Supply chain optimization

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Supply-chain optimization (SCO) aims to ensure the optimal operation of a manufacturing and distribution supply chain. [1] This includes the optimal placement of inventory within the supply chain, minimizing operating costs including manufacturing costs, transportation costs, and distribution costs. Optimization often involves the application of mathematical modelling techniques using computer software. It is often considered to be part of supply chain engineering, although the latter is mainly focused on mathematical modelling approaches, whereas supply chain optimization can also be undertaken using qualitative, management based approaches. [2]

Contents

Applications

Typically, supply-chain managers aim to maximize the profitable operation of their manufacturing and distribution supply chain. This could include measures like maximizing gross margin return on inventory invested (GMROII) (balancing the cost of inventory at all points in the supply chain with availability to the customer), minimizing total operating expenses (transportation, inventory and manufacturing), or maximizing gross profit of products distributed through the supply chain. Supply-chain optimization addresses the general supply-chain problem of delivering products to customers at the lowest total cost and highest profit, trading off the costs of inventory, transportation, distributing and manufacturing. In addition, optimizing storage and transportation costs by means of product / package size is one of the easiest and most cost effective initial implementations available to save money in product distribution. [3]

Supply-chain optimization has applications in all industries manufacturing and/or distributing goods, including retail, industrial products, and consumer packaged goods (CPG).

Approaches and solutions

The classic supply-chain approach has been to try to forecast future inventory demand as accurately as possible, by applying statistical trending and "best fit" techniques based on historic demand and predicted future events. The advantage of this approach is that it can be applied to data aggregated at a fairly high level (e.g. category of merchandise, weekly, by group of customers), requiring modest database sizes and small amounts of manipulation. Unpredictability in demand is then managed by setting safety stock levels, so that for example a distributor might hold two weeks of supply of an article with steady demand but twice that amount for an article where the demand is more erratic. Universally accepted statistical methods such as Standard Deviation and Mean Absolute Deviation are often used for calculating safety stock levels.

Then, using this forecast demand, a supply-chain manufacturing Production Planning and distribution plan is created to manufacture and distribute products to meet this forecast demand at lowest cost (or highest profitability). This plan typically addresses the following business concerns: - How much of each product should be manufactured each day? - How much of each product should be made at each manufacturing plant? - Which manufacturing plants should re-stock which warehouses with which products? - What transportation modes should be used for warehouse replenishment and customer deliveries?

The technical ability to record and manipulate larger databases more quickly has now enabled a new breed of supply-chain-optimization solutions to emerge, which are capable of forecasting at a much more granular level (for example, per article per customer per day). Some vendors are applying "best fit" models to this data, to which safety stock rules are applied, while other vendors have started to apply stochastic techniques to the optimization problem. They calculate the most desirable inventory level per article for each individual store for their retail customers, trading off cost of inventory against expectation of sale. The resulting optimized inventory level is known as a model stock. Meeting the model stock level is also an area requiring optimization. Because the movement of product to meet the model stock, called the stock transfer, needs to be in economic shipping units such as complete unit loads or a full truckload, there are a series of decisions that must be made. Many existing distribution-requirements-planning systems round the quantity up to the nearest full shipping unit. For example, the creation of truckloads as economic shipment units requires optimization systems to ensure that axle constraints and space constraints are met while loading can be achieved in a damage-free way. This is generally achieved by continuing to add time-phased requirements until the loads meet some minimum weight or cube. More sophisticated optimization algorithms take into account stackability constraints, load and unloading rules, palletizing logic, warehouse efficiency and load stability with an objective to reduce transportation spend (minimize 'shipping air').

Optimization solutions are typically part of, or linked to, the company's replenishment systems distribution requirements planning, so that orders can be automatically generated to maintain the model stock profile. The algorithms used are similar to those used in making financial investment decisions; the analogy is quite precise, as inventory can be considered to be an investment in prospective return on sales.

Supply-chain optimization may include refinements at various stages of the product lifecycle, so that new, ongoing and obsolete items are optimized in different ways, and adaptations for different classes of products, for example seasonal merchandise. It should also factor in risks and unexpected constraints that often affect a global supply chain's efficiency, including sudden spikes in fuel costs, material shortages, natural disasters such as hurricanes, and instability of global politics.

Whilst most software vendors are offering supply-chain optimization as a packaged solution and integrated in ERP software, some vendors are running the software on behalf of their clients as application service providers.

Claimed advantages

Firstly, the techniques being applied to supply-chain optimization are claimed to be academically credible. Most of the specialist companies that have been created as a result of research projects are in academic institutions or consulting firms: and they point to research articles, white papers, academic advisors and industry reviews to support their credibility.

Secondly, the techniques are claimed to be commercially effective. The companies publish case studies that show how clients have achieved significant and measurable benefits in terms of reduced inventory and lower logistics cost levels, while typically maintaining or improving customer service through better predictability and improved availability. Kokoris notes that a supply chain optimization initiative can represent "an untapped opportunity to realize increased short and long-term cash flows and cost savings". [4] However, there is limited published data outside of these case studies, and a reluctance for some practitioners to publish details of their successes (which may be commercially sensitive), therefore hard evidence is difficult to come by. Last, not least, independent advisors or benchmarks show the stickiness and benefits achieved in specific sub-sectors.

The different routines in supply-chain optimization have reached mature status and allow companies to gain competitive advantage by increased effectiveness and measurable savings, not only but supply chain optimization can bring in a better quality of clothes, possibly better collaboration, and increase profits. [5]

Direct plant shipments

Also known as direct shipment, direct plant shipment (DPS) is a method of delivering goods from the plant to the customer directly. At the same time regional centers, strategically located, provide overnight shipments to the maximum number of customers. This delivery scheme reduces transportation and storage costs.

