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Building a Data Science Practice: Technology and Organisational Considerations Kee Siong Ng

Explore the transformative power of data science across varied industries and understand the impact on organizational strategies and technological considerations. Learn from real-world examples and discover the key to successful data-driven decision-making.

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Building a Data Science Practice: Technology and Organisational Considerations Kee Siong Ng

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  1. Building a Data Science Practice:Technology and Organisational ConsiderationsKee Siong Ng

  2. Big Data Has Arrived THE DIGITAL UNIVERSE WILL GROW 44X IN THE NEXT 10 YEARS

  3. From Real-time Prediction of Flu Trends… Using data on keyword searches, Google and Centre for Disease Control (CDC) can now predict in real-time the onset and severity of flu trends in many countries. This is useful in the control of dangerous flu strains like H1N1. Similar techniques can be used to analyse the impact of the current haze and inform policies!!

  4. To Winning Presidential Campaigns… Harper Reed CTO of OfA Dan Wagner CAO of OfA

  5. And Designing Self-Driving Cars

  6. Retail • CRM – Customer Scoring • Store Siting and Layout • Fraud Detection / Prevention • Supply Chain Optimization • Advertising & Public Relations • Demand Signaling • Ad Targeting • Sentiment Analysis • Customer Acquisition Industries Are Broadly Embracing Data Science • Financial Services • Algorithmic Trading • Risk Analysis • Fraud Detection • Portfolio Analysis • Media & Telecommunications • Network Optimization • Customer Scoring • Churn Prevention • Fraud Prevention • Manufacturing • Product Research • Engineering Analytics • Process & Quality Analysis • Distribution Optimization • Energy • Smart Grid • Exploration & Production • Refining & Marketing • Government • Market Governance • Counter-Terrorism • Econometrics • Health Informatics • Healthcare & Life Sciences • Pharmaco-Genomics • Bio-Informatics • Pharmaceutical Research • Clinical Outcomes Research

  7. Now There Are Empirical Proofs that It's Working • Case studies and economic theory suggest a potential connection between data-driven decision making and productivity. • A recent systematic empirical study of 179 large publicly traded firms using standard econometric method discussed in HBR reveals: Companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors

  8. Confluence of Big Ideas = Lollapalooza Effect

  9. From Consumer Internet to the Industrial Internet

  10. Democratisation of Data

  11. Distributed Data Computing Platforms Client ... ... Greenplum ... ...

  12. Modern Analytical Approaches • From Exact Causal theories (e.g. gravity) to Probably Approximately Correct theories with performance guarantees. • From Domain Knowledge and Experience to the "Unreasonable Effectiveness of Data" at solving hitherto difficult problems. • From Individual Expert predictions to Wisdom of the Crowd. Leslie Valiant Peter Norvig Scott E. Page

  13. Wisdom of the Crowd: Prediction Markets

  14. Helping Organisations Evolve…

  15. Transformation Catalysts

  16. Hiring and Keeping Data Scientists

  17. The Question of Org

  18. Data Science Initiative: Spectrum of Outcomes • Bad: Hot mess of organisational wrangling over issues like • Data ownership • Where analytics should live • Shortsighted technology investments • Digging-in-of-heels around legacy platforms • Analytical project work-to-nowhere • Good: Company transformation built-upon data-derived innovation • Data science generated IP and competitive advantage • Executive alignment on data initiatives • Thriving data science culture • Clearly defined paths from modelling to operationalisation for P&L impacts

  19. A Premorterm: Biggest Obstacles to Data Science Adoption All I want to know is where I'm going to die so I'll never go there. Charlie Munger

  20. Summary – Transformation Success Criteria • Establish a clear vision for the role of Big Data Analytics • Understand end-to-end platform dependencies • Embrace the Analytics Data Lake paradigm • Educate and build your Data Science Dream Team • Organise to your contextual reality • Initiate smart processes • Deliver one concrete win • Socialise, socialise, socialise

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