Forecasting Demand and Beyond
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1 Forecasting Demand and Beyond Prepared by Inez Blackburn July 9, 2003
2 A Few Forecasting Techniques - Grocery Industry Pile high and watch it fly Random walk Dart Board Back in to Bonus I m the Market Leader Last year plus 10% Lock and Load 2
3 Collaborative Demand Forecasting... The process of collectively estimating future demand for an organization s products or services
4 Interesting Demand Influences and Relationships Beer and bad weather Spirits and really bad weather Red wine and the Atkins diet Ice wine and over 55 Martinis and Baby Boomers Crown Royal and under 25 Growing importance of ethnic population and imported beer 4
5 Demand Forecasting Customers Who is target customer Size of target market Buying power Buying behavior Growth potential Products Unique or commodity Really New or Me Too Size of market Market potential Capacity for Profit Competitors? Market Position? Promotions? 5
6 Transition Cycles in Consumer Marketing Advertising (Awareness) Promotion (Preference) Warehousing Merchandise Processing Delivery Shelf Stocking Product Use After-Sales Support Manufacturing/ Distribution Cycle Retail Cycle Purchase/ Consumption Cycle Satisfaction of Consumer Demand Production Scheduling Demand Estimation Distribution Centre Merchandise Planning Inventory Reporting Product Selection Point of Sale Store/Category Selection Product/Program Evaluation/Modification Product to shelf Consumer Feedback Shelf to Consumer Product to Consumer 6
7 Forecasting Implications Manufacturer Distributor Manufacturer Distributor Internet Conventional Agent LCBO Agent LCBO Consumer Past Consumer Future 7
8 Elements of Collaborative Demand Forecasting Consumer Predictability Effective Communication Levels of Influence & Responsibility Manage Process Demand Forecasting Inventory Policy Scheduling and Production 8
9 Collaborative Demand Forecasting will require a strong commitment to effective communication and the continuous sharing of information between key stakeholders
10 Demand Forecasting Forecasters Management Sales Force Historical Data Demand Forecasting Market Consumer Influences Influences Working Forecast Distribution Finance Sales Manufacturing 10
11 Inventory Policy Total Cost Safety Stock Reorder Point Order Quantity Inventory Policy Forecast Inventory levels Number of Orders Customer Service Number of Turns 11
12 Scheduling & Production Demand Allocation Capacity Resource Materials Inventory Replenishment Demand Management Scheduling & Production Balancing & Optimization Accurate Budgets Dependable Plans Finite Capacity Scheduling 12
13 Demand Forecasting Challenges Too much information Not enough information Wrong information Can t find information Do not understand information Cannot share information Do not use information Garbage in Garbage out 13
14 Information Sources Manufacturer Retailer POS Data Sale of data info Consumer Data Consumer Data Primary Market Research Primary Market Research Secondary Market Research Secondary Market Research Promotion and Advertising Promotion and Advertising Market Trends Market Trends Consumer Dynamics at Consumer Dynamics at Retail Retail New Product Performance New Product Performance 14
15 Information Sources cont d Manufacturer Warehouse and shipment data Consumer preference data Geo-demographic information Space management data Market level data (pricing, marketshare, shipments, etc.) Airmiles Retailer Warehouse and shipment data Consumer preference data Geo-Demographic Information Space management data Market level data (pricing, marketshare, shipments, etc) 15
16 Collaborative Forecasting Opportunities Collaborative forecasting significantly increases forecast accuracy Most companies utilize 25-50% of available information to forecast demand An opportunity for Marketing and sales to work together more often More information will be shared and internalized Most forecasting information requirements exist in your organization 16
17 Collaborative Forecasting Benefits More accurate demand forecasts resulting in increased sales and profits Ability to more effectively capitalize on market opportunities Better understanding of the evolution of consumer needs More effective new product launches and promotions Faster adoption of current and emerging technologies and industry initiatives (ECR and Category Management) More effective communication between the LCBO and the Trade 17
18 Collaborative Forecasting Benefits - Supply Chain More effective production scheduling and lead times More effective utilization of supplier production facility Reduced out of stocks and higher fulfillment accuracy More effective and efficient utilization of Supply Chain Resources (ABC impact) (i.e. scheduling and receiving) 18
19 Something to think about... What information will you require from the Trade and the LCBO to collaboratively forecast the following and how would you measure your success? Crown Royal Gift Set Crown Royal Limited Edition Absolut Mandrin 19
20 Appendix 1 - Scorecards
21 A Typical Scorecard Category - Canadian Whisky Manufacturer # Skus $ Sales Trend $ Profit Trend Vendor A Vendor B Vendor C Vendor D 21
22 Consumer Behavior MEASUREMENT Item share of Cons. Requirements Penetration Frequency Basket Analysis Units/Transaction Cherry Pickers/Loyals PURPOSE Brand Loyalty % HHLDS Purchasing Frequency Purchase % Shoppers Buying Propensity Pantry Load Value of Consumers 22
23 Do you Understand How your Products are Purchased? Can you identify your most loyal consumer? Do you understand what they purchase most often? 23
24 Consumer Behavior Scorecard Basket Case # 1 Average Shopping Basket Value % Consumers with Baskets > $60 % Consumers with Baskets > $35 % Consumers with Baskets < $20 Basket Case # 2 Category Penetration % Consumers with Baskets > $60 and buy cheese % Consumers with Baskets > $35 and buy cheese % Consumers with Baskets < $20 and buy cheese 24
