“Artificial Intelligence is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
Definition courtesy of Google
“In commerce, supply chain management, the management of the flow of goods and services, involves the movement and storage of raw materials, of work-in-process inventory, and of finished goods from point of origin to point of consumption.”
Definition courtesy of Wikipedia
How Artificial Intelligence Will Disrupt Supply Chain Management
The supply chain and logistics sector is booming. M&A deals in Europe and the UK represent 54% of the overall global market (although there has been a decrease in value), and new technology is presenting unprecedented opportunities for new and current businesses in the sector.
Storing inventory can be costly and getting your stock levels right is hard. If you’ve ever asked the supermarket assistant whether they have your favourite brand of cereal lurking in the storeroom only to be disappointed as they return with a shake of the head, you’ll know the frustrations of bad inventory management.
Businesses are deploying a range of AI tools to make sure they have the right stock for customers when they want it. The key here is achieving this without having to stockpile too much, as storing items brings a raft of problems like insurance, theft, cost and perishability.
There are many ways technology can help: weather predictions, analysing customer behaviour, assessment of manufacturing processes, and many more. The Weather Company uses weather predictions to power supply chain management – if there is a heatwave coming then order more ice cream! It sounds simple, but unless this information is embedded reliably into the supply chain process, then the thousands of extra products that need to be ordered in hot weather may not all be considered.
Transportation Network Design
For businesses that transport large volumes of products or supplies, ensuring the process is efficient should be a priority. When you are dealing with thousands of vehicles and millions of potential routes, creating the most efficient processes quickly becomes too complicated for the human mind. Optimising transport networks is the perfect task for AI – the variables can be plugged into algorithms to work out the most effective and efficient solutions.
Llamasoft is one provider that offers solutions to this complex problem; their case study on shipping is a perfect example of the complexity of the problem and the incredible value that AI can bring to the table. Llamasoft was able to build a model for current operations as a baseline and then layer on hundreds of different scenarios that provide actionable recommendations.
Purchasing covers a lot of different areas: decisions on whether to produce versus buy-in (make-or-buy decisions), managing suppliers, purchasing processes and hiring decisions. These are all areas that can benefit from AI.
Sourcing tools are one of the most interesting developments in purchasing AI. These tools allow businesses to process large numbers of detailed applications and score them accurately. This isn’t just a simple case of looking at the price, but also processing other factors like the vendor’s financial status (the Red Flag Alert Tool is perfect for this) and historic performance. Once a feedback loop has been established, the software can learn from its decisions and zero in on the most important factors.
By making better purchasing decisions, companies can attract better vendors, save resources and build the right supplier base to drive its business forward.
According to the Institute of Business Forecasting 44% of business forecasters felt that artificial intelligence and machine learning are the technology advancements that will have the largest impact on forecasting and planning: by far the biggest share of the vote.
It's critical to get demand right, and the variables are considerable; AI that can consider all variables and evolve is going to be incredibly valuable.
The landscape is changing rapidly. Merck can change forecasts based on far-off natural disasters, and Starbucks can generate servicing recommendations based on customers approaching the store. With 55% of organisations looking to invest in AI to improve demand planning, change is here to stay.
Running efficient warehousing operations has many challenges: the objective is to collect and despatch orders in the minimum time and at minimum cost. Amazon has invested heavily in robotics to make this process more efficient, believing that artificial intelligence can add another layer of efficiency.
A number of start-ups are working in the space, with one a company called Soft Robotics. They produce AI robots that have vision systems and rubber grippers to process orders into different bins. The fascinating aspect of the technology is that it can learn to pick up different objects – it doesn’t need to be programmed for every type of different object!
Customer Relationship Management
Supply chains have large numbers of stakeholder touchpoints – from suppliers, to transport, to customers – so keeping those relationships positive is a key enabler for effective supply chain management.
At the moment there are a few areas in a CRM that AI enables: improved automation, turning CRMs into virtual assistants and improved sales activity. It’s still relatively early days, but CRM systems can now learn from the data they hold to make suggestions on activity. This has incredible power to enable employees in the supply chain to access the best real-time information from which to make decisions and take action.
The future of supply chain management will be shaped by AI and machine learning; the technology is finally here to back up the great ideas so watch this space.
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