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Data Science in Retail: Growing
your Capability for Strategic
Advantage
ENDA RIDGE, PHD
HEAD OF ALGORITHMS, UK FMCG
“Data is the new oil”
“The sexiest job of the
century”
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analy...
 Science
We know what the
scientific method is
What is Data Science for the Enterprise?
“Data Science is the discipline of discovering data and
understanding data to fin...
What is Data Science?
 Opportunities in new data sources, new products, new understanding
 Efficiencies in automation, p...
What is Data Science?
“Data Science is the discipline of discovering data and
understanding data to find opportunities, ef...
High maturity organisations
Frame a
business
hypothesis
Gather and
generate
data
Analyse
Confirm with
experiment
Copyright...
What Data Science is not…
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
7
https:...
Data Science Involves Uncertainty
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
...
Data Science Involves New Data
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
9
...
Data Science involves Varied Activities
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_...
Data Science involves Experiments
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net
11
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net
12
The Enterprise Matrix
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
16
Marketing...
The Enterprise Matrix
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
17
Marketing...
5 Challenges for Data Science
Org structure & the customer
Enabling the team
Making insights actionable
Integration with t...
Challenge #1: structure and customer
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_rid...
Action #1: Chief Data Scientist (CDS)
 Centre of Excellence
 A Senior Advocate
 Business Side
 Clear Engagement Model
...
Challenge #2: Enabling the team
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
21...
Action #2: build tactical environment
 Then build out
 Scale
 Permission groups
 Proxy access
 Local admin rights
 L...
Challenge #3: making insights actionable
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda...
Action #3: Operating Model
 Realistic middle ground
 Use version control
 Create ‘integration tests
cases’
 Create Dat...
Challenge #4: data community
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge
25
Ma...
 Create Terms of Reference
 Quick wins
 Create marketing materials for Data Science
 Have clear Engagement materials
...
Challenge #5: Getting & keeping people
Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_r...
Action #5: Prioritised Hires
 Less genius, more resilience and
practicality
 Keep them focused
 Clear progression struc...
5 Challenges for Data Science
Org structure & the customer
Enabling the team
Making insights actionable
Integration with t...
Data Science
 A practical definition of Data Science and how retail
can benefit
 Operational and organisational challeng...
Data Science in Retail - growing your capability (Keynote at Polish Data Science In Business December 2016)
Data Science in Retail - growing your capability (Keynote at Polish Data Science In Business December 2016)
Data Science in Retail - growing your capability (Keynote at Polish Data Science In Business December 2016)
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Data Science in Retail - growing your capability (Keynote at Polish Data Science In Business December 2016)

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Confusion, hype, failure to start. Data Science has huge potential to change an organisation. It has real potential to improve the top and bottom lines. But many organisations become mired in the associated cultural, technological and people change. Data Science is delivered as an interesting report rather than a driver of change. Data Science identifies algorithms that are run in the safety of a lab but never make it into production. Why does this happen and what can be done to avoid it?

This talk will cover:
- a practical view of Data Science and how retail can benefit
- operational and organisational challenges and conflicts
- Get started! 5 tips to proving your worth to leadership starting now

Published in: Data & Analytics
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Data Science in Retail - growing your capability (Keynote at Polish Data Science In Business December 2016)

