Copyright © 2011 SYSPRO All rights reserved. Inventory Optimization User Group 17 th August 2011

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter What we’ll cover Why Optimize Inventory? The Four Steps to Inventory Optimization Measurement of Inventory Performance The IO Suite in Relation to other SYSPRO Modules Looking at the Four Steps in more detail

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Why Optimize Inventory? Inventory costs a lot to acquire Inventory often in top two assets Inventory costs a lot to keep Storage costs 20% - 40% of its cost value Poor stock turns a low return Inventory affects service levels Customer satisfaction Without customers you don’t have a business Supply chains don’t work without inventory Cost Inventory represents an opportunity for big gains

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Benefits of Inventory Optimization Improved forecast accuracy A better estimate of the demand Lower safety stock Reduces investment in inventory Typical reductions of 20% - 30% Improved stock turns Improves achieved service levels Typical increases of 3% - 30% Improved sales turnover Improved ROI Identifies waste in the supply chain Focuses on where value is delivered Cost

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Forecast Error Why Inventory Optimization? Time Level of Inventory Forecast Lead Time Lead Time Error Inventory Optimization Actual Demand The primary drivers of Inventory Optimization are uncertainties in Supply and Demand

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Causes of inventory Uncertainties in demand Uncertainties in supply Lead time greater than service time Demand & supply quantities not equal Limitations on order frequency Higher service levels Demand Supply

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter There are three kinds of inventory Time Level of Inventory Safety or buffer stock Lowers risk of stock outs Balance between cost and service Cycle stock To meet demand levels Constrained by batch size, EBQ, MOQ, or shipping constraints Excess stock Result of poor forecasts, policy settings or management Minimum Maximum Average Stock

Copyright © 2011 SYSPRO All rights reserved. The Four Steps to Inventory Optimization

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter The 4 Steps to Inventory Optimization Understand the importance and behaviour of the stock codes in each location Get the best possible estimate of Demand (Forecast) Set the appropriate stock levels to meet this demand (Stock Policy and Modelling) Replenish Timeously to Plan

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter The inventory variables Actual Demand Demand Forecast Forecast Accuracy Order frequency Lead time Order or lot size Delivery reliability Target service level Time-phased Target Inventory Stock Policy Supply sideDemand side Modeling

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Graphic illustration of the 4 Steps Let’s take a look at what the IO Suite does Inventory Forecasting (and Families & Groupings) Inventory Optimization Remember the 4 Steps? After this we will delve into a more detailed view

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Step1: Identifying key items through Pareto analysis – importance and behaviour D 46% of items C 16% of items 80% A 17% of items 95% 100% Sales value ranking of items Percentage sales value Percentage active stock codes 98% B 21% of items 1. Importance and Behaviour

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Step 2: Get the best possible Forecast April May Jun e July Aug Sep t Oct NovDec Jan Feb Mar April May Jun e July Aug Sep t Oct NovDec Jan Feb Mar April May Jun e July Aug Sep t Oct NovDec Jan Feb Mar Now Actual Demand Best Fit Algorithm Demand Forecast 1. Input Historical Data (in this Example We Have 2 Years) 2. Use Inventory Forecasting or Families & Groupings to Find the Best Suited Algorithm 3. Use the Algorithm to Forecast into the Future 2. Best estimate of Demand

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Step3: What is the right stock level for this Demand? April May Jun e July Aug Sep t Oct NovDec Jan Feb Mar April May Jun e July Aug Sep t Oct NovDec Jan Feb Mar April May Jun e July Aug Sep t Oct NovDec Jan Feb Mar Now Actual Demand Best Fit Algorithm Demand Forecast How Much Stock For This Demand?

