Information, Analysis, and Knowledge Management in the Baldrige Criteria

1. Information, Analysis, and Knowledge Management in the Baldrige Criteria Examines how an organization selects, gathers, analyzes, manages, and improves its data, information, and knowledge assets. 4.1 Measurement and Analysis of Organizational Performance a. Performance Measurement b. Performance Analysis 4.2 Information and knowledge Management a. Data and Information Availability b. Organizational Knowledge

2. Functions of Information Management • Understand customers needs and customer satisfaction • Provide feedback to workers • Establish a basis for reward/recognition • Assess progress and the need for corrective action • Reduce costs through better planning and improvement

3. Empirical Survey Results(William Schiemann & Associates) • Measurement-management companies are more likely to: • be in top third of industry financially • complete organizational changes successfully • reach clear agreement on strategy among senior managers • enjoy favorable cooperation and teamwork • have more employee empowerment • have a greater willingness to take risks

4. Development of Information • Information is necessary for both control and improvement • Information derives from analysis of data • Data, in turn, come from measurement

5. Process Flow Measurement Data Analysis Information

6. Leading Practices(1 of 2) • Develop a set of key performance indicators (KPI’s) that reflect customer requirements and key business drivers • Use comparative information and data to improve overall performance and competitive position • Involve everyone in measurement activities and ensure that information is widely visible

7. Leading Practices(2 of 2) • Ensure that data are reliable and accessible to all who need them • Use sound analytical methods to conduct analyses and use the results to support strategic planning and daily decision making • Continually refine information sources and their uses within the organization

8. Example: Ritz-Carlton • “We only measure what we must. But, we make sure that what we measure is important to our customers.” • 50% marketing and financial data; 50% quality-related productivity data. • Cost of quality is top priority. Are improvements important to customers, providing a good return, and done quickly?

9. Designing Measurements (Metrics) – APQC (1 of 2) • Plan • How will you use the data? • Have you selected and defined your measures? • Collect • How will you collect the data?

10. Designing Measurements (Metrics) – APQC(2 of 2) • Analyze • How can you ensure that the data will be relevant and believable? • What does the data indicate? • Adapt • How will you communicate your findings? • What kind of action should occur?

11. Types of Measurements • Strategic Measurements • Measure the effectiveness and appropriateness of strategies • Operational (Performance) Measurements • Measure the effectiveness and efficiency of activities

12. Linkages to Strategy Key business drivers (key success factors) Strategies and action plans Measures and indicators

13. Functions of Strategic Measurements • Clarify and translate vision and strategies • Communicate and link strategic objectives and measures • Plan, set targets, and align strategic initiatives • Enhance strategic feedback and learning

14. Balanced Scorecard(Kaplan & Norton) • Financial perspective • Customer perspective • Internal perspective • Innovation and learning perspective Leading measures Lagging measures

15. customer satisfaction rating * * * * * time on hold (telephone) Interlinking • Quantitative modeling of cause and effect relationships between external and internal performance criteria

16. Use of Comparative Data • Comparative data: industry averages, best competitor performance, world-class benchmarks • Helps recognize the need for improvement • Provides motivation to seek improvement

17. Process-Level Measurements • Does the measurement support our mission? • Will the measurement be used to manage change; that is, actionable? • Is it important to our customers? • Is it effective in measuring performance? • Is it effective in forecasting results? • Is it easy to understand and simple?

18. Creating Effective Process Performance Measures • Identify all customers and their requirements and expectations • Define work processes • Define value-adding activities and process outputs • Develop measures for each key process • Evaluate measures for their usefulness

19. Tools for Data Analysis • Statistical summaries and charts • Trends over time • Comparisons with key benchmarks • Aggregate summaries and indexes • Cause-and-effect linkages and correlations (interlinking) • Data mining Basic Advanced

20. Managing Data and Information (1 of 2) • Validity – Does the indicator measure what it says it does? • Reliability – How well does an indicator consistently measure the “true value” of the characteristic? • Accessibility – Do the right people have access to the data? • Security– Do the wrong people have access to the data?

21. Managing Data and Information(2 of 2) • Timeliness – When will the information be available when needed? • Integration – Is it easy to move the data from one system to another? • Modularity– Is it easy to interchange one subsystem to another? • Scalability – Is it easy to adjust the system in response to change in transaction volume?

22. The Cost of Quality (COQ) • COQ – the cost of avoiding poor quality, or incurred as a result of poor quality • Translates defects, errors, etc. into the “language of management” – $$$ • Provides a basis for identifying improvement opportunities and successes/failures of improvement efforts

23. Quality Cost Classification • Prevention • Appraisal • Internal failure • External failure

24. Return on Quality (ROQ) • ROQ – measure of revenue gains against costs associated with quality efforts • Principles • Quality is an investment • Quality efforts must be made financially accountable • It is possible to spend too much on quality • Not all quality expenditures are equally valid