Does this sound familiar? "Are you sure those numbers are right?" "Why are your numbers different than theirs?"
We've all heard it and had that gut wrenching feeling of doubt that comes with uncertainty around the quality of the numbers.
Stop the madness! Presented in Dunwoody on April 18 by industry leading expert Mary Levins who discusseses what it takes to successfully take control of your data using the Data Governance Framework. This framework is proven to improve the quality of your BI solutions.
Mary is the founder of Sierra Creek Consulting
Stop the madness - Never doubt the quality of BI again using Data Governance
1. Stop the Madness!
Never doubt the quality of BI again using
Data Governance
Mary Levins, PMP
April 18, 2013
2. About 3sage Consulting
Consultant-owned firm of proven, tenured consultants specializing in
Information Management
Our People
• “Big Firm” Talent, each with 10-20 years experience in Information Management
• Proven success to bring business value & context to every data initiative
• Capability to execute all phases (strategy -> delivery) of large-scale data programs and projects
Deliver Results
• Our consultants deep business acumen and technical expertise is crucial to design the right
solution.
• Our consultants have substantial breadth across multiple Information Management disciplines,
but significant depth in at least one core competency.
• 3sage is focused in Atlanta – each initiative is paramount as our business depends on it and our
consultants live here with our clients.
4
3. Topics
• BI Governance vs Governance of BI Data
• Why is Data Governance Important for BI?
• Data Governance Framework
• Data Governance in Action and Lessons
Learned
• Future Challenges
4. BI Governance vs Data Governance
• BI Governance
– governing activities in a BI environment
– project oriented (defined beginning and end, and defined scope and
resources)
• Data Governance
– applying data governance disciplines across the enterprise
– Program oriented (group of related projects with strategic goals)
Data Governance is an Integrated discipline for
assessing, managing, using, improving and protecting
data for the strategic benefit of the organization
5. • Data is the Foundation and must be managed to run, improve, and expand
the business
Raw Data To Meaningful Information
- Depends on Quality Data
Insight
Knowledge
Information
Data
Discrete facts
Definition
Format
Growth
Strategic Direction
Business Value
Value
Inference
Predictive
Decision-making
Patterns
Trends
Relationships
Assumptions
Necessary for the
Business = Data
Asset
Operational
Intelligence to Run
the business
Analytical Intelligence
to Improve the
Business
Strategic and
Predictive Intelligence
to Expand the
Business
Is
Knowledge
Really
Power?
6. • Data is the Foundation and must be managed to run, improve, and
expand the business
Discrete facts
Definition
Format
Relevance
Growth
Business Value
Value
Inference
Patterns
Trends
Relationships
Necessary for the
Business
Operational to run the
business
Analytical to Improve
the Business
Strategic and Predictive
Insight to Expand the
BusinessIs
Knowledge
Really
Power?
Raw Data To Meaningful Information
- Depends on Quality Data
7. Breakout Discussion Points
• What are your biggest data related challenges
impacting your BI initiatives?
• What level of data governance maturity do
you think your organization is?
8. Common Business Concerns related to
Bad Data
8
I have to make
assumptions
on the data to
use
There are
multiple
answers to the
same question
There are no
clear
consistent
definitions
We have
multiple
versions of the
truth
I have to
reconcile and
restate metrics
You have to
have a lot of
friends to get
what you need
Data doesn’t kill
business, it’s
the use of the
data that kills
We need a
common way to
look at critical
metrics
I have no
confidence in the
data or existing
reports
10. Data Governance Maturity
Where is your organization?
• High level of
dependency on
"Tribal Knowledge"
across the
organization
• Data is created on
an as needed basis
with no or few
rules/standards
• Ownership and/or
stewardship models
are undefined
• Data quality issues
are addressed after
they occur
(reactive)
• Decision making
dependent on
consensus and/or
multiple systems
• Heroic culture
(performance
measured by
"fixing" problems)
• No Active Data
Governance
Strategy
• Data Projects on
need basis
• Governance program
has been implemented
at an enterprise level
• Metadata
management and data
standards are in place
across the enterprise
• Data standards
processes are in place
• Proactive monitoring
for data quality
controls feeds into the
governance program
• Governance policies are
used to set, communicate,
and enforce business and
IT information
management
• Governance is second
nature throughout the
enterprise
• Agility and responsiveness
is greatly increased due to
a single unified view of
enterprise data
• Enterprise data governance
enables high-quality
information sharing across
all divisions
Aware Reactive Proactive Managed Innovative
• Leadership is
aware of the
importance of
Data Governance
and the impact on
the performance
of the
organization.
