Moving up the value chain – data, information, knowledge, wisdom

What’s the difference between data, information, knowledge, and wisdom?

John Bredehoft pointed me to an academic definition from Sujatha Das, in her post Difference between Data, Information, Knowledge and Wisdom.

Value increases dramatically with each step up. Knowledge is far more valuable that just information. Wisdom far surpasses knowledge in value.

I previously discussed here and here a company called Narrative Science. They provide a service that will convert raw data into a news report.

The impact of creative visualization is to help us move up the value chain quickly.  The same with services such as Narrative Science.  At low cost and low effort, they can move us up the value chain as well.

Check out Sujatha Das’ article for the full length version of her definitions. Here are highlights:

A datum is the value of an observable, measurable or calculable attribute. Data is more than one such attribute value.

(I)nformation, in general terms, is data plus conceptual commitments and interpretations. Information is data extracted, filtered or formatted in some way…

Knowledge is a subset of information. But it is a subset that has been extracted, filtered, or formatted in a very special way. … The quality of its knowledge then, will be largely dependent on the tendency of its validation rules and tests to produce knowledge that improves organizational performance (the organization’s version of objective knowledge).

Wisdom, lastly, has a more active component than data, information, or knowledge. It is the application of knowledge expressed in principles to arrive at prudent, sagacious decisions about conflicting situations.

Some examples:

Data – the transactions in your accounting systems general ledger or a list of every product sale including product number, customer name, sales rep, office & date.

Information – monthly or quarterly income statement and balance sheet or summary sales report by product or office or sales rep.

Knowledge – the reasons for budget variances, whether favorable or unfavorable or what products have increasing or shrinking sales and whether sales by product, office, or sales rep are above/below targets. This would combine information from the general ledger or sales reports with information about budget and sales targets. 

As John points out in his post, Sujatha Das on data, information, knowledge, and wisdom, Knowledge Science’s descriptions quarterly earnings reports or baseball game descriptions would be here.

Wisdom – whether to expand a particular ministry or cut it back or tell a program manager to get started on spending for a key project for which the planning work has not yet started but needs to begin (if the reason for a favorable budget variance is upfront costs have not yet been incurred) or whether it’s time to drop a product or increase/cut back promotional efforts for a specific product.

Value of each step increases dramatically as we move up from data to information, to knowledge, and finally to wisdom.