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JPK
Gro
upBusiness Forecasting and Analytics Forum
March 1-2 • San Francisco, CA
Utilizing Predictive Analytics toIdentify Business Drivers for Growth
Predict trends, understand customers, improve business
performance, drive strategic decision-making, and predict behavior
March 2, 1:00pm
View presentation online at:
https://jpkgroupsummits.com/attendee1
Prashant Gupta – Cisco
Prashant Gupta is a senior data scientist and have been working in Silicon valleyfor 16 years. He is well known for his abilities to find patterns in the toughest of
data and generating revenue from data.
Utilizing Predictive Analytics to Identify
Business Drivers for Growth
Prashant Gupta
Principal Data Scientist
1
Quick Intro
• Data Scientist having fun in Silicon Valley for last 17 years
• Worked on interesting projects - Apple, Cisco, HP, Informatica, OOCL
• Recently had paper published in ISM ( Institute of Supply Management )
• Created “profitable” and “successful” small businesses in bay area
• Run a non-profit 501©(3) for cultivating entrepreneurship in kids
• Advisor to startup’s
• Currently working @ Cisco – Central Planning Supply Chain
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Maximize
Profits
Minimize Business Expense
How many of us truly understand factors impacting our business and to what degree ?
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Sales• customer demographics • store location• weather
Customer• age • occupation • family status• income level • gender
Expenses• Prices of raw materials• Labor wage rates • Facility rental rates
Finance Marketing Time Competition
3/1/2016Anthony Tarantino, PhD, Six Sigma Master Black Belt, CPIM, CPM
LinkedIn Profile: https://www.linkedin.com/pub/anthony-tarantino-phd/1/40a/808 Email: [email protected]
6
Visual Correlation analysis of inter-dependencies in various supply chain elements. This correlation graph shows cause and effect relationships between elements with wide variations in their levels of interdependence.
Blue = Greater Positive Correlation
Red = Greater Negative Correlation
Let’s start with – Understanding business without Bias & Ego
1. Data sources
• Transactional data ( What they buy )
• Support experience data ( What products they have issues with )
• Demographic data ( General data about their lives )
2. Building dataset
• Feel and understand the data
• Maintain good excellent data quality
3. Building / Testing / Refining models.
• No single model is good enough
• Iteratively increasing model accuracy
Household Income (Income; rounded to the nearest $1,000.00)
Gender (IsFemale = 1 if the person is female, 0 otherwise)
Marital Status (IsMarried = 1 if married, 0 otherwise)
College Educated (HasCollege = 1 if has one or more years of college education, 0 otherwise)
Employed in a Profession (IsProfessional = 1 if employed in a profession, 0 otherwise)
How does our customer look like ?
Actual database attributes
1. amex_gold2. amex_regular3. discover_gold4. discover_regular5. gas_or_retail_gold6. gas_or_retail_regular7. mastercard_gold8. mastercard_regular9. visa_gold10. visa_regular11. investment_active12. dollars_computing_home13. business_owner14. single_parent15. occup_detail_input16. buy_chan_propens_inet17. buy_chan_propens_mail18. buy_chan_propens_phone19. business_owner_input20. apparel_general_sc21. appliances_sc22. electronics_sc23. gifts_holiday_sc24. children_products_sc25. lifestyles_sc26. online_ordr_amt_avg27. other_merchandise_sc28. pets_sc29. sports_and_leisure_sc30. telecommunications_sc31. entertainment_sc32. value_priced_sc33. new_parent34. child_near_hs_grad35. college_grad_life_evnt36. empty_nest_life_event37. newlywed38. new_mover
2000 +
Defining business strategy
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Looks too complex for my business
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Case Study: Tino IQ
Result speak for themselvesPeople trust in them more to identify stocks being manipulated
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Case Study: UBER
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Learnings from case studies
Financial Predictions and Consumer transportations are some of the most complex business around
They involve all areas of growth we discussed:
Sales Customer Expenses Finance Marketing Time Competition
If these companies can succeed. Why not your business ???
Future Best Practices
The next generation business will build on today’s best practices by:
More deeply understanding the business
Utilizing advanced modeling tools & techniques
Moving to hybrid-cloud-based platforms
Creating centers of excellence (CoE) to champion change management and best practices
Data driving action rather than action driving data.
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Thanks
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