USING FORECASTING TOOLS

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2 USING FORECASTING TOOLS IFS Inventory Planning and Replenishment IFS CUSTOMER SUMMIT 2011, CHICAGO

3 GREG ROMANELLO SENIOR IMPLEMENTATION MANAGER IFS Customer Summit 2011, Chicago

4 KARIN RAINESALO BUSINESS SOLUTIONS CONSULTANT IFS Customer Summit 2011, Chicago

5 AGENDA What is IPR and why use IPR? New Parameters on Inventory Parts Classification ABC/Frequency/Lifecycle Planning policies Planning hierarchy Planning parameters Example planning hierarchy changes planning parameter IFS Demand Planning Change forecast data Example forecast changes planning paramters Calculation Explanations and Simulation Execute replenishment. 5 IFS Customer Summit 2011, Chicago

6 WHAT IS IPR?

7 WHAT IS IPR AND WHY USE IPR? What is IPR? Why IPR? IPR = Inventory Planning and Replenishment Functionality to manage part replenishment. Works with Order Policy Code B parts: Safety Stock Reorder Point Lot Size Next Order Date You ve always had the ability to enter values for safety stock, reorder point, and lot size. IFS Applications has had functionality to help you calculate those values using historical data. Didn t consider future demand. IFS Customer Summit 2011, Chicago

8 MAIN FEATURES OVERVIEW Definition: A solution for inventory replenishment using reorder levels IPR calculate values for: Safety Stock needed to absorb variation in demand or lead-time. Reorder Point the inventory level at which you need to create a replenishment order Lot Size the quantity to order when the reorder point is reached Next Order Date given the current stock level and forecast Reorder point Safety Stock Stock Next Order Date Expected Lead Time Receipt Time Lot Size IPR adds forecast info as an input to calculate these values.

9 TARGET GROUPS RECOMMENDATION Replenish Fulfill Supply Lead Time Delivery Lead Time IPR is a reorder point-based planning system. Planning of a part is independent of other parts. If the demand for a part depends almost entirely on other parts, MRP-based solutions work better. If a part has many sources of demand (>10), reorder point works fine even though all demand is dependent. The result of an inspection is just replenish/don t replenish the forecast is not distributed upstream as in an MRP system. Under which circumstances should IPR be deployed? Spare part logistics Distribution and trade Common components used in many bills of materials IFS

10 CLASSIFICATION

11 CLASSIFICATION ABC ANALYSIS Classification by turnover value ABC analysis Cumulative Value Distinguish the vital few from the trivial many. A small number of parts will correspond to a large portion of total value. The classification defines the operative and strategic focus. 100% 95% 80% A B C Cum. No of parts 11

12 CLASSIFICATION FREQUENCY ANALYSIS Classification based on history frequency The frequency will determine how difficult is to plan the parts Fast movers predictable demand and easy to forecast Slow movers unpredictable demand and low forecast accuracy The frequency class will help to decide the best forecasting and inventory planning method. It also supports strategic decisions about product range, supply model, etc. Demand FAST MOVER MEDIUM MOVER SLOW (NO) MOVER Average Demand Average Demand Average Demand Period 12

13 CLASSIFICATION ABC/FREQUENCY/LIFECYCLE STAGE This classification is grouped by lifecycle stages. The classification is done by site or asset class. Example: Spare parts at site 90 AF BF CF AM BM CM AS BS CS AF BF CF AF BF CF AM BM CM AM BM CM AS BS CS AS BS CS AF BF CF AM BM CM AS BS CS CS Today Expired Decline Mature Introduction Development Introduction Stage Duration Decline Inactivity Days Expired Inactivity Days 13

14 CLASSIFICATION PURPOSE The classification ABC/Frequency/Lifecycle is the foundation for the planning policies to be applied. Frequency Frequency Fast movers have high forecast accuracy and low variation Slow movers are impossible to forecast and intermittent ABC Class CF CM BF BM AF AM A-parts are important and need/justify a lot of attention C-parts are not important and should not require a lot of attention CS BS AS Lifecycle stage Mature parts have a reliable forecast New parts (Introduction) require a manual estimate Declining/Expired parts shall not be replenished Volume Value 14

15 CLASSIFICATION PROCESS Determines ABC Class Determines Frequency Class based on number of issues per year (or number of periods) and classification boundaries by site. Determines Lifecycle Stage based on days between issues and classification boundaries by company. A background job that can be scheduled. Stock 15 IFS Customer Summit 2011, Chicago