  1. 1. Data Science in Retail: Growing your Capability for Strategic Advantage ENDA RIDGE, PHD HEAD OF ALGORITHMS, UK FMCG
  2. 2. “Data is the new oil” “The sexiest job of the century” Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net 1
  3. 3.  Science We know what the scientific method is
  4. 4. What is Data Science for the Enterprise? “Data Science is the discipline of discovering data and understanding data to find opportunities, efficiencies and improvements” Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 3
  5. 5. What is Data Science?  Opportunities in new data sources, new products, new understanding  Efficiencies in automation, process changes, organisation change  Improvements in product features, product offerings Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 4 “Data Science is the discipline of discovering data and understanding data to find opportunities, efficiencies and improvements”
  6. 6. What is Data Science? “Data Science is the discipline of discovering data and understanding data to find opportunities, efficiencies and improvements” Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 5  Data Science uses the scientific method  Experiments to test hypotheses  Rigorous measurement  Making changes and observing effects
  7. 7. High maturity organisations Frame a business hypothesis Gather and generate data Analyse Confirm with experiment Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge Data-driven operations Data-driven products 6
  8. 8. What Data Science is not… Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 7 https://vimeo.com/88093956
  9. 9. Data Science Involves Uncertainty Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 8  Data  Processes  Questions  Solutions
  10. 10. Data Science Involves New Data Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 9  Surveys  Web scrapes  Systems  Logs  3rd party
  11. 11. Data Science involves Varied Activities Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 10  Data joins  Visualizations  Algorithms  Languages
  12. 12. Data Science involves Experiments Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net 11
  13. 13. Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net 12
  14. 14. The Enterprise Matrix Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 16 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment
  15. 15. The Enterprise Matrix Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 17 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment Data Science
  16. 16. 5 Challenges for Data Science Org structure & the customer Enabling the team Making insights actionable Integration with the data community Getting and keeping people Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 18
  17. 17. Challenge #1: structure and customer Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 19 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment Data Science You need to demonstrate value fast  But  All want to own ‘the sexiest job of 20th century’  Rebranding  Perhaps non-Agile ways of working  Perhaps not ready to execute
  18. 18. Action #1: Chief Data Scientist (CDS)  Centre of Excellence  A Senior Advocate  Business Side  Clear Engagement Model  ‘Ready’  ‘Done’  Pipeline Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 20 Project Project Project CDS
  19. 19. Challenge #2: Enabling the team Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 21 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment Data Science You need Data and Technology to do Data Science  But  Tradition of control  Generally slow  Incentivised to maintain status quo
  20. 20. Action #2: build tactical environment  Then build out  Scale  Permission groups  Proxy access  Local admin rights  Licencing  Tech Support  Data governance  Data feeds Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 22 Lab Data store Applica tions Dev tools
  21. 21. Challenge #3: making insights actionable Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 23 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment Data Science You need Data Science turned into Algorithms in products  But  Own opinions on tech  Not familiar with Data Science methods and code  Product lens
  22. 22. Action #3: Operating Model  Realistic middle ground  Use version control  Create ‘integration tests cases’  Create Data Science user stories  Keep algorithms simple  See ‘Guerrilla Analytics’ Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 24 Lab Factory Interfaces
  23. 23. Challenge #4: data community Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 25 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment Data Science You need access to data You need customers  But  Gatekeepers  Perceived threat  Rebranding  Confusion with customer
  24. 24.  Create Terms of Reference  Quick wins  Create marketing materials for Data Science  Have clear Engagement materials  Engage with broader data community (forums, talks etc) Action #4: Set out your stall Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 26
  25. 25. Challenge #5: Getting & keeping people Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 27 Marketing Sales / Trading Logistics Other IT, InfoSec, Architecture Product Development BI & Analytics HR & Recruitment Data Science You need key hires and the market is competitive  But  Existing pay structures  Existing job formats  Hiring agencies
  26. 26. Action #5: Prioritised Hires  Less genius, more resilience and practicality  Keep them focused  Clear progression structures  Establish training budget Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 28
  27. 27. 5 Challenges for Data Science Org structure & the customer Enabling the team Making insights actionable Integration with the data community Getting and keeping people Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 29
  28. 28. Data Science  A practical definition of Data Science and how retail can benefit  Operational and organisational challenges and conflicts  Get started! 5 tips to proving your worth now  Find me  on Twitter @enda_ridge #GuerrillaAnalytics  on my blog http://guerrilla-analytics.net Copyright Enda Ridge 2016#GuerrillaAnalytics http://guerrilla-analytics.net @enda_ridge 30

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