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Advanced Operational Benchmarking

Advanced Operational Benchmarking. Strategic Benchmarking John Paul Professor & Research Fellow BEM School of Management, Bordeaux, France, Managing Director , iCognitive, Singapore. www.icognitive.com. Agenda. Introduction of Traditional Benchmarking

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Advanced Operational Benchmarking

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  1. Advanced Operational Benchmarking • Strategic Benchmarking • John Paul • Professor & Research Fellow BEM • School of Management, Bordeaux, France, • Managing Director, iCognitive, Singapore. • www.icognitive.com

  2. Agenda • Introduction of Traditional Benchmarking • Advanced Operational Benchmarking (AOB) • What is AOB? • Analytical Hierarchy Process (AHP) • Data Envelopment Analysis (DEA) • Result Control Process • AOB Benefits and IT Overview 2 iCognitive

  3. Traditional Benchmarking Supply Chain Operational Reference (SCOR) Model Plan Plan Plan Plan Plan Source Make Deliver Source Make Deliver Source Deliver Deliver Make Source Return Return Return Return Return Return Return Return Suppliers’Supplier Customer’sCustomer Your Company Supplier Customer Internal or External Internal or External Enable SCOR Model Building Block Approach Processes Metrics Best Practice Technology 3 iCognitive

  4. Traditional Benchmarking SCORCard SCOR Level One Metrics Performance results for SEA Pharmaceutical Industry Metrics Calculations 4 iCognitive

  5. Statistical Analysis of Traditional Benchmarking Median Best-in-class • Best-in-Class is based on Pareto’s 80-20 rule • Best-in-Class is defined as the average performance of the top 20% of companies • Median is defined as the average performance of the 40th to 60th percentile of companies 5 iCognitive

  6. Decision Making Support of Traditional Benchmarking • The benchmarking is done based on each metric individually • Not designed to identify a company’s overall performance • Looking at the past 6 iCognitive

  7. Agenda • Introduction of Traditional Benchmarking • Advanced Operational Benchmarking (AOB) • What is AOB? • Analytical Hierarchy Process (AHP) • Data Envelopment Analysis (DEA) • Result Control Process • AOB Benefitsand IT Overview 7 iCognitive

  8. Introduction to Advanced Operational Benchmarking (AOB) • AOB combines the classic benchmarking with advanced mathematical models • Allow company to predict the outcome of an action • Theoretically evaluate various dynamic properties of complex problem 8 iCognitive

  9. Agenda • Introduction of Traditional Benchmarking • Advanced Operational Benchmarking (AOB) • What is AOB? • Analytical Hierarchy Process (AHP) • Data Envelopment Analysis (DEA) • Result Control Process • AOB Benefits and IT Overview 9 iCognitive

  10. Analytical Hierarchy Process - AHP • A popular tool used by decision makers when the choice of • alternatives is influenced by both quantitative and qualitative • data. • Capture both subjective and objective evaluation measures 10 iCognitive

  11. AHP Implementation in AOB • Step 1: Determine the criteria factors and the • alternatives • Step 2: Hierarchy of decisions and establish priority • Step 3: Pairwise comparison Scale • Step 4: One-One Comparison • Step 5 : AHP Results 11 iCognitive

  12. AHP Implementation in AOB • AHP results by Performance attribute classification 13 iCognitive

  13. Agenda • Introduction of Traditional Benchmarking • Advanced Operational Benchmarking (AOB) • What is AOB? • Analytical Hierarchy Process (AHP) • Data Envelopment Analysis (DEA) • Result Control Process • AOB Benefits and IT Overview 14 iCognitive

  14. Data Envelopment Analysis - DEA 15 iCognitive

  15. Data Envelopment Analysis - DEA • DEA Frontier and CRS model Criteria B Extreme Limit in The Market – The Frontier Input oriented CRS model θ*= Min θ ∑ λjxij ≤ θxioi= 1,2,….,m; ∑ λjyrj ≥ yior= 1,2,….,s; λj≥ 0 Criteria A 16 iCognitive

  16. DEA – Implementation in AOB • Step 1: Defining Inputs and Outputs • Inputs and outputs are selected base on high level that has direct impact on Supply chain operations and profitability. 17 iCognitive

  17. DEA – Implementation in AOB • Step 2: Actual and Targets( based on Hypotheticall Efficient DMU) 18 iCognitive

  18. DEA – Implementation in AOB • Step 3: Model Results for growth and operational Efficiencies • CRS Input oriented model is used • Company D is the relatively most efficient • company in terms of growth • Companies need to reduce their inputs • or improve their outputs to achieve • higher efficiency • Potential targets are set for each inefficient • company 19 iCognitive

