Inventory Forecasting: It Doesn't Take a Village, Just Marketing and Merchandising

Transcription

1 Inventory Forecasting: It Doesn't Take a Village, Just Marketing and Merchandising ACCM, May 2007 Presented by: Gina Valentino Presented by: George Mollo, Jr. Owner Hemisphere Marketing President GJM Associates, Inc. 1

2 What You ll Learn Why forecasting is important What are the components How to spot trends What data is used next year Who else is using the data...right now 2

3 Forecasting Overview Forecasting is the term used to mathematically predict how many orders will placed during the life of the catalog. What does the life of the catalog mean? It s the term used to identify a period of time--specifically referring to the day the very first order is taken to the day the last order is taken from a single marketing effort (i.e. Drop 1 of a Catalog) 3

4 Why Forecast? Order and Revenue Stream By initiative (i.e. catalog, , etc.) By Day, Week, Month, Year, Drop Cross-Company Uses Marketing Merchandising Call Center Distribution Center Finance 4

5 Forecasting Helpful Hints Spreadsheet based; link as much as you can, note hardcoded data, build an assumptions page, and think ahead Excel only has 256 columns thus, do not put daily info across (horizontally) Determine which days begin and end the week to ensure your operational systems agree Usually data is Gross not Net check your system(s) with other departments Link information Forecasting goal: be +5% -5% by week The more historical data, the more reliable the forecast 5

6 Forecasting Where to Begin Display a large year-at-a-glance wall calendar Use the Contact Strategy and Circulation Plan Create three main Excel workbooks A. Daily [07Daily] B. Response Curves & Forecast [07RCF] C. Sales & Order Forecast [07Calendar] Hint: Always begin file names with the year, and add alpha suffix to indicate revisions 6

7 Contact Strategy & Circulation Plan Example: Summary of Contacts Jan Fall 1 Drop 1 Fall 1 Drop 2 Fall 2 Drop 1 Holiday 1 Drop 1 Holiday 1 Drop 2 Holiday 1 Drop 3 Feb Mar Apr May Jun Jul M 7/10 Aug Sep Oct Nov Dec M 8/7 M 9/11 M 10/9 M 11/6 M 11/27 7

8 Contact Strategy & Circulation Plan Example: Circulation Plan Summary Season Drop Mail Date Event Mail Qty GDS Ords AOV $/bk rr% Fall 1 Drop 1 Drop 2 7/10/2007 8/7/2007 Summer R 225, ,000 $693,000 $380,625 15,750 8,750 $44.0 $43.5 $3.1 $ % 5.0% Fall 2 Drop 1 9/11/2007 BTS 225,000 $693,000 15,750 $44.0 $ % Holiday Drop 1 Drop 2 Drop 3 400,000 $1,531, ,000 $382, ,000 $300,125 31,200 7,500 6,125 $49.1 $51.0 $49.0 $3.8 $3.1 $ % 6.0% 4.9% 10/9/2007 Fall 11/6/2007 with Gifts 11/27/2007 R 8

9 Excel Workbook: 07Daily Example: Daily Tallies Day Sun Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Date 5/28/2007 5/29/2007 5/30/2007 5/31/2007 6/1/2007 6/2/2007 6/3/2007 6/4/2007 6/5/2007 6/6/2007 6/7/2007 6/8/2007 6/9/2007 6/10/2007 All Daily All $ales Orders Sales % Daily Daily by Week $1, % $1, % $1, % $1, % $1, % $1, % $2, % $2, % $1, % $1, % $1, % $1, % $1, % $2, % Cume Cume Daily Cume Cume Weekly Weekly Ords % Weekly Weekly $ales Sales % by Week Orders Orders % $1, % 14.5% % $3, % 14.9% % $5, % 14.1% % $7, % 13.3% % $8, % 11.8% % $10, % 14.1% % $12, % 17.3% % $2, % 15.5% % $3, % 14.7% % $5, % 14.0% % $7, % 13.2% % $8, % 11.6% % $10, % 14.0% % $12, % 17.1% % Look for patterns in daily percentages. Use patterns to forecast sales and orders. Cume Cume Monthly Monthly Year to $ales Orders Date $ales $55,450 1,432 $251,900 $57,200 1,470 $253,650 $59,000 1,506 $255,450 $60,700 1,540 $257,150 $1, $258,650 $3, $260,450 $5, $262,650 $7, $264,660 $9, $266,570 $11, $268,380 $12, $270,090 $14, $271,600 $16, $273,410 $18, $275,620 Year to Date Orders 4,938 4,976 5,012 5,046 5,076 5,112 5,156 5,196 5,234 5,270 5,304 5,334 5,370 5,414 Daily AOV Yr AOV

10 Using the Daily Numbers Using the overall percentages by week, you can begin to forecast weekly response for each mailing. Divide the day s actual performance by percent of the week it represents. Sun Mon Tue Wed Thur Fri Sat Daily Daily GDS % Orders % by Week by Week 15.5% 15.5% 14.7% 14.7% 14.0% 14.0% 13.2% 13.2% 11.6% 11.6% 14.0% 14.0% 17.1% 17.1% For example, if the Total Orders from Sunday is 45 then divide 45 by 15.5% to calculate the forecast for the week. The answer is 290 forecasted orders for the week. 10

