134: The Value of Item Master Data Management Mike Lapchick, Shotfarm John Poss, Ace Hardware Corporation

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1 134: The Value of Item Master Data Management Mike Lapchick, Shotfarm John Poss, Ace Hardware Corporation June 12,

2 THE VALUE OF ITEM MASTER DATA MANAGEMENT Session Description When trading partners exchange data beyond basic item information, retailers and suppliers both benefit from increased efficiencies along the supply chain. This session will focus on understanding the importance of deploying an item master data management solution to enable continuous process improvements for your business. Topics will include marketing data/attributes, warehouse management business processes, supply chain benefits, data governance and scorecarding. 2 2

3 WHAT WILL YOU GET OUT OF THIS SESSION Marketing Data Attributes Supply Chain/Warehouse Data Governance Scorecards 3 3

4 WHY YOUR ORGANIZATION NEEDS TO HAVE AN ITEM MANAGEMENT PROGRAM Retailers: Order Management Systems Catalog Management Systems Warehouse Management Systems ERP PIM/Internal Catalog Wholesalers/Suppliers: Support all systems 4 4

5 THE PRODUCT DATA SPECTRUM Supply Chain Data Example: Pallet Size, Container Weight, Pack Count Owned by: IT, SupplyChain Systems: SAP, JDA Exchange: EDI, GDSN, SAS Importance: Minimized Delivery Delays Reduced Stocking Delays Efficient Order Fulfillment Inventory Control Overlap Ecommerce/Marketing Data Example: Features & Benefits, Images, Video Owned by: Marketing & Ecommerce Teams Systems: MDM, PIM, DAM Exchange: Manual Importance: Speed to Market Reduced Resource Costs Higher Conversions Fewer Returns 5 5

6 6 6

7 WHAT WILL YOU GET OUT OF THIS SESSION Understand the where Marketing and Ecommerce data fits within the Product Data Spectrum, who owns it and what channels it serves. Understand fail points within the typical Product Data Workflow Understand the importance of data accuracy, quality, and completeness Ideas on how to develop a workflow and toolset strategy that will allow your ecommerce business to scale 7 7

8 THE PRODUCT DATA SPECTRUM Supply Chain Data Example: Pallet Size, Container Weight, Pack Count Owned by: IT, SupplyChain Systems: SAP, JDA Exchange: EDI, GDSN, SAS Importance: Minimized Delivery Delays Reduced Stocking Delays Efficient Order Fulfillment Inventory Control Natural Overlap Ecommerce/Marketing Data Example: Features & Benefits, Images, Video Owned by: Marketing & Ecommerce Teams Systems: MDM, PIM, DAM Exchange: Manual Importance: Speed to Market Increase Conversions Reduce Returns Reduce Labor Costs 8 8

9 E-COMMERCE / MARKETING DATA Definition Any field of product data that can affect a consumer s buying decision. The Product Dataset Checklist Accuracy: Correct Measurements and Specifications, Color-corrected Images Quality: High resolution professional images, well-written descriptions, clear meanings. Completeness: All of the attributes and media necessary to make a buying decision in that category Why they re so important Increase Speed to Market Increase Sales/Conversions Reduce Returns Reduce Labor Costs SEO (Search Engine Optimization) & Marketplace Differentiation 9 9

10 E-COMMERCE / MARKETING DATA Clearing the air If this dataset is so important, why don t my suppliers have good data on their own products? Manufacturers do have the data There are no low resolution cameras! Okay so then why can t I get it from them? Too many channel and partner requirements Too many systems & owners internally Asking the wrong person Not enough time 10 10

11 E-COMMERCE / MARKETING DATA Increase Conversions In order to have a web page that produces average conversion rates, product specifications, descriptions and at least one image are required. To produce above average conversion rates, additional high resolution content is required

12 E-COMMERCE / MARKETING DATA Reduce Returns Facts What would your company spend on marketing to increase sales by more than 10%? In 2014, online product returns cost US retailers nearly $26B or 10% of all online sales. Much of this 10% can be regained quickly and inexpensively with more accurate product data. Top Reasons: Didn t fit Wasn t as described Specifications were inaccurate The product or color was different than it appeared online Wrong Product/Size received Changed Mind 12 12

13 E-COMMERCE / MARKETING DATA Increase Speed to Market Facts A reseller cannot begin selling a product online without product information. 90% of ecommerce/marketing data is transferred manually and without process. 93% of all product data requires some modification by the reseller which adds delays and opportunities for error. Almost every pair of trade partners has its own way of requesting, transferring, identifying, and formatting product information. Reasons: Manufacturers are challenged by too many requests and formats No centralized exchange 13 13