  19. Agenda • Introduction of Traditional Benchmarking • Advanced Operational Benchmarking (AOB) • What is AOB? • Analytical Hierarchy Process (AHP) • Data Envelopment Analysis (DEA) • Result Control Process • AOB Benefits and IT Overview 22 iCognitive

  20. Result Control Process • Implementation Steps • Process review • to clearly identify and analyze the overall • benchmarking by using data input from previous • models. • Evaluation model and interpretation • It reflects the current strategic positioning of the company within the overall industry • Recommendation based on decomposition • It identify improvement directions and set the base for future design. 21 iCognitive

  21. Result Control Process • Bi-Directional Analysis 22 iCognitive

  22. Result Control Process • Bi-Directional Analysis 23 iCognitive

  23. Agenda • Introduction of Traditional Benchmarking • Advanced Operational Benchmarking (AOB) • What is AOB? • Analytical Hierarchy Process (AHP) • Data Envelopment Analysis (DEA) • Result Control Process • AOB Benefits and IT Overview 24 iCognitive

  24. AOB Benefits • Measure Effectiveness and Efficiency AOB 25 iCognitive

  25. AOB Benefits • Measure Effectiveness and Efficiency 26 iCognitive

  26. AOB IT Overview AHP one- one comparison Grade engine Industry Range EME (effectiveness measurement Engine) Extreme Limit in The Market – The Frontier Scipo Application server Scipo Web server Effectiveness Results Scipo Data Mart Enterprise Information Systems Server-side Data Access Server-side Business Logic Server-side Presentation SCHEM Tool Client-side Presentation ASPX Reports ETL (Extract, Transform, Load) Scor metrics Logic ASP & ASPX pages SAP R/3 SQL server ASPX Reports Performance Targets Input & Outputs Databases Enterprise Applications SCIPO Efficiency Measurement DEA Models Efficiency Results SCIPO : Supply Chain Information Portal SCHEM: Supply Chain Effectiveness Measurement Joe ZHU DEA Excel Solver 27 iCognitive

  27. iCognitive Thank You! Q&A!!! john.paul@icognitive.com suresh.indukuri@icognitive.com www.icognitive.com 28 iCognitive

  28. Backup Slides john.paul@icognitive.com suresh.indukuri@icognitive.com www.icognitive.com iCognitive

  29. Traditional Benchmarking SCOR Level One Metrics Back iCognitive

  30. Traditional Benchmarking Typical SCORCard Back iCognitive

  31. Traditional Benchmarking South East Asia Pharma SCORCard Scope for Improvement BIC Back iCognitive

  32. Traditional Benchmarking Metrics Calculations Cost Asset Management Profitability Cost of Goods Sold: Operating expenses: Operating income: Return on Assets: Net profit (after tax) : Days of Sales Outstanding: Inventory Days of Supply: Days of Payables Outstanding: Cash-to-Cash Cycle Time: Asset turns : [operating income] / [total gross annual sales]  result = percentage [total annual cost of goods sold] / [total gross annual sales]  result = percentage [5 point annual average of gross accounts receivable (AR)] / [total gross annual sales / 365]  result = time (in days) [5 point annual average of gross value of inventory at standard cost] / [annual cost of goods sold (COGS) / 365]  result = time (in days) [Asset turns] * [Net profit – Sales]  result = percentage [operating expenses] / [total gross annual sales]  result = percentage [net profit after tax] / [total gross annual sales]  result = percentage [5 point annual average of gross accounts payable (AP)] / [total gross annual material purchases / 365]  result = time (in days) [inventory days of supply + days of sales outstanding – days of payables outstanding]  result = time (in days) [total gross annual sales] / [total net assets]  result = turns per year Back iCognitive

  33. AHP Implementation in AOB • Step 1: Determine the criteria factors and the alternatives 11 iCognitive

  34. AHP Implementation in AOB • Step 2: Hierarchy of decisions and establish priority Select the best company with overall supply chain and business excellence Cost Asset Management Profitability Cash-Cash Cycle time Asset Turns Operating Income Return On Assets Cost of Goods Sold Net Income (Profit) Inventory Days Of Supply Operating Expenses D of Payables Outstanding D Of Sales Outstanding Cogs Operating Expenses Cash-Cash Cycle Time One-One comparison between each alternatives is done for each criteria . Only one example (cost of goods sold) is shown due to space constraint. Company A Company D Company B Company C Company E Company F Company G Company I Company J Company K Company L Company M Company N Company O Company H 12 iCognitive

  35. AHP Implementation in AOB • Step 3: Pairwise comparison Scale • A core characteristic of AHP model – allow to solve qualitative decision by using quantify technique • The approach is to identify how important one criteria compare to another one is 13 iCognitive

  36. AHP Implementation in AOB • Step 4: One-One Comparison ex: Cost of Goods Sold 14 iCognitive

  37. DEA – Implementation in AOB • Step 2: Model Overview iCognitive

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