How to Ask for Money for your Data

How to Ask for Money for your Data Management Projects Upon leaving this presentation, attendees will have the framework for developing a financial business case for justifying budget for data management projects. Business and IT persons attempting to secure moneys for data profiling, data governance, data integration and data stewardship projects are often discouraged by senior management’s lack of sponsorship and/or attention. This course will give data managers the tools to uncover the real dollar impacts of poor data management within their enterprise, and to articulate the real or potential negative impacts to the operations. This interactive presentation will consist of actual examples and success stories, along with detailing the process for uncovering pain points, monetizing findings and creating a cohesive case for data management investments. Discussion points will include: defining your data management needs, identifying key stakeholders and their agendas, uncovering specific and definable financial impacts of poor data management, monetizing findings, preparing a cohesive business plan to clearly articulate your case for spending, and how to ask for the money! - datablueprint. com 1/31/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

How to Ask for Money for your Data Management Projects Jeanne Laughlin Director of Sales and Marketing Data Blueprint jlaughlin@datablueprint. com 1. 804. 521. 4258 - datablueprint. com 1/31/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

Agenda • • Introduction Why are YOU here? Common Data Management Projects How to create a business plan for your data management project: – – What? Why? End Goal? What happens if. . ? • Go Get the Money!

Why are YOU here? • • You are experiencing data management problems You are doing the work of 2, or 3, or 4 people You have high deliverables and no budget There is a lack of focus on data management and how this costs the company time, money, credibility, opportunities, compliance • You lack of high level sponsorship, executives say: – – If it ain’t broke, why fix it? What will this do to meet specific goals of division? It’s someone else’s problem That’s the way we always did things

Common Data Management Projects • Develop Data Governance policy • Integrate siloed data sources • Re-design data architecture to allow for ease of use, expansion and reduced costs • Create data warehouse • Assess data quality and create business rules for going forward • Assess data management maturity • Create a strategy for managing data • Create a metadata management strategy

Steps for making it happen. . See worksheet

How does your data management needs affect your organization? - datablueprint. com 2/5/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

Examples

Monitization: Legacy System Migration to ERP • Challenge – Millions of NSN/SKUs – Key and other data stored in clear text/comment fields – Original suggestion was manual approach to text extraction – Left structuring problem unsolved • Solution – – - datablueprint. com Proprietary, improvable text extraction process Converted non-tabular data into tabular data Saved a minimum of $5 million Literally person centuries of work 2/5/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

An Iterative Approach to Data Quality Engineering Unmatched Ignorable Items Rev # (% Total) NSNs (% Total) Avg Extracted Items Matched Items Per Item (% Total) Items Matched Extracted 1 329948 31. 47% 14034 1. 34% N/A N/A 264703 2 222474 21. 22% 73069 6. 97% N/A N/A 286675 3 216552 20. 66% 78520 7. 49% N/A N/A 287196 4 340514 32. 48% 125708 … … 11. 99% … 582101 1. 100022 161 … … 55. 53% … 640324 … 14 94542 9. 02% 237113 22. 62% 716668 1. 114291 415 68. 36% 798577 15 94929 9. 06% 237118 22. 62% 716276 1. 113928 151 68. 33% 797880 16 99890 9. 53% 237128 22. 62% 711305 1. 115300 75 67. 85% 793319 17 99591 9. 50% 237128 22. 62% 711604 1. 115439 205 67. 88% 793751 18 78213 7. 46% 732980 1. 207281 69. 92% 236 884913 - datablueprint. com 237130 22. 62% 2/5/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

Results…Integrated Sales Reporting • Problem: – Multiple unintegrated sales reporting systems, due to merger/acquisition activity, made it extremely difficult and time consuming to get complete view of sales activity. Inconsistent reporting results reduced management’s ability to react quickly, to forecast accurately and to increase inventory turnover. • Solution: – Data reverse-engineering approach to analyze the disparate systems and then provided an integrated solution • Results: – Integrated and more accurate sales reporting improved forecasting – Increased inventory turns by allowing supply chain group to make faster decisions and to react more quickly to market fluctuations and unexpected opportunities – Sales analyst turnover was reduced, thereby eliminating HR costs which were projected in excess of $50 K per resource 13 - datablueprint. com © Copyright 07/23/08 previous by Data Blueprint - all rights 11/28/2009 © and Copyright thisyears and previous years by Data Blueprint - allreserved! rights reserved!

