GETTING DATA INTEGRATION AND DATA HARMONIZATION RIGHT TO ENABLE TRADE PROMOTION OPTIMIZATION. Peter Brousil Data Solutions & Strategy W. W.

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1 GETTING DATA INTEGRATION AND DATA HARMONIZATION RIGHT TO ENABLE TRADE PROMOTION OPTIMIZATION Peter Brousil Data Solutions & Strategy W. W. Grainger

2 W.W. Grainger, Inc. is a Publicly held, business-tobusiness distributor of products used to Maintain, Repair and Operate facilities. MRO Market Headquartered in Lake Forest, Illinois

3 Some of the Brands Grainger distributes include: Proctor & Gamble, Clorox, Kimberly- Clark, Johnson & Johnson, Diversey, Rubbermaid, 3M

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5 Grounding the Conversation The Data Asset: Is a collection of aligned data elements that creates a Competitive Advantage through faster, more reliable, fact based decision making, moving the enterprise away from intuition, historical and market awareness based decision making. Decision Support Systems DSS 1985 Executive Information Systems EIS 1990 Data Warehouse DW 1995 Business Warehouse BW 2000 Customer Data Integration CDI 2006 Demand Signal Repository DSR 2008 Integrated Data Store IDS 2010 Enterprise Integrated Data Asset 2014

6 Why are we still talking about this? 1. Often viewed as non-essential 2. Not directly responsible for revenue generation 3. Evolving Market Strategy Omni Channel 4. Evolving Data ecosystems 70% of CPG s agree that data quality issues exist from external sources such as POS (epos), syndicated data, etc. Source: Promotion Optimization Institute 2015 Research

7 Integrated Data Benefits 1. Quicker decisions 2. Repeatable & consistent decisions 3. More iterative decisions 4. Scalable decisions 5. Decision improvement proliferation 6. Decision clarity & accountability

8 Data Harmonization Challenges 1. Non-Aligning Data Sources Dimensional data Definitions of a week? Metrics Definitions of Sales? 2. Bad data 3. Unanticipated costs Data investigation/data quality 4. Lack of cooperation data silo s 5. Perception that Data Integration is hard 6. Investments: Projects vs Architecture

9 Data Roles Chief Data Officer and data team Center for Data Integration Client Alliance requirements & tester Data Hunter Data Source Alliance Data Ingest Data cleans/fix and propagate Data Harmonization Least Common Denominator Data Integrator align data by dimensions Data Delivery Repeatable/reliable

10 Data Tasks 1. Establish a detailed set of rules for the Dimensions, Attributes & Metrics 2. Avoid ambiguity Start from data source 3. Implement a system! 4. Build in quality checking data fixing 5. Establish unique dimensional ID and MANY dimensional Hierarchies

11 Data just data Trade Promotion Transaction Data (P,G,T,T) How much did we (are we going to) spend? With What Retailer? On what Products? During what time duration? Using what tactic? WHAT IS OUR GOAL? Category Penetration, new product support, increase market share, increase margin... What have we done, what do we plan on doing (based on history)? Value add: Articulate promotional execution Visibility into promotional plans

12 and more Data Syndicated data (P,G,T) How much did we sell (units, revenue) (Total, base & incremental) Who sold it? What products sold? Pain points start: What is a week? The manufacturer sold item x and the Retailer sold item y Value Add: Price for lift - Compare Incremental product units/revenue to promotional spend ROI - Compare tactic efficacy toward goal (ROI)

13 and more Data Point of Sales (P,G,T) How much did we sell (units, revenue) (Total, base & incremental) Who sold it? What products sold? Pain points continue: Week and Product definition pain continues Point of Sales - No Lift Measures (base vs incremental) Vary by sales channel Value add: Completes coverage of market Gut check on Syndicated data sources Discuss with internal and the customer (two audiences)

14 and more Data Financial Data COGS, C&C - Alignment to Point of Sales? Product decomposition Bill of Material Coupon data (distributed, redeemed, forecast)

15 and more data campaigns (Drop date, Products response curves ) Advertisement data Sales Data (as a leading indicator) Macro/Micro Economic data Weather data Local Events

16 Increased delivery Promotional Effectiveness Market Mix Optimization New Product Launch Demand planning Promotional Evaluation Market Mix Analysis Pricing Scenario planning Guided Selling $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

17 Questions? Peter Brousil Data Solutions & Data Strategy (312)