1. 1. Demand Driven MRP Case Studies Erik Bush CEO, Demand Driven Technologies
2. 2. Objective of this presentation Provide an inside look at 3 successful Demand Driven MRP implementations Highlight how specific attributes of DDMRP are used to address a wide range of user environments
3. 3. Agenda Amore Pacific Satuerca StemCell
4. 4. Amore Pacific
5. 5. Together We Can AMORE PACIFIC
6. 6. 6 Index Part 1 : About AMORE PACIFIC Part 2 : SCM History of AMORE PACIFIC Part 3 : Lunching DDMRP Part 4 : Results & Lessons Learned
7. 7. Our Brand : Beauty & Health History of Endless pursuit for beauty 1930193019301930---- Mother, the root ofMother, the root ofMother, the root ofMother, the root of AMOREPACIFICAMOREPACIFICAMOREPACIFICAMOREPACIFIC 1960196019601960---- Start of doorStart of doorStart of doorStart of door----totototo----doordoordoordoor sales systemsales systemsales systemsales system Category diversificationCategory diversificationCategory diversificationCategory diversification (make(make(make(make----up, personal care)up, personal care)up, personal care)up, personal care) IPOIPOIPOIPO 1980198019801980---- Reshaped labor relationsReshaped labor relationsReshaped labor relationsReshaped labor relations Corporate restructuringCorporate restructuringCorporate restructuringCorporate restructuring Intensified competition andIntensified competition andIntensified competition andIntensified competition and sales channelsales channelsales channelsales channel diversificationdiversificationdiversificationdiversification (Dep. store, Specialty store)(Dep. store, Specialty store)(Dep. store, Specialty store)(Dep. store, Specialty store) 2000200020002000---- Global expansionGlobal expansionGlobal expansionGlobal expansion
8. 8. 8 29 Brands : across all categories in Beauty & Health Skin Care, Make-up, Fragrance, Hair Care, Body Care, Oral Care, Green Tea, Beauty Food
9. 9. 9 Part 2. SCM History of AMORE PACIFIC SCM Strategy & IT System History 1996 2002 2007 2014 Excel Base MRP System MRP System developed by COBOL Lunch SAP R3 ERP Add on SAP APO Module Implement DDMRP R+ System Weekly Cycle Product planning Reduce lead time, Setup time, Lotsize Increasing frequency of order flexibility Synchronizing Demand planning Strong network with Supplies Share all of Information Operation Excellence Decouping Demand planning Independent of purchasing Available of stock
10. 10. Good forecasting? Sales Forecast : The accuracy of M+3 forecast is less than 10%. Purchasing team could not depend on the sales forecast, used only as a reference. Best policy of purchasing department : Try to reduce the lead time because the accuracy of short term forecast is high. [ Accuracy of Sales Forecast]
11. 11. 11 Part 3. Lunching DDMRP [ 30 ] The Five Components of DDMRP Demand Driven Material Requirements Planning Strategic Inventory Positioning 1 Buffer Profiles and Levels 2 Dynamic Adjustments 3 Demand Driven Planning 4 Visible and Collaborative Execution 5 Modeling/Re-modeling the Environment Plan Execute
12. 12. 12 Product BOM Raw material, component package material, bulk
13. 13. HubPack BulkWeig htingRaw C.P Supplier's Amore pacific Injecti on W/H Buffering in front of the suppliers drum work center andAPs warehouse Reduced the finished goods L/T Strategic Inventory Positioning W/H Decor ation 3days3days 14days 7days
14. 14. All parts Stocked () Non-Stocked () Replenished Replenished Over-ride Min-max Non-buffered Lead Time Managed DDMRP Part type Raw materials Packing materials Buying goods Non Stocked Non-Buffered N/A Short L/T, 80% items(cheap, easy) All Lead Time Managed N/A N/A N/A Stocked Min-Max Outside stored Bulk raw material N/A N/A Replenished All items except Min-Max parts Long L/T, top 20% items All imported tube All items of glass Other Strong items - Injection, Pumps, tubes, single box, tray, etc Some items of large supply variability (suppliers capacity limit, etc) Replenished _override New items expected to be used the Replenished method
15. 15. Red Zone Base Red Zone Safety Yellow Green Step 2: Buffer profile Implementation division : cosmetic plant all of raw material 100%(about 1500 items) some of long LT packing materials (about 300 items) Lead Time Lead Time Variability Long/High 30% 80% Medium 50% 50% Short/Low 80% 30% ADU : Past 90 days Spike Order : Demand plan of 2~5 times Lead time MOQ : Packing unit as a multiple
16. 16. Step 3 : Dynamic Buffer Management Decided to utilize adjustments to Lead Time to flex buffer instead of using Planned Adjustment Factor Seasonality :Addressing Chinese New Year Adjusted lead time from 90 days to 120 days to increase yellow zone size Items supplied from China Worked well only 3 days of shortage
17. 17. 17 Utilization of lead time adjustments to address Chinese New Year Delivery has delayed : 60K Standard Lead time increased from 90days to 120days One supply order wasnt delivered on time But its ok buffer was able to absorb the impact
18. 18. ResultsResultsResultsResults 1. Raw materials Reduce the Inventory level 20 % Reduce the load of order management 30% 2. Packing materials Service level (purchasing response rate 60% -> 90%) Imported packing materials : Service level 99% Possible to share the long term purchasing plan with supplier
19. 19. Result Reduce Raw material inventory & work load
20. 20. Result Component packaging material On time delivery has improved Major improvement in only 2 months stabilized