25 Performance Scorecard % sales % Shelf %Display Vendor A 25% 25% 15% Vendor B 40% 15% 5% Vendor C 10% 35% 20% 25
26 Appendix 2 - Statistics 101
27 Forecasting Techniques Time Series Analysis Moving Averages Exponential Smoothing Regression Analysis 27
28 Time Series Analysis Time Series Analysis identifies patterns in data Trends Seasonal Cyclical Random 28
29 Time Series Analysis Trend Seasonal Cyclical Random 29
30 Moving Averages Simple Moving Averages Average of past data over a specific time period and uses the result to forecast the future Weighted Moving Averages Assigns a predetermined weight to each data point and thereby puts more weight on recent time periods as a basis for forecasting Rule # 1 - A forecast is never 100% accurate Rule # 2 - If it is something is wrong 30
31 Exponential Smoothing Uses exponential weights to to accomplish weighted moving average Exponential smoothing uses alpha α (a value greater than 0 and less than 1) Requires two data points original forecast actual demand for for present time period F t+1 = F t + α ( D t -F t ) n α = 2/(n+1) = number of periods in a moving averages 31
32 Regression Analysis Regression analysis used for long range forecasts because moving averages and exponential smoothing can average out important seasonal trends Focus on dependent and independent variables Y= a + bx Y is the dependent variable X is the independent variable a,b are constants 32
33 Basic Scheduling Activities Demand Forecast Aggregate Scheduling Master Scheduling Ensure that the right things are done by the right people at the right time to produce the desired product through the most efficient use of resources MRP Capacity Planning Project scheduling 33
34 Economic Order Quantity Economic Order Quantity = the square root of (two times the actual demand for inventory use times ordering cost) divided by the carrying cost Tip - Too complicated for today s exercise 34
35 Appendix 3 - Supply Chain Trends and Initiatives
36 Efficient Consumer Response - Background ECR began when retailers began searching for a way to compete in an environment where consumers have a lot of shopping choices and suppliers have a number of alternatives for distribution A timely, accurate, paperless flow of information Smooth, continual products flow matched consumption 36
37 ECR Vision Timely, accurate, paperless, information flow Supplier Distributor Retail Store Consumer HHLD Smooth, continual, product flow matched to consumer 37
38 Evolution Towards Future Supply Chain Progressive ECR Implementation Steps 1. UPC 2. POS Scanning 3. Category Mgmt Plannograms 4. EDI 5. Partnerships 6. Multi-Company Teams 7. POS Data Vendor Forecast by Warehouse 8. POS Data Vendor Forecast by Store 9. Warehouse Perpetual Inventory cont... 38
39 Evolution Towards Future Supply Chain cont... Progressive ECR Implementation Steps 10. Cross-Docking via UCS 11. Store Perpetual Inventory 12. EFT Based on Vendor Owned Inventory 13. Full Replenishment 14. Collaborative Forecasting 39
40 The Flows of Information Support Two Independent Replenishment Cycles Consumer Store Supplier Replenishment Pull to Store Warehouse Replenishment Push to DC 40
41 ECR Industry Requirements Managed E-Business Solutions Intranets Extranets VANS Electronic Catalogues Connectivity - Business to Business & Business to Consumer Electronic Payment Solutions 41
42 FORECASTING: Procter & Gamble/Wal-Mart Continuous Replenishment That Eliminates Written Orders and Invoices True Partnership Based on Achieving Long Term Benefits for Both Parties WAL-MART P & G JIT Purchasing Store Database of Scanner Data Forecasting Production Scheduling Marketing Eliminates need for push sales INCREASED SALES DECREASED INVENTORIES - Concentrate on Consumption of Product rather than Just Getting it Out of the Warehouse 42
43 Must link ECR Strategies to Financials Functional Model Focus ECR Strategies Initiatives Product & Distributions Operations Consumer Efficient replenishment Efficient Promotions Efficient Store Processes Category Management Efficient Assortment Efficient Product Intro. Strategy & Planning Order Management Delivery Receiving Payment & EDI Strategic Program Planning Event Presentation & Selection CAO ASN s Labor Scheduling Receiving Merchandising Strategy Relationships Business Processes ABC Measurement Org. Capabilities Information Tech Results Category Analysis Category Analysis 43 Opportunity Evaluation
44 Virtual Value Chain ABM Introduce Products Forecast and Plan Promote Products Replenish Products Merch. Products Conduct Research Develop New Products New Item Introduction Forecast and Plan Production Manage Customers Orders Procure Materials Produce Products Manage Sales Plan Execute Sales Presentation Manage Customer Advertising Manage Trade deals Sales admin Continuos Execute Sales Replenishment Plan Order Retail Pricing management Store Merch. Physical Customer Movement Service Orders Waiting Unloading Receiving Cross Dock Load Product Unsaleable 44
45 EC Growth - and EDI in the Next 5 years Fax Em ail Structured m ail File Transfer VAN-EDI Direct EDI 45
46 Relationship of E-E Commerce to Industry Verticals Logistics Manufacturing Retail Hi-Tech Finance SME s Outsourcing Web Hosting Electronic Catalogues High Bandwidth Freight Rating Systems Services 46
47 Components of Electronic Commerce CALS Procurement Cards Firewall Systems Shared Databases E-catalogues Image Interchange E-Forms Application Integration Electronic Funds Transfer Integrated Messaging Mail Enabled Applications Fax Conversions to /EDI Secure Messaging EDI 1 Directory Services Internet Applications Standards VANs 2 Technical Data Interchange Bulletin Board Systems On-Line Services File Transfer 3 1. Always in EC 2. Usually in EC 3. Som etim es in EC 47
48 Canadian Supply Chain Initiatives Efficient Consumer Response Grocery Efficient Consumer Response Drug Efficient Foodservice Response Canadian VICS Council EHCR Efficient Healthcare Response 48
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