So you have a great idea for the data in your organization. Maybe it’s been acknowledged by some prominent leaders, but nothing ever happens. When the speaker has done his Action Plans for organizations over the years, he’s heard more questions from clients directed elsewhere in the organization about how to get the initiatives moving than he has heard about the initiatives he is creating. Organizations are mostly not good at moving good ideas forward. Why does this happen and what can be done about it? The speaker will share his experience with utilizing his favorite skill – getting things done in enterprises. Dislodge the logjams, make data a key asset, and make your organization an attractive, progressive place for data talent in 2021.

1. Slide 1
Unlock Potential
William McKnight
President
McKnight Consulting Group
www.mcknightcg.com
@williammcknight
Why Organizations Don’t Change When
They Need To
@williammcknight

2. Slide 2
ARCHITECTURE BUSINESS
Sample Projects Justified
Healthcare
• Claims Routing
• $25M
Financial
• Loan Origination
• $22M
Pharmaceutical:
• Offer Analysis
• $35M
Telecommunications:
• Full CDR Analysis
• $22M
Retail:
• Offer Optimization
• $35M

3. Slide 3
You Come Up With a Great Idea and
the Organization Responds with…

4. Slide 4
The Why
ROI concerns
Credibility
Terminology
Organization

5. Slide 5
Acknowledging the Strategic
A Place for Learning and Innovation
The Unknown Upside
The intuitive thinking employed by HiPPOs
(highest-paid person’s opinions)

6. Slide 6
Workloads

7. Slide 7
Ordered Benefits: What Makes it
Difficult
Benefits can be direct or indirect
First order benefits have a direct relationship to the
bottom line
Second order benefits have an indirect relationship
The system will enable an activity that in turn provides the
benefit
Third order benefits have a transitive relationship
The system enables an activity that allows performance of
another activity which actually provides the benefit

8. Slide 8
Data Warehousing (as an example)
Justifying a Data Warehouse Project
Data warehousing seen as a stand alone project
Built for one application
Justifying a Data Warehouse Program
Data warehouses store enterprise data
Inclusion of data is based on governance
The goal of the program is to enable the component of
the applications it supports

9. Slide 9
What is being justified?
An information management program which will
store data for several projects
Why use a data warehouse architecture versus
independent data marts?
A project which will use a data store to store
data
Why do this project?
The inclusion of new projects into an existing
data store program
Why architect this project into the data store instead of
building an independent data store?

10. Slide 10
Return on Investment
(Returns - Investment)/Investment
ROI should always be supported with a time
period (i.e. 301% return in 3 years)
ROI should be presented with assumptions and
risks and be itemized
By source system, subject area, business problem
solved, users, levels of summary, and/or amount of
history data
Add the possibilities! But don’t oversell
Used for Predicting and Measuring

11. Slide 11
Information Management Program
Justifications (TCO)
Operational System Impact
One way of doing things
Tools competence
Consolidating Expense Streams
Enterprise Subject Areas

12. Slide 12
Typical Approach by Domain
Domain Approach
Data Warehouse ROI or TCO
Data Lake ROI
Master Data Management TCO foremost
Analytics ROI
Customer Relationship Management ROI or TCO
Stream Processing ROI

13. Slide 13
Variations on the ROI Theme
Payback Period Analysis
Return on Investment
Net Present Value
Internal Rate of Return

14. Slide 14
Presenting the ROI Possibilities
For each suggested business project, present at
least 3 possible scenarios along with the odds of
that scenario happening, forming a probability
distribution
Best Case
Little Goes Wrong
Worst Case
Most everything goes
wrong
Planned Case

15. Slide 15
Tangible versus Intangible Returns
Tangible Returns - Returns you decide to
measure
More activities have a measurable return than you
may think
Usually 1-2 returns are reasonable to measure for
each phase
Intangible Returns - Returns you decide not to
measure
These will not justify data warehouse efforts

16. Slide 16
Need to Know
Discount Rate
Ask CFO office
Duration
2-4 Years
Time Blocks
Minimum: Quarter
Suggestion: Half-Year

17. Slide 17
Sample Cash Flow to ROI
Total Year 1 Year 2 Year 3
Cost savings $140,000.00 $0.00 $60,000.00 $80,000.00
Financial Return $140,000.00 $0.00 $60,000.00 $80,000.00
Hardware $120,000.00 $100,000.00 $10,000.00 $10,000.00
Investment $120,000.00 $100,000.00 $10,000.00 $10,000.00
ROI -100.00% -45.45% 16.67%

18. Slide 18
Sample Break Even, IRR, NPV
ROI -100.00% -45.45% 16.67%
Cash Flow -$100,000.00 $50,000.00 $70,000.00
Cumulative Cash Flow (Break Even) -$100,000.00 -$50,000.00 $20,000.00
IRR 0% -50% 12%
NPV @ 4% COM ($96,153.85) ($49,926.04) $12,303.71

19. Slide 19
Worksheet: Probability Distribution
Probability of ROI 1 40%
Probability of ROI 2 30%
Probability of ROI 3 30%
Total Year 1 Year 2 Year 3
Cost savings $140,000.00 $0.00 $60,000.00 $80,000.00
ROI -100.00% -45.45% 16.67%
Total Year 1 Year 2 Year 3
Cost savings $80,000.00 $0.00 $30,000.00 $50,000.00
ROI -100.00% -72.73% -33.33%
Total Year 1 Year 2 Year 3
Cost savings $260,000.00 $10,000.00 $100,000.00 $150,000.00
ROI -90.00% 0.00% 116.67%
Weighted ROIs: -97.00% -40.00% 31.67%

