Ansgar Thiede on Leveraging AI solutions for supply chain efficiency

In almost every industry, buyers are becoming more demanding. The supply chain industry is no exception to that, asking businesses to meet buyer needs effectively in a relentless quest for speed and agility. In today’s digital economy, supply chain professionals need to look for adaptable, connected solutions to achieve new levels of responsiveness, performance, and profitability. In this context, data analytics and artificial intelligence can be game changers to improve decision-making processes in revolutionary ways.

 

Efficiency in the spotlight

 

Over the past 10 years, customers have developed a desire to have what they want, when they want it – even when the distribution center holding that item is across the country. The right technologies are crucial to provide faster, more accurate deliveries, as well as greater shopping convenience and choice.

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As supply chain grows more complex with growing customer demand, businesses realize that their supply chain must become intelligent and highly efficient for it to function properly, and this means it must be digitised and technology-enabled. Data analytics, in turn, is the ability to quickly turn massive amounts of visibility and operational data into focused, actionable insights. The ultimate benefit lies in freeing up human effort and reducing the heavy lifting of manual operations. Especially in areas such as goods sourcing and supply, AI models could take a greater role in automating tasks in the future.

 

Holistic perspectives are key

 

All the talk about data analytics and artificial intelligence yet falls into broader conversations the supply chain industry has undertaken for a while already. Recent developments have shown us that disruption mitigation has turned mission-critical for many businesses. Economic crises and natural disasters are just two examples showcasing that supply chains need to respond to and recover from unexpected risk events. 

 

Agile supply chains are successful because they can adapt strategically. They manage the impacts of unexpected demand shifts, both up and down, interrupted goods flows, and transport or shipping disruptions. Visibility, disruption preparedness, and scalability are key to achieving this. 

 

However, by far the most important element in a holistic supply chain is the frictionless integration of all the various strands of data and technology on a single platform to leverage the full potential of data models and advanced analytics.

 

Boosting supply chain efficiency end-to-end

 

With businesses improving agility and resiliency on a broader scale, we witness growing demand for implementing automated solutions, robotics, and AI-powered technologies to help with capacity planning and logistics. Businesses gain insight into forecasting the number of orders that need to be fulfilled, the number of employees or vehicles required to meet demand, and identifying any potential problems encountered in the system. 

 

In that context, new digital technologies will help to create new levels of insight, creating a more innovative process for improving operational performance end-to-end. Moreover, potential lies in improving warehouse efficiency in areas such as inventory management (slotting) or resource planning and routing. 

 

What does the future hold?

 

Emerging technologies such as AI or Gen AI offer massive potential in the efficiency of supply chains. However, while the need for robust innovation is widespread, it will take years for the wider industry to embrace these technologies fully. The integration of AI in the supply chain is only set to showcase its potential within the broader supply chain ecosystem. 

 

From procurement to delivery, emerging technologies enable businesses to conquer supply chain complexities more efficiently. Add the growing pressure on companies to take action on building more agile and resilient operations, data-driven technologies will have a major impact on how to drive business value in the supply chain in the future. 

 

By Ansgar Thiede, VP Data Science at Körber Business Area Supply Chain 

KAIR Editor

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