• Enterprise Data
Governance
organizational
structure defined
and sponsored
Level 1 Level 2 Level 3 Level 4 Level 5
11. Benefits of Data Governance
• Increase Revenue
– Business Growth
• Reduce Costs
– Protect the investments in new initiatives (BI/ ERP)
– Improve Efficiencies
– Simplification
• Minimize Risk (compliance, security, privacy)
– Liability and Fraud
– Compliance to internal standards, policies, guidelines
12. Data Governance is an Integrated discipline for assessing, managing, using,
improving and protecting data for the strategic benefit of the organization
Data Governance Framework
Key Disciplines and Sub-disciplines
11. Technologies
• Workflow Routing Tools
• Collaboration Tools
• DQ Tools
12. Infrastructure
1. Data Governance Organization
2. Data Stewards
3. Policies and Procedures
4. Data Quality and Compliance
5. Data Quality Assurance
6. Information Lifecycle Management
7. Data Privacy and Risk Management
8. Meta-data Management
9. Data Model
Process
DataTechnology
People
The Data Governance process covers the people, process, technology, and data disciplines to ensure
a holistic solution is designed
Change
Management
14. Siebel
®
Single Integrated
Architecture
Worldwide
New World:
Integrated data
Real-time
Schedule - 24-hour
clock
Global
One instance
2128 instances of 887 applications
Old World:
Data and processes customized to fit business,
geography or application
Interfaces helped customize data for downstream
applications
Separate silos maintaining data
Each instance controlled their own schedule
A Global Integrated Solution requires an Integrated
Approach for Managing Data & Processes
SAP
DATA GOVERNANCE DRIVER
15. Procurement
Requestor or
Employee
Central Vendor
Administrator
Supplier
Employee
Accounts
Payable
Operations
Buyer
Technology
High-Level Information Life Cycle – With Non-Quality Data
Submit request
for supplier
master record
to be set up.
Request
OK?
Request tool Oracle
Review
request
Create supplier
master record in
Oracle.
Receive
payment
Receive
reimbursement
Process
Invoice
Payment
Process
Employee
reimbursements
Place order
with supplier
Receive
order
Send request
to authorizing
agent.
Review and
approve
request.
Manager or
Authorizing
Agent
Receive notification
that supplier setup is
complete.
Type
completion info
into SARS.
SARS
NoFrom
previous
page
CVA rejects
request in
SARS
Receive
reject notice
Receive
reject notice
Support
Contact
Receive request to
investigate rejection
issue (email, phone,
BLT, etc)
Investigate
rejection
issue
Investigate
rejection
issue
Investigate
rejection
issue
Investigate
rejection
issue
Resolve
rejection
issue
Resolve
rejection
issue
Resolve
rejection issue
or notification
of resolution
Resolve
rejection
issue
Impact to request process:
• Additional rework
• Time delay in completing business txn
• Extra resources
• Duplication of effort
16. Procurement
Requestor or
Employee
Central Vendor
Administrator
Supplier
Employee
Accounts
Payable
Operations
Buyer
Technology
High-Level Information Life Cycle – With Good Data
Submit request
for supplier
master record
to be set up.
Request
OK?
Request tool Oracle
Review
request
Create supplier
master record in
Oracle.
Receive
payment
Receive
reimbursement
Yes
Process
Invoice
Payment
Process
Employee
reimbursements
Place order
with supplier
Receive
order
Send request
to authorizing
agent.
Review and
approve
request.
Manager or
Authorizing
Agent
Receive notification
that supplier setup is
complete.
Type
completion info
into SARS.
SARS
No
See
next
page
17. Business Impact
of Reducing Rejected Supplier Setup Requests
What is the impact of reducing rejected setup requests?
• Decreased or no time delay in placing orders to suppliers, paying supplier invoices, and
reimbursing employees for expenses. How did this slow down a product introduction?
Shipments? Contracts? Take to another level of detail.
• Reduced rework by employee (reject the request, ensure investigation and resolution, re-
review updated request).
• Reduced rework by requestor who submitted the original request (to investigate and
resubmit).
• Reduced rework by support employee (to investigate and resolve).
• No frustrated employees
• No frustrated suppliers, many of whom are also Agilent customers.
• No loss of service to the company because payment has not been made.
Thanks for the
timely payment!
Thanks for the
timely
reimbursement!
18. Lessons Learned
• Data governance can influence common processes through Data
Standards and rules
• Established controls will minimize exceptions and rework resulting in
greater efficiencies
• A defined organization structure will help business owners/ partners to
define and maintain business requirements
• Data governance can leverage & tighten linkage between Business, IT, and
other Enterprise teams
• Consolidation and communication of data and business rules into an
enterprise location helps to drive quality across the enterprise
– Change Management Process
– Collaboration
19. Future Challenges
• Technology Changes are driving a greater need for
Data Governance
– How do we maintain trusted and secure information
in these new environments
• Listen to Books and Read our Cell Phones
• Play music on our TV’s and watch movies on Computers
• Data Explosion – data growth is predicted to be 44
times by 2020
– How do we share and synchronize so much data
internally and externally?
• Culture and Communication Changes
– Innovation can only occur in an Inclusive Culture
– New language of texting acronyms (OMG!)