Best Practices for Improving Data Quality

1
Best Practices for Improving Data Quality

• CSM NAME
• Customer Success Manager
• salesforce.com

2
Training
Executive Sponsorship
Data Quality
Change Management
Implementation
Process Definition
3
Agenda

• The Importance of Data
• Achieving High Quality Data
• Leveraging People, Processes and Technology
• Questions

4
Importance of Data

• Inaccurate report metrics
• Bad information wastes users time and effort
• Marketing wastes money and effort pursuing bad
  prospects
• Understanding your customer is impossible
• IT wastes time sifting through information and
  trying to make sense of it
• Operations has difficulty reconciling data
  against financial and other backend information
• User get frustrated, you lose valuable by-in and
  adoption
• Analysts rate bad data as one of the top 3
  reasons for CRM failure

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Achieving High Quality Data?

• Data Profiling
• Data Control
• Data Integration
• Data Augmentation
• Data Monitoring

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Achieving High Data Quality Data Profiling

• Understand your Data Sources
• Where is everything coming from
• Understand your datas weaknesses
• Pinpoint your problems and find ways of improving
  this
• Understand your Mapping and usage of Data
• Entity Level Mapping (Account, Opportunity,
  Contact)
• Field Level Mapping (state, city etc)
• Dont Duplicate information between entities
• Create your Data Quality Plan

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Achieving High Data Quality Data Control

• Correct Inaccuracies and Inconsistencies in Data
• Leverage Automated routines/tools to clean data
• Leverage Users to Fix data (its their data)
• Make sure Data Ownership and Sharing is accurate
• Critical to keep data in the right peoples hands
• Make sure your hierarchy, groups, teams etc are
  kept up to date
• Proactively Have meetings with Sales Management
  to understand org changes
• Define your CRUD rights on each profile
• Give users access rights to only the information
  they should have
• Prioritize your data control process
• Fix high visibility/usage information first
  (duplicates, addresses, emails)
• Fix business specific information next
  (opportunity types, stages etc)
• Remove duplicate fields (dont repeat account
  info on contact)

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Achieving High Data Quality Data Integration

• Understand your Masters
• Account Master (is the key stored on all other
  systems
• Product Master
• Avoid stale information, misinformation from
  spreading
• Integrated solutions make it easier for users and
  reliable for customers
• Create links or integrated apps to avoid
  duplicates in many systems
• Create a true 360 view of your customer
• Link order entry, fulfillment apps to
  salesforce.com
• Make some information read only
• Use processes like case submission to update
  account master info

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Achieving High Data Quality Data Augmentation

• Add Missing information from 3rd party DBs
• Phone and emails,
• Executive contact information,
• DB info (SIC, Industry)
• Understand what data would provide additional
  value
• Poll your sales and marketing users and see what
  is needed
• Add Behavioral specific data
• Purchasing Pattern
• Internal Intelligence
• Strengthen Customer and Contact Records to
  increase your understanding

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Achieving High Data Quality Data Monitoring

• Procedures and Policy
• Data Quality is everybodys responsibility
• Define centralized process for mass loads
• Alerts and workflow to monitor data
• Reports and Dashboards to monitor quality

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Improvement checklist

• Do you understand what data you have in
  salesforce.com?
• Where is it coming from what is wrong?
• Have you cleaned your data?
• Remove duplicates (manually and through tools or
  partners)
• Have you integrated your data?
• Do your applications tie together?
• Have you augmented your data?
• Have you added information to help your sales
  users?
• Do you monitor your data?
• Get the reports, dashboards and automation in
  place to monitor the health of your data

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People Assigning Responsibility for Data Quality

• Users are trained that data integrity is a
  collective responsibility
• Users are trained on how data will be used
  (establish reasons for why data needs to be clean
  and accurate)
• Assign super user, geography lead or some other
  owner to keep regions data in tact
• Internal Business users or IT is spot checking
  and monitoring data on a regular basis

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Process Data Quality Procedures Occur Regularly

• Exception reports run monthly to find incomplete
  records or records with incorrect picklist values
• Administrator dashboards assist in quick
  identification of erroneous/missing data
• Workflow in place to monitor new data creation
• Corporate Marketing uses Campaign Status to
  indicate Returned Mail so bad lead records can be
  updated/purged
• SFDC routinely reconciled against other data
  points
• SFDC data is always changing so these processes
  are on-ongoing!

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Technology Automating Data Improvement

• DB other SFDC partners can help!
• DB/Hoovers other information imported
  periodically to automatically update account
  records
• Inside Scoop or other partners to augment and
  cleanse information
• Workflow can help!
• Emails requesting missing information
  automatically sent to owner when a record is
  incomplete
• Sforce can help!
• Generate your own alerts through the API
• Script adds missing information
• Script updates erroneous information
• Create integration points
• Account Master/Product Master/Address Masters
• Address Cleansing
• Keep Relationships automated

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Questions