Collaborating towards data governance

1. Salesforce Data Governance and
Stewardship Roundtable Workshop
Matt Jeffries
Senior Manager, Product Marketing
mjeffries@salesforce.com
Collaborating towards data governance
Eric Kasserman
Senior Manager, Data.com SI Partner Program
ekasserman@salesforce.com

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3. Format – What we are going to be doing
A forum of discussion topics with experts and best practices
Introduction and Overview 10 minutes
How to get started with a data stewardship program 25 minutes for topic intro and discussion
How to navigate the challenges of a program mid journey 25 minutes for topic intro and discussion
Showing ROI at the end of initiative and identifying future needs 25 minutes for topic intro and discussion
Q&A and Wrap-up 5 minutes

4. More data is being created than ever before
The Market and your Customers are Moving Faster

5. By 2020, 70 percent of F500 companies
will make decisions from a mash-up of
more than 5 third party data sources.
*Source: IDC ICT Market Outlook & 3rd Platform Update. Oct 2013.

6. Endemic data challenges
What we Have Seen Customers Struggle With
Name Phone
Bob Johnson 415-536-6000
Bob Johnson 650-205-1899
Rob Johnson 415-536-6100
Bob C. Johnson 408-209-7070
Bob Johnson 415-536-6000
Rob Johnson 650-205-5555
Bob T. Johnson 650-780-9090
Robert Johnson
(415) 536-2283
✓
90%Incomplete
74%Need Updates
21%Dead
15%+Duplicate
20%
Useless

7. What part of the organization
are you from?
Harness your data
Unleash your organization
Know your customer
C LEVEL
•CEO-Executive
•COO-Operations
•CMO-Marketing
•CTO-Technology
•CIO-Information
•CXO-Other
MARKETING
•Product
•Engineering
•Lead Generation
•Brand Management
SALES
•Customers
•Competitors
•Offerings
•Forecasting
SUPPORT
•Customers/SLAs
•Satisfaction
•Research & Design
•Third Party
Affiliates
FINANCE
•Billing/Revenue
•Accounting
•Forecasting
•Reporting
HUMAN CAPITAL
•HR/Administration
•Talent Acquisition
•Staffing & Comp
•Payroll/Benefits
•Training & Career
Mgmt
OPERATIONS
•Engineering
•Suppliers/Vendors
•Delivery/Logistics
IT
•ERP/Accounting
•CRM/SFA
•Content/Storage
•Asset Management
•Security
LEGAL
•Regulatory
•Compliance
•Contracts
•Risk Management
Every Team Cares About Customer Data Quality

8. Presenters:
Introduction of an area of
thought leadership in data
governance and stewardship.
Present 2-3 key topics for
discussion at table.
Participants:
Be ready to share your
experiences, challenges and
questions!
Table Owners:
Help facilitate the discussion
and capture key points.
Provide best practices and
knowledge sharing.
Roles and Responsibilities
Plan for Today

9. 1. Getting started with a data stewardship program
2. Getting tactical in the middle of a initiative
3. Measuring success and the path forward post project
Key Topics for Today

10. Data Governance Framework
Think about your organization as you discuss:
• General management
statementsPolicy
• Specific mandatory
controlsStandards
• Recommendations
/best practicesGuidelines
• Step by step
instructionsProcedures

11. Today’s Presenters
Ernest Lessenger
Enable Path
Adam Menzies
Summa Tech
Keith Metcalf
Traction on Demand

12. Ernest Lessenger
Enable Path

13. Getting Started with Data
Stewardship

14. Data Governance and Stewardship
How to get started
Governance Stewardship
Setting
the rules
Monitoring
day to day
activities
Getting started on Governance:
Get a team empowered to make key
decisions (eg: what is an account)
Getting started on Stewardship:
Full time, part time, what tools?

