Information Presentation Quality
“Information Presentation Quality Characteristics”
This blog is the third and last of a series of blogs on the critical-to-quality characteristics of information quality required to achieve Total Information Quality Management. For information to have quality to knowledge workers:
- It must be clearly defined so knowledge workers understand its meaning
- It must be complete, accurate, and consistent across all data stores
- It must be accessed and presented in a timely basis, and in an unbiased way that reveals the truth, so that the knowledge workers can take the right action or make the right decision (more…)
Information Content Quality
Information Content Quality Characteristics Larry English
One of the root causes of poor quality information is defects in the data definition, specifically the “information product specifications.” Because information is a product of our business, manufacturing and service processes, the analogy of an “information product” is real, and the requirement for quality in “information product specifications” is a critical requirement for Information Quality.
This blog is the second of a series of three blogs on the critical quality characteristics (or measures) of information quality required on the TIQM Quality System.
- Information Product Specification Data Quality
- Information Content Quality
- Information Presentation Quality
Information Content Quality Characteristics
- Information standards
- Data names
- Data definitions
- Attribute valid value set or range of values
- Value format for structured attributes (VIN, SSN, Product Codes)
- Business rule specifications of constraints on data
- Information Steward accountable for data definition quality
Information Content Quality Characteristics: The major information
content (data values) quality characteristics
include:
- Definition conformance. Data values are consistent with
the attribute (fact) definition - Completeness. Each process or decision has all the information
it requires- Record completeness. A record exists for every real world object or event the enterprise needs to know about
- Value completeness. A given data element (fact) has a value stored for all records that should have a value
- Validity. Data values conform to the information product specifications
- Value validity. A data value is a valid value or within a specified range of valid values for this data element
- Business rule validity. Data values conform to the specified business rules
- Derivation validity. A derived or calculated data value is produced correctly according to a specified calculation formula or set of derivation rules. If the base values are accurate, and the calculation is correctly performed, then result will be Accurate
- Accuracy. Data values are correct.
- Accuracy to surrogate source. The data agrees with an original, corroborative source record of data, such as a notarized birth certificate, document, or unaltered electronic data received from a party outside the control of the organization that is demonstrated to be a reliable source
- Accuracy to reality. The data correctly reflects the characteristics of a real-world object or event being described. Accuracy and precision represent the highest degree of inherent information quality possible
- Precision. Data values are correct to the right level of detail, such as price to the penny or weight to the nearest tenth of a gram
- Non-duplication. There is only one record in a database representing a given real-world object or event
- Source quality warranties/certifications. The source of information: (1) guarantees the quality of information it provides with remedies for non-compliance; (2) documents its certification in its information quality management capabilities to capture, maintain, and deliver quality information; or (3) provides objective and verifiable measures of the quality of information it provides in agreed-upon quality characteristics
- Equivalence of redundant or distributed data. Data in one database is semantically equivalent to data about the same objects or events in another database
- Concurrency of redundant or distributed data. The information float or lag time is minimal between (a) when data is knowable created or changed) in one database to (b) when it is also knowable in a redundant or distributed database, and concurrent queries to each database produce the same result
For more about Information Content Quality, see Chapter 6, “Assessing
Information Quality,” in Improving Data Warehouse and Information Quality.
This contains a more comprehensive list of quality characteristics with examples.
It also describes how to measure these quality characteristics. The next blog
will discuss information presentation quality characteristics required for the
finished Information Product presented to the knowledge workers.
What do you think? Share your experiences in measuring information content
quality, especially accuracy.
IQ and Information Product Specifications Quality
One of the root causes of poor quality information is defects in the data definition, specifically the “information product specifications.” Because information is a product of our business, manufacturing and service processes, the analogy of an “information product” is real, and the requirement for quality in “information product specifications” is a critical requirement for Information Quality.
This blog is the first of a series of three blogs on the critical quality characteristics (or measures) of information quality required to achieve Total Information Quality Management.
