This course will introduce participants to the fundamentals of performance measurement, including concepts, metrics, and frameworks. Participants will learn to identify, select, and apply performance measurement tools to improve organizational performance. The course will cover different performance measurement metrics and frameworks, including financial, operational, and balanced scorecards.

• Calculate and interpret common financial ratios.
• Analyze a business's financial statements.
• Evaluate a company's financial performance using market-based measures.
• Compare and contrast the advantages and disadvantages of using accounting and market-based measures for financial performance analysis.
• Identify trends and patterns in a business's financial performance over time.
• Interpret financial performance data in the context of industry benchmarks and competitors.
• Apply critical thinking skills to assess the reliability and validity of financial performance data.
• Synthesize the impact of external factors, such as economic conditions and regulatory environment, on financial performance analysis.
• Define and explain the concept of economic value added EVA.
• Calculate EVA using company financial data.
• Interpret EVA results to evaluate a company's financial performance.
• Compare EVA results to other financial performance measures, such as return on investment ROI and return on equity ROE.
• Evaluate the impact of EVA on a company's financial decision making, such as investment and financing decisions.

• Define and explain the concept of operational performance.
• Identify and define key drivers of operational performance, including quality, dependability, speed, cost, and flexibility.
• Develop and implement metrics to track and measure each driver of operational performance.
• Analyze and interpret operational performance data to inform decision making and continuous improvement initiatives.
• Evaluate the relationships between different drivers of operational performance and the impact on overall performance.
• Apply best practices for data collection, storage, and analysis in operational performance measurement.
• Synthesize the impact of technology and data analytics on operational performance measurement and decision making.
• Evaluate the trade-offs between operational performance drivers, such as cost and quality, in decision making.
• Apply critical thinking skills to assess the validity and reliability of operational performance data.

Profitability and Intellectual Capital:

• Understand the principles of activity-based costing and its application to customer profitability analysis.
• Analyze customer data to identify cost drivers and calculate customer profitability.
• Calculate customer lifetime value using company data.
• Interpret customer profitability analysis results and make recommendations for improvement.
• Develop strategies to maximize customer profitability.
• Define and explain the concepts of customer profitability analysis and customer lifetime value.
• Apply activity-based costing to allocate costs to individual customers and calculate customer profitability.
• Calculate customer lifetime value using company data, including customer acquisition cost and expected customer lifespan.
• Evaluate the impact of customer profitability analysis on sales and marketing strategies, customer retention, and customer relationship management.
• Synthesize the relationship between customer profitability and overall organizational profitability.
• Analyze customer data to identify trends and patterns in customer behaviour and performance.
• Evaluate the trade-offs between serving profitable and unprofitable customers in decision-making.

• Definition and explanation of performance measurement metrics and frameworks
• Different performance measurement metrics and frameworks, including financial, operational, and balanced scorecards
• Relationships between different performance measurement metrics and frameworks and their impact on decision making
• Evaluation of the impact of performance measurement metrics and frameworks on organizational culture, employee motivation, and performance improvement
• Trade-offs between different performance measurement metrics and frameworks in decision making
• Best practices for data collection, storage, and analysis in performance measurement metric and framework selection
• Impact of technology and data analytics on performance measurement metric and framework selection and Implementation
• Purpose and components of the Balanced Scorecard, Performance Prism, SMART Pyramid, and the European Foundation for Quality Management EFQM model

• Managers and supervisors
• Business owners and entrepreneurs
• Financial analysts and accountants
• Operations managers
• Human resource professionals
• Data analysts and data scientists
• Quality control professionals
• Project managers
• Consultants