Partnering in a Shared Supply Chain - A Case for Data Quality Kathy Welch Master Data, Wegmans Food Markets, Inc. Rob Hoffman Mgr OTC / Customer

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2 Partnering in a Shared Supply Chain - A Case for Data Quality Kathy Welch Master Data, Wegmans Food Markets, Inc. Rob Hoffman Mgr OTC / Customer Supply Chain, The Hershey Company Jeff Cowan Industry Development Director, GS1 US

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4 Agenda Wegmans Food Markets Partnering in a Shared Supply Chain A Case for Data Quality Transforming our Business The Hershey Company Where we Started Where we are Heading GS1 US National Data Quality Program

5 $7+B Retailer Founded in 1916 Headquartered In Rochester, NY 88 Stores With 45,000+ Employees Fortune 100 Best Companies To Work For The Best Super Market in America

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8 Partnering in a Shared Supply Chain Collaboration Trusted Data Eliminate disruptions & delays Remove or reduce costs Improve efficiency in warehouse and transportation Maintain consistent low prices, and consumer gains in service levels Advance tracking and monitoring Eliminate invoice disputes Speed to shelf with new items Advance in Omni-channel and trusted data for our consumers Do what s right for our communities (food safety, sustainability, product info.)

9 What Makes a Great Trading Partner? Proactive communication Actively involved in goal setting process Tracks and achieves goals Senior management commitment and involvement Cross functional participation at supplier/retailer meetings Good training process for new personnel Sense of urgency at all levels to handle issues Highest level of data quality with strong data governance Standardized methodology for sharing product information with customers and consumers Continuous improvement philosophy

10 Best Practices at Wegmans Synchronizing quality item data involves good business practices and a company wide understanding of industry standards (people, processes and technology) R&D, Package Engineering, Data Sync, IT and Sales Establish a protocol for your data that follows the GS1 Package Measurement Rules and GTIN Allocation Rules At Wegmans, new item introduction should provide complete and accurate information GTINs should be published prior to item introduction. Align your sales team with an accurate data source Provide the resources for your sales team to know if new items have been successfully published before item introduction Manage any changes to Net Content and Case Pack Changes in accordance with GTIN Allocation Rules.

11 Vendor Supply Chain Score Card Data Inventory Metric Previous Current Variance Metric Previous Current Variance GENERAL MILLS (PILLS) CRP Goal Year Period to Goal Trend Goal Year Period to Goal Trend Master Data Completeness 100% 100.0% 100.0% 0.00% Graph WHS Days of Supply (Dollars) Data Synchronization 98% 97.0% 98.0% 0.00% Graph WHS Days of Supply (Cases) Item Data Accuracy (33 audits) 100% 91.4% 93.7% -6.29% Graph Store Days of Supply (Dollars) N/A N/A Invoice Accuracy 98% 100.0% 100.0% 2.00% Graph DC to Store Service Level 95% 91.2% 98.4% 3.4% Graph Graph Graph Graph TRUE Metric Previous Current Variance Previous Current Variance Goal Year Period to Goal Trend Year Period to PY Trend Order Cycle Time (Days) Graph PO Count Graph Supplier Service Level 98% 99.5% 100.0% 2.00% Graph Expected Avg. Unload Time (Hours) Graph PO Requested On Time Delivery 90% 71.0% 86.0% -4.00% Graph Vendor Item Count Graph On Time Delivery 98% 71.0% 71.0% % Graph Terms (Days) Total DOS Variance OVERALL SC PERFORMANCE % - Graph Terms / Total DOS Freight EDI Forecast Freight / EDI WFM YES NO Order/Delivery Process Other Metrics and General Information GOALS Meets or Exceeds Goal (Under for DOS) Within 10% of Goal More than 10% off of Goal

12 A Case for Data Quality

13 Quality Data is a Competitive Advantage in an Information Driven Supply Chain COMPLETE. CONSISTENT. ACCURATE. ON TIME. STANDARDS BASED