- Information Product Specification Data Quality
- Information Content Quality
- Information Presentation Quality
What constitutes the “Information Product Specifications” data?
• Information standards
• Data names
• Data definitions
• Attribute valid value set or range of values
• Value format for structured attributes (VIN, SSN, Product Codes)
• Business rule specifications of constraints on data
• Information Steward accountable for data definition quality
(more…)
Hospital Billing Errors ‘Kill’ Patients
Hospital billing mistakes have become so prevalent that a niche industry has evolved to help patients decipher their bills and help correct the errors. ”Pat Palmer, founder of Medical Billing Advocates of America, estimates that she finds multiple errors in 8 out of every 10 hospital bills she reviews” (Dina ElBoghdady, “Killer Billing Errors,” Washington Post, June 27, 2004, p. F01. Accessed Aug 9, 2007 at: http://www.washingtonpost.com/wp-dyn/articles/A7351-2004Jun26.html ).
One patient saw the bill of $25,652.14 for her 2-hour routine operation, reduced to a cost of $17,000 billed to the insurance company and her cost reduced to $2,148, after correcting errors and overcharges.
While this error-rate was not statistically measured, nor would it apply to all hospital bills, it points out a huge problem in Information Quality in the health care system, not counting actual medical errors caused by information defects.
The consequence of health care over billing is significant. It contributes to the high costs of health care, which is one major cause of personal bankruptcy.
(more…)
Information Quality & Management Transformation
I recently received an email from one of my early clients. After having worked in four different companies in four different industries, she came to a sad conclusion, writing:
“The thing that they all have in common is a desire to cut corners and deal with quality later. It takes a lot of energy to be the information quality cheerleader, and I find it discouraging and overwhelming at times. Keep writing your articles and books to encourage all the people like me who are dealing with these issues every day.” P. G.
The discovery that P. G. has experienced is, unfortunately, the norm—not the exception. There are two critical elements in this experience.
IQ in Internet and e-Business Information
“In e-Business, the Information IS the Business”
Having just completed writing a chapter on “IQ in the Internet and e-Business Environments” in my forthcoming book, Information Quality Applied: Best Practices for Improving Business Information, Processes and Systems (John Wiley & Sons), I wanted to share a few excerpts from this chapter. This is one of ten chapters focused on applying sound quality principles to the unique quality issues in various information value “circles” such as “Prospect to Satisfied Customer,” “Order to Cash” Supply chain, for example.
There are three categories of information in the Internet environment to which quality principles must be applied:
* Web-Based Documents and Web Content
* Data “Shared” by Internal Processes and Internet Processes
* Information Collected or Created in e-Commerce and e-Business value chains, including third party business partners
The major problem with IQ in the Internet is that business is conducted in “cyberspace” with no person “minding the store” or monitoring the e-Business transactions.
Here I will address some problems and improvements in the first category.
(more…)
IQ Lessons Learned: Consumer Reports Recalls Faulty Car Seat Study
IQ in the News
Most people have probably heard about the highly reputable Consumer Reports’ recall of its flawed testing of infant car seat safety. The report, issued January 5, 2007, found that many car seats failed the high-speed side impact test it conducted (the government requires passing of frontal crashes of 30 mph. Consumer Reports tested at 35 mph for frontal crashes and 38 mph (so they thought) in side impact crashes. The findings seemed to indicate a high degree of failure with nine failing some or all of the crash tests, and only two doing well in all tests.
However, the government found a problem with the way the testing was conducted. Instead of a 38 mph side crash, the test simulated a side-impact crash of over 70 mph with very inconsistent results that would have come from 38 mph tests. Consumer Reports recalled the entire report January 18.
IQ Lessons Learned From the Consumer Reports Recall:
Negative impact on consumers and their confidence in the organization:
- The impacts of the faulty testing where dramatic and swift. The Executive Director of the Washington State Safety Restraint Coalition exclaimed that “Consumer Reports screwed up….They really upset people and created enormous confusion.”
