioned. From these experiments and calculations, we now know that the gravity of the earth accelerates objects at ~ 32.2 feet per second-squared.

This principle applies in business as well.

Having worked in the world of business management and computers since the time of the introduction of the personal computer (PC) in the early 1980s, I have found that many, many business people -- from owners, to CEOs, to CFOs, to middle managers, and on down the line -- confuse "information" with "knowledge". In fact, a very common fallacy is the belief that more "information" will lead to better management which will, in its turn, lead to better results.

Therefore, organization spend a considerable amount of some very limited resources (namely, time, energy, and money) acquiring or creating systems to give them more "information."

When all is said and done, however, these business folks often are not significantly better off than they were before they spent their precious time, energy and money, simply because, like the world before Newton, they have no "theory" by which to interpret the information they have. Without this theoretical "framework" in which to fit their body of information, many of their management actions are not much more than flailing at the wind. Some of their efforts work and some do not, but they generally cannot tell you (specifically or accurately) why one initiative worked and another similar one failed.

There are three required steps to gathering what one needs to take timely and effective action:

1. One must take the data (the raw, undigested facts -- perhaps line upon line of numbers) and convert the data into "information."

2. "Information" is data "digested" and put into a form (i.e., a chart, a graph, summed, analyzed statistically) that allows the user to quickly assess the essential implications of the underlying data.

3. The resulting "information" must be placed into a theoretical context -- a "framework" -- whereby the potential outcomes of any actions that might be indicated by the information may be fully comprehended.

Without these three steps, your organization may drown in data or become infatuated with "information" and, yet, never be able to move effectively when times are the most challenging.

©2008 Richard D. Cushing