11 Using the Daily Numbers You try it: The combined number of orders for Sunday and Monday total 300 Based upon the chart to the right, what is the order forecast for the week? Sun Mon Tue Wed Thur Fri Sat Daily Daily GDS % Orders % by Week by Week 15.5% 15.5% 14.7% 14.7% 14.0% 14.0% 13.2% 13.2% 11.6% 11.6% 14.0% 14.0% 17.1% 17.1% 11

12 Using the Daily Numbers You try it: The combined number of orders for Sunday and Monday total 300 Based upon the chart to the right, what is the order forecast for the week? Sun Mon Tue Wed Thur Fri Sat Daily Daily GDS % Orders % by Week by Week 15.5% 15.5% 14.7% 14.7% 14.0% 14.0% 13.2% 13.2% 11.6% 11.6% 14.0% 14.0% 17.1% 17.1% ANSWER 300 divided by 30.2% (15.5%+14.7%) equals 993 orders 12

13 Excel Workbook: Response Curves Ideally, build individual performance history for each initiative Using the same template (from the daily sales & forecast tally), develop historical response information Along side the historical, build the actual performance Track the variances 13

14 Response Curves Example: Historical Order Curve 30% 28% 25% 22% 20% 18% 15% 15% 10% 10% 5% 0% 5% 2% Week 0 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 14

15 Response Curves By week four, 85% of the orders are complete ( ) Example: Forecast for the Fall 1 Drop 1 Mailing Circulation Budget Orders Budget GDS Historical Curve Budget Orders Actual Orders % Variance Historical Curve Budget GDS Actual GDS % Variance Budget AOV Actual AOV 225,000 15,750 $693,000 Week % Week % 2, Week % 3, Week % 4, Week % 2, Week % 1, % -2.6% 2.5% -0.3% -8.3% -4.9% 2.20% 15.30% 22.00% 27.80% 17.90% $15,246 $106,029 $152,460 $192,654 $124,047 $14,444 $104,000 $154,852 $193,000 $113, % $62,370 $61, % $48.40 $ % $44.88 $ % $44.00 $ % $43.69 $ % $43.76 $ % $39.60 $40.72 Week 6 Total 5.00% % , , % -2.0% 5.80% % $40,194 $693,000 $41,414 $682, % $51.04 $ % $44.00 $

16 Response Curves Sample Chart: Orders 5, , , , , Budget Orders Actual Orders 16

17 Spotting a Trend Budget Orders Forecast Orders Actual Orders 5,000 4,410 4,500 4,000 3,500 Actual running 28% below budget Reduce FC by 28% 3,465 3,182 3,000 2,835 2,500 2,500 2,363 2,045 2,000 1,575 1,700 1,500 1,136 1, Week 0 Week 1 Week 2 Week 3 Week 4 Week 5 Week 17 6

18 Spotting a Trend 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, Week 0 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 18

19 Trend Tips Watch the cumulative Question the segmentation Question the mailing distribution Uncontrollable circumstances Be patient and discuss with Inventory Control 19

20 Forecasting Double check formulas Add hidden true/false to help catch errors Always add to 100% Forecasting orders is foremost Remember end of the calendar year carry-over data Have one person who forecasts knowledge builds based upon experience Include narrative by day to explain oddities (wall calendar is very helpful) Forecasting is only as good as the data available 20

21 Working Together Annual planning Marketing builds by catalog based upon the customer file more top down development Inventory Control builds from the ground-up and across catalogs Have ONE counterpart Sounding board, discussions, problem solving Utilize expertise and departmental knowledge 21

22 No Tarot Cards Necessary Data drives decisions History does repeat itself Information impacts Inventory, Customer Service, Warehouse and Finance Work together to be accurate and have consensus 22

23 Bridge to Inventory Forecasting 23

24 Review Marketing Approach Inventory Approach Combined forces yield consistent results However. Take a step back To properly forecast we must PLAN!!! 24

25 Inventory Accuracy Starts with Analysis/Planning Communication Planning Process (top down) Item Planning (bottoms up) Relationships Creative Information Conscious of Timing 25

26 Merchandise Analysis Definition: The application of a consistent set of metrics to the catalog merchandising effort in support of the overall business Why? Supports the planning effort Establishes discipline Forces cost analysis Flushes out hidden problems in the business 26

27 Purpose of Plans Provides a Blueprint ( MAP ) Ensures Brand Consistency & Focus Sets Clear Merchandise Focus Avoids Paradox of Choice Establishes Control Points High Level Approach Understand Horizon View 27

28 Planning Process Overview Take A Simple & General Approach Improve majority of items - Don t try for 100% accuracy on all items ALMOST Right NOW is better than EXACTLY Right Later! Reduce exceptions Use Historical Analysis Plan by Horizon/Season not by Drop 28

