The information age was born in 1946 when the ENIAC1 came online. That was just before Deming went to Japan in what was to prove a turning point in the industrial age. The quality revolution ushered in the maturing of the industrial age through quality principles applied to manufacturing. The resulting elimination of waste and increased focus on customer needs have decreased the costs of doing business and increased business effectiveness and customer satisfaction.
During the same half century, however, the information age has changed how work is performed from manual labor to intellectual work at all levels in the enterprise. But the same information technology has been used in ways that have introduced unnecessary complexity and waste while automating the manual processes of the industrial age.
Naisbitt correctly states that, "In the new information society, that key resource has shifted to information, knowledge and creativity."2 The quality principles Deming, Ishikawa, Juran, Crosby, Imai and others have applied to improve product quality have not been applied to information. These same quality principles, proven over the last fifty years, apply directly to the improvement of information quality, the new "currency."
Without quality information an organization cannot thrive:
- Two 20-year-old "calculation errors" for pension withholding left Los Angeles County with $1.2 billion in unforeseen liabilities and will force the county to spend an additional $25 million a year to make up for insufficient contributions to the fund (Los Angeles Times, April 8, 1998).
- Wrong price data in retail databases costs American consumers $2.5 billion in annual overcharges (Information Week, September 14, 1992).
- A $2 billion company discovered it was not invoicing four percent of its orders, leaving $80 million in uncollected revenue.
- In August 1997, Hudson Foods lost its largest customer, Burger King, due to E. coli bacteria contamination that caused several illnesses. The plant had two problematic practices: poor record-keeping and the mixing of one day's leftover hamburger into the next day's production. The information quality problem of not knowing which batches were mixed caused the largest meat recall in U.S. history: 25 million pounds. Without its largest customer, Hudson Foods was not able to be profitable, having to sell the plant. The rest of Hudson Foods was subsequently acquired by Tyson Foods (The Tennessean, August 24, 1997).3
The bottom line is that data quality problems hurt the bottom line.
What is Information Quality
Quality is "consistently meeting customer expectations." Knowledge workers those who use information to perform their work are information "customers." Information quality is "consistently meeting knowledge worker and end-customer expectations."4 Figure 1 describes the general expectations of the information required to perform work.
|Figure 1: Information Quality Characteristics |
Information is not a byproduct, nor documentation. It is a direct product of processes that capture knowledge about the persons, places, things and events discovered while conducting business transactions.
Shoshana Zuboff describes the duality of information technology with the notion that it does not just automate activities. It also "produces" information and has coined the term informate to describe this capacity.5
Business processes that plan, design, manufacture, market, sell and distribute goods and services, and that operate the business are the processes that produce information. If electronically collected information has quality and is sharable, it can add high value.
For information to have quality it must be produced according to a well-defined information product specification in the same way manufactured products are produced according to specs. What is the definition of the data discount rate: the percent or amount of discount from the sale price? What are valid values: 10 percent or 0.10? What business rules govern it: apply it before tax or after tax?
Information customers need to understand the meaning of data in the same way products have an owner's manual to describe a product's use. Many costly business errors come from having different interpretations. The space probe that crashed into the back side of Mars on September 23, 1999, was placed into the wrong altitude orbit around the planet when an engineering team (information producers) sent data in English units that NASA navigators (information customers) interpreted as metric measurements.
The information supplier role applies to the person whose work causes knowledge to be created or updated. Information producers are those who create ideas or designs, as in a new product developer, or who are points of contacts for knowledge exchange, such as when an order representative "takes" an order from a customer.
Virtually everyone in the enterprise, whether a machine operator, an executive manager or a clerk who deals with customers, plays both roles. They use some information (as knowledge workers) to produce new information (as information producers).
Some business roles do not produce information, but they transcribe it from one form to another, such as when someone takes a customer-completed order form and enters it electronically into a database. This "data intermediary" role does not create the data content, but only puts it into a form that others (information customers) can use. Such intermediary processes add an additional point of information handling that can cause delay (called information float) and an additional point in which data translation and transposition errors can be introduced. A major problem in intermediary processes exists when application edits find anomalies, but the intermediary is not able to correct them because they are not at the point of knowledge. This requires information scrap and rework to correct the data not created properly on the original form.
Another role is that of the process owner. Every manager who manages processes that create or update data has accountability not just for the process integrity, but also for the quality of the products produced whether tangible products or information products.
The supplier-customer relationship is business to business. Process owners are not accountable for the process to up-line management. They are accountable to downstream process owners who depend on that information. As Ishikawa says, "The next process is the customer."6
The information resource has two distinctions that demand understanding and attention at all levels in the organization:
- Information is intangible and nonconsumable. As such it has not been taken as a serious object for management. With every other resource, managers are held accountable. Few organizations have information quality accountability written into a manager's job description.
- Information is the resource required to manage every other enterprise resource. Data is the electronic representation of objects and events the enterprise must know about and manage. Financial management is not managing currency; it is managing the information about the enterprise's financial assets.
There are two messages here:
- If information is used to manage all the other resources of the enterprise, shouldn't we be managing information as a business resource? "Managing information as a by-product will not work."7 You must apply the same principles to information as you apply to other resources: a) planning a well-defined data architecture like a blueprint and designing databases to support all knowledge worker requirements; b) leading and directing with information policies and data standards, and holding managers accountable for information just as they are accountable for financial and people resources; c) controlling costs by not developing redundant applications and databases; d) organizing with a strong information management function that provides leadership and direction, facilitates information planning and implements controls to assure quality information production.
- If inaccurate and missing information causes processes to fail and increases costs of information scrap and rework that squanders all the other resources, shouldn't we be applying information quality management principles to information?
If you are not managing your information, you are not managing your business.
- Electronic Numerical Integrator and Calculator.
- Naisbitt, John and Aburdene, P. Re- inventing the Corporation. New York. Warner Books. 1985. P. 5.
- English, Larry P. Improving Data Warehouse and Business Information Quality. New York. John Wiley & Sons. 1999. PP. 7-12.
- English, Larry P. "Data Quality: Meeting Customer Needs." DM Review. November 1998. P. 46.
- Zuboff, Shoshana. In the Age of the Smart Machine: The Future of Work and Power. New York. Basic Books. 1988. P. 10.
- Imai, Massaki. Gemba Kaisen. New York. McGraw-Hill. 1997. P. 44.
- Huang, Kuan-Tese. Lee, Yang and Wang, Richard. Quality Information and Knowledge. Upper Saddle River. Prentice-Hall. 1999. P. 21.
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