14 A Case for Data Quality Increased customer satisfaction and confidence, access to trusted source of product information, eliminate confusion, reduce returns and influence sales with rich content Right product delivered to the right place, at the right time, and first to market strategies require accurate data Enhanced trading partner collaboration Improved efficiencies across all business processes Business processes for both supply and demand that benefit: Master Data Governance Data Synchronization Supply Chain Transportation, Warehouse Management, Shelf Sales and Marketing Information Technology Accounting reduced invoice payment delays

15 Quality Data Equals Better Business Performance Maintaining quality and complete data is the essential foundation for advancement in critical systems and tools. When data is consistently accurate, it enables trading partner relationships to work on value-added projects, and less time on fixing issues. Sharing up to date and timely data realizes increased supply chain efficiencies, and a competitive advantage in the marketplace. Access and Visibility allows employees to spend significantly less time searching for information and fixing errors. Executive Management support provides critical resources necessary for a sustainable data quality environment

16 Companies with a strong data governance program ensure processes and procedures are in place to establish and maintain accurate data over the lifecycle of their products. Adhere to GS1 Standards and Rules for foundational attributes in internal setup Assign data owners throughout the organization Appoint one entity/department/individual as the sole owner of product data Audit all new items produced in a sustainable production environment ready for shipment (finished goods) Execute communication on attributes, both internally and externally

17 GS1 US National Data Quality Program 2015 GS1 US, Inc. All rights reserved. Details can be found in the GS1 US National Data Quality Program Framework.

18 Transforming our Business Accurate & consistent information across channels Enriched omni-channel shopping experience Build improved processes and leverage advanced tools that rely on quality item information Collaborate on value added projects with our best trading partners.

19 Rob Hoffman Manager OTC / Customer Supply Chain

20 The Hershey Company The Hershey Company (NYSE: HSY), headquartered in Hershey, PA is a global confectionery leader. Approximately 13,000 employees globally Over 80 brands that drive over $7.1 Billion in annual revenue Milton Hershey School for underprivileged children, established in 1909, is administered by the Hershey Trust Company. The children attending the school receive education, housing, and medical care thriving as direct beneficiaries of The Hershey Company s success

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22 Partnering in a Shared Supply Chain Collaboration Trusted Data Eliminate disruptions & delays Remove or reduce costs Improve efficiency in warehouse and transportation Maintain consistent low prices, and consumer gains in service levels Advance tracking and monitoring Eliminate invoice disputes Speed to shelf with new items Advance in Omni-channel and trusted data for our consumers Do what s right for our communities (food safety, sustainability, product info.)

23 Partnering in a Shared Supply Chain We Share The Same Goals Collaboration Provide our consumers a positive experience Efficiently Timely Accurately As cost effectively as possible Sharing QUALITY data is the only option! Trusted Data 23

24 Where Hershey Started Milestones 2002 Publishing to the GDSN Data quality questions from our partners 2006 Top to Top Meeting with Wegmans Transformed our production data collection process Implemented governance process to ensure case weights & dimensions were updated during 1 st production Initiated audit process to capture weights and dimensions at all levels of packaging

25 Product Audit Process Transformation of product data collection and product audit process

26 Where We Are Headed Attribute Explosion!! Forcing us to look at data quality well beyond the size and weights of our physical products Number of Attributes

27 Where We Are Headed Ownership of the data is top priority Governance structure who owns and manages what data Without data governance, publishing accurate data is a gamble Data Governance Education Why is it necessary to govern and provide quality data? Adherence to GS1 Standards and Package Measurement Rules provides consistency for End-to-End Supply Chain Data Management Technology Product Information Manager (PIM) PIM will assist in the governance process

28 PIM Benefits 3 Primary use cases: 1. GDSN 2. SmartLabel 3. ecommerce PIM enables Hershey to: Simplify the aggregation of product data across multiple source systems Publish product data in a consistent and accurate manner Highlight data governance concerns Comply with new GDSN standards and customer requirements

29 SmartLabel What is it? An initiative to align manufacturers on an industry solution to provide consumers with product information via mobile and web technology Consumers are increasingly interested in what s in the products they buy, where they come from, and how they are made The consequences of inaccurate allergen data being shared with a consumer can be extreme Sharing QUALITY data is the only option!