15. Getting Started
Data Governance
Understand your legal and regulatory environment:
• Encryption, Data Retention, Auditing, and Data Residency (HIPAA, SOX, DoE, EU, etc)
• Required or forbidden information (DoL, PIIA, KYC, etc)
Understand your requirements for accuracy, precision, grain, timeliness, quality,
consistency, comprehensiveness, relevance, accessibility, etc
Define and classify your data
Understand the flow of data, where it is gathered, and how it is used to further your
organizational strategy

16. Getting Started
Data Governance
Follow your legal and regulatory requirements:
• These are typically defined by policies, which you may help to create
• Requirements often have well-established pathways to work within or around them
• You may have to work with Security, Disaster Recover, and Backup teams
Understand your requirements for accuracy, precision, currency, etc.
• Remember that you can never recover a loss in any of these dimensions
• But you do not have to retain the highest levels at all times, in all systems
Enforce proper terminology and data classification
Define the flow of data, where it is gathered, and how it is used to further your
organizational strategy

17. Table Discussion Questions
Getting started with a data stewardship program
• What are the field’s (or set of fields) requirements for currency, timeliness, precision, grain, etc.
• Who provides the data? Can they meet the requirements? If not, can you clean, augment, or
enforce better quality?
• Who can create, see, edit, or delete the data? Does it need encryption, tracking, or other security
restrictions?
• Don’t forget to consider both Operational and Analytical uses of data. You may need different data
models to serve both requirements.

18. Adam Menzies
Summa Tech

19. Getting Tactical within an Initiative
De-duplication, data standardization and using referential data sources

20. Data Architecture
Key architecture decisions and governance
Database ERP
Salesforc
e
DatabaseDatabase
Database ERP
Salesforc
e
DatabaseDatabase
Master Data
Management
System
Salesforc
e
Database

21. Data Hygiene
Keeping it clean with de-duplication and standardization
Proactively setting
up Salesforce to
prevent duplicates
and enforce
standardization is
essential.
You can do this by:
• Duplicate Management (new in Spring ‘15)
• Validation Rules
• State and Country picklists
• Use Correct Field Types
• Streamlined record entry through referential
databases (Data.com)

22. Data Cleansing
Tools for improving the database health
Reactive cleansing will always been a part of the ongoing data management strategy.
Automated Manual
Excel Tools
Custom
Exception
Reports
Data.com
Duplicate
Reports
Data.com
Clean
Jobs
Master Data
Management
Systems

23. Database health is more
than scrubbing existing
data.
Is missing data hurting your organization
100% Clean and Not Done
Marketing
Goals
Sales Goals
Customer
Service and
Retention
Database
Health

24. Table Discussion Questions
De-duplication, data standardization and using referential data sources
• What potential culture challenges exist in improving data governance in your organization?
• Who in your organization would be decision makers on what data each system of record owns?
• What other data sources do you use to populate your organization’s databases and what
challenges do they present?

25. Keith Metcalf
Traction on Demand

26. Measuring Success and the Post
Project Path Forward
Reporting, analytics, measurement and showing an ROI

27. You Have a Problem, How do you Address it?
Define
Analyze
Measure

28. Share insights on how you’ve been able to
define the data governance challenge in your
company…
A problem not defined cannot be solved
Define
Success Criteria
(metrics that stakeholders care about)
Include Problem Indicators
(duplicates, frustrated users, field bloat)
Definition

29. Share insights on how you’ve been able to
get buy-in or plan to approach getting buy-in.
Once defined, how do you get buy-in?
Analyze
Success Criteria
(stakeholder valued metrics and quantitative ROI)
Building a Business Case
(funding, project sponsors)
Buy-in

30. What did success look like on your Data governance project?
What tools have you heard of that could help show success?
It is a journey not a mission
Measure
Reports and Dashboards
(data quality, business value and progress snapshots)
In Salesforce Tools for Success
(completeness icons, dupe alerts)
Showing
Results

31. Table Discussion Questions
De-duplication, data standardization and using referential data sources
Define
• Share insights on how you have been able to define the data governance problem in your company
Analyze
• Once the problem is defined, success criteria identified and cause analyzed; How do you turn
analysis into buy in?
Measure
• Once you project was completed, what did success look like?

32. Final Thoughts
Matt Jeffries

33. Thank you