Thomas W. Gruen, Ph.D. Retail Out-of-Stocks: Finding a Solution

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Transcript of Thomas W. Gruen, Ph.D. Retail Out-of-Stocks: Finding a Solution

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Thomas W. Gruen, Ph.D. Retail Out-of-Stocks: Finding a Solution Slide 2 2007 Thomas W. Gruen Retail Out-Of-Stocks: Finding a Solution Thomas W. Gruen, Ph.D. Professor of Marketing University of Colorado at Colorado Springs, USA September 27, 2007 Slide 3 If you think Out-of-Stock items are not a problem Toilet tissue 3 2007 Thomas W. Gruen Slide 4 Then why Do we waste 21% of a shoppers time looking for an OOS item? Does a typical store spend $800 per week on employees solving shopper OOS issues? Do we completely satisfy customers on less than 10% of their shopping trips? Reduce the effectiveness of 1/7 of our promotions? Is one of every 13 items on a shoppers list not going to be available? Do we encourage loyal customers to try other brands and shop at other stores? 4 2007 Thomas W. Gruen Slide 5 Agenda Review what we know about retail out-of- stocks from our research Present 7 general areas that need to be addressed: Most areas focus on data Show how measurement can direct us to solutions by revealing the root causes Demonstrate our approach to reducing out-of-stocks. 5 Slide 6 2007 Thomas W. Gruen Why should we pay attention to OOS? Lost Sales & Margin For Manufacturer Lost Sales And Margin For Retailer Domino Effect On Categories Dissatisfied Customers Here are some findings from our 2002 study. These generated the interest (and another research grant) for the current study! Lets find out why. 6 Slide 7 2007 Thomas W. Gruen Two Studies 1.2002 GMA/FMI/CIES Study Worldwide Extent of OOS Shopper Reaction When Faced with OOS Root Causes 2.Current 2007 Study Aimed at Solutions Preliminary Report Completed in June Published in September 7 Slide 8 2007 Thomas W. Gruen 8 First Studys Objectives on a worldwide basis, with the objectives: 1.to present an updated and accurate map of facts surrounding retail out-of-stocks in the Fast Moving Consumer Goods (FMCG) industry, 2.to examine out-of-stocks worldwide, examining rationale for similarities and differences, n Examine extent of Out of Stocks n Examine cause of Out of Stocks n Examine consumer response to Out of Stocks Slide 9 2007 Thomas W. Gruen 9 Research Project Inputs: 52 Studies 16 previously published academic and industry studies 36 studies proprietary to this report Covering: Number of retail outlets examined: 661 Number of FMCG categories included: 32 Number of consumers surveyed world-wide: 71,000 Number of countries represented: 29 This was a huge study! So what did we find out Slide 10 ExtentDefinitions Differ n Store-based definition: u Percentage of SKUs not on the retail store shelf at a particular point in time. u Measured by audits, normally in selected categories, then aggregated. n Shopper-based definition: u Number of times a shopper looks for an item in the store and does not find it on the expected shelf. u Calculated as a percentage. u Measured by estimation from store POS data. u Helpful for examining fast-moving items. 10 2007 Thomas W. Gruen Slide 11 Clarifying what an OOS is OOS Event Physical lack of salable product on the shelf OOS Attributes Aspects of the OOS event(s) that can be measured and that can be calculated as an OOS rate. Frequency, Duration, Simultaneous events, Availability, Lost unit sales, Lost monetary sales, and Customers impacted 11 2007 Thomas W. Gruen Slide 12 OOS Rates are Calculated from Attributes Summary of OOS Rates: 1. Item OOS Event Rate 2. Category OOS Event Rate 3. OOS Duration Rate 4. Shelf Availability Rate 5. OOS Lost Unit Sales Rate 6. OOS Sales Loss Rate 7. OOS Customer Impact Rate 12 2007 Thomas W. Gruen Slide 13 Worldwide Extent > 8% *Note: Europe includes all Europe including Eastern Europe Credit: Gruen, Corsten, and Bharadwaj 2002 Background: What We Know About OOS 13 Slide 14 2007 Thomas W. Gruen 14 PROMOTIONAL OUT-OF STOCKS U.S retail out-of-stock rate: 7.9% Promotional out-of-stock rate: 17.1% Slide 15 2007 Thomas W. Gruen 15 EXTENT VARIES BY CATEGORY Reliable data from three or more studies Slide 16 2007 Thomas W. Gruen 16 EXTENT VARIES BY DAY OF WEEK Reflects expected patterns due to shopping and deliveries Slide 17 2007 Thomas W. Gruen 17 EXTENT: DURATION More than half are OOS more than 24 hours! Slide 18 2007 Thomas W. Gruen 18 Background: Extent Interpretation and Implications In spite of heavy investments to improve supply chains, worldwide OOS levels still average 8%, or from the shoppers perspective, for every 13 items a shopper plans to purchase, one will be OOS. For promoted items, OOS levels average 16%, which translates to one OOS item for every 7 promoted items a shopper plans to purchase. Thus, in an industry heavily dependent upon promotions, the impact of one-seventh of promotional dollars is reduced. Sales velocity always affects the rate of OOS. 18 Slide 19 2007 Thomas W. Gruen Q: HOW MUCH