21. 21. 21 Closing The Meaning of Implement the DDMRP with TOC concept? => Change the planning paradigm change from point to range estimation at the same confidence level => Change the planning paradigm from forecast and inventory precision to establishing appropriate buffer ranges trust the system Sales forecast, S&OP : mixed use with a valid technique Started small and built confidence as results were achieved
22. 22. Satuerca
23. 23. March 27th, 2015 Presented at the Demand Driven World Conference Houston, TX
24. 24. SATUERCA ACTIRO ESTAMCAL MECANIFRAN 24 INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS Founded in 1967 Horizontal forging (parts between 50g and 2kg) Machining Focused on the automotive supply sector 2 factories located in Spain and 1 in Romania 135 workers 15,000 m2 between the 3 factories Founded in 1967 Horizontal forging (parts between 50g and 2kg) Machining Focused on the automotive supply sector 2 factories located in Spain and 1 in Romania 135 workers 15,000 m2 between the 3 factories
25. 25. Our productsOur products 25 Gears Clutch Bodies Cams Bearings Nuts INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
26. 26. Special Nuts Cams 26 Our productsOur products Gears Bearings Clutch bodies INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
27. 27. 27 Why DDMRP?Why DDMRP? PLANNING Critical process Situation description Customer forecast/orders varying even on due date Delays of raw material deliveries Daily consumption from consignment stocks Planning history Until 2012, planning was dependant on a single persons analysis From 2012 to 2013 use of Excel September 2013 until present day: DDMRP Methodology applied Necessities Methodology to manage this information on a daily basis: Stock levels Detection of new Work Orders (WO) requirements New raw material purchase requirements Which raw material Open Supply orders need to be controlled In Process WO that need to be expedited INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
28. 28. 28 Changing to DDMRPChanging to DDMRP 1st- Strategic Inventory Positioning 2nd- Buffer profiles and Level Determination 3rd- Dynamic Buffers 4th- Demand-Driven Planning 5th- Execution DEMAND ANALYSIS Change in the way DEMAND is understood Forecast/Orders beyond a reliable horizon are no longer taken into account Only committed orders (date and quantity) are considered DEMAND INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
29. 29. 29 CUSTOMER B RESULTS: Bad forecasts meant that stock was out of control, what was needed wasnt available and the forged parts were no longer required Urgencies in both factories The forecast for the next three weeks was the input to start the forging process 2 weeks later, when the forged parts were delivered to Mecanifran, a new forecast would tell us whether they were then required for the next process. INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS BEFORE
30. 30. NOW 30 RESULTS: Buffers controlled in every strategic position LT reduction of 50% (from 20 to 10 days) Stock reduction ( 3,700,000 parts to 2,700,000 parts 35% in three months) No more urgencies, the distortion that bad forecasts produced has been eliminated Machine Capacity has increased by using them for what is really needed INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS CUSTOMER B
31. 31. 31 3th- Dynamic Buffer Adjustments The Planning Manager should know of any extraordinary changes to products so as to be able to indicate such changes in the buffer parameters. In addition to this, they must review the behaviour of the buffers periodically to be aware of whether readjustments are necessaryINTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
32. 32. 32 RESULTS Reduction in production planning changes Machine capacity improved Production for one week is planned Daily information updated vs Weekly information updated Improved reaction to changes Facilities are used more efficiently maintaining same service levels (98+%) Regulation of the stock levels - stock is available for all production requirements Customer B is the best example INITIAL REQUIREMENTS Part and Inventory data must be correct and updated DEMAND has to be filtered INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
33. 33. 33
34. 34. 34 CUSTOMER B 445945 PART
35. 35. 35
36. 36. 36 AVERAGE STOCK 175 TN DDMRP TARGET: 184 TN ADU 9,228 (3/16/2015) RAW MATERIAL STOCK (2 WEEKS) = 92TN MATERIAL IN PROCESS (2 WEEKS) = 92TN TOTAL = 184 TN CAMS 13% OF TOTAL PRODUCTION
37. 37. 37
38. 38. BECOMING DDMRP 38 INTRODUCTION MARKET PRODUCTS PRODUCTION PROCESS DDMRP RESULTS
39. 39. StemCell
40. 40. STEMCELL Technologies Experiences from our Demand Driven journey March 2015 - Juan Abbud, Aida Mujkanovic CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of StemCell Technologies is strictly prohibited
41. 41. Dr. Allen Eaves Founder, President & CEO A Family Owned Company We can move quickly in a fast moving market We listen to our employees & customers Growth over 20 years dependent on sales revenue a great discipline! Sales are largely dependent on the new products that we develop New products are developed by our outstanding R&D scientists - who are essential to STEMCELLs success! Planning and prioritization of new product development is done carefully and confidentially Leadership & decisions are focused on long-term growth and stability
