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Listen "AI in Supply Chain and Economics of Logistics - Frank Corrigan"
Episode Synopsis
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
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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