AI in Supply Chain and Economics of Logistics - Frank Corrigan

The Minhaaj's Podcast

Francis Corrigan is Director of Decision Intelligence at Target Corporation. Embedded within the Global Supply Chain, Decision Intelligence combines data science with model thinking to help decision-makers solve problems.

00:00 Intro

01:21 Data Science applications in Logistics and Supply Chain, Cost and Performance trade-off

03:21 Amazon vs Target fulfillment Model, Owning vs Coordinating with Last Mile companies e.g. FedEx

08:36 Suez Canal Container Blockage, Fallback plan at Target

10:37 Predicting products to Stock in Bottle Neck Scenarios

12:42 Air Freight vs Sea Shipments Costs, Ideal vs Real World Deliveries

15:48 Lack of Good Data and Prediction Challenges

18:00 Managing Expectations as Head of Analytics, Importance of Communicating

20:11 Stakeholder Management & Data Science Newsletter

23:39 Technical and Non-technical Teams Coordination, Speed Reading

26:36 Data Stories and Visualizations

29:47 Reporting Pipelines vs Story Narration

31:37 Times Series, Prophet, Flourish and Hans Rosling

35:28 Economist turned Data Scientist, Embarrassment as Motivation

38:20 Lack of Practical Skills of Data Science at University

41:18 Employer’s Perspectives on Data Science Talent

45:24 What Causes Data Teams Failure

48:40 COVID 19 and Times Series Corruption, Anomaly Detection

56:15 Toilet Paper Demand Scenario, Commodity Pricing Alerts

59:50 Automating Alerts for Panic Situation

01:02:10 Pandemic as a Blessing for Digital Business, Exponential Growth Rates and Tuition Fee Reimbursement for Employees

01:06:06 Data as Decision Support System, Strategic Decision Indicators

01:08:08 Capital in 21st Century, Thomas Piketty and Free Markets

01:11:31 Failures of Capitalist Societies on Individual Front and Socialist Aversion of Wealth Generation

01:15:15 UBI, Interventions, and CEO to Lowest Paid Worker Ratio

01:18:25 Career Blunders and Regrets

01:22:12 Psychometric Tests for Intellect Filtering, Behavioral Stability and Creativity Trade-off

01:24:08 Target’s Epic Failure in Canada, What Data Science could have Prevented

01:25:08 Gameplan to Compete with Walmart and Amazon

01:28:00 Sarimax, Armiax and Volatility Management, Planning vs Forecasting

01:31:33 Deep NNs or Lack thereof, Explainability and Monte Carlo as Alternative

01:34:00 Model Parsimony in Times Series, Baseline Models in Excel

01:37:50 R vs Python, Specific Use Cases

01:40:25 Delegating and Element of Trust

01:43:20 Time and Space Complexity of Models, Netflix and Deployments at Target

01:46:00 Political Impacts on Shipments, Narratives and Hypothesis Testing

01:48:00 Nate Silver, Nassem Talib, and Early Inspirations

01:52:05 Work-life Balance

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