Machine Learning and Analytics in Logistics and Supply Chain - - PowerPoint PPT Presentation

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Machine Learning and Analytics in Logistics and Supply Chain - - PowerPoint PPT Presentation

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Machine Learning and Analytics in Logistics and Supply Chain Presented by: Pavel Gupta Co-Founder, NeenOpal Analytics Bangalore, India 9 th Global Supply Chain and Logistics Summit 16 Nov 2016 www.sclgsummit.org Agenda Supply Chain:

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16 Nov 2016

9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Machine Learning and Analytics in Logistics and Supply Chain

Presented by: Pavel Gupta

Co-Founder, NeenOpal Analytics Bangalore, India

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16 Nov 2016

9th Global Supply Chain and Logistics Summit www.sclgsummit.org

9 Feb 2011

  • Supply Chain: Challenges and Trends
  • Introduction: Machine Learning and AI
  • Case Study – ML and AI in Supply Chain and Logistics
  • Getting Started with Machine Learning
  • Conclusion

Agenda

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16 Nov 2016

9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Supply Chain Challenges

  • Lower Prices
  • Faster Delivery
  • Higher customer service expectations
  • Demand volatility
  • High number of products
  • Supply complexities
  • More frequent shipments
  • Transparency and sustainability

“Companies that continue to utilize traditional supply chain models will struggle to remain competitive and deliver orders that are complete, accurate and on-time.”

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

A Lot of New Products

Today Amazon sells over 480 million products in the USA. Amazon’s product selection has expanded by 235 million in the past 16 months. That’s as average addition

  • f

485,00 new products per day.

A typical Amazon fulfilment centre

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16 Nov 2016

9th Global Supply Chain and Logistics Summit www.sclgsummit.org

A Very Long Tail Demand

0.9 million 1.2 million 1.7 million 6.7 million 24 million 30 million 60 million 96 million

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Machine Learning and AI

The Future is Here

  • The most innovative companies in the world – that

have disrupted their respective industries – rely on Machine Learning to drive their business processes and a great customer experience

  • The

future

  • f

business innovation has Artificial Intelligence (AI) at its very core

  • Machine Learning (subfield of AI) is no longer restricted

to research labs and is fast becoming the cornerstone

  • f business disruption
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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

What was before Machine Learning?

Humans versus Machine “All knowing programmer” Program Results Data Feedback

Deterministic Future Outlook

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Machine Learning in our Business

Humans versus Machine Learner Model Data Historic Data Decision-Making Predictions

  • Manual(query)
  • Automatic (programmatic)

Push decision-making to the edge

Probabilistic Future Outlook

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Machine Learning Explained

Square footage Bed- rooms Age School Rating

Price INPUT OUTPUT W1 W2 W3 W4 PRICE(Square Footage, Bedrooms, Age, School Rating) = w1 x sf + w2 x br + w3 x age + w4 x sr

House No. Square Footage Bedrooms Age School Rating Final Price

H1 1000 4 3 2 $100,000 H2 800 3 1 4 $90,000 H3 1200 5 3 5 $125,000 H4 600 2 5 1 $60,000 H5 1500 6 3 3 $150,000

Groundtruth

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16 Nov 2016

9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Learning Algorithms

Mail Spam Non-Spam

Regression Classification Ranking Supervised Unsupervised Reinforcement

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Neural Networks

Square footage Bed- rooms Age School Rating

INPUT

Hidden 1 Hidden 2 Hidden 3 Hidden 4

Price OUTPUT HIDDEN

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Deep Learning

Square footage Bed- rooms Age School Rating

INPUT

Hidden 1.1 Hidden 1.2 Hidden 1.3 Hidden 1.4

Price OUTPUT

Hidden 2.1 Hidden 2.2 Hidden 2.3 Hidden 2.4 Hidden 3.1 Hidden 3.2 Hidden 3.3 Hidden 3.4

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Case Study

Transforming Supply Chain and Logistics

Improving Customer Satisfaction for a major Logistics Company

Business Challenge:

Develop real-time customer feedback and analysis framework to measure customer satisfaction levels.

Situation:

  • Existing process was not capturing valuable customer data

Solution/Approach:

  • Collect and aggregate the customer data on areas such as billing,

complaints, repairs, contracts, social media and contact center calls.

  • Big data analytics model provides real-time feedback and risk flagging

for the customers om the verge of churning

Impact:

  • Reduction in customer complaints & improved customer satisfaction

levels

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Getting Started

Start small by leveraging the cloud

  • Low hanging fruit: Business problem – “If we just knew…”
  • Start Supervised: Historic data with ground truth
  • Do not start with Big Data
  • Use cloud-based offerings:

– Microsoft Azure Machine Learning – Amazon Machine Learning – Google Cloud Machine Learning – Big ML

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9th Global Supply Chain and Logistics Summit www.sclgsummit.org

Thank You

Pavel Gupta

Co-Founder @ NeenOpal Analytics +91-9910945784 pavel.gupta@neenopal.com