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Data Envelopment Analysis (DEA) Tool for Benchmarking

Data Envelopment Analysis (DEA) Tool for Benchmarking. DEA is a key benchmarking tool - Multidimensional analytical in nature - Deals with multiple-input, multiple-output productivity ratios.

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Data Envelopment Analysis (DEA) Tool for Benchmarking

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  1. Data Envelopment Analysis (DEA) Tool for Benchmarking

  2. DEA is a key benchmarking tool - Multidimensional analytical in nature - Deals with multiple-input, multiple-output productivity ratios • It supports the identification of Best Practice Units and can help identify those that either need improvement or could be used for benchmarking. • Could be deployed in Internal, Process, Competitive and Strategic Benchmarking. • Offers more insight than a traditional “gap analysis” generally used in benchmarking. • Basic intuition: • - Input/output model formulation that defines the efficiencies of various entities called DMU’s, the decision making units; • - The analytics discriminates the relative efficiencies of various DMU’s; • - Identifies Peers for the inefficient firms, whom they can emulate in order to improve their efficiencies.

  3. Which Unit is most productive?(one input and one output) DMU labor hrs. #cust. 1 100 150 2 75 140 3 120 160 4 100 140 5 40 50 DMU = decision making unit

  4. DMU labor hrs. #cust. #cust/hr Relative Efficiency 1 100 150 1.50 80.21% 2 75 140 1.87 100 % 3 120 160 1.33 71.12% 4 100 140 1.40 74.87% 5 40 50 1.25 66.84% #cust. 200 x slope = 1.87 x x x 100 DMU’s 1,3,4,5 are dominated by DMU 2. x labor hrs. 50 100

  5. PERFORMANCE DATA OF FOUR DMUs (two inputs and one output)

  6. COMPARITIVE PERFORMANCE OF FOUR DMUs COMPARITIVE PERFORMANCE OF FOUR DMUs

  7. COMPARITIVE PERFORMANCE OF FOUR DMUs

  8. B A D (8.5, 11) (1.0, 4.78) (3.0, 7.70) Efficiency Frontier C (.93, 5.57) Capital employed / Value Added Efficiency Frontier O Employee / Value Added

  9. B A D E (8.5, 11) (1.0, 4.78) (3.0, 7.70) (3.69, 4.78) Efficiency Frontier C (.93, 5.57) Capital employed / Value Added Efficiency Frontier O Employee / Value Added

  10. E B A D (3.69, 4.78) (8.5, 11) (1.0, 4.78) (3.0, 7.70) Efficiency Frontier C (.93, 5.57) Capital employed / Value Added Efficiency Frontier Best PossiblePerformance Relative Eff. = ActualPerformance √(3.692+4.782) OB = = = 43.44% √(8.52+112) OE O Employee / Value Added

  11. D E B F A (8.5, 11) (3.69, 4.78) (.93, 11) (1.0, 4.78) (3.0, 7.70) Efficiency Frontier C (.93, 5.57) Capital employed / Value Added Efficiency Frontier O Employee / Value Added

  12. A F G D B E (8.5, 11) (.93, 11) (3.69, 4.78) (3.0, 7.70) (8.5, 4.78) (1.0, 4.78) Efficiency Frontier C (.93, 5.57) Capital employed / Value Added Efficiency Frontier O Employee / Value Added

  13. E F G A B D (3.69, 4.78) (8.5, 4.78) (1.0, 4.78) (8.5, 11) (.93, 11) (3.0, 7.70) Efficiency Frontier C (.93, 5.57) Capital employed / Value Added Efficiency Frontier Best PossiblePerformance Relative Eff. = ActualPerformance √(3.692+4.782) OB = = = 43.44% √(8.52+112) OE O Employee / Value Added

  14. Setting Performance Targets for the Inefficient Firms • Firm B can move up to the efficient frontier in at least three ways: • Reducing only the number of employees: • By moving to the point F • => Input Target for Employees = 0.2 x 0.93 = 0.186 • => Employees Surplus = Current input – Input target • = 1.7 – 0.186 = 1.514 • 2. Reducing only its capital employed: • By moving to point G • => Input Target for Capital = 0.2 x 4.78 = 0.956 • => Capital Surplus = Current input – Input target • =2.000 – 0.956 = 1.244 • 3. (a) Reducing both, the capital employed as well as the number of employees, in the same ratio; or • (b) Enhancing value added only; • By moving to point E

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