5 Ways AI Can Improve Your Supply Chain
Artificial intelligence (AI) is starting to work its way into numerous industries, supply chain being one of them. This technology is on track to have a revolutionary impact on the future. The way a supply chain operates today will differ drastically once AI is fully implemented. Below are five areas of supply chain where AI is starting to have this drastic impact.
5 Ways AI Can Improve Your Supply Chain
1. Time to Quote
The quoting and estimation process currently requires many hours of manual work to accurately relay relevant information to customers. It’s odd that two seemingly identical projects both require significant investments in time and resources from a supplier to fully understand costs; however, there are many steps that go into the quotation process, and minor differences in projects may result in significant costs. Solving the “problem” of a quotation is no easy task, but here’s where AI can help.
AI has the capability to quickly take in data from multiple sources, understand the previous answers to the above “problem” and deliver a solution quickly. Imagine an estimator who knew (off the top of their head) exactly how they had put together every quote they and all their coworkers ever built. Now imagine if that estimator could use that data to instantly put together a new quote, while at the same time optimizing the profitability of the project based of traits shown by the customer that reflect their target costs and price sensitivity.
2. Lead Time Accuracy & Efficiency
Similar to the impacts AI provides to the quoting process, the accuracy of lead time quotes will improve and the process will be more efficient; however, AI can play a much larger role in the lead time space. Based on current projects, manpower, holidays, and other company events, an estimator can provide an accurate lead time estimate to most of their potential clients. AI technology can take that one step further by optimizing run schedules, reducing bottlenecks, optimizing staffing within the manufacturing plant, and providing real-time, up-to-date information on projected lead times. Outside of the manufacturing process, AI has the ability to optimize distribution networks and provide extremely accurate data on expected transportation times.
3. Demand Planning & Sales Projections
Mankind has been attempting to predict markets since the beginning of the trade economy, which is no easy task due to the number of variables and unexpected occurrences that affect them. AI can digest these variables and produce models that are more precise and accurate than traditional ones. AI can also consider competitor products, market trends, current sales numbers and many other outside variables to accurately predict product demand.
4. Disruption Recovery
Making quick strategic decisions during a time of heavy pressure can be extremely difficult. When issues arise such as a fire at a manufacturing facility, it can complicate multiple supply chains. It can be difficult for the both the customer and supplier to make decisions that will put projects back on track, but with the implementation of AI, decision makers can easily input data into AI-enabled software to help them decide the best course of action to take. While models provide valuable insights in these situations, they can take too much time to build and process; whereas AI can quickly build models during these types of situations and present valuable insights to the decision makers.
5. Inventory Management
Optimizing inventory to eliminate backorders and bottlenecks while preventing excess build up is key to an efficient supply chain; it can be tough to figure out things like optimal reorder points, how to account for risk in inventory buildup, and where to hold inventory. By inputting live data into AI-enabled technology, it can automatically update this information continuously based on goals set by inventory managers. These targets fluctuate constantly due to changes in supply, demand, and the flow of goods so AI will continuously monitor this data, in addition to other variables, to give managers the most up-to-date information and inventory levels will be able to quickly adapt to changes in other areas along the supply chain.
AI requires a lot of good, clean data to be truly effective. The earlier AI is incorporated into the supply chain, the sooner it can begin to collect and process that data. The longer AI is enabled, the more valuable the insights become and the more powerful the models grow. The supply chain industry, along with many others will be forever changed by AI and it will only become more prominent in the future.