30 ecommerce Consumers require a high level of trust before making an On-line purchase. On-line purchasing decisions are highly dependent on the accuracy of the product data shared. It is the difference between a positive or negative experience. VS Sharing QUALITY data is the only option!

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32 The Five Reactions to Data Quality 1. Denial (Shock & Numbness) Overwhelming task too much data in too many places. Internal alignment issues The data belongs to the other guy. Alienation and fear Good Luck with that. 2. Anger (Reacting & Push Back) The data is fit for use. We are doing fine and getting orders out despite the data. Frustration and even blocking Go fix the problem but don t change anything. 3. Bargaining (Yearning and Searching) We ll do better ongoing. Promises to review the current process GS1 US ALL RIGHTS RESERVED

33 The Five Reactions to Data Quality 4. Depression (Despair, Disorganization, Blocking) Fits and starts of the process. Unrealistic delays. Status Quo. 5. Acceptance (Reorganization and Recovery) Get the right tools and technology to scale up to a practical level. Alignment around solid, repeatable processes. Integration across constituent parties. Celebration of confidence in data GS1 US ALL RIGHTS RESERVED

34 Case for Change Cost of Doing Business Strategic Point of Difference Transactional Data for Supply Chain Enriched Data for E-Commerce Aggregated Data for Consumer Insight Consumer Experience & Engagement 2016 GS1 US ALL RIGHTS RESERVED

35 The Case for Certification A certification program provides the industry with a consistent, standards-based approach to ensure the proper processes, and procedures are in place to ensure consistent, accurate, complete data over time. Short-term: reduces the need for demand-side audits and scorecards while their supply-side partners modify their current business practices. Long-term: eliminates the need for demand-side audits and scorecards. Creates efficiencies for all trading partners GS1 US ALL RIGHTS RESERVED

36 Aggregate Item & Case Scorecard ITEM Sample Size: 1,754 unique GTINs Physical Audit compared to Master Data CASE Sample Size: 1,700 unique GTINs Physical Audit compared to Master Data KPI % Accurate KPI % Accurate Item Accuracy* (height, width, depth) 79.5% Case Accuracy* (height, width, depth, gross weight) 55.5% Pack Quantity 73.3% Country of Origin (COO) 89.1% Brand 54.2% Declared Net Content /UoM 97.3% Pack Quantity 79.3% Country of Origin (COO) 78.0% Brand 78.2% Declared Net Content / UoM NA *Item Accuracy Detail *Case Accuracy Detail KPI % Accurate KPI % Accurate Height 85.2% Width 88.7% Depth 87.7% Height 85.2% Width 91.8% Depth 93.3% Gross Weight 71.4% 2016 GS1 US ALL RIGHTS RESERVED

37 National Data Quality Program Path Retail Grocery Educate NDQ Workshops Measure NDQ Program Execution Healthcare Apparel/GM Define NDQ Program Foodservice Analyze Current State FOUNDATIONAL PROGRAM: CURRENT FOCUS July 2013 Present 2016 GS1 US ALL RIGHTS RESERVED

38 What does the Program cover? Certification 2015 GS1 US, Inc. All rights reserved.

39 Certification Process & Scoring Data Governance Process: Within the GS1 US National Data Quality Program, an organizations master data management and data governance process is assessed to determine the degree which people processes and procedures are in place to ensure quality data is maintained. Organizations with centralized business processes and business systems will only need to be certified once. Organizations with disparate processes and systems will need to be certified for each process/system. Must achieve a minimum score of 90% GS1 US ALL RIGHTS RESERVED