42. 42. The promise of stem cell research Cells for transplantation Adult Tissue Specific Stem Cells Bone marrow for leukemia Nerve cells for Parkinson's & Alzheimer's disease Heart muscle cells for heart disease Pancreatic islet cells for diabetes Cultured Cells Drug screening and potential therapeutics Toxicity testing Study cell differentiation Understand prevention & treatment of cancer/disease Pluripotent Stem Cells
43. 43. STEMCELLs Planning Considerations
44. 44. STEMCELLs Planning Puzzle Global, High Mix, Low Volume Sales by productInventory by product Planned Product Introductions 5 years Seasonality and growthOff the shelf sales
45. 45. Deep Bills, Long lead times & growth Cell Separation Cocktail Bill of Material, LT & CLT Changing Demand - 517 day cumulative leadtime, 300 days in prequalified base raw material, difficult to obtain, requires QC qualification - strategic part - Supports multiple products within a family 239 finished goods - Growing sales and product lines require buying for growth - Lot Consistency and Shelf life constraints intermediates and their effect on FG
46. 46. Manufacturing constraints - MOQ - Sample based QC testing significant LT, capacity constraint (i.e. 55 of 56 days) - Dedicated equipment for some product lines long setup vs run time strategy is to size batches of low volume product to cover long periods and maintain equipment availability minimum equipment batch size - Inventory footprint is low - Manufacturing variability multiple possible uses for certain parts use is test result based - Shelf life synchronization considerations, lot mixing constraints
47. 47. Keeping up with growth
48. 48. Problem Statement Limited ability to identify and exploit opportunities for improvement in the Supply Chain during day to day operations Labour intensive processes consume planning and procurement resources on tactical activities and limit operational agility Lack of data consistency limits metric development on the performance of the supply chain Difficult to maintain inventory at optimum level, opportunities for reduction exist according to analysis to date exceptions driving special cases are not always captured in the system and are difficult to analyze
49. 49. Operational objective Improve Plan to Produce Improve service levels while maintaining the optimum inventory level establish and maintain optimum inventory, control oscillation Establish process efficiencies in the Plan to Produce process by optimizing the use of the ERP and supporting systems Develop and establish the required datasets to support the Plan to Produce process and its continuous improvement
50. 50. Adopting DDMRP
51. 51. DDMRP a better fit for our planning goals System Comparison DDMRP is directly aligned with the objectives of our current planning system This eliminates manual work to achieve our desired output from the planning process The DDMRP model provides simpler and more effective metrics System design creates opportunities for process automation Simulation based on historical data validated buffer performance and service levels
52. 52. Simulation sample - ADU vs. variability PART - A
53. 53. Solution Proposal Adopt DDMRP as planning methodology Update BOM configurations to support strategic inventory positioning Capture complete demand and supply pipeline on ERP system (some information for special cases on other systems) Certify Planning and Procurement teams - CDDP
54. 54. Implementation process
55. 55. System Design BOM Structure
56. 56. Steady usage constant availability Metrics and Analytics System inputs, setting part types 20 % 80 %
57. 57. Spotty usage constant availability, strategic parts Steady usage constant availability Metrics and Analytics System inputs, setting part types 20 % 80 %
58. 58. Metrics and Analytics System inputs, setting part types Demand Driven Planning 20 % 80 %
59. 59. Measuring System Inputs and Performance
60. 60. Metrics and Analytics Buffer Performance Details
61. 61. Identify parts with risks in Supply and higher variability Assign to correct buffer, address cause when possible Complements LT variability metrics Identifying opportunities for improvement Leadtime Variability Purchased Parts
62. 62. Future Considerations what is next for us? Deploy metrics and link them to execution, periodical metric reviews buffer status meetings Dynamic adjustment model for applicable RO and MM parts Continue monitoring and adjusting parts attributes Rollout DDRMP for pilot product end to end (Raw FG) Build BOM dataset strategic buffer analysis Explore opportunities for improvement MOQ, Leadtime and Variability invest to redefine constraints as appropriate
63. 63. Key implementation factors at STEMCELL Secure executive sponsorship by demonstrating value Simulation with your data helps Understand the scope of applicability and expected benefits fit to business An implementation partner that knows your system is highly valuable Train everyone! Make sure the BOM definition in your system is correct Strong data team ability to run trending calculations and validate settings is invaluable focus on data quality Plan for the transition support users by providing them context to understand the new ordering patterns Plan the integration of the planning system into all related processes
64. 64. Questions?