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Nikos Iosif International Business Development, MANTIS

Nikos Iosif International Business Development, MANTIS. British Aerospace Gec-Marconi aerospace General Motors Mazda Motor Parts Europe Messier-Bugatti Aerospace Messier Dowty Aerospace Smiths Industries Volkswagen Group Service Volvo VCE NATO Supply Agency MAN Bus & Trucks Porsche

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Nikos Iosif International Business Development, MANTIS

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  1. Nikos Iosif International Business Development, MANTIS

  2. British Aerospace Gec-Marconi aerospace General Motors Mazda Motor Parts Europe Messier-Bugatti Aerospace Messier Dowty Aerospace Smiths Industries Volkswagen Group Service Volvo VCE NATO Supply Agency MAN Bus & Trucks Porsche Abbey National Bank plc Euronet British Gas Transco British Gas Services Scottish Hydro Electric Fuji Film Sverige AB Pharmacia Esab MK Electric CPC Foods Lucent Technologies Donaldson Halfords The Wilkinson group Sketchley Superquinn Alcro Beckers Meria Nova Oy Carlsberg Tetley Get Technocar SEAT Electrolux Outdoor Products Electrolux Professional Viamar Skoda Some Of Our Customers

  3. Supply Flow Management Executive Information Systems Modelling and Simulation Replenishment Planning Production Planning & Scheduling Demand Forecasting

  4. Syncron B2BOUR SUPPLY CHAIN VISION

  5. Syncron - Supply Chain Management next Are you operating in isolation rather than in partnership?

  6. Syncron - Supply Chain Management Do you still focus on local optimisation with limited visibility? next

  7. Syncron - Supply Chain Management You can make earlier decisions in conjunction with your partners next

  8. Transactional backbone system System of record for all information Large user base within an organization Wide focus on all business functions Financial, Manufacturing, etc. Decision-support system Complex algorithm execution Rapid result generation Simulation modeling and what-if analysis Small user base of key individuals within an organization Targeted focus on key business problems What’s the Difference ? SCM ERP

  9. Issues purchase orders Reports on-hand inventory levels Archives actual order & shipment history Issues stock replenishment orders Issues work orders to shop floor Calculates optimal purchase order quantity and timing Determines right product, right place, right time, right quantity Uses historical and current order information to predict customer demand Optimally calculates timing and quantity of replenishments Creates detailed capacity, labor and material constrained works order schedules Collaborative business planning Alerting & exception management based on business rules What’s the Difference ? SCM ERP

  10. Forecasting

  11. Purpose Of Forecast • What decisions will be made as a result of the forecast? • Company corporate planning? • Capacity planning? • Manpower planning? • Sales targeting? • Annual budget? • Cash flow? • Production planning? • Inventory requirements? Long-term Short-term

  12. Syncron Demand Forecast Process • Calculates future forecasts based on the demand history and the latest demand. • Checks for any change in the pattern of demand. • Detects increasing or decreasing trends in demand. • Measures and reports on the accuracy of the forecasts including the impact of manual adjustments.

  13. Elements Of Syncron Forecasting

  14. Cyclical variation Base level External factors Trend Forecast Components FORECAST COMPONENTS

  15. Forecasting Demand

  16. NEW OBSOLETE Demand Patterns LUMPY SLOW ERRATIC NEGATIVE TREND FAST Trend DYING

  17. Forecast Error • All forecasts are single point estimates • Demand is usually random • Hence, forecasts always have error • Forecast error = actual demand - forecast • Most important to forecast the error

  18. Trigg’s Tracking Signal • Notifies the user of items where the forecast is no longer keeping track of actual demand.

  19. Seasonality

  20. YEAR ONE YEAR TWO Causes Of Seasonality • Time of year • Public holidays • Sales effort • Annual price increase • Catalogue issue

  21. Volume Density • The volume density facility allows you to define density factors on a calendar basis, and to adjust the demands, forecasts and hence recommended orders to take account of these factors.

