Recap


This chapter is dedicated to Roslyn Rosenthal Marasco (1921-1998).

We need to make the following progression clear to managers:

Data Information Knowledge Wisdom

The arrows here should be read as "can lead to." Misapplication at any step along the way leads to the wrong answer. Starting out with "good data" is a must, but it is no guarantee that anything useful comes out at the other end.

There is an enormous gap between stage one and stage four. Too many technical organizations focus almost exclusively on improving data collection ("metrics"), without working on their abilities in the next three phases. I think this behavior has its roots in managers who come from an engineering or science background: they want numbers. But numbers are useless without intelligent interpretation; in fact, numbers will at best get you only halfway up the ladder. This approach won't lead to much overall improvement in your organization, because bad answers derived from clean data just don't do you very much good. It's what you do with the data that counts.

You can gather data automatically. Getting to stage two entails intelligent human analysis and synthesis. Achieving stage three requires an intellectual framework from which you can derive general principles. Finally, progressing to stage four demands, once again, human intelligence and great judgment, so that the application to the real world can be effective.

Awareness of the world around us exists at various levels of abstraction. The higher the level of abstraction, the more generally can we apply our awareness to real-world situations. D-I-K-W represents increasing levels of abstraction, and abstracting the right stuff grows harder at each stage. Data is concrete and specific; wisdom is abstract and universal; information and knowledge are intermediate states. It is important not to confuse information with knowledge or knowledge with wisdom. When you have a concept in hand that derives from data, ask yourself whether it is information, knowledge, or wisdom. The answer to that question is often crucial.

We can think of people in the three phases of life as being capable agents who perform different transformations. We can modify our chain with more generic arrows:

Data

(is gathered and transformed by schleppers into)

Information

(which is transformed by machers into)

Knowledge

(which is transformed by mensches into)

Wisdom

This representation explains why we swim in data, distill some of it into information, refine precious little of that into hard-earned knowledge, and extract very scarce wisdom as the ultimate product. We start out with a lot at one end of the chain and get very little at the other end. The process itself requires that as we move up the abstraction ladder, we formulate our conclusions in fewer, simpler, and more powerful ideas. More important, the number of available agents goes down by a factor of 10 at each stage of the process; the work gets harder, and there are fewer competent people to do it at each level.

The agents who do the work at each stage bring to it their particular skill set; having 10 times the agents of the wrong type at any juncture is worthless. No, it is a classical impedance-matching problem: You have "stuff" in a certain state, and you need to transform it into "stuff" of the next-higher state. Only people with requisite experience and maturity can perform the necessary transformationand do it correctly and efficiently. Distinguishing quality from mediocrity is a moral action, requiring passion as well as intelligence and judgment.

Our job as managers of the managers is to make sure that we have the right people stationed at the right places at the right time. Only then can we hope to reap the complete benefits of the progression from data to wisdom.




The Software Development Edge(c) Essays on Managing Successful Projects
The Software Development Edge(c) Essays on Managing Successful Projects
ISBN: N/A
EAN: N/A
Year: 2006
Pages: 269

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