Gary Cokins, an expert in performance improvement and cost management, presented insights into business analytics at a seminar. He emphasized the importance of analytics in making informed decisions, differentiating between business intelligence and business analytics, and the benefits of predictive modeling over traditional forecasting. The presentation also discussed the necessity of overcoming barriers to effective analytics implementation and the role of customer lifetime value in strategic decision-making.

1. Business Analytics - Highlights
Gary Cokins, CPIM
Illinois CPA Society Seminar
October 21, 2014
Slideshare by:

2. About Gary
•Gary Cokins is an internationally recognized expert, speaker, and author in performance improvement systems and cost management.
•BS Degree (with honors) in Industrial Engineering/Operations Research from Cornell University
•MBA (with honors) from Northwestern University
•Career highlights: FMC Corporation, Deloitte Consulting, KPMG, EDS, SAS
•Professional affiliations: IMA, IFAC, CAM-I, AICPA, AAA…
•National Baseball Hall of Famer (oldest computer baseball game)
•Prolific book writer, blogger
http://www.garycokins.com/menu-bio

3. Gary Cokins, CPIM
Analytics-Based Performance Management LLC
Cary, North Carolina USA
www.garycokins.com
919.720.2718
gcokins@garycokins.com
Contact Gary

4. “40% of important decisions are not based on facts but rather on intuition, experience, and anecdotal evidence.”
Jeanne X. Harris, Accenture
Why Business Analytics?

5. Better decisions
Better Actions
Purpose of Business Analytics

6. Goals of Analytics:
Gain Insight
Solve Problems
Make better and quicker decisions
Take action

7. BI vs. Business Analytics
Business Intelligence
Business Analytics
Consumes stored information
Monitors the dials on a dashboard
Answers existing questions
Produces new information
Moves the dials on a dashboard
Creates new questions
Answers new complex, more relevant questions

8. Domains of Business Analytics
Retail: Markdown and assortment planning Marketing: CRM, segmentation, and churn analysis Financial services: Risk management, credit scoring Pharmaceutical: Drug development Text: Sentiment analytics Fraud: insurance and medical claims Manufacturing: Warranty claims Hospital: Patient scheduling Human Resources: Workforce planning Police: Crime pattern analytics … and more

9. Descriptive vs. Inferential Analytics
Reactive
Standard Reports
Ad Hoc Reports
Query Drilldown (or OLAP)
Alerts
Proactive
Statistical Analysis
Forecasting
Predictive Modeling
Optimization
Descriptive
Inferential

10. Statistics is more confirmatory than exploratory.
Great business analysts search for confirmation that two or more factors driving their data are related.
Case for Statistics

11. Forecasting vs. Predictive Modeling
Forecasts
Predictive models
Tell you how many ice scream cones will be sold in July, so you can set expectations for planned costs, profits, supply chain impacts and other considerations
Tell you the characteristics of ideal ice scream customers, the flavors they will choose and coupon offers that will entice them

12. Forecasting vs. Predictive Modeling
When to use:
Forecasts
Predictive models
To help you do a better job of buying raw materials for the ice scream, and to have them at the factory at the right time
If the marketing department is trying to figure out how, where, and which most attractive customers to market the ice scream

13. Given the scarce resources of our marketing budget, which customer should we pursue?
A. Most profitable customer
B. Most valuable customer
The difference is Customer Lifetime Value
Customer Value Management

14. Which customer is more important for a pharmaceutical supplier?
Customer Lifetime Value
Dentist A
Sales = $ 750,000
Profits = $ 100,000
Age 61
Dentist B
Sales = $ 375,000
Profits = $ 40,000
Age 25
More profitable
More valuable

15. Focusing on the number of customers acquired results in a degraded mix as low-value customers are easier to acquire
A customer-centric strategy will not acquire any customers; only high-value ones
Customer Acquisition Strategy
Solution:
Determine which type of customer is attractive to acquire, retain grow, or win back. Which customer types are not?
Create a spend budget for attracting, retaining, growing, or recovering each customer segment

16. Optimizing Customer Value – “Smart” Sales Growth
* You can destroy shareholder wealth creation, (erode your profits) by:
* Over-spending unnecessarily on loyal customers for what is needed to retain them
* Under-spending on marginally loyal customers and risk their defection to a competitor

17. Role of Analytics
Analysts must overcome hunches and gut-feel guesses by others, and prove which actions yield the highest financial returns

18. The impact of reduction in uncertainty
Everything starts with sales!
The demand forecast of your product is the independent variable. (First domino)
All other measures are dependent variables. (Remaining dominos)
Forecasts are based on history. “Best methods selection” chooses a “best fit forecasting method.”
As history changes, sometimes radically (new competitors), “best fit” method becomes stale.

22. * Higher ROI from leveraging automation
* Deeper actionable insights and understanding
* Reducing uncertainty and managing risk
* More intelligent and tested decisions
* A bridge to culture of optimization
Benefits of Business Analytics
Competency with Business Analytics yields a lasting and sustainable competitive advantage

23. * Fear of loss of power and decentralizing decision rights
* Confirmation bias interpreting results to confirm preconceptions
* Lack of analytical talent
* Thinking small/”toll gate” approach
* Lack of leadership and willpower
Risks from pursuing Business Analytics
You can do one thing wrong and fail.. You have to do many things correct to succeed!

24. Three types of concerns:
* Logical concern: Confusion versus understanding
* Your audience thinking, “I don’t get it”
* Emotional concern: Fear versus a favorable action
* Your audience thinking, “I don’t like it”
* Personal concern: Mistrust versus confidence
* Your audience thinking, “I don’t like you.”
“Beyond the Wall of Resistance”
By Rick Maurer

25. Technical barriers include IT-related issues
Perception barriers are excess complexity and affordability
Design deficiencies include poor measurements or their calculations and weak models and assumptions
Organizational behavior barriers involve resistance to change, culture, leadership
Barrier categories

26. “Moneyball” tells the story of how quantitative analysis can overcome perceptions of old school thinking.
The Oakland As lowered their salary costs, but did not begin winning until they applied deep analytics.

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