40 Data Quality Assessment The Data Quality Assessment asks probing questions regarding: Data Governance Data Quality GTIN Management Product Management Attribute Accuracy Data Synchronization Training 2016 GS1 US ALL RIGHTS RESERVED

41 Certification Process & Scoring Education & Training Protocol: Individuals responsible for the data should take the quiz for areas within their responsbility determined by supplier. Each individual must achieve a minimum score of 90% GS1 US ALL RIGHTS RESERVED

42 Certification Process & Scoring Attribute Audit Conducted by category to ensure a sample of all packaging types and configurations. Based upon a representative sample of new and existing items. Must achieve a minimum score of 90% accuracy for all KPI s at the item and case. There is an opportunity to remediate and reconcile results; and opportunity to re-audit. Details can be found in the GS1 US National Data Quality Program Framework GS1 US ALL RIGHTS RESERVED

43 Foundational Brand Name Initial Data Quality Attributes Declared Net Content/UoM Pack Quantity GTIN Once the GTIN is shared with a trading partner a change to any of these attributes, independent of which stage in the product development cycle (preproduction or production will need to adhere to the GS1 GTIN Allocation Rules. Fundamental Linear Dimensions (height, width, depth) * Gross Weight /UoM* Country of Origin Ti-Hi *Overall Accuracy: if any of the linear dimensions or gross weight is out of tolerance the item/case is considered inaccurate. A change to any of these attributes in the product pre-production stage does not require adherence to the GS1 GTIN Allocation Rules. Once in production the rules will need to be adhered to GS1 US ALL RIGHTS RESERVED

44 GS1 US National Data Quality Program Organizations can apply to GS1 US or a certified Solution Partner for certification. Several options exist for certification: Category Business Unit Business Process Business System Organizations determine how they will become certified (e.g., single category, all categories at once, etc.) GS1 US ALL RIGHTS RESERVED

45 The Importance of Data Accuracy The Effect of a Quarter Inch XYZ Widget Company Hypothetical Widget *Pallet Height Limit is typically 56 inches (including wooden pallet) Scenario 1 (Published Data) Case dimensions in x 7.68 in x 5.25 in Actual Pallet pattern = 20 x 9 = 180 cases Full trailer (double stacked) = 50 pallets, or 9,000 cases Scenario 2 (Physical Reality) Case dimensions in x 7.68 in x 5.00 in Potential Pallet pattern = 20 x 10 = 200 cases Full trailer (double stacked) = 50 pallets, or 10,000 cases, 1,000 more cases than originally configured! The quarter inch buffer per case allows an additional layer to be added to the pallet and still meet the 56 inch limit GS1 US ALL RIGHTS RESERVED

46 The Importance of Data Accuracy The Effect of a Quarter Inch Let s say that there were 500,000 cases of the XYZ Widget sold in 2015 Scenario 1 (Published Data) 9,000 cases per trailer Approximately 56 trailers Let s say it costs $3,000 to ship a trailer $168,000 total cost Scenario 2 (Physical Reality) 10,000 cases per trailer Approximately 50 trailers Let s say it costs $3,000 to ship a trailer $150,000 total cost Shipping 6 less trailers would equate to about $18,000 in savings in the grand scheme of things, this may not sound like much, but remember this is only for one product that XYZ Company makes. Let s pretend that XYZ Company has 200 SKUs, and only 3% of them have the height overstated in a similar fashion. That would be $108,000 in potential savings! 2016 GS1 US ALL RIGHTS RESERVED

47 Tools - GS1 US National Data Quality Program Documents GS1 US National Data Quality Program Framework GS1 US National Data Quality Program Assessment GS1 US National Data Quality Program - Data Governance Best Practice Guidance Quick Start Guidance GS1 US ALL RIGHTS RESERVED

48 Contact Information Jeff Cowan Industry Development Director GS1 US TEL Connect with the GS1 US community on 2016 GS1 US ALL RIGHTS RESERVED

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