1. Talking to non-technical people about data (Especially if they’re your boss) OSCON July 22, 2015 Linda Powell, CDO CFPB

2. Why should business leaders invest in data? The problem –  Building an infrastructure to securely manage data is expensive  Data requires organization and structure – it takes time and people to manage data effectively  Data is often considered an IT challenge - but it lives between IT and the business

3. 3 Understand the Business  The Industry  Your company’s role in the industry  Management’s goals and objectives  Increase market share  Maximize shareholder profit  Do good in the world  Support an agenda  Meet the organization’s mission  What risks are management sensitive to  Market changes  Economic conditions  Internal issues  Speak the same language  Translate technical jargon to business jargon

4. 4 A Little Bit of Marketing  Develop an elevator pitch – a short well thought out summary of the work you do. Examples:  I’m a data scientist, I use my technical, analytical, and statistical skills help the marketing team target the right audience for their products.  I’m a chief data officer, I’m responsible for managing the company’s data assets – much like the CFO is responsible for managing the company’s financial assets.  I’m a data governance professional, I help my company ensure we have efficient communication and processes, while minimizing risk. Note: The terms SDLC, terabyte, server, and virtual are not in these descriptions.

5. 5  Assume the other person is not familiar with the software or hardware you’re using and does not know what you mean by gig, ram, SQL, I/O channels, or virtual.  Find a way to relate the technical concept to something in everyday life or specific to the company.  Lead with the end result - e.g. your report that used to take 15 minutes to generate now takes 20 seconds.  The right picture is worth a thousand words. When you Need to Get Technical

6. Sample Analogies – start with something known Metadata facilitates data processing and analytics Soup is the data Can is the database Label is the metadata

7. 7 Sample Analogies – Put things in context How much data is a lot? 1 terabyte of data is about equal to the library of congress’ print collection. How many terabytes of data are you managing? Why is my system so slow? We are trying to push a watermelon through a garden hose. We need to cut it up, feed it through, and reassemble it at the end. Why don’t we just ask for whatever data they have? Imagine I asked everyone to give me 1 paragraph on their summer vacation. From that I tried to compare where the people went, the dates they traveled, and who they traveled with – I didn’t ask for what I need so my analysis will be hard, inaccurate, or impossible.

8. 8 Data can tell a compelling story if you let it: A CFPB study found that 43 million Americans have overdue medical debt on their credit reports. Outstanding debt can lead to decreases in their credit scores. Most lenders decide to grant credit and set interest rates based on credit scores. The study found that medical debt is often unexpected and incurred differently than other unpaid bills and that consumers can become responsible for medical debt because of billing issues between medical providers and insurers. In fact, consumers aren’t always aware they owe medical debt until they get a call from the collection company or discover it on their credit report. The CFPB found that medical debt is not as good a predictor of a consumer’s credit reliability as other types of debt.

9. 9 Visualizing data  Don’t:  Make it too complex  Visualize the obvious E.g. 366 (Cobb), 359 (Hornsby), 356 (Jackson)

10. 10 Visualizing data Do: Let the picture tell a story

11. 11 Summary  Understand what the industry leaders need  Speak to them in their jargon  Find a way to relate your information to the known world  Have your data tell a story  Visualize your data where it makes sense