Algorithm

Certified Inventory Optimization Professional (CIOP) is an end-to-end supply chain certification program. The certification consists of 30 modules focusing both on traditional and futuristic topics. The traditional topics are introduction to supply chain management, all about inventory, strategic business planning, forecasting, demand management, capacity management, sales and operations planning (S&OP), master scheduling (MPS), materials requirements planning (MRP) and production activity control (PAC). It also includes topics on procurement, warehousing, transportation, distribution, and packaging. The topic on the future trends such as Blockchain, Internet of Things (IoT), Robotic Process Automation (RPA), Machine Learning (M/L) and Artificial Intelligence (AI). There is a significant focus on supporting technologies such as forecasting and process mapping tools such as Microsoft Visio. In addition to the above indicated topics the participants need to master over 3000 terminologies in supply chain management.

An algorithm is a mathematical model used to search over large data sets with an optimization approach. Algorithms are normally perform the lowest level searches in nature like random search, sorting and key-composition. Some of the most common problems that an algorithm can solve are sorting, finding the minimum number of pieces that fit in a space, the shortest path between two points and search over a graph. 

Most algorithms also perform sub-optimizations over other functions. The main function of an algorithm is to find the solution to a problem by discovering the best (or shortest) path that exists amongst all the possible solutions. Algorithms also used to reduce the cost of operation and improve productivity by finding the optimal configuration among multiple choices.

Many companies implement Algorithm Based Productivity Improvement (ABI) because it provides information regarding how and why certain decisions were made which improved overall efficiency. For example, a company that purchases a large quantity of cheap cars on a weekly basis will waste production if it bought cheap cars which are rarely used. If a company implemented Algorithm Based Productivity Improvement they would reduce waste because they would only purchase the cars that are used the most. Similarly, warehouse owners implementing Algorithm Based Productivity Improvement reduces inventory-related delays because they know where the products are, when they are there and in what quantities to keep them.

In an informational lead time delay, a firm can measure the difference between expected lead times and actual lead times. Information regarding expected lead times can be derived from historical sales lead data, historical warehouse traffic data or current sales and inventory information. Measurements of current and historical lead times will provide firms with a current and future picture of how long it takes to deliver different products to its customers.

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