1. Best Practices for Data
Governance and Stewardship
Beth Fitzpatrick, Director Product Marketing, Data.com
David Hughan, VP Professional Services, Data.com
2. Governance and Stewardship
Common understanding
Rules/policies that are designed to
maintain data order.
Quality, management, policy, risk
management
Thresholds and
Measures
Rules and
Systems
Assignments/actions and personas
designed to uphold data governance
Obligations and
role responsibility
Motivation to
participate. Culture
3. • Downstream “Target”
Why do we care about data?
• Upstream “Source”
Where is it from?
Motive
Trust
Knowledge
Intent
Where is it consumed
Timeliness
Usage
Insight
Action
4. Data Governance is an Investment (vs. Expense)
Where you choose your investment goals, manage your risks
Source: DAMA DMBOK
Data Management Functions Environmental Elements
Data
Governance
Goals &
Principles
5. What We Have Found With Customer Data
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. Data Governance and Stewardship Roundtable
Identify, discuss, diagnose, prescribe and treatment of key challenges
In Discovery Mode
• Share top 5 current challenges
• Discussion and discovery
• Identify core components and
dependencies
• Table top 5 challenges
Path to Success
• Expert diagnosis and consulting
• Prioritization and planning
discussion
• Best practices & success planning
• What you can do now
8. Data Governance Workshop Groups
Group 1
• Heather Talerico
• Forrest Cook
• Raju Iyer
• Dean Carter
• Ryan Axelson
• Catalina Chen
• Cody Royster
• Stephanie Thompson
• Angela Moran
• Amanda Benjamin
• Sriram Sundar
• Jitesh Shah
• Julie Harden
• Rebekah Bretz
• Susan Youngquist
• Maggie Palumbo
• Jodi Schiff
• Myra Braselton
• Chip Sayre
• Kori Kirkbride
• Nick Slater
• Debbie Hart
• Briana Naescher
• Nicole Hansen
• Camille Miras
Group 2 Group 3 Group 4
+ Chris Belding
+ Ali Sadat+ Danny Lai+ Dan Milbrath
+ Beth Fitzpatrick+ Dave Hughan+ Eric Kasserman
+ Marc Delurgio
CustomersData.com
+ Round table in the
back of this room
+ Foothill G2+ Foothill G1+ Long tables in the
front of this room
9. • Getting ahead with Salesforce.com
– Integration
– Analytics
– Stewardship/Governance
• Data Stewardship Key Areas
– Cultivating data stewardship
– Data quality, analysis and metadata
– Data standards, enforcement and compliance
Why do you care about Data?
Areas to think about during roundtable discussions
• Getting ahead with Data.com
– API
– Advanced use cases
– Building data from change
• Data Governance Key Areas
– Record creation and management processes
– System of record/Customer Master
– Policy/rules creation and management
11. Data Quality Guiding Principles
• Know where you’re going and make hard decisions on priorities.
• Ownership: Clear ownership of core data.
• Definitions: Widely understood definitions of account, customer etc.
• Objectives: Agree on areas of focus and how it will be used.
1. Agree on a Clear Vision and Ownership
• Highlight focus areas for data quality in the system.
• Flag governance status and quality score clearly. Use icons.
• Leverage validation rules, record types, profiles and dependent
pick lists.
• The “Give” (and take).
2. Articulate Priorities
12. Data Quality Guiding Principles
• Give users the tools to be successful.
• Search before create. Warn if duplicate.
• A common key adds power: D-U-N-S
• Easy enrichment: MDM, Data.com, Address Validate.
• Empower reps: social stewardship.
3. Ensure Usability at Point of Entry
• Governance and Stewardship teams support quality.
• Monitoring and approval of key information : Several approaches
• Management of bulk-loads.
• SME/ Gatekeeper for integrations.
4. Have Experts Support the Process
13. Data Quality Guiding Principles
• Get rid of the noise.
• Develop and apply an archiving policy
(ie both at account and overarching level).
• Regular de-duplication cycles based on pre-agreed scenarios
(eg CRM Fusion demandtools initially then dupeblocker).
• Conduct regular field audits (eg fieldtrip).
5. Conduct Regular Housekeeping
• Foster a culture of Data Stewardship. Celebrate success.
• Define measures and score – automatically.
• Report and stress single KPI – by org, BU, User.
• Measure improvement over time.
6. Measure . . . And Hold Accountable
Editor's Notes
Hygiene
Typical Discoveries across all of our clients show us that:
90% of CRM’s have incomplete data – in regards to how Jigsaw defines complete
74% need updates – outdated title, missing email, etc…
21% are dead or inactive.
This is a very powerful metric that our model – the community model – allows us to capture
This is where you leverage the information from another user by NOT campaigning to an inactive record – thus saving you money and time
7% duplicates – based upon the way sales and marketing data is captured and the multiple sources – duplicates are inevitable
Jigsaw can impact all of these – in real time – allowing the admin to manage the hygiene process and act as a data steward instead of doing the hygiene activities
