This document discusses how companies can make their data work for them in the information age. It emphasizes removing bias when using data to make decisions, considering every possible angle and perspective, asking the right questions, focusing on applied results rather than just analysis, and establishing data first principles like ensuring decisions are supported by evidence. The presentation provides examples of how companies can analyze customer, sales, and transaction data to gain insights about repeat customers, identify opportunities, and improve performance.

1. Make Your Data Work For You
Rob Ortiz
Director
Keyence
Arthur Bailey
Director
Samsung Electronics

3. Why are we here?
• Any time a new age comes to humanity, it
forces a shift in focus and strategy.
We are now firmly in the Information Age.
Are you ready?
What does this mean for companies?
What change in thought needs to occur?
No…that’s a different lecture
• Bronze Age
• Iron Age
• Middle Age
• Renaissance
• Industrial Age
• Space Age
• Information Age

4. 2 5 7 9 13 16 18
26
33
41
51
65
80
101
130
175
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Worlds Data in ZetaBytes

5. …40 years of age, with a child under the age of 10…
If you are……
4 Minutes

7. We use Data ‘Guided’ decisions every day

8. Data
Human
Intelligence
Machine
Intelligence
Why Does It Fail?
85% of Data
Projects fail to
produce results
~Pactera Report

9. King Croesus
547 BC
Lydian Empire

10. Model Trained!
Confidence = High

11. “Should I go to war with Persia?”

12. “If Croesus goes to war, he will destroy a great empire.”

14. Going to see Grandma in Florida
Let’s go back to the GPS
• “How do I get on I-95?”
• “How do I get to Grandma’s?”
• “Should I go to Grandma’s?”

17. The Anchor Effect
“A cognitive bias that causes individuals to rely too heavily on
their previous points of reference”

18. Examples of the Anchoring Effect
• Own Role Infallibility
• “It’s not a marketing problem, it’s got to be sales”
• Ain’t broke don’t fix it
• “We’ve always done it this way”
• Blaming external factors
• “The economy has been down”
• Constantly digging for the expected “answer”
• “I'm not seeing what I expected. Keep looking”

19. Why?

20. So how do we solve it?
Tell the executive team they are wrong
Invest in hundreds of additional analysts
Keep consultants on retainer
Or
Ask an unbiased party to test every theory

22. Customer ID Product Group Sum Qty Avg Qty Max Qty Min Qty Sum of Amount …..
10111 Sensor 8 4 5 3 349.91$ Ect..
Day of Week Count unique customers Sum Sales Sum QTY Sale per unit Sale per customer
MON 2 1,040.95$ 14 74.35$ 520.48$
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Product Group Count transactions Sale per unit Sale per transaction Count of Weekday
Sensor 3 42.16$ 126.47$ 1
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$

23. Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Transactions CustomerCustomer ID Industry Size Salesperson Region
10009 Retail $100 M Ian North
10087 Electronics $1 B Cathy South
10111 Home Goods $5 B Ian East
10178 Retail $250 M Blake Central
10265 Wholesale $10 B Cathy South
10352 Electronics $100 M Ed South
Customer ID Date Time Access Source
10009 2019/11/02 (SAT) 8:32 Help Guide Google
10009 2019/11/03 (SUN) 14:18 Account Info Direct
10009 2019/11/05 (TUE) 20:53 Help Guide Email
10111 2019/11/01 (FRI) 11:10 Video LinkedIn
10265 2019/11/06 (WED) 15:37 Account Info Email
10265 2019/11/01 (FRI) 14:21 Account Info Direct
Web Activity
Salesperson Date Time Event Customer ID
Blake 2019/11/01 (FRI) 11:18 Phonecall 30823
Cathy 2019/11/04 (MON) 16:14 Salescall 10087
Donna 2019/11/04 (MON) 16:18 Phonecall 15765
Ed 2019/11/05 (TUE) 9:54 Web 19876
Blake 2019/11/06 (WED) 10:19 Service 21548
Cathy 2019/11/05 (TUE) 14:51 Web 13767
Sales Activity
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Salesperson Date Time Event Customer ID
Blake 2019/11/01 (FRI) 11:18 Phonecall 30823
Cathy 2019/11/04 (MON) 16:14 Salescall 10087
Donna 2019/11/04 (MON) 16:18 Phonecall 15765
Ed 2019/11/05 (TUE) 9:54 Web 19876
Blake 2019/11/06 (WED) 10:19 Service 21548
Cathy 2019/11/05 (TUE) 14:51 Web 13767
Customer ID Industry Size Salesperson Region
10009 Retail $100 M Ian North
10087 Electronics $1 B Cathy South
10111 Home Goods $5 B Ian East
10178 Retail $250 M Blake Central
10265 Wholesale $10 B Cathy South
10352 Electronics $100 M Ed South
Customer ID Date Time Access Source
10009 2019/11/02 (SAT) 8:32 Help Guide Google
10009 2019/11/03 (SUN) 14:18 Account Info Direct
10009 2019/11/05 (TUE) 20:53 Help Guide Email
10111 2019/11/01 (FRI) 11:10 Video LinkedIn
10265 2019/11/06 (WED) 15:37 Account Info Email
10265 2019/11/01 (FRI) 14:21 Account Info Direct
Customer ID Date Time Access Source
10009 2019/11/02 (SAT) 8:32 Help Guide Google
10009 2019/11/03 (SUN) 14:18 Account Info Direct
10009 2019/11/05 (TUE) 20:53 Help Guide Email
10111 2019/11/01 (FRI) 11:10 Video LinkedIn
10265 2019/11/06 (WED) 15:37 Account Info Email
10265 2019/11/01 (FRI) 14:21 Account Info Direct
Salesperson Date Time Event Customer ID
Blake 2019/11/01 (FRI) 11:18 Phonecall 30823
Cathy 2019/11/04 (MON) 16:14 Salescall 10087
Donna 2019/11/04 (MON) 16:18 Phonecall 15765
Ed 2019/11/05 (TUE) 9:54 Web 19876
Blake 2019/11/06 (WED) 10:19 Service 21548
Cathy 2019/11/05 (TUE) 14:51 Web 13767
Date Time Customer ID Product Group Qty Amount
2019/11/04 (MON) 12:30 10111 Sensor 5 149.95$
2019/11/04 (MON) 14:21 10135 Measurement 9 891.00$
2019/11/06 (WED) 19:38 10352 Software 1 1,899.99$
2019/11/09 (SAT) 19:30 10111 Sensor 3 199.96$
2019/11/10 (SUN) 11:27 10165 Measurement 1 99.99$
2019/11/10 (SUN) 19.30 10891 Sensor 1 29.49$
Customer ID Industry Size Salesperson Region
10009 Retail $100 M Ian North
10087 Electronics $1 B Cathy South
10111 Home Goods $5 B Ian East
10178 Retail $250 M Blake Central
10265 Wholesale $10 B Cathy South
10352 Electronics $100 M Ed South

24. Repeat Customers
Customers who purchased more than 6 items
And never spends less than $399.99
Customers who only buy Software
5.3%
4.9%
14.7%

25. Which customers who usually repeat, aren’t?
What about Software only customers?

26. Data First Principles
1. What data do we have that supports our decision?
2. What data will this decision generate?
3. What is the numeric value that will dictate success?

27. Making your data work for you
• Remove bias from building targets
• Consider every possible angle
• Ask the right questions
• Consider Data First Principles
• Set honest and realistic expectations
• Focus on the applied result
• Not the analysis itself

29. Thank You
Booth 1434