HAVE OOS RATES CHANGED? Coca-Cola Research Council 1996 study = 8.2% (USA only) Our GMA/FMI/CIES 2002 study = 8.3% (Worldwide; 7.9% USA) A: Not Much. But there are so many new kinds of technology in scanning systems, databases, computer assisted ordering (CAO) systems, etc Background: Extent 19 Slide 20 2007 Thomas W. Gruen WHY HAVENT OOS RATES CHANGED? Technology improvements have been offset by process complexity SKU proliferation Promotional proliferation Store level assortment Store level planogramming Retailers face increased pressure to keep labor costs down Background: Extent 20 Slide 21 2007 Thomas W. Gruen SHOPPER RESPONSE 1.Do not purchase 2.Purchase elsewhere 3.Substitute same brand 4.Substitute different brand 5.Delay purchase THERE ARE 5 SHOPPER REACTIONS WHEN FACED WITH AN OOS: 21 Slide 22 2007 Thomas W. Gruen How Do Shoppers Respond to Out of Stocks? When a shopper confronts an out-of-stock: SHOPPER RESPONSE Retailers are likely to lose on Avg. 40% of the intended purchases Manufacturers lose 35% of intended purchases 22 2007 Thomas W. Gruen Slide 23 SHOPPER RESPONSE REGIONS Note differences in brand substitution across regions! 23 Slide 24 2007 Thomas W. Gruen 24 SHOPPER RESPONSE Varies Greatly by Category Range of store switch varies from 13% to 40% Fem Hygiene buys at another store 3 times more than Towels 24 Slide 25 2007 Thomas W. Gruen 25 SHOPPER RESPONSE Grocery Store Featured Category Source: ECR-UK 2005 Slide 26 2007 Thomas W. Gruen 26 SHOPPER RESPONSE Drug Store Featured Category Source: ECR-UK 2005 Slide 27 2007 Thomas W. Gruen Multiple Out-of-Stocks In a Single Shopping Trip Can Cause the Shopper to Leave the Store Source: GS1 Columbia, Diagnosis Report, 2007 27 Slide 28 2007 Thomas W. Gruen 28 QUIZ QUESTION: EFFECT OF MULTIPLE OOS IN A SINGLE TRIP With an average OOS level (8%) and a shopper purchasing 40 items statistically what % of trips will he/she be completely satisfied (i.e. no OOS)? A. 4% B. 24% C. 44% D. 64% E. Cant tell from the information given Slide 29 2007 Thomas W. Gruen 29 From Appendix E, p. 65 Slide 30 2007 Thomas W. Gruen 30 LIKELIHOOD OF 100% CUSTOMER SATISFACTION If a retailer can cut the OOS rate in half, the potential for 100% satisfaction skyrockets! Thanks to Synchra Systems, Inc. for this chart! Slide 31 2007 Thomas W. Gruen 31 IMPLICATIONS: RETAILER SALES LOSSES DUE TO OOS ARE ABOUT 4 PERCENT Sales Losses are similar worldwide, but vary greatly among categories 31 Slide 32 2007 Thomas W. Gruen Calculating a companys lost sales from OOS: OOS Rate _______% x Category Avg Lost Sales_______% x Total Category/ Organization Sales $_____ = Sales Lost to OOS $_____ Example: Avg OOS rate8% X MFR Avg Loss30% X Category Sales$1B = Lost sales $24,000,000 Typical Retailer Sales Loss/$1B total sales is about $32 million 32 Slide 33 2007 Thomas W. Gruen 33 FINDINGS: IMPLICATIONS The implications of our findings suggest that the cost of out-of-stocks to retailers is greater than what has been reported in previous studies. Our findings show that a typical retailer loses about 4 percent of sales due to having items out-of-stock. A loss of sales of 4 percent translates into a earnings per share loss of about $0.012 (1.2 cents) for the average firm in the grocery retailing sector where the average earnings per share is about $0.25 (25 cents) per year. Slide 34 2007 Thomas W. Gruen Motivation Additional Costs OOS Lowers Impact of Promotions and Trade Promotion Funds OOS Distorts True Store Demand, thus Forecasting, Category Management and Related Efforts are Less Accurate and Effective OOS Increases Overall Costs of Relationship with Retailer (Increased Post-Audit Activity, Irregular Ordering) OOS Distorts True Shopper Demand thus Decreases Forecasting and Ordering Accuracy Operational Costs are Increased through Personnel Looking for OOS Items, Providing Rain Checks to Shoppers, Unplanned Restocking, etc. (could be $1.0 Million for 100 stores) Direct Loss of Brand Loyalty and Brand Equity OOS Encourages Trial of Competitor Brands Lowered Overall Effectiveness of Sales Team Resources Direct Loss of Store Loyalty Decreased Customer Satisfaction OOS Encourages Trial of Competitors Stores Permanent Shopper Loss Rate is Undocumented, but Annual Cost is US$1 Million per Every 200 Shoppers ManufacturersRetailers Operational Strategic Slide 35 2007 Thomas W. Gruen Costs of Addressing OOS in Store For Retailers: Labor Spent Satisfying Shopper OOS Questions $800/week/store for an Average Food Store About $4.1million annually 100 stores For Shoppers: Shoppers spend >20% of the Average Shopping Trip Waiting for an Answer 35 Slide 36 2007 Thomas W. Gruen Lets Examine the Causes of Out-of-Stocks Where does the breakdown occur? Supply chain? Retailer ordering? Retailer merchandising? Uneven consumer demand? 36 Slide 37 2007 Thomas W. Gruen 37 Lowering OOS Begins With Understanding the Causes of OOS Retail store ordering and forecasting causes (about of OOS) Retail store shelving and replenishment practices where the product is at the store but not on th