The Fifth Elephant winter edition 2019
Winter edition of India's most renowned conference on big data and data science
The Fifth Elephant is rated as India’s best conference on big data, data science and application of data to real-life use cases.
It is a conference for practitioners, by practitioners. The Fifth Elephant completed its seventh edition in Bangalore, on 26 and 27 July 2018. The Bangalore edition caters to data and ML engineers, architects, technologists, data scientists, product managers, researchers and business decision-makers.
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The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
PS
Piyush Srivastava
@piyushkrsrivastava
Role of Data in Solving Capacity and Efficiency Problems in Real-time Logistics
Submitted Dec 10, 2018
Technical level:
Intermediate
In the world of real-time Logistics, every minute counts. It shows up not just as customer experience (SLA-Compliance & NPS), but also as the overall ability to accept N orders (Capacity) and deliver them in optimal time using minimum resources (efficiency). Such systems need to react fast to on-ground changes such as traffic, weather, availability of delivery-executives and their proximity to demand areas, availability of shipment at the source (in Swiggy’s case, prepared food at restaurants) etc. Both, real-time and historical data play a significant role in choosing “what” to optimize for and “how”. In this talk we discuss some of these challenges at Swiggy, the nature of historical and real-time data, and our journey of using these inputs in designing optimal solutions for Capacity (when exactly should we stop accepting orders) and Efficiency (orders/delivery-executive/unit-time). We also discuss challenges with data accuracy, high-variance and the necessary trade-offs in designing an optimial system.
Outline
- Introduction and Context
- The Capacity Problem - what is it; why it is important?
- The Efficiency Problem - what, why and the necessary trade-offs
- Data and its Nature
- Challenges with Accurate Data Capture
- Challenges with high Variance
- Real-time Vs. historical data
- Representing Capacity
- Aggregated capacity (Zone-level)
- Point-in-time-capacity (Order-level)
- Journey and Results: Solving for Capacity
- Efficiency Levers
- Predictions and accounting for errors
- Trade-offs
- Optimal Assignment
- Batching
- Aggregate Analysis Vs. Specific Analysis
- Pitfalls of Aggregate Analysis
- Conclusions
Requirements
None
Speaker bio
Piyush works as Director Engineering, Delivery team, Swiggy. He is responsible for building tech platforms for real-time logistics. Prior to this he worked with Last Mile logistics division in Flipkart where he led the development of the Mapping solution and helped deliver last mile optimal-routing solutions.
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Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
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