Information systems might differ wildly in form and application but essentially they serve a common purpose which...
is to convert data into meaningful information which in turn enables the organisation to build knowledge:
- Data is unprocessed facts and figures without any added interpretation or analysis. "The price of crude oil is $80 per barrel."
- Information is data that has been interpreted so that it has meaning for the user. "The price of crude oil has risen from $70 to $80 per barrel" gives meaning to the data and so is said to be information to someone who tracks oil prices.
- Knowledge is a combination of information, experience and insight that may benefit the individual or the organisation. "When crude oil prices go up by $10 per barrel, it's likely that petrol prices will rise by 2p per litre" is knowledge.
The boundaries between the three terms are not always clear. What is data to one person is information to someone else. To a commodities trader for example, slight changes in the sea of numbers on a computer screen convey messages which act as information that enables a trader to take action. To almost anyone else they would look like raw data. What matters are the concepts and your ability to use data to build meaningful information and knowledge.
Converting data into information
Data becomes information when it is applied to some purpose and adds value for the recipient. For example a set of raw sales figures is data. For the Sales Manager tasked with solving a problem of poor sales in one region, or deciding the future focus of a sales drive, the raw data needs to be processed into a sales report. It is the sales report that provides information.
In the first column below you'll see some examples of the huge amount of data that managers may receive. The second column then shows how the various types of data could be processed to create useful information.
|Data||Possible methods of converting data into information|
|Sales figures||Plot charts and identify trends|
|Market and competition data||Find average or typical values|
|Financial performance||Present complex data as a chart or graph|
|Production output||Monitor changes over time and forecast future values|
|Costs of resources or other inputs||Compare figures and identify similarities or differences|
|Staff absences, holidays or sick leave||Assess whether a result is significant or occurred by chance|
|Accident records||Assess whether one thing is related to another|
Table 1.1 Converting data to information
Collecting data is expensive and to merit the effort, you need to be very clear about why you need it and how you plan to use it. One of the main reasons that organisations collect data is to monitor and improve performance. Measure what matters might be a bit of a cliché but if you are to have the information you need for control and performance improvement, you need to:
- collect data on the indicators that really do affect performance
- collect data reliably and regularly
- be able to convert data into the information you need.
Here are some perspectives from CEOs on the indicators that they track. Read their comments and then decide for yourself. What are the measurements that matter to you?
|There are few metrics to which I pay closer attention than "system uptime" -- how often Sun systems are up and running at customer sites. The most important commitment that we can make as a company is to share our customers' risk. Most of our customers face the same risk: computer systems that go down when people need them.|
Scott McNealy, President and CEO of Sun MicroSystems
|I monitor costs because being low-cost is the core of our business strategy. The rationale behind an airline like Go is that keeping costs low lets us offer customers a cheaper way to fly -- and, as a result, more people will want to travel.|
Barbara Cassani, ex-CEO of Go Fly (now part of EasyJet)
|We are a service organization. Our customers are the citizens of Charleston. In my 17 years as head of this organization, the question that I've always asked myself is, "are citizens happy with the job that we're doing?" One metric I use to answer that question is the number of complaints that we receive. Complaints provide a window into your overall performance. When one citizen makes a complaint, four or five others probably feel the same way but either don't take the time to complain or don't think that it would do any good.|
Reuben Greenberg, Chief of police, Charleston Police Department, South Carolina.
|The difference between a great technology company and an average technology company is how much intellectual property a company creates. I keep a close eye on two measurements. One is our rate of innovation in existing products. I want to know how many customer-requested features are making it into the next release. The other measurement that I track is patent flow.|
Edward Iacobucci, Founder, chairman, and CTO, Citrix Systems Inc.
To be useful, data must also satisfy a number of conditions. It must be:
- relevant to the specific purpose
- timely; data that arrives after you have made your decision is of no value
- in the right format; information can only be analysed using a spreadsheet if all the data can be entered into the computer system
- available at a suitable price; the benefits of the data must merit the cost of collecting or buying it.
The same criteria apply to information. Throughout this book you will repeatedly see the importance of:
- getting the right information and
- getting the information right.
A manager investigating poor punctuality of trains on a particular line needs information showing all the arrival data on that line. Data on other lines is irrelevant, unless late connections elsewhere are causing the problem. Just as important, the manager must use the data correctly. One day of engineering works will have a major impact on a week's results. Wrongly interpreting the results could identify a problem where no problem actually exists.
Converting information to knowledge
Ultimately the tremendous amount of information that is generated is only useful if it can be applied to create knowledge within the organisation. Building and managing knowledge is one of the greatest challenges that faces organisations in the twenty first century. We hear a lot about the knowledge economy and for many organisations it is their knowledge or 'know how' that defines their competitive advantage.
For more information on this title
This is an excerpt from Making sense of data and information, produced by Elearn Training Company and published by Elsevier; copyright 2007. It is reprinted here with permission.
Read the excerpt to learn about data, information and knowledge, or download a free .pdf of the entire chapter "Defining data, information and knowledge."
There is considerable blurring and confusion between the terms 'information' and 'knowledge'. It is helpful to think of knowledge as being of two types:
- Formal, explicit or generally available knowledge. This is knowledge that has been captured and used to develop policies and operating procedures for example.
- Instinctive, subconscious, tacit or hidden knowledge. Within the organisation there are certain people who hold specific knowledge or have the 'know how' -- "I did something very similar to that last year and this happened….."
Clearly, both types of knowledge are essential for the organisation.
Information on its own will not create a knowledge-based organisation but it is a key building block. The right information fuels the development of intellectual capital which in turns drives innovation and performance improvement.
What does a data quality assessment require?