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OPERATIONALIZING
ANALYTICS AND AI
Vishwa Kolla
Head, Advanced Analytics
John Hancock Insurance
TOPICS
2
Drivers Levers Case Studies
A JOURNEY TO DELIVER VALUE MIGHT INCLUDE HELPING …
3
REDUCE
COMPLAINTS
GROW
WALLET-
SHARE
GROW
CSAT
REDUCE
CHURN
REDUCE
CO...
1997
2011
2016
ANALYTICS / AI IS AN ENABLER
4
Smart
Human
Smart
Human
Normal
Human
Normal
Human
Smart
Machine
OK
Machine
Smart
Machine
OK
Machine
Weak
Process
Weak
Proc...
Smart
Human
Smart
Human
Normal
Human
Normal
Human
Smart
Machine
OK
Machine
Smart
Machine
OK
Machine
Weak
Process
Weak
Proc...
Normal
Human
OK
Machine
Strong
ProcessSteven Crampton and Zackary Stephen
New Hampshire
Beat Grand Masters + Machine
2005
...
“Weak human + machine + better process was superior to a strong
computer alone and, more remarkably, superior to a strong ...
ITERATIONS  VALUE ; INCREASING ADOPTION IS TODAY’S FOCUS
9
Data Models Insights ADOPTIONIterations
VALUE TO FIRM
FOCUS
TOPICS
10
Drivers Levers Case Studies
AI IS BUILT
11
AI is not something you buy; it’s something you build.
It’s not something you outsource; it’s something you...
BIG DECISIONS
12
BUY BUILD IT FOR ME BUILD IN-HOUSE
Cost Customization Man-Hours
Build-time Support Knowledge
gain
Cost Cu...
NO DEARTH OF BUILD OPTIONS
13
EXCEL SHINY R
HOME GROWN LOW CODE
TOPICS
14
Drivers Levers Case Studies
EXCEL IS OUR DEFACTO STARTING POINT
15
PROFILING AUTOMATED
EXPLORATION
DATA CLEANSING
ACCELERATORS
RULES ENGINE FRONT-END ...
EXCEL SERVES US WELL FOR RAPID POC
16
THE GOOD
EASY
ADAPTABLE
THE BAD
DATA CONNECTION
LATENCY
SINGLE THREADED
THE UGLY
VIS...
SHINY IS REALLY SHINY ; ACCELERATES ADOPTION
17
Shiny R
App
Web
scrapping
Sentiment
Analysis
Word
clouds
Topic
Modelling
W...
WE FIND SHINY IS AN AGILE WAY TO DATA SCIENCE
18
1. Shiny Dashboard
2. Plotly
3. Ggplot
4. Render
5. Ggvis
6. Shiny.Semant...
USE SHINY ONLY IF YOU HAVE A COMMUNITY OF ADOPTERS
19
THE GOOD
VISUAL DATA
CONNECTIVITY
POWER OF R
DS ALGORITHMS
THE BAD
H...
HOME GROWN IS A DOUBLE-EDGED SWORD
20
FOUNDATIONAL USP CORE-IP
ONE-OFF RE-INVENTING
THE WHEEL
NON-CORE
IP
LOW CODE CAN ACCELERATE ADOPTION FOR A LOW(ER) COST
21
BI IN
EXCEL
STAND-
ALONE BI
BI ON
WEB
BI ON
MOBILE
BI FOR
MOBILE &
...
USE “FIT FOR PURPOSE” WHEN CHOOSING AN OPTION
22
POC PROTOTYPE PROD
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1615 track 1 kolla_using our laptop

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1615 track 1 kolla_using our laptop