29 Plan! Plan!! Plan!! Process should start 6-12 months before mailing Consider product lead times (photography and catalog availability work backwards from mail date) QA issues Importing vs. Domestic Issues (lead times, margins, rebuy times, etc.) Merchandise Assortment Plans (top down) Item Level Plans: Repeat/New (bottom up) Focused targets to Value, Price Points & products appropriate to target niche 29

30 Planning Factors (Category) Four Key Factors: Item Counts (based on pages/density) Demand Space Allocations Space Costs (not necessary but ) 30

31 Planning Factors (Category) Assortment Planning Key factors to consider Productivity Index (Category) (% of demand / % of items) Space Index (Category) (% of demand / % of space) Ad to Sales Ratio (Sell Ratio) (Item percent of page * cost per page) / Projected item $$ demand in Offer Page Average Editorial pages included? 31

32 Merchandising Planning/Forecast Key factors to consider Top Item Forecast vs. Bottom Item Forecast Relationship (within a dept.) Price Points (category and overall) Average Price offered vs. Average Price Sold Average Item Index (relationship of an item to all others) Use Averages (Page, Spread, Item, etc.) If calculated as an index --- provides directional information and highlights anomalies. 32

33 Merchandise Analysis Price Point Analysis Average Price Offered versus Average Price Sold Average Price Offered = the subconscious view of price/value Average Price Sold = Customers reaction to your price points/value Factoid: Difference should be +/- 20% 33

34 Demand Is All Demand captured? Why is it Important to Capture all Demand? Shadow/Lost Demand Are there limits? Not sure? Test Order w/ mixed BO & in stock 34

35 Impact to Forecasting False conclusions dropping wrong items/colors/sizes Buying wrong items (overstock) Hidden Impacts Increased list rental/acquisition costs Understated response rates Overstated fill rates Increased overstock (across the board) greater risk with wide variation in price points offered 35

36 Planning Factors (Item) Item Relationships (More may be LESS). New vs. Repeat Item relationships Space Allocation (% of page) & Location Margin Targets & Price Points Average Price Offered vs. Sold Estimated Item Profitability Vendor Performance History 36

37 Vendor Relationships Impact on timing -- Treat vendors as partners Share information Understand their process before blame The Godfather rule This will improve your forecasting and reduce backorders! 37

38 Forecasting Tips Do NOT confuse forecasting with buying Always consider the time horizon Mollo s Rule of Forecasting Cause of Backorders? 30-40% of backorders are caused by bad timing, not bad forecasts Walk the Wall Build Internal communications Call center Distribution center Management 38

39 Forecasting Tip Horizon Planning Inventory Buying can be Scheduled on a Horizon (and allow for less costly changes) Benefits to Other Areas Creative costs can be substantially reduced DC supplied forecasts for bin profiling and setup Last minute exceptions - handled more efficiently 39

40 Merchandising Strategy 40

41 Merchandising Strategy Assumptions Products fatigue if not reinvented or renewed. Best customers need more newness because of their interest in the book and rate of purchasing activity. The cost of paper and postage will continue to increase. Competition will continue to increase in all distribution channels. (MO/Store/E- commerce). No more than 1/3 of new products are winners Perform above book average Are profitable 41

42 Merchandising Strategy Axiom: Sales in a typical catalog, regardless of product category, are distributed across items as follows. Best selling Middle Bottom 1/3 1/3 1/3 2.0x book average.8x book average.26x book average Be cognizant and constantly strive to replace the bottom 1/3 with winners; thereby improving the overall performance of the offer. 42

43 Merchandising Strategy Axiom: As items (space, pages, circulation, etc). are increased or decreased the impact on sales is equal to between 1/3 to 1/ 2 of the change. e.g., If we increase the space devoted to an item by 60% we would expect the sales of the item to increase between 20 and 30%. Rule of 50: Changes will only yield 50% of the expected results! 43

44 Item Selection Tips Set Thresholds Margins (within category targets) Sell Ratio Return Rates Factor any Additional Costs Carrying Costs Special Prep or Shipping Costs 44

45 Item Selections Relationships Price Points (within Category) Competition (External & Internal) Ranking (A-B-C) Forecasting Accuracy Guaranteed to Improve Establish a Pro-Forma Item P&L 45

46 Marketing Mdse/Inv Overall success is dependent on the relationship and cooperation between these two essential disciplines (and other departments). They are the critical presiding decision makers that control the book content and customer reach. They are a check and balance on each other. 46

47 Final Thoughts!!! Parting Rules of Business Almost Right Now is Better than Exactly Right later.. A bad decision is better than no decision at all! Do 1st things First, 2nd things NEVER! Always tell the bad news first-never last 47

48 Questions? Thank you for your attention!! 48

49 Inventory Forecasting: It Doesn't Take a Village, Just Marketing and Merchandising ACCM, May 2007 Presented by: Gina Valentino Presented by: George Mollo, Jr. Owner Hemisphere Marketing President GJM Associates, Inc. 49