16 CLASSIFICATION RESULTS 16

17 PLANNING POLICIES & PARAMETERS

18 DETERMINE PLANNING POLICIES PLANNING PARAMETERS The IPR calculates 4 planning parameters which are used to create replenishment proposals: Stock Lot size Safety Stock Reorder Point Next Order Date Reorder point Safety Stock Time Lot Size Next Order Date Receipt IPR offers a number of different methods to calculate these parameters Expected Lead Time 18

19 PLANNING PARAMETERS SET THE DEMAND MODEL In order to calculate the planning parameters it is necessary to have an estimate of future: Demand (Forecast) Expected demand variation (Demand forecast error) The Demand Model defined on Inventory Part will dictate what data to use to estimate the future. Forecast from IFS/Demand Planning Yearly prediction Manual entry History inventory transactions are used ADVICE: Use Forecast for: Mature Fast and Medium movers Important parts where a reliable forecast can be created manually Parts with trends, campaigns, seasonality etc. Use History for Mature Slow Movers 19

20 PLANNING PARAMETERS HOW TO DETERMINE LOT SIZE Manual manual entry of the lot size Stock Time Coverage the lot size is calculated to cover a number of days demand Economic Order Quantity (EOQ) A trade-off between inventory holding cost and ordering cost The result is dependent on Demand, Part Cost, Inventory Interest Rate, Ordering Cost ADVICE: Time coverage is a commonly used model it is easy to understand and communicate EOQ gives good results, but requires significant analysis to determine the right input parameters Lot Size Max Order Cover Time By using IFS/Demand Planning, the lot sizes will change dynamically with seasonality, trends, campaigns, etc. Time 20

21 PLANNING PARAMETERS HOW TO DETERMINE LOT SIZE Additional parameters that control the lot size: Stock Max Order Cover Time can be defined to limit the lot size when EOQ is used Durability Min, Max and Multiple Lot Size Lot Size Time Max Order Cover Time By using IFS/Demand Planning, the lot sizes will change dynamically with seasonality, trends, campaigns, etc. 21

22 PLANNING PARAMETERS HOW TO DETERMINE SAFETY STOCK Stock The purpose of a safety stock is to cover for uncertainty in demand quantity or supply lead time Manual manual entry of the safety stock Time Coverage the safety stock is calculated to cover a number of days demand Reorder point Safety Stock Next Order Date Expected Lead Time Receipt Time Lot Size Historical Uncertainty the safety stock is calculated using Standard deviation, Lead time, Service Rate [%], Lot Size Demand Forecast Demand Average Demand Mean Absolute Error rather than using historical standard deviation, the historical forecast error is used ADVICE: Mean Absolute Error will show good results for mature Fast and Medium Movers. Time Coverage is a robust and visual model Special models should be used for slow movers Period By using IFS/Demand Planning, the safety stock levels can be kept lower, as historical variation that originates from seasonality, trends, campaigns etc., is filtered. 22

23 PLANNING PARAMETERS HOW TO DETERMINE REORDER POINT The Reorder point is defined as either of: Manual manual entry of reorder point Stock Lead-time driven calculated as the demand during the lead time plus safety stock ROP In addition to this, a number of models are added to handle slow-moving parts (< 10 transactions per period): Demand LT Safety Stock Time Slow Movers Lifecycle Slow Movers Lead time Croston Lifecycle Croston Lead time Next Order Date Expected Lead Time Receipt 23

24 INVENTORY PART MODELS Demand Model Safety Stock Model Lot Size Model Order Point Model 24 IFS Customer Summit 2011, Chicago

25 INVENTORY PART COVER TIMES Cover Times 25 IFS Customer Summit 2011, Chicago

26 INVENTORY PART EOQ PARAMETERS Inventory Interest, Ordering Cost, Service Rate 26 IFS Customer Summit 2011, Chicago

27 PLANNING PARAMETERS PLANNING HIERARCHY A number of parameters are needed in order to calculate the planning data Demand Model Safety Stock Model Lot Size Model Order Point Model Inventory Interest Rate Service Rate Ordering Cost Instead of defining these parameters for each part, they can be maintained in a planning hierarchy IFS

28 PLANNING HIERARCHY Hierarchy is in place to define: Inventory interest Ordering cost Service rate Models Cover times Lower level hierarchical value overrides higher level value: Company Site ABC/Frequency/Lifecycle stage Asset Class Commodity Group Supplier Inventory Part 28 IFS Customer Summit 2011, Chicago

29 PLANNING HIERARCHY EXAMPLE Set parameters at different levels and they ll pass to the inventory parts. Example: company inventory interest rate = 15% IFS Customer Summit 2011, Chicago

30 PLANNING HIERARCHY EXAMPLE However, if a part belongs to Asset Class 20 or 40, the inventory interest rate is 12%. 30 IFS Customer Summit 2011, Chicago

