Technology Infrastructure Breakout Session. How to Obtain a 17:1 ROI Using a Next Evolution Approach to Global Data Quality

Transcription

1 Technology Infrastructure Breakout Session How to Obtain a 17:1 ROI Using a Next Evolution Approach to Global Data Quality

2 Welcome Evan Kent Global Vice President Chandos Quill Vice President, International Solutions Session Objective: Why data quality is a key component of ccrm Managing big data on an international level and optimizing it to support overall marketing strategies How to build a business case and gain buy-in from key stakeholders Implementing a data quality initiative in a way that reduces risk and ensures success Measuring the impact by creating a meaningful ROI 2

3 To prepare for digitization, you must have a technology set to deliver this across all channels. TV Print Radio DM EM Display Search Social Mobile Retail Site CC Data User ID Cookie Address Phone Session Name Device ID IP Cross-channel technology delivery Personal Offer Content Insights Resolve Identities Map Events Determine Strategy Deliver Experience Product Distribution Offer Price Media Experience 3

4 Schneider Electric Moving a Fortune 354 company one data source at time 4

5 Schneider Electric Global Specialist in Energy Management: billion of sales in 2012 of sales in new economies employees in 100+ countries of sales devoted to R&D Utilities & Infrastructure Industrial & machines Data centres 15% Non-residential buildings Residential Diversified end markets FY2012 Sales (b ) 9% 22% 25% 29% North America 25% 28,300 Balanced Geographies FY 2012 sales & YE emp Rest of World 18% 22,000 Asia Pacific 27% 42,600 Western Europe 30% 44,200

6 What a unique time in history to be in marketing Our day has come! In 2012 (that s 31 zeros!) Corporate s daily Tweets daily Facebook posts daily Mobile subscribers Smart phone users From digital exoskeleton to nervous system Digital exoskeleton Nervous system Proliferation of data has provided us with granular & specific information on customer and prospect behavior The combination of traditional marketing, digital marketing and analytics are the new compliments Sophisticated data management is the path to organic growth Edd Dumbill, Strata, Aug. 29, 2012

7 Is the customer really at the center? Are you listening to me? Result: A disjointed brand experience, a sub-optimal sales cycle, wasted resources.

8 Integrate and automate the inbound/outbound to mirror the buying cycle It s a win-win! Digitization enables marketing to offer the right content at the right time. Customers are not bombarded, sales doesn t waste their time.

9 Solution Event Portals SFDC Customer Master Web XLS Social Reg Forms 37 Global Source Systems Call Center Siebel Micro sites Bar Napkins First Logic Hygiene/Std. Q coding Merge/ purge Rules GMDB Remove duplicates Address standardization Contact history Contact subscriptions Data overlays Warranty Rebate Schneider Electric Merkle

10 So why data hygiene? Global is blind without local Efficiency & ROI Complex CDIs 1.65M records per update Recover records Combine digital actions to drive print support 10

11 And for Schneider Electric, the starting point was improving the data quality in the global database Merkle s Approach Schneider s Implementation Speed to market Contact Strategy Data Validation, Enrichment and Sourcing Marketing action layer Informationdriven insight layer Speed: Real-time decision making Cross-sell, up sell Course correct Meaningful: What are we solving for? Usage Enrich data set Data Hygiene and Governance Foundation layer Cleaning: Standardization De-duplication Accuracy of info Eliminate waste

12 The Data Quality Issue Matrix Data quality issues are not the result of any one thing and become even more complex when dealing with data from multiple countries Most common issues include: Missing data Stale data Bad data Duplicate data GMDB On a global basis, these issues are even more prevalent: Dual language keyboards Fantasy street names Unique naming conventions

13 Solution 37 Global Source Systems Schneider Electric Merkle First Logic Merge/ purge GMDB First-pass -- or -- Quarterly Net New Local Data Quality Solution #1 Local Data Quality Solution #2 Local Data Quality Solution #3 Cleansing, standardization, verification, correction, suppression

14 Obtaining buy-in through a business case Schneider Electric Merkle Identify the Top X dirty data countries. Match with the Merkle country partnerships Determine test qty Determine eligible attributes Decide methodology Design a calculator Create scorecard Communicate expectations w/teams Stakeholders Influencers Approvers Admit a Problem Sample Forecast Test Results Identify Stakeholders Ask for permission Or beg for forgiveness? Present the Findings Run the Data Forecast Final Results Run a Pilot Involve all stakeholders Publish findings broadly Ask for more $$$ Pull the data Run the data Analyze results Update calculator Update scorecard Communicate Pull the data Run the data Analyze results Make recommendations 1 4

15 Schneider Electric The impact 15

16 Netherlands: key findings Data Quality Flags % 10% 12% 44% 1% 1% 27% Mailable Distr. Data Quality Components Impact Records Submitted 58, % 100% 80% 28% Number of records with mailable = Y 42,102 Number of records with mailable = N 16,148 Number of records with Q4, Q5 and Q6 8,378 Number Q4-Q6 of records corrected to Y after cleansing 1, % Number Q1-Q3 records suppressed after cleansing 7, % 60% 40% 20% 0% 72% %Mailalbe N Y

17 Netherlands: key findings Verification and Standardization: Correction and Suppression:

18 pages of paper saved Trees conserved Savings over 3 years 18

19 Key Takeaways Decide build or buy Identify dirty data countries in relation to your strategic objectives Create a baseline through business case Develop standard quality codes for your MDB Test > Roll out > Quarterly updates (or as needed) Demand samples of corrected records Document your findings

20 Thank you Evan Kent Global Vice President Customer Retention Schneider linkedin.com/in/evankent Chandos Quill Vice Presiddent, International Solutions Merkle Inc.