14 E-COMMERCE / MARKETING DATA Reduce Labor Costs Facts The cost to get high quality content from supplier to web (request, receive, identify, enrich, reformat and upload images, video, product attributes and descriptions) can be as high as $4.25 per SKU. It takes an average of 2.2 requests to receive initial product content from a supplier with an average grade of C+ on quality and completeness of content. $5B resource inefficiency. Reasons: Manufacturers and Retailers are challenged by too many requests, formats, systems, and workflows. No centralized exchange for the management, distribution, & translation of ecommerce/marketing data 14 14

15 E-COMMERCE / MARKETING DATA Things you can do Retailers: Know that you re one of many retailers: make things as easy as possible on your suppliers. Building an in-house system for them to upload content to does not accomplish this :) Be clear, consistent and concise in your communication Don t look to Supply Chain owners for Ecommerce/Marketing Data. Manufacturers: Find a system that can accommodate ALL of your Ecommerce/Marketing Data (MDM) and make sure it can export to your partners in their format if possible. Try to avoid requiring your partners to use your proprietary system because it puts you in a line with other suppliers. Keep your data current! 15 15

16 ACE HARDWARE CORPORATION 16 16

17 SUPPLY CHAIN/WAREHOUSE DATA Global Industry Standards Product Data Exchange The Quality of Product Data Retail vs. Non-Retail Package 17 17

18 THE VALUE OF PRODUCT DATA Sample copy 18 18

19 VALUE OF PRODUCT DATA Sample copy 19 19

20 VALUE OF PRODUCT DATA Sample copy 20 20

21 THE VALUE OF PRODUCT DATA How accurate is your product data? Initial Shipment Audited YTD 44.7% of all new items presented to Ace have some kind of product data issues 37.5% Incorrect Measurements 12.5% Incorrect Weight Value 4.2% Barcode Data not Matching 21 21

22 WHAT IS A TRUCKLOAD? 22 22

23 WHAT IS A TRUCKLOAD? Truckload Orders = Truckload Deliveries at Truckload Prices? Perception vs. Reality Profits are left at the dock 23 23

24 VALUE OF PRODUCT DATA 24 24

25 VALUE OF PRODUCT DATA Pallet Information Pallet Hi / Ti Information Shared? Efficiencies in Ordering 50 Cartons = Pallet PO = 49 or 51 Cartons! Efficiencies in Filling Customer Order Avoiding Potential Damages While in Transit Distribution Labor Savings Avoiding Multiple Trips To Bin 25 25

26 VALUE OF PRODUCT DATA Product Information Are all packaging levels identified? Delays Stocking Questions Develop During Retail Order Filling 26 26

27 RETAIL STORES LOVE PRODUCT DATA Product Displays Well Product Fits as Designed Proper Spacing for Shelves Controls Inventory 27 27

28 THE VALUE OF PRODUCT DATA Who is the Key Holder of Product Data? Are New Items Audited Prior to Spec Sheet Publication? Errors or Packaging Questions May Delay Deliveries Distributor Investigates Issues Is the Product Received the Product Needed? Consumers Thrive on Information 28 28

29 SOME KEY TAKE A WAYS Labor Savings - $$$$ * Avoid Relocating Inventory if Product Information is Correct * Proper Information Identifying All Packaging Level * Avoid Potential Down Stacking Pallets if Pallet Tier Information Shared Avoid Delaying Promotional Product Delivery At Retail - $$$$ * Warehouse Investigating if Correct Product Arrived Manufacture Number Case Pack Quantity Correct? Product Measurement 29 29

30 DATA GOVERNANCE THE PRODUCT DATA SPECTRUM Supply Chain Data Example: Pallet Size, Container Weight, Pack Count Owned by: IT, SupplyChain Systems: SAP, JDA, Oracle Exchange: EDI, GDSN, SAS, 3 rd Party, Datapool Importance: Minimized Delivery Delays Reduced Stocking Delays Efficient Order Fulfillment Inventory Control Overlap Ecommerce/Marketing Data Example: Features & Benefits, Images, Video Owned by: Marketing & Ecommerce Teams Systems: MDM, PIM, DAM Exchange: Manual Importance: Speed to Market Reduced Resource Costs Higher Conversions Fewer Returns 30 30

31 VENDOR SCORECARDING If you don t report on it, you don t know how well/poorly you are doing!!!!!!! No feedback means the retailer is probably not looking at all the data. Data accuracy improves your bottom line by XYZ percent 31 31

32 THE VALUE OF ITEM MASTER DATA MANAGEMENT QUESTIONS? John Poss Mike Lapchick 32 32

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