20. Slide 20
To Use ROI
Get the discount rate
Know the Revenue Generation
and Cost Reduction dollars by
year for the next 3 years
Break out Labor Reduction by
Resource Persondays and Rate
Know the Costs to Implement

21. Slide 21
To Use ROI
Estimate the costs and benefits for 3 scenarios
Expected
Low
High
Estimate the probabilities of each scenario
Total adds to 100%

22. Slide 22
How to Attain Business Quantification
Usually a matter of the best estimates of those who should
know
If the data warehouse is enabling a new product or service, the
data warehouse justification gets tied into the new product or
service justification
Otherwise, the best way is through interactive sessions with
the users prototyping with them actual data and drilling on the
anticipated returns
Controlled experiments
Statistical analysis of the results with extrapolation

23. Slide 23
Other Examples
Increased revenue per customer
Increased customer acquisition
Savings due to reduced cost of marketing campaigns
Cost benefits of decrease in customer attrition
Improved marketing employee productivity
Reduced IT spend in supporting databases
Reduced likelihood of regulatory fines
Reduced cost to recover from a breach
Improved efficiency in fraud management
Reduced cost of infrastructure

24. Slide 24
A Corporate Governance Committee
Interest in major additions of usage, subject
areas, and data sources should be brokered by
this committee if any of:
Perceived ROI is used as a driver for company efforts
and therefore a forum is needed to confirm and refine
these estimates
Limited budget or people resources
Expansion of data and data uses may strain the
scalability of the environment

25. Slide 25
Prioritizing Efforts
Ease to Do
Prerequisites First
ROI

26. Slide 26
“The Dawn of Man”
Does the Impact of Transformational
Change Always Have to Be Like This?

27. Slide 27
Successful Organization
Transformation Efforts…
Require much more than “the right
analytics” and “good planning” and
“good technology”
Present great opportunities, but also
poses significant implementation risks
Encounter many risks that are “people”
related, which must be managed for
successful implementation

28. Slide 28
Some “People” Risks That Can Slow
Down/Hinder Analytics
§ Leaders not aligned
with transformation
case for change
§ Departments may feel
they have little or no
input in change process
§ Employees concerned
about how new
processes will impact
their current jobs
§ Corporate culture
resistant to change,
tries to maintain way
things have always
been done
§ Interruptions in day-to-
day operations
§ Simultaneous rollout of
other projects
§ Staff not adequately
prepared to execute
new processes and
technology
§ New job roles that
require more complex
organizational
coordination
Change readiness and organization impact assessments can provide
additional insights into the people risks associated
with the implementation

29. Slide 29
Click to edit Master title style
Unlock Potential
Key Areas of Change by Information
Management Discipline

30. Slide 30
Data Warehouse/Data Lake/Data Hub
• USE the Data platform, not old ways to get data
• Accept the data in the platform, not question its quality or
completeness
• Think of other uses for the data in the platform
• Contribute derivations, calculations, summarizations for
the platform, not just take data off the platform for Excel

31. Slide 31
Master Data Management
Get their master data from MDM
Contribute their master data to MDM
Buy into the new business processes to
generate/update master data
Contribute their processes
Effectively use the new business processes to
generate/update master data

32. Slide 32
Response to Change
Denial – The change won’t happen
It won’t affect me
It will be short-lived
Anger
Depression
How can I stop it? (Bargaining)
I’ll try
This isn’t bad
I’m spreading the word!

33. Slide 33
People and Change
Source: reply-mc.com

34. Slide 34
Organization Change Management
(OCM) Focus Areas
OCM focuses on
mitigating “people”
risks and enabling
realization of
business benefits
Engage &
Communicate
Stakeholder
Management
Address
Organizational
Implications
Change
Readiness
Train the
Workforce

35. Slide 35
OCM: Embedded or Stand-Alone
Embedded in a project to support that project
Stand-Alone
In support of multiple projects
In development or production
Part of Data Governance or other organization
Recommend to orient it to projects, have short-term
wins

36. Slide 36
How much OCM to do?
Widespread Org
Implications
Stakeholders
Numerous and
Potential for
Unsupportive
Jobs
Changing
Org Used
to Change
Process
Change
Stakeholder
Management
Change
Readiness
Engage &
Communicate
Address
Organizational
Implications
Train the
Workforce

37. Slide 37
2021 Advanced Analytics Topics
2021 Trends in Enterprise Analytics
Increasing Artificial Intelligence Success with Master Data Management
Comparing the Enterprise Analytic Solutions
Data Pipelines in the Enterprise and Comparison
Platforming the Major Analytic Use Cases for Modern Engineering
The Shifting Landscape of Data Integration
Showing ROI for Your Analytic Project
Using Data Platforms that are Fit-For-Purpose
What is my Enterprise Data Maturity 2021
Methods of Organizational Change Management
Analytic Platforms Should be Columnar Orientation
Measuring Data Quality Return on Investment

38. Slide 38
Why Organizations Don’t Change
When They Need To
Presented by:
William McKnight
President
McKnight Consulting Group
(214) 514-1444
wmcknight@mcknightcg.com
www.mcknightcg.com