31 PLANNING HIERARCHY Models and lot size cover times set for different combinations of ABC Class, Frequency, and Lifecycle Stage. 31 IFS Customer Summit 2011, Chicago

32 Each setting shows its source: company, site, ABC/Frequency/Lifecycle, Asset Class, Commodity Group, Supplier, Inventory Part 32 IFS Customer Summit 2011, Chicago

33 Each setting shows its source: company, site, ABC/Frequency/Lifecycle, Asset Class, Commodity Group, Supplier, Inventory Part 33 IFS Customer Summit 2011, Chicago

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36 IPR EXAMPLE A mature, fast-moving part with a forecast. Economic order quantity has been used to determine values for lot size. Initial order cost determined by Company value Change suppliers to one that results in a higher ordering cost. New value is calculated for lot size. 36 IFS Customer Summit 2011, Chicago

37 COCA-COLA PLANNING POLICIES 37 IFS Customer Summit 2011, Chicago

38 COCA-COLA PLANNING PARAMETERS 38 IFS Customer Summit 2011, Chicago

39 COCA-COLA CHANGE PRIMARY SUPPLIER 39 IFS Customer Summit 2011, Chicago

40 COCA-COLA PLANNING PARAMETERS AFTER SUPPLIER CHANGE 2010 IFS

41 PLANNING PARAMETERS DEPENDENCIES Parameter Value Required Input Demand Model Forecast Forecast from IFS/Demand Planning Yearly Prediction Inventory Part / Planning / Pred Year Cons Qty History Inventory transactions Safety Stock Model Manual Inventory Part / Planning / Safety Stock Time Coverage Safety Stock Cover Time Historical Uncertainty Inventory transactions + Service Rate(%), Inventory Part / Aquisition / Expected Lead Time Mean Absolute Error Forecast from IFS/Demand Planning + Service Rate(%), Inventory Part / Aquisition / Expected Lead Time Lot Size Model Manual Inventory Part / Planning / Lot Size Time Coverage Lot Size Cover Time Economic Order Quantity Inv Interest (%), Ordering Cost, Part Cost Order Point Model Manual Inventory Part / Planning / Lot Size Lead Time Driven Inventory Part / Aquisition / Expected Lead Time Slow Movers - Lead Time Inventory Transactions + Service Rate(%), Inventory Part / Aquisition / Expected Lead Time Slow Movers - Lifecycle Inventory Transactions + Service Rate(%), Inventory Part / Aquisition / Expected Lead Time Croston - Lead Time Forecast from IFS/Demand Planning + Service Rate(%), Inventory Part / Aquisition / Expected Lead Time Croston - Lifecycle Forecast from IFS/Demand Planning + Service Rate(%), Inventory Part / Aquisition / Expected Lead Time IFS

42 IFS DEMAND PLANNING

43 PLANNING PARAMETERS SET THE DEMAND MODEL In order to calculate the planning parameters it is necessary to have an estimate of future: Demand (Forecast) Expected demand variation (Demand forecast error) The Demand Model defined on Inventory Part will dictate what data to use to estimate the future. Forecast from IFS/Demand Planning Yearly prediction Manual entry History inventory transactions are used ADVICE: Use Forecast for: Mature Fast and Medium movers Important parts where a reliable forecast can be created manually Parts with trends, campaigns, seasonality etc. 43

44 IFS DEMAND PLANNING DEMAND MODEL = FORECAST 2010 IFS

45 IFS DEMAND PLANNING FORECASTING A statistical forecasting tool with graphical and tabular displays. Use historical data to make predictions about the future. A variety of forecasting models and metrics Naïve Moving average Exponentially Weighted Moving Average (EWMA) Single (Level) Adaptive Single Double (Level and Trend) with Dampening Least Square Regression with Trend Dampening Croston s Brown s Model Multiple Regression Best fit Bayesian IFS DEMAND PLANNING

46 IFS DEMAND PLANNING FORECASTING Seasonality System-defined or user-defined A variety of error measurement methods. Campaigns, Inheritance, Cannibalism Uses a combination of statistical methods and judgmental adjustments Collaboration Collaborators use a web-based client to view or input forecasts on a subset of items, customers Tightly integrated with IFS Planning components. IFS DEMAND PLANNING

47 IFS DEMAND PLANNING AND IPR When the Demand Model is Forecast, IFS Demand Planning is the source of estimates of future demand. Mature, fast-moving parts Other parts that can be manually forecast reliably. Parts with seasonality, campaigns, trends. Lot size and safety stock levels can be varied from period to period, based on changing demand: seasonality, campaigns, trends, events. 47 IFS Customer Summit 2011, Chicago

