Tqm ch 03

1 THE MANAGEMENT AND CONTROL OF QUALITY, 5e, © 2002 South-Western/Thomson LearningTM

Chapter 3Chapter 3

Information Analysis and Information Technology


Information Analysis And Information Technology

• Quality programs are dependent on good information systems, chief information officers have the opportunity to plan an intergal and highly visible role in shaping the quality of the corporation.

• The Information Analysis Category examines an organization’s information management and performance measurement systems and how the organization analyzes performance data and information.

1 Measurement and Analysis of Organizational Performance 2 Information Management( Data Availability, Hardware and Software)


Reasons of Implication• If you don’t measure results, you can’t tell

success from failure

• If you can’t see success, you can’t reward it – and if you can’t reward success, you are probably rewarding failure

• If you can’t recognize failure, you can’t correct it


Organizational Implication


Decision MakingDecision Making

• The ability to how quickly decisions are made, communicated, and carried out at all levels, for this it is very important how efficiently information will exchange with subordinates, peers, customer, suppliers or bosses. Effectiveness of decision making are essential for competitive advantage.


Process Flow

Measurement

Data

Analysis

Information


CustomerRequirements

Measurements

Processes ResultsDesign

Control

Prediction

Validation

Use of Information and Analysis

Measurement supports executive performance review and daily operations and decision making.


Benefits of Information Management

• Understand customers 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


Empirical Survey Results

• Measurement-management companies are more likely to:– be in top third of industry financially– complete organizational changes successfully– reach clear agreement on strategy– enjoy favorable cooperation and teamwork– have more employee empowerment– have a greater willingness to take risks


Example: Federal Express

• “We measure everything. Then…we prioritize what processes are key to the company.”

• Most data collection systems are automated, making it fast and easy.

• Seeks internal measures that are predictors for external measures.


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?


Leading Practices (1 of 2)

• Develop a set of performance indicators 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


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


Balanced Scorecard

1. Financial perspective

2. Internal perspective

3. Customer perspective

4. Innovation and learning perspective

Leading measures

Lagging measures


Key Types of Business Performance Measures

• Customer satisfaction measures• Financial and market performance

measures• Human resource measures• Supplier and partner performance

measures• Company-specific measures


Example: Wainwright Industries

• Safety

• Internal customer satisfaction

• External customer satisfaction

• Six sigma quality (manufacturing defects)

• Business performance


Common Quality Measures

• Nonconformities (defects) per unit

• Errors per opportunity

• Defects per million opportunities (dpmo)


Importance of Comparative Data

• Comparative data: industry averages, best competitor performance, world-class benchmarks

• Helps recognize the need for improvement

• Provides motivation to seek improvement


Linkages to Strategy

Key business drivers (key success factors)

Strategies and action plans

Measures and indicators


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?


Creating Effective 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


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 success of improvement programs


Quality Cost Classification

• Prevention

• Appraisal

• Internal failure

• External failure


Quality Cost Management Tools

• Cost indexes

• Pareto analysis

• Sampling and work measurement

• Activity-based costing


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


Managing Data and Information

• 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?


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


Interlinking

• Quantitative modeling of cause and effect relationships between external and internal performance criteria

customersatisfactionrating

time on hold (telephone)

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Tqm ch 03

Education

control of quality

sigma quality

cost of quality

comparative information

information sources

information analysis

internal measures

external measures