  22. 1997 1998 1999 2000 2001 Volume Density

  23. Volume Density 1997 1998 1999 2000 2001

  24. Volume Density

  25. CHANGE OF DEMAND TYPE

  26. Flier? Exceptional Demands If a demand is unusually high or low and unlikely to be repeated, do not use to update forecast 60 50 40 30 Demand 20 10 0 1 3 5 7 9 11 13 15 17 19 21 23 Period

  27. STEP CHANGE AUTOMATIC RE-INITIALISATIONCONSECUTIVE FLIERS

  28. NEW New Products • User knowledge • Statistical monitoring • Allocation to similar seasonal group • Pre launch • Supersession

  29. PRE-LAUNCH PRODUCTS NEW PRODUCT PROCESSING USER ESTIMATE LAUNCH PERIOD CURRENT PERIOD

  30. NEW PRODUCTS USER ESTIMATE MOVING AVERAGE STANDARD SYNCRON MOVING AVERAGE NEW PRODUCT INITIALISE

  31. REPORT GENERATOR USER REPORT 1 USER REPORT 2 SYNCRON FILES USER REPORT 3 ________________________________________________________________________________________________________________________________ REPORT DESIGN SELECTION CRITERIA SORTING ARITHMETIC FUNCTIONS GRAPHICS DATA TRANSFERS STORED PROCEDURES

  32. Management By Exception Reports Powerful exception reports focus management attention on items where: • Exceptional demand last period • Tracking signal indicates rapid change of demand level • Strong positive trend • Negative trend • Demand class improved or deteriorated • Forecasts amended by management Essential for large inventories

  33. Forecast adjustments Reason codes Manual Intervention

  34. Inventory Basic ConceptsReplenishment Systems

  35. Basic Systems In Stock Control When to order? How much to order? Basic systems provide answers to the questions:

  36. Basic Systems For Stock Control • Fixed order quantity • Fixed order cycle • Min/max system

  37. THE FIXED ORDER QUANTITY SYSTEM MAXIMUM RATE OF USAGE WITHOUT STOCK-OUT **REORDER QUANTITY (Q) *REORDER LEVEL POINT (A) . . . . . . . . . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . • . STOCK LEVEL Q Q EXPECTED RATE OF USAGE (R) BUFFER STOCK LEVEL . . . . LEAD TIME (L) TIME *ROL= Forecast over lead -time + buffer stock **ROQ can be determined by EOQ or Coverage Analysis

  38. THE FIXED ORDER CYCLE SYSTEM *ORDER UP TO LEVEL **REORDER QUANTITY Q3 **REORDER QUANTITY Q3 Q2 STOCK LEVEL . . . . . . . . . . . . . . Q2 Q1 Cover period . . . . . . . . BUFFER STOCK LEVEL LEAD TIME (L) LEAD TIME (L) REVIEW PERIOD (T) TIME REVIEW PERIOD (T) *OL=Forecast of Demand in cover period + Buffer Stock **ROQ=Order Level-Effective Stock + Back Orders

  39. The Inventory Process • The Syncron inventory process recalculates the following inventory values for each product using the latest forecast and associated adjustments • VAU class • Inventory control type • Review time • Buffer stock • Order level

  40. VALUE OF ANNUAL USAGE THE 80 - 20 RULE Products Turnover

  41. EXAMPLE VAU ANALYSIS

  42. ABC Classification • Basis for an ordering policy • Guide to the relative importance of a product to the business • Allows for effective resource management appropriate for a products importance • Means of balancing inventory cost against risk to service

  43. Multi Dimensional Pareto Analysis To separate high volume, low value from low volume, high value

  44. Overview of Multi-Pareto Process • The process works by automatically allocating products to different parameter sets as well as by VAU • Volume (up to 5 different classes) • Frequency (up to 5 different classes) • Importance (up to 3 different classes)

  45. Order Level Order level for a product is an order up to level and the value is used to determine whether an order needs to be placed and how much to order. It is also used to ensure a pre-determined level of service to the customer.

  46. Customer Demand Variability Demand Month

  47. MANAGING FORECAST ERROR THE OPTIONS BUFFER STOCK Demand Month

  48. MANAGING FORECAST ERROR THE OPTIONS BUFFER STOCK Lead time Review time Target service level Average demand Variability of demand Batch size Demand Month

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