1. 1 LECTURE 6 Process Measurement Business Process Improvement 2010

2. Process Metrics Measurement – the act of quantifying the performance dimensions of products, services, processes, and other business activities. Measurement – the act of quantifying the performance dimensions of products, services, processes, and other business activities. Measures and indicators - numerical information that results from measurement Measures and indicators - numerical information that results from measurement –Defects/unit –Errors/opportunity –dpmo

3. Types of Metrics Discrete metric – something that is countable Discrete metric – something that is countable Continuous metric – something concerned with the degree of conformance to specifications Continuous metric – something concerned with the degree of conformance to specifications

4. Effective Metrics SMART SMART –simple, –measurable, –actionable (they provide a basis for decision-making), –related (to customer requirements and to each other), and –timely.

5. 5 Identifying and Selecting Process Metrics Identify all customers and their requirements and expectations Identify all customers and their requirements and expectations Define work processes Define work processes Define value-adding activities and process outputs Define value-adding activities and process outputs Develop measures for each key process Develop measures for each key process Evaluate measures for their usefulness Evaluate measures for their usefulness

6. Dashboards and Scorecards Dashboard – collection of key operational measures Dashboard – collection of key operational measures –Graphs, charts, visual aids –Daily information for management and control Balanced Scorecard – summary of broad performance measures across the organization Balanced Scorecard – summary of broad performance measures across the organization –Strategic guidance

7. Data Collection Key Questions Key Questions –What questions are we trying to answer? –What type of data will we need to answer the question? –Where can we find the data? –Who can provide the data? –How can we collect the data with minimum effort and with minimum chance of error?

8. PRASETIYA MULYA’s ADMINISTRATION TEAM What types of defects/errors might occur? How to measure them?

9. Check Sheets Check sheets are special types of data collection forms in which the results may be interpreted on the form directly without additional processing.

10. Check Sheet Creates easy-to-understand data Creates easy-to-understand data Builds, with each observation, a clearer picture of the facts Builds, with each observation, a clearer picture of the facts Forces agreement on the definition of each condition or event of interest Forces agreement on the definition of each condition or event of interest Makes patterns in the data become obvious quickly Makes patterns in the data become obvious quickly xx xxxxxx x

11. Sampling What is the objective of the study? What is the objective of the study? What type of sample should be used? What type of sample should be used? What possible error might result from sampling? What possible error might result from sampling? What will the study cost? What will the study cost?

12. Sampling Methods Simple random sampling Simple random sampling Cluster sampling Cluster sampling Judgment sampling Judgment sampling

13. Selecting a Sampling Plan A good sampling plan should select a sample at the lowest cost that will provide the best possible representation of the population, consistent with the objectives of precision and reliability that have been determined for the study.

14. Data Classification Type of data Type of data –Cross-sectional —data that are collected over a single period of time –Time series —data collected over time Number of variables Number of variables –Univariate —data consisting of a single variable –Multivariate —data consisting of two or more (often related) variables

15. Sample Statistics Sample Size

16. Problem A utility requires service operators to answer telephone calls from customers in an average time of 0.1 minute or less and either respond to them or refer the customer to the proper department within 0.5 minute. The manager is interested in estimating the actual overall time for both components, in total. A pilot study sample of 30 actual operator times was drawn, and the results are given in the following table. If the service manager wants to be 95 percent confident that the overall time is correctly estimated, with a 3 percent probability of error, what size sample should be taken?

18. Metrology - Science of Measurement Accuracy - closeness of agreement between an observed value and a standard Precision - closeness of agreement between randomly selected individual measurements

19. Repeatability & Reproducibility Studies Quantify and evaluate the capability of a measurement system Quantify and evaluate the capability of a measurement system –Select m operators and n parts –Calibrate the measuring instrument –Randomly measure each part by each operator for r trials –Compute key statistics to quantify repeatability and reproducibility

20. 20 Process Capability The range over which the natural variation of a process occurs as determined by the system of common causes The range over which the natural variation of a process occurs as determined by the system of common causes Measured by the proportion of output that can be produced within design specifications Measured by the proportion of output that can be produced within design specifications

21. Process Capability Study 1. Choose a representative machine or process 2. Define the process conditions 3. Select a representative operator 4. Provide the right materials 5. Specify the gauging or measurement method 6. Record the measurements 7. Construct a histogram and compute descriptive statistics: mean and standard deviation 8. Compare results with specified tolerances

22. Process Capability Index The process capability index, Cp (sometimes called the process potential index), is defined as the ratio of the specification width to the natural tolerance of the process. Cp relates the natural variation of the process with the design specifications in a single, quantitative measure.

23. 23 Calculating Process Capability Indexes C p = USL - LSL 6  C pl, C pu } USL -  3  C pl =  - LSL 3  C pk = min{ C pu =

24. Nominal specification5 Upper tolerance limit6.75 Lower tolerance limit3.25 PROBLEM DATA123456789101112131415 14.924.655.776.255.275.225.475.715.244.425.144.925.794.925.68 24.265.545.264.885.415.384.684.545.585.184.265.783.834.805.74 34.945.004.765.666.025.084.564.174.724.794.715.504.304.754.65 44.295.424.794.444.914.654.704.875.414.735.485.054.785.595.20 55.434.795.034.306.075.114.504.914.654.70 64.816.044.665.474.974.905.244.794.715.50 75.274.475.254.275.515.914.865.744.816.04 84.965.184.464.345.024.664.355.035.324.30 9 10

25. Spreadsheet Template