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Industries which produce products especially if they are advanced or complex such as the automotive, aviation and electronic industries need to cope with a weakness: late delivery of parts. These industries produce products which contain many thousands of parts, and have to face the challenge of managing suppliers, inventory and production lines. Just like a puzzle is not complete if even one part out of a thousand is missing - so is an airplane that is missing a screw or an electronic device because that component's delivery was delayed by the supplier. The company may find itself with a product stuck on the assembly line without being able to continue production until the arrival of the long-awaited shipment. Beyond the financial damage in such a situation, it also means that the end customer will not receive his order at the appointed time - which could harm the company's reputation, credibility and profitability.

Many industries are by nature industries that are reactive instead of proactive, and procurement and supply chain managers will take action when parts are not being delivered on time. Only when the production line has stopped, because the parts have not been delivered in a timely manner will they start chasing after the suppliers and parts. The tools at the companies' disposal make it possible to identify the problem when it occurs, but it is too late.

So how can you change from being responsive to being able to look ahead and foretell the expected shortages. The answer is creating an algorithm that predicts which suppliers and what parts will be problematic. Today there is a whole world of ERP and MRP tools for scheduling and managing materials, and they do what is necessary, but ultimately they are all reactive - allow for a response only when the crisis is in its full swing. In fact, these are intra-organizational tools that do not address the suppliers' side. We have created a solution that combines the algorithm and the service that accompanies it to be proactive, controlling the situation in advance by early identification and handling of the problematic components before the status turns from green or yellow to red. The traffic lights are not just an image. The statuses of different parts are illustrated with these colors, allowing the user to easily identify an item that is in danger of being delayed. The algorithm analyzes information from a large number of sources and draws conclusions based on that. The algorithm weighs the data and draws a forecast, whether or not a part will arrive on time over the next three months. It relies on the supplier's supply history, the number of known parts he has in stock and production, his relevant purchase order confirmations, and finally his service index.

There might be an item that is due in two weeks and its supplier always meets the required delivery date. On the other hand, there is a required item for another two months - so the client is not dealing with it, but its supplier has an history of tardiness, a point the client is not necessarily aware of. The algorithm will paint that item in red so that the organization will take care of it in advance.

Identify the weak link in the chain

Essentially, this is a solution created by a combination of past, present and future. The algorithm takes past data, through the communication with the supplier and the present data - and based on this predicts the future. It paints the problematic items in red and tells the user:'Here's your problem, focus on it . 'Thus, organizations as well as supply chain and procurement managers are able to predict where the future "bottleneck" will be. The algorithm detects which parts will jam their assembly lines in advance, thus saving employees time that might have been wasted on having to recalculate a route. This solves a common problem of procurement people, who drown in information and deal with the search and solution of problems rather than preventing them in advance and enabling efficient and un interrupted work.

The use of such an algorithm will help any supply chain team by:

• >> Ensuring suppliers On Time Delivery
• >> Enhancing suppliers traceability and visibility
• >> Effective suppliers risks management
• >> Effortless suppliers communication