  1. 1. OPERATIONALIZING ANALYTICS AND AI Vishwa Kolla Head, Advanced Analytics John Hancock Insurance
  2. 2. TOPICS 2 Drivers Levers Case Studies
  3. 3. A JOURNEY TO DELIVER VALUE MIGHT INCLUDE HELPING … 3 REDUCE COMPLAINTS GROW WALLET- SHARE GROW CSAT REDUCE CHURN REDUCE COST TO TARGET GROW BOTTOM-LINE GROW TOP-LINE REDUCE COST TO ACQUIRE
  4. 4. 1997 2011 2016 ANALYTICS / AI IS AN ENABLER 4
  5. 5. Smart Human Smart Human Normal Human Normal Human Smart Machine OK Machine Smart Machine OK Machine Weak Process Weak Process Weak Process Strong Process WHAT WILL YIELD THE BEST OUTCOME? 5
  6. 6. Smart Human Smart Human Normal Human Normal Human Smart Machine OK Machine Smart Machine OK Machine Weak Process Weak Process Weak Process Strong Process A STRONG PROCESS IS CRITICAL 6
  7. 7. Normal Human OK Machine Strong ProcessSteven Crampton and Zackary Stephen New Hampshire Beat Grand Masters + Machine 2005 THE OUTCOME (THOUGH NON-INTUITIVE) IS REMARKABLE 7
  8. 8. “Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.” – Gary Kasprov WE EMPHASIZE PROCESS (OVER PURPOSE) FOR THE MOST PART 8
  9. 9. ITERATIONS  VALUE ; INCREASING ADOPTION IS TODAY’S FOCUS 9 Data Models Insights ADOPTIONIterations VALUE TO FIRM FOCUS
  10. 10. TOPICS 10 Drivers Levers Case Studies
  11. 11. AI IS BUILT 11 AI is not something you buy; it’s something you build. It’s not something you outsource; it’s something you cultivate internally, until it becomes a trusted core capability. And it is not, counter- intuitively, just about technology; it is, truly, about machines learning from humans. Developing a successful AI algorithm today requires the presence of humans in the learning loop, especially during the process of training the algorithm—a resource-consuming undertaking that many companies woefully underestimate. -- Brad Fisher, KPMG Source: https://www.forbes.com/sites/kpmg/2017/08/09/realizing-the-promise-of-artificial-intelligence/#7362edfb485e
  12. 12. BIG DECISIONS 12 BUY BUILD IT FOR ME BUILD IN-HOUSE Cost Customization Man-Hours Build-time Support Knowledge gain Cost Customization Man-Hours Build-time Support Knowledge gain
  13. 13. NO DEARTH OF BUILD OPTIONS 13 EXCEL SHINY R HOME GROWN LOW CODE
  14. 14. TOPICS 14 Drivers Levers Case Studies
  15. 15. EXCEL IS OUR DEFACTO STARTING POINT 15 PROFILING AUTOMATED EXPLORATION DATA CLEANSING ACCELERATORS RULES ENGINE FRONT-END ADHOC ANALYSES MODEL EXPERIMENTS FRONT Variable Name Start Value End Value Capped Value ELSE VAL Capped Var Desc ELSE_VAL_DESC DEMO_AGE 0 18 1 55 01 - 0 to 18 05 - 50 - 60 DEMO_AGE 18 30 2 55 02 - 18 to 30 05 - 50 - 60 DEMO_AGE 30 40 3 55 03 - 30 to 40 05 - 50 - 60 DEMO_AGE 40 50 4 55 04 - 40 to 50 05 - 50 - 60 DEMO_AGE 50 60 5 55 05 - 50 to 60 05 - 50 - 60 DEMO_AGE 60 71 6 55 06 - 60 to 71 05 - 50 - 60 DEMO_AGE 71 81 7 55 07 - 71 to 81 05 - 50 - 60 DEMO_AGE 81 91 8 55 08 - 81 to 91 05 - 50 - 60 DEMO_AGE 91 999 9 55 09 - 91 to 999 05 - 50 - 60
  16. 16. EXCEL SERVES US WELL FOR RAPID POC 16 THE GOOD EASY ADAPTABLE THE BAD DATA CONNECTION LATENCY SINGLE THREADED THE UGLY VISUALIZATION LIBRARY ALGORITHMS
  17. 17. SHINY IS REALLY SHINY ; ACCELERATES ADOPTION 17 Shiny R App Web scrapping Sentiment Analysis Word clouds Topic Modelling Word Frequency
  18. 18. WE FIND SHINY IS AN AGILE WAY TO DATA SCIENCE 18 1. Shiny Dashboard 2. Plotly 3. Ggplot 4. Render 5. Ggvis 6. Shiny.Semantic 7. ShinyBS 8. ShinyJqui 9. Leaflet 10. ShinyCCSloaders 11. Ggmaps 1. Caret 2. Tm 3. Dplyr 4. Tidyr 5. Stringr 6. Car 7. Vcd 8. Rccp 9. Jsonlite 10. Httr 11. Devtools UI.R SERVER.R VISUAL ENHANCE MENTS STRATEGY CHANGE BUISNESS INPUT UI SMOTHING DATA ENGG. ALGO RECALI BRATION SCRUBBING EDA BIVARIATE ANALYSIS TEXT ANALYTICS CLASSIFI CATION AI SCRUBBING IMAGE PROCESSING ML TIME SERIES ANALYSIS
  19. 19. USE SHINY ONLY IF YOU HAVE A COMMUNITY OF ADOPTERS 19 THE GOOD VISUAL DATA CONNECTIVITY POWER OF R DS ALGORITHMS THE BAD HARDER TO LEARN VISUALS THE UGLY LIMITED SCALABILITY MEMORY HOG
  20. 20. HOME GROWN IS A DOUBLE-EDGED SWORD 20 FOUNDATIONAL USP CORE-IP ONE-OFF RE-INVENTING THE WHEEL NON-CORE IP
  21. 21. LOW CODE CAN ACCELERATE ADOPTION FOR A LOW(ER) COST 21 BI IN EXCEL STAND- ALONE BI BI ON WEB BI ON MOBILE BI FOR MOBILE & WEB LOW CODE
  22. 22. USE “FIT FOR PURPOSE” WHEN CHOOSING AN OPTION 22 POC PROTOTYPE PROD

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