Solving…. . Global Data Integration Problems • Problem: – Silo-based systems & data sources required an army of operational staff to reconcile, monitor and report across the enterprise – Business decisions greatly hindered by the inability to paint an integrated view of products, transactions and clients – Desire to establish Deutsche Bank as a major global investment firm required the development of an integrated global trading platform • Solution: – Re-architected data solutions for transaction processing, account and product master data and total transaction lifecycle management – Designed, developed and implemented large scale database and data transformation solutions • Results – Operational costs reduced by millions of dollars – Deutsche Bank was able expand revenues by attracting a larger market share of Prime Brokerage clients and increasing products used by existing customers – Enabled the successful implementation of a global, service-oriented platform

Defining a measure of "Batteryness" • Problem: – Identified opportunity to significantly increase revenue through add-on sales to web customers. Millions of dollars being spent with other retailers on batteries to power Radio. Shack purchases • Solution: – Developed text-parsing to identify battery and other add-in products to be offered when customers purchase products • Results: – Increased in sales of high margin add-on products by over $2 M per year – Solution scaled to other products – "Would you like fries with that burger? "

Monitization: Time & Leave Tracking At Least 300 employees are spending 15 minutes/week tracking leave/time - datablueprint. com 2/5/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

Computer Labor as Overhead - datablueprint. com 2/5/2010 © Copyright this and previous years by Data Blueprint - all rights reserved!

Improve Total Life Cycle Management of Equipment • Problem: – United States Marine Corps (USMC) Global Combat Support System (GCSS-MC) is working to improve the combat effectiveness of the operating forces and to support emerging doctrine and warfighting strategies and impacts on ship designs and acquisitions – Technical initiative to provide Data Profiling/C leansing/ Integration/ Governance effort – Need to better label and track equipment in order to positively impact warfighting efforts and to reduce data anomolies and errors • Solution: – During initial short term engagement, successfully conducted data quality and profiling initiative on 6 data sources (see results on following page) • Results – Identified approximately $5 billion of equipment does not tie out between the LUAF and RTLS – Approximately $531 million of SAC 3 items have duplicated serial numbers – Engaged to assist on a larger, more inclusive data profiling/ cleansing/ integrating project starting in March

Data Profiling Proof of Concept Purpose: (1) To identify and provide metrics on data quality issues for a subset of USMC supply chain data (2) To demonstrate the viability of commercial data profiling tools to quickly identify and measure possible data anomalies Project Overview • Three week data profiling pilot project for USMC Center Of Business Excellence • Profiled six data sources supporting the USMC supply process • Rapidly analyze data and produce statistics about patterns, frequencies & other attributes about the data • Use the statistics to identify potential data health issues and link them to business impact through collaboration with business data experts Data Profiling Process • Set up profiling and database software in the USMC environment (3 days) • Obtain source data (2 days) • Load into Relational Database (1 day) • Profile All Columns in All Tables (less than 1 hour) • Analyze Profiling Results (9 days) – Use statistics to infer data and business rules – Verify hypotheses with functional users of the data • Prepare and present findings to sponsors (2 days) Business Value • Highly cost-effective, repeatable process for identifying potential data health issues within the USMC • Data quality remediation plans can be more easily prioritized and resourced using the metrics generated by our approach • Potential cost and risk reductions realized by implementing needed data quality controls discovered during data profiling • Potentially reduces the cost of system migrations because of the automated approach to understanding the data in the As-is system

Go Get the Money. . . 1. Identify and schedule meeting with individual or team that has money spending authority 2. Start at the end, i. e. “the reason for this meeting is to show you how our company can: – – Save XXX amount of money” Increase profits by $XXX” Increase sales by $XXX” Reduce these specific compliance risks which costs our company $XXX per year” 3. Make sure that presentation is geared toward end users, do not give technical IT oriented briefing to business users

4. Focus on the benefits to your audience – “Will increase revenue for our department” – “Will help you to meet your strategic goals for the year” – “Will show executives that you are a team player” – “Will put our department in the limelight” – “Will generate ROI, thereby securing our standing as thought-leader within company” 5. Keep message succinct and organized, do not go “off-script” 6. Clearly outline costs, benefits, timelines and milestones 7. Ask for the money, then STOP talking

Speaker Contact Info jlaughlin@datablueprint. com 1. 804. 521. 4258 23