Data Infrastructure for Your Retail Digital Strategy

185 views

Published on

Retailers are facing disruptive times and are pressured to diigtize their businesses. While data remains at the center of all operations, it can also be leveraged as a core enabler of your strategy if your data infrastructure follows these tenets

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

Data Infrastructure for Your Retail Digital Strategy

  1. 1. Data Infrastructure For your Retail Digital Strategy Atif Rahman @atifshaikh 07.12.2016
  2. 2. • The lion • Slow and Fast decision making What comes to your mind when you see this? Running or Analytics?
  3. 3. SYSTEM I SYSTEM II Running Knee-Jerk Flight or Fight Long Term Analysis Big Picture
  4. 4. SUBSTITUTION EXTENSION TRANSFORMATION • More Channels • More Noise • More of Everything • Incremental • Replacements • New Shiny Tool • New Way of Work • New Products • New Experiences Typical Digital Strategy Journey
  5. 5. DIGITAL TRANSFORMATIONS AROUND US Enablers are all there – Technological, Social, Regulatory. Barriers to entry are virtually non existent
  6. 6. Amazon Go – Back to the Human Experience Blending Digital with the Physical
  7. 7. PEOPLE BUSINESS MODEL Building Blocks of a Digital Strategy CLOUDMOBILE SOCIAL IOT ANALYTICS DATA
  8. 8. Leading Digital, Westerman et al. 2014 SYSTEM I VS SYSTEM II THINKERS
  9. 9. FOMO, FUD OR SOMETHING REAL?
  10. 10. SIMPLY THROWING MONEY AT A PROBLEM RARELY WORKED
  11. 11. Somethings money cannot buy? PHYSICAL COMPETENCIES INTANGIBLES DATA STORES DISTRIBUTION BRAND EXPERIENCE PROCESSES ORG MATURITY DATA POINTS ANALYTICS
  12. 12. Customer Experience Operational Processes Business Model Areas to Transform
  13. 13. Tenets of a (good) Data Infrastructure DATA AGILE ELASTIC HOLISTICFLEXIBLE ANALYTICAL
  14. 14. Compared to Waterfall
  15. 15. ELASTIC • Scale Up / Down (Handling Spikes) • OnDemand Backup • Linearly Scalable
  16. 16. HOLISTIC DATA LAKES ALLOW FOR NEARLY ALL THE DATA TO BE USED FOR KEY ACTIVITIES Data Diversity and Comprehensiveness
  17. 17. FLEXIBLE Not bound in traditional rigid structures (relational etc.). NOSQL
  18. 18. ANALYTICAL • Culture of (Scientific) experimentation • Segmentation Frameworks • Data & Analytic Products (e.g. Segmentation) Most Analytics newcomers expect a definite end goal whereas top analytics teams deliver incremental value over rapid iterations in a ’safe’ work enviornment.
  19. 19. Iteration 1 Iteration 2 Iteration 3 Iteration 4 Iteration N • First time a lot of experiments must be undertaken with variations • Clearly irrelevant experiments will filter out • The problem statement starts to become more prominent • Potential close solutions are in sight • Winning recipes are converged! Growth Hacking How to play your cards well…
  20. 20. Hackathons • Community (eCommerceSea) • DYOB (Destroy Your Own Business) • WWAD (What Would Amazon Do)
  21. 21. DON’T BE AFRAID OR OVERWHELMED; FOLLOW THE TENETS AND SHORTLIST
  22. 22. Disclaimer: The talk is aimed at people new to Data and Analytics and hence prefers simplification over rigor. QUESTIONS?

×