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Step3: Set the Appropriate Stock Levels AprilMayJuneJulyAugSeptOctNovDecJanFebMar Now Demand Forecast Min Max Resulting Stock (Average) Depending on Your Stock Policy IO Calculates Min/Max Levels for the Forecast 2. Let’s say we decide the Min/Max Levels were not ideal so we try different policy options 3. Set Appropriate Stock Levels Cost Stock policy

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Step 4: Replenish Timeously to the Plan AprilMayJuneJulyAugSeptOctNovDecJanFebMar Now 4. MRP Calculates How Much Replenishment & By When Demand Forecast Min Max Resulting Stock (Average) Once we are satisfied with the Min/Max Levels – this becomes input to MRP 2. MRP Takes Calculated Min/Max Levels, the Opening Stock, Orders In Process and Lead Time, and Suggests Replenishment To Comply With The Stock Policy

Copyright © 2011 SYSPRO All rights reserved. Measurement of Inventory Performance

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Determining Inventory Performance Try to find a balance between Service and the investment in inventory to provide it Measure the Service delivered to the customer Measure the quality of the Forecast (Forecast Error or Accuracy) Measure how fast the inventory “turns over” Stock Turns = Annual Cost of Sales / Cost of Stock An alternate view of this is the “stock cover” Months Cover = 12 / Stock Turns

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter The IO Suite and Other SYSPRO Modules Inventory Forecasting Sales Orders Families and Groupings Inventory Optimization Requirements Planning Inventory Forecast Master Data, Setup, Stock on Hand Min / Max levels Work in Progress Purchase Orders Open Purchase Orders Open Jobs Historic Demand Forecast Master Data, Setup, Stock on Hand Open Jobs Open Purchase Orders 2. Best estimate of Demand 3. Set Appropriate Stock Levels 4. Replenish Timeously to Plan 1. Importance and Behaviour

Copyright © 2011 SYSPRO All rights reserved. Behaviour and Importance of Stock Codes

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Analyse for Importance and Behaviour Example from a SYSPRO customer Over SKUs Many of these have erratic demand Use a Pareto (ABC) based on sales value or gross profit to analyse importance Use a Pareto based on hits (demands) as a simple indicator of forecastability Combine these to manage in like groups

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Use a combination of Hits and Sales Value Hits (Demands): A > 36 p.a. B 13 to 35 p.a. C7 to 12 p.a. D1 to 6 p.a. Sales Value: A80% (> R p.a.) B95% (R to R p.a.) C98%(R to R p.a.) D100%(R1 to R p.a)

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Examples of the Combined Ranking ItemHitsQtySales Value Hits ABC Sales ABC Both RF AAAA VH AAAA H7F DADA F ACAC P CACA RF ADAD

Copyright © 2011 SYSPRO All rights reserved. Getting the Best Possible Forecast

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Forecast = Mean 100 Max Demand 200 Min Demand 50 Half the Average Demand Double the Average Demand Forecast without Seasonality Demand Forecasting Based on Average Demand Leads to Poor Forecast Accuracy Average Demand = 100 units Demand Varies from units

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Average Demand 100 Min Demand 50 Max Demand 200 Actual (+) Actual (-) Revised Forecast Forecast with Seasonality Demand Forecasting Based on Accurate Seasonal or Other Trends Leads to Better Forecast Accuracy

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter A more complex demand pattern

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Looking at 3 Years of Demand Average for forecast Average stock 2.5 months Stock Turns 4.8 Service level < 85% Forecast Accuracy < 60%

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Using a more suitable Algorithm Holt-Winters Multiplicative Average stock 2 months Stock Turns 6 Service level 90% Forecast Accuracy > 90%

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Forecast Accuracy

Copyright © 2011 SYSPRO All rights reserved. Set Policy and Model Stock

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Setting Dynamic Min / Max Levels Average stock 1.2 months Stock Turns 10.2 Target Service level 95% Forecast Accuracy > 90%

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Safety Stock vs Service Level Investment 70 % 75 % 80 % 85 % 90 % 95 % 100 % Service Level 2 weeks4 weeks 6 weeks 10 % 3 %

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Achieved Service Levels Achieved Service Level for a Selection Set

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Achieved Service Levels

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter Sort on Actual Shortfall Descending

Copyright © 2011 SYSPRO All rights reserved. Manage the Plan through MRP

Copyright © 2011 SYSPRO All rights reserved. Simply Smarter IO Levels in Requirements Planning

Copyright © 2011 SYSPRO All rights reserved.