Supply Chain & Logistics

Increasing the Efficiency of Supply Chains

Operational Efficiency

Major logistics providers have long relied on analytics and research teams to make sense of the data they generate from their operations. Operating in an industry with low margins, AI's ability to streamline supply chain and logistics functions delivers a competitive advantage for early adopters by reducing costs and enhancing productivity.

Problem Statement


Over the past 30 years, there has been a dramatic shift in customer expectations. Due to advances in transportation and communications, corporations have become increasingly global, requiring vast amounts of merchandise to be shipped internationally in a timely manner. The internet has spawned the age of online commerce in which consumers expect their orders to be delivered within two days or faster. The growth of big data has created massive amounts of logistics data -- outstriping a corporations ability to fully leverage this resource. The growth of online retail has driven prices down and squeezed margins.

These changing dynamics have increased the volume and complexity of supply chains profoundly. As a result, these challenges have forced retailers, wholsalers, manufacturers, and couriers to seek ways to minimize costs and maximize margins while improving delivery speeds to remain competitive. The tightrope of customer demands (e.g. fast shipping) and business demands (e.g. higher profit) have created a need for more operational efficiency. Artificial Intelligence is a tool that can solve many of these difficult changes.

AI Use Cases

AI is a powerful tool that can automate manual tasks, increase the efficiency of human workers, and improve the customer experience.

Business Process Automation

  • Robotic Process Automation (RPA)
    • Automate painfully manual back-office tasks.
    • Commonly used in claims processing, automated approvals, document classification, and other repetitive processes.
    • Natural Language Processing (NLP) for data cleansing and building data robustness.
  • Chatbots
    • Streamlining procurement related tasks through automation and augmentation of human tasks.
    • Examples include supplier inquiries, purchase requests, FAQ, and other repetitive work.

Inventory Management

  • Inventory Planning
    • Automatically raise POs with suppliers based on shortages or predicted demand shortages.
  • Recommenders
    • Recommend products that are in excess and automatically reduce price to clear inventory based on historical buying patterns.

Predictive Analytics

  • Route Optimization
    • Reduce costs with better route planning for multi-stop journeys.
  • Analytics
    • Predict the occurrance and root cause of stock out events before sales are lost.
    • Plan supply at a component level with dynamic replenishment estimated time of arrival.

Supply Chain Planning

  • Demand Forecasting
    • Forecast demand for the future, forecast the decline and end of life of a product on a sale channel and the growth of a new product introduction.
  • Supply Forecasting
    • Based on supplier commitments and lead time, bills of material and purchase order data can be used to predict supply requirements.

Robotics Process Automation (RPA) and the Skymind Intelligence Layer (SKIL)

RPA is a new class of software that automates business processes at a fraction of the cost of traditional solutions, without the need to change existing IT systems. RPA works by replicating manual activities that people currently undertake, using existing core applications, accessing websites, and manipulating spreadsheets, documents, and email to complete tasks.

Integrated with existing RPA vendors, the Skymind Intelligence Layer (SKIL) enables teams to leverage the power of AI within their existing claims workflows. The benefits for insurance include the reduction of a claims documents processing time, 24/7 uninterrupted operations, and the reduction of human errors.

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Insurance

Automating back-office tasks using machine learning and RPA.

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E-Commerce

Create personalized recommendations based on browsing and buying behavior

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