Managing by Facts

1. Managing by Facts Chapter 18 Achieving Quality Through Continual Improvement Claude W. Burrill / Johannes Ledolter Published by John Wiley & Sons, Inc., 1999 Prepared by Dr. Tomi Wahlström, University of Southern Colorado Chapter 18

2. In God we trust, all others must have data! The Need for Data • Quality cannot be assessed, and quality cannot be improved without having access to relevant data • To judge things impartially and make fair comparisons, it is necessary to have facts - data • Whatever is important is measured, and whatever is measured becomes important Chapter 18

3. Data and Quality • “A requirement for a product must specify not only an attribute or function, but it must also state the standard against which the attribute or function will be judged and the process to be used in measuring the product” - this is where data comes on the scene • Data related directly to the question: • Does the product meet the requirements? Chapter 18

4. Quantitative and Qualitative Data • Data can be: • Quantitative: expressed in numbers • Qualitative: verbal or nonnumeric • Sometimes, it is more practical to work with non-quantified data, since not everything can be reasonably and beneficially quantified Chapter 18

5. Uses of Data • Data is used to: • Manage a process • Cost of quality and allocating resources • Understand a process • Defect is injected to system and quality control system failed to eliminate it • Control a process • Improve a process Chapter 18

6. Collecting Data • Before collecting anything, ask: • What is the purpose of collecting the data? • What data do I need? • How will I collect it? • How will I analyze it? • What conclusions am I attempting to draw? • How will I present those conclusions to achievemy objective? Chapter 18

7. Collection Process • Some points to keep in mind when building a data-collection mechanism: • Understand clearly all uses of data • Organize data collection • Collect data so as to simplify the task of analysis • Keep a clear record of where data came from and important circumstances around it Chapter 18

8. Collection Problems • People forget and later make an estimate • Sometimes it requires ingenuity to collect the data you need • Data accuracy • The need for accuracy depends on the use to be made of the data • Sometimes more important to make sure that data is representative Chapter 18

9. Problems with Data • False data • People lie, deceive, and slant data in their favor especially when data is used to appraise them • Mistaken data • People unaware that they are giving false data • Incorrect data • Unavailable data • Useless data Chapter 18

10. Classification of Data • To understand the underlying message in the data, it needs to be organized, summarized, and interpreted • Classification scheme: collection of subsets that are mutually exclusive and exhaustive • Classification: labeling of the elements according to the classes they belong Chapter 18

11. Schemes for Data Classification • Enumerative (hierarchical) or faceted (synthesized) • What others have done: • Temporal aspects • Location • Characteristic or the defect Chapter 18

12. Questions? Chapter 18

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