- When designing tests, as you will with IQ assessments, you must assure you design the tests properly. Measuring validity and accuracy are two distinctly different measurements. You can test validity by defining the business rules, valid values or ranges the data must conform to, and conduct these tests electronically with IQ assessment software or your own validity routine tests.
But to measure accuracy, you must confirm the data values correctly correspond to the characteristic of the real world object or event, the data represents. To perform this test, you must compare the data with the characteristic of the real world object itself.
In the case of car seats, Consumer Reports believes, rightly as I believe, that crash tests should be conducted at high speeds, more representative of actual accident experience.
- When you make a mistake, own up to it and apologize for it. Then do everything you can to ameliorate the error and its impact.
Consumer Reports retracted the report as soon as they determined the serious problem with the study.
Jim Guest, President of Consumer Reports, wrote, “A message to our readers” on the Consumer Reports home page, with important messages to his customers, “I took action when we discovered a mistake in our side-impact crash tests.” “We strive to be accurate and fair, and I regret this error. I want to make sure that our actions are as thorough and transparent as possible so that we preserve your trust as we continue to test, inform, and protect consumers.”
- When you have IQ problems, but must have accurate and complete data, you must pay the price of the process failure and the costs of “information scrap and rework.” Consumer reports is retesting all of the infant car seats to provide the comparable data.
- “Reputation” of an information provider is not a guarantee of the quality of information provided. Even the best make mistakes.
One must error-proof its processes based on root cause of failure. A better measure is the reliability of the processes to provide consistent, quality information based on the kinds of error-proofing provided and consistency of the process results.
- When you have a significant IQ problem, you must analyze the root cause(s) and improve the process to prevent the root cause(s) from causing failure again.
Consumer Reports will be conducting extensive analysis as to what went wrong in these tests to assure they will not recur. This is the same approach when we find critical IQ problems. We must conduct root cause analysis, find the root causes and improve and verify the efficacy of the improvements to prevent defect recurrence.
What do you think?
Treat Your Information Customers Well
By this time, most of us have already broken the New Year resolutions that we have made. Whether or not this has been your case, let me propose a “better-late-than-never” resolution that can make all the difference in your own career:
Seek out one of your internal “Information Customers,” someone who depends on the information you create, whatever it is. Ask them how well the information meets their needs to perform their work properly the first time. Is it complete? Is it accurate? Is it timely? Is it presented clearly and understandably?
If it does not meet their needs completely, analyze the root cause. Hint, ask “Why?” five times to get back to the root cause. Then analyze and improve the process causing the missed requirement in a way to prevent future recurrences.
Having done this, you will probably have “delighted” your Customer, encouraging them to do the same.
PS: Document the impacts of the improvement in terms of saved time and materials and other costs of “information scrap and rework” you will have accomplished.
This is how you can change your company forever, one improvement at a time.
What do you think? Let me hear from you about your experience.
Information Quality and Accountability
All he wanted for Christmas was anything but what he got. Jeffrey Skilling, former Enron CEO moved to his new residence at the Federal Correctional Institution in Waseca, Minnesota, where his sentence calls for him to live for the next 24 years for his role in fraud, conspiracy, insider trading and other crimes leading to the collapse of Enron. These crimes led to the loss of thousands of jobs, more than $60 billion in company stock and more than $2 billion in employee pension plans.
But Mr. Skilling will have a new job as well. He will probably work as a food service helper, painter or plumber. While this is not the cush job he had as CEO at Enron where he earned $151.7 million over the three years during the time he perpetuated his fraud, he will get from 14 to 40 cents per hour. At the top pay, Skilling could earn $832 per year. At that rate it would take 74.5 million years to pay back the stock and pension losses he foisted on the stakeholders.
So what is the point here? (more…)
The Gift of High Quality Information
What would happen if your knowledge workers returned from the holidays and when they “opened” their data marts, they found nothing but high quality information? No missing information to have to hunt for. No wrong information to have to correct. No misleading information to cause them to make the wrong decision.
Imagine what it would be like if people could do their value work without hunting for, correcting, or recovering from failure caused by poor quality
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