48 IFS DEMAND PLANNING AND IPR EXAMPLE A mature, fast-moving part with a forecast. Demand model for the part is Forecast; forecast has been used to determine values for safety stock, reorder point, lot size. Change the forecast to add an event or campaign. New values are calculated for safety stock, reorder point, lot size. 48 IFS Customer Summit 2011, Chicago

49 ABSOLUT BEFORE CHANGE VALUES FOR PLANNING PARAMETERS 49 IFS Customer Summit 2011, Chicago

50 ABSOLUT BEFORE CHANGE FORECAST 50 IFS Customer Summit 2011, Chicago

51 ABSOLUTE AFTER CHANGE IN FORECAST 51 IFS Customer Summit 2011, Chicago

52 ABSOLUT NEW SAFETY STOCK, ORDER POINT, LOT SIZE VALUES 52 IFS Customer Summit 2011, Chicago

53 CALCULATION EXPLANATIONS

54 An analysis tool is available so you can see how IPR does its calculations. You can also simulate changes without having to update the database. And you can create graphs of the data used in the IPR calculations. IFS Customer Summit 2011, Chicago

55 The first tab shows the parameters used in the calculations and the policies selected. 55 IFS Customer Summit 2011, Chicago

56 The second tab shows the values calculated for all the planning parameters. Column C can be used to perform simulations. For example 56 IFS Customer Summit 2011, Chicago

57 Change the order cost from 10,000 to 20, IFS Customer Summit 2011, Chicago Since the Lot Size model is EOQ, there should be a change in the Lot Size. Lot size changes from 9,943 to 14,062.

58 Change the safety stock time coverage from 5 to 10. Since the Safety Stock model is Time Coverage, there should be a change in the Safety Stock. Safety stock changes from 8,459 to IFS Customer Summit 2011, Chicago

59 CREATE GRAPHS FROM DATA 59 IFS Customer Summit 2011, Chicago

60 EXECUTE REPLENISHMENT

61 PERFORM REPLENISHMENT TWO OPTIONS Next Order Date Stock Next Order Date is the date when a part will reach its reorder point Considering supply and the largest of forecast and actual demand Displayed on overview Supplier for Purchase Part, from where requisitions can be created Reorder point Safety Stock Time Days To Next Order Date indicates priority Order Proposal Next Order Date Expected Lead Time Receipt A background job that will compare the available stock with the reorder point and create requisitions 61

62 EXECUTE REPLENISHMENT NEXT ORDER DATE 62 IFS Customer Summit 2011, Chicago

63 SUMMARY

64 INVENTORY PLANNING AND REPLENISHMENT BENEFITS Powerful, efficient and impartial management of large numbers of parts Classification of parts and inventory management policies defined by groups Integrated with IFS/Demand Planning for improved response to changes in demand and forecast accuracy Calculation of next order date for prioritization of proposals Decision support for the planner to schedule orders Special support for slow movers (Poisson-distributed demand) Rapid ROI and substantial improvement potential: Lower inventories, improved customer service, less scrap and obsolescence Less administration, cost reduction opportunities A powerful, yet proven, solution for distribution and spare parts management High performance because all heavy calculations are performed in the Demand Server 64

65 CUSTOMER EXAMPLES IPR is live at 2 pilot customers: John Deere (Sweden, Finland) PMC Servi Group (Norway) IPR is based on a Scandinavian extension called APO that has been implemented at approximately 20 customers already Some examples of customers using the Scandinavian extension APO are: Systembolaget, Retail, >400 sites with 1500 parts each, Sweden AK-Maskin, spare parts retailer (agriculture), Norway SKM Fellesköpet, automotive spare parts (agriculture), Norway BOS Bertel O. Steen, automotive spare parts, Norway Byggmax, building material retailer, Sweden, Norway, Finland 65

66 QUESTIONS?

67 THANK YOU FOR ATTENDING. STOP BY THE MEET THE EXPERTS AREA. IFS Customer Summit 2011, Chicago

68 THIS DOCUMENT MAY CONTAIN STATEMENTS OF POSSIBLE FUTURE FUNCTIONALITY FOR IFS S SOFTWARE PRODUCTS AND TECHNOLOGY. SUCH STATEMENTS OF FUTURE FUNCTIONALITY ARE FOR INFORMATION PURPOSES ONLY AND SHOULD NOT BE INTERPRETED AS ANY COMMITMENT OR REPRESENTATION. IFS AND ALL IFS PRODUCT NAMES ARE TRADEMARKS OF IFS. THE NAMES OF ACTUAL COMPANIES AND PRODUCTS MENTIONED HEREIN MAY BE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS IFS