How to Build a Business Case for Data Management Steve Sarsfield Product Marketing Manager, Talend

Transcription

1 How to Build a Business Case for Data Management Steve Sarsfield Product Marketing Manager, Talend

2 Agenda Business Impact of Poor Data Management Corporate Growth and Data Pervasive Nature of Data the Butterfly Effect How companies handle the Butterfly Effect Strategies for Selling the Business Case for Data Management Finding and Marketing Value Understanding Opposing Forces What Happens if you Do Nothing Other Techniques for Overcoming Objections

3 SECTION 1: IMPACT OF POOR DATA MANAGEMENT

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5 Implications for Integration Challenge: As a company grows, so does its information architecture Requirement: Resources are often replicated. Tendency to become chaotic

6 What is the Butterfly Effect?

7 Data s Butterfly Effect Orders: Europe Shipments: Europe Inventory Sales Sales: Europe Market Research Capacity General Ledger Payments Bills Orders Credit Campaigns Responses Services Shipments Surveys Deliveries Complaints Customers Customer Service KPI s Support Requests

8 Data s Butterfly Effect General Ledger Sales Orders: Europe Sales: Europe Shipments: Europe Failure to Comply with Regional Laws Market Research Inventory Inability to deliver orders; Premium Pricing from vendors Capacity Payments Wasted Time Checking and Rechecking Financial Reports Orders Credit Issued to Risky Customers Credit Denied to Good Customers Fraud Bills Credit Customers Campaigns Inability to Reach Target Markets Responses Missed Shipments High Shipping Costs Customer Service Services Shipments Deliveries Inaccurate Business Intelligence KPI s Complaints Support Requests Surveys Poor Service

9 Big Data Make Scientific Discoveries Sentiment Analysis Understanding of Buying Patterns Social Networking Mobile Devices Transactions Detect Fraud Risk Modeling Gain Competitive Advantage Network Devices Sensors

10 Solutions to the Disparate Data Analysts Lacks coordination Project-based & Consolidation Important Step in Agile Data Management Data Warehouse Effective, but tendency toward data dump Master Data Management Effective but may take time to achieve Maturity >>>>>>>>>>>>>>>>>> Application Integration Effective but may take time to achieve

11 SECTION 2: Strategies for SELLING THE BUSINESS CASE

12 Finding Value Revenue Efficiency Compliance

13 Profiling: Technical Metrics Where is the value? Measurable Dimensions for Data Quality Intangible Dimensions Dimension Description Dimension Description Accuracy Integrity Consistency Completeness Does the data accurately represent reality or a verifiable source? Do broken links exist between data that should be related? Is there a single representation of data? Is any key information missing? Relevance Usability Usefulness Every piece of information stored is important in order to get a true business representation The stored information is usable by the organization with ease The stored information is applicable for the organization Uniqueness Is the data value unique? i.e. no duplicate values or records Believability The level to which the data is regarded as true and credible Accessibility Precision Is the data easily accessible, understandable, and used consistently? Is data stored with the precision required by the business? Unambiguous Each piece of data has a unique meaning, and can be easily comprehended Timeliness Is the information update frequency adequate to meet the business requirements? Objectivity Data is objective, unbiased and impartial i.e., it does not depend on the judgment, interpretation, or evaluation of people

14 People Building Value Technologists Metrics Business Metrics 12% of the attribute does not follow standard syntax. 13% of our US mail addresses fail address validation. 9% of my contacts have cannot be marketed to via . 3% Cannot be contacted by either e- mail or US mail. Decision Metrics This customer data is good enough to use for a campaign.

15 Finding Value Example What is our top selling product across all our pubs and restaurants? Number 1 Number 2 Number 3 Coke Pepsi Coca Cola Value Reporting accuracy Time spent checking and rechecking Trust in all metrics Warehouse management Spoilage Vendor negotiation benefits

16 Compelling Proposals Find the ROI Revenue, Efficiencies, Compliance Talk about project in terms of business benefits Give clear metrics on success and failure Limit Scope and Hold Market Your Team Be ready with an elevator pitch Newsletters/Social Media/ s Include a do-nothing option

17 Sample Proposal Problem The entry of erroneous data into the CRM system causes shipping penalties of $30,000 per quarter and other losses due to inefficiency. Human resources devote a full time employee to mitigate the problem. Annual impact Shipping penalties and re-ship costs $120,000 ($30,000 per quarter) Man Hours $100,000 per year. Solutions Sales training ($5000) Realtime address checking ($50,000). Impact Reduce shipping penalties by 50% in first year. Further reductions in subsequent years. Decreasing followup work for Nigel by 50%. Gives Nigel time to assist in manufacturing. Year 1 (June-Dec) Year 1 costs training and Address Validation $55,000 Year 1 savings: Shipping $60,000 Year 1 savings: Man Hours + $50,000 Total Savings = $110,000 Toal ROI Year 1 $55,000 Year 2 Year 2 costs training and Address Validation $27,500 Year 2 savings: Shipping $75,000 Year 2 savings: Man Hours + $60,000 Total Savings = $135,000 Toal ROI Year 1 $107,500 Options Keep status quo: Continue annual costs of $220,000 Continual increase in customer dissatisfaction.

18 Objections to Data Management Accessibility Expertise Unrealistic Scope What is a customer, product? Technical Tracking Revenue Tracking Efficiency Compliance Processes Corporate Mission Stockholders and quarter close Corporate Greed Drudgery Fear Indifference Resistance to Change Emotional

19 Overcoming Objections Point out the Burning Bridge Sell Upper Management Be Aware of Corporate Revenue Meanwhile, Go for Cheap Wins Use Case Studies to Make your Point Bring in Analysts & Experts Consider Guerilla Marketing

20 Ways Our Customers are Tracking Value Data Integration Transfer Times and Latency Savings Associated with Data Quality More Accurate Reporting Better CRM, Better Customer Service Mailing Costs More Accurate Physical Warehouse Total Cost of Ownership License Maintenance Services Hardware Training Business Process Improvements Speed of Development, Re-use and Collaboration Instead of taking up to a month to create complex reports in order to meet these regulatory requirements, Accent Group can collate relevant data from all sources accurately in just one day. This has had a significant effect on productivity and customer service, by providing staff with an easy-to-use open source data integration tool that can radically reducing the time usually taken to process applications. Andy Gowdy MBCS CITP, Legacy System Manager It's proving to be 3 times faster than developing the same ETLs by hand and the ability to reuse Jobs, instead of rewriting them each time, is extremely valuable. Inderjit Chhatwal Vice President and Business Systems Development Manager, Allianz Global Investors Distributors LLC

21 Key Take-aways Data is Pervasive Driven by Corporate Growth and now Big Data Find your Marketing Value Revenue Efficiency Compliance Be a Student of Objections Be Patient as your Data Management Strategy Matures Prepare for What s Ahead THANKS! Steve Sarsfield [email protected]

22 Thank You