See also

Related Research Articles

<span class="mw-page-title-main">Logistics</span> Management of the flow of resources

Logistics is the part of supply chain management that deals with the efficient forward and reverse flow of goods, services, and related information from the point of origin to the point of consumption according to the needs of customers. Logistics management is a component that holds the supply chain together. The resources managed in logistics may include tangible goods such as materials, equipment, and supplies, as well as food and other consumable items.

Logistics engineering is a field of engineering dedicated to the scientific organization of the purchase, transport, storage, distribution, and warehousing of materials and finished goods. Logistics engineering is a complex science that considers trade-offs in component/system design, repair capability, training, spares inventory, demand history, storage and distribution points, transportation methods, etc., to ensure the "thing" is where it's needed, when it's needed, and operating the way it's needed all at an acceptable cost.

<span class="mw-page-title-main">Supply chain</span> System involved in supplying a product or service to a consumer

A supply chain, sometimes expressed as a "supply-chain", is a complex logistics system that consists of facilities that convert raw materials into finished products and distribute them to end consumers or end customers. Meanwhile, supply chain management deals with the flow of goods within the supply chain in the most efficient manner.

Vendor-managed inventory (VMI) is an inventory management practice in which a supplier of goods, usually the manufacturer, is responsible for optimizing the inventory held by a distributor.

<span class="mw-page-title-main">Cross-docking</span> Practice in logistics of unloading directly to customer or other transportation

Cross-docking is a logistical practice of Just-In-Time Scheduling where materials are delivered directly from a manufacturer or a mode of transportation to a customer or another mode of transportation. Cross-docking often aims to minimize overheads related to storing goods between shipments or while awaiting a customer's order. This may be done to change the type of conveyance, to sort material intended for different destinations, or to combine material from different origins into transport vehicles with the same or similar destinations.

Yield management is a variable pricing strategy, based on understanding, anticipating and influencing consumer behavior in order to maximize revenue or profits from a fixed, time-limited resource. As a specific, inventory-focused branch of revenue management, yield management involves strategic control of inventory to sell the right product to the right customer at the right time for the right price. This process can result in price discrimination, in which customers consuming identical goods or services are charged different prices. Yield management is a large revenue generator for several major industries; Robert Crandall, former Chairman and CEO of American Airlines, gave yield management its name and has called it "the single most important technical development in transportation management since we entered deregulation."

<span class="mw-page-title-main">Distribution center</span> Building stocked with goods for delivery

A distribution center for a set of products is a warehouse or other specialized building, often with refrigeration or air conditioning, which is stocked with products (goods) to be redistributed to retailers, to wholesalers, or directly to consumers. A distribution center is a principal part, the order processing element, of the entire order fulfillment process. Distribution centers are usually thought of as being demand driven. A distribution center can also be called a warehouse, a DC, a fulfillment center, a cross-dock facility, a bulk break center, and a package handling center. The name by which the distribution center is known is commonly based on the purpose of the operation. For example, a "retail distribution center" normally distributes goods to retail stores, an "order fulfillment center" commonly distributes goods directly to consumers, and a cross-dock facility stores little or no product but distributes goods to other destinations.

The beer distribution game is an educational game that is used to experience typical coordination problems of a supply chain process. It reflects a role-play simulation where several participants play with each other. The game represents a supply chain with a non-coordinated process where problems arise due to lack of information sharing. This game outlines the importance of information sharing, supply chain management and collaboration throughout a supply chain process. Due to lack of information, suppliers, manufacturers, sales people and customers often have an incomplete understanding of what the real demand of an order is. The most interesting part of the game is that each group has no control over another part of the supply chain. Therefore, each group has only significant control over their own part of the supply chain. Each group can highly influence the entire supply chain by ordering too much or too little which can lead to a bullwhip effect. Therefore, the order taking of a group also highly depends on decisions of the other groups.

Inventory control or stock control can be broadly defined as "the activity of checking a shop's stock". It is the process of ensuring that the right amount of supply is available within a business. However, a more focused definition takes into account the more science-based, methodical practice of not only verifying a business's inventory but also maximising the amount of profit from the least amount of inventory investment without affecting customer satisfaction. Other facets of inventory control include forecasting future demand, supply chain management, production control, financial flexibility, purchasing data, loss prevention and turnover, and customer satisfaction.

<span class="mw-page-title-main">Push–pull strategy</span> Business terms

The business terms push and pull originated in logistics and supply chain management, but are also widely used in marketing and in the hotel distribution business.

The term demand chain has been used in a business and management context as contrasting terminology alongside, or in place of, "supply chain". Madhani suggests that the demand chain "comprises all the demand processes necessary to understand, create, and stimulate customer demand". Cranfield School of Management academic Martin Christopher has suggested that "ideally the supply chain should become a demand chain", explaining that ideally all product logistics and processing should occur "in response to a known customer requirement".

Revenue management is the application of disciplined analytics that predict consumer behaviour at the micro-market levels and optimize product availability, leveraging price elasticity to maximize revenue growth and thereby, profit. The primary aim of revenue management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment.

Field inventory management, commonly known as inventory management, is the task of understanding the stock mix of a company and the handling of the different demands placed on that stock. The demands are influenced by both external and internal factors and are balanced by the creation of purchase order requests to keep supplies at a reasonable or prescribed level. Inventory management is important for every other business enterprise.

In marketing, carrying cost, carrying cost of inventory or holding cost refers to the total cost of holding inventory. This includes warehousing costs such as rent, utilities and salaries, financial costs such as opportunity cost, and inventory costs related to perishability, shrinkage (leakage) and insurance. Carrying cost also includes the opportunity cost of reduced responsiveness to customers' changing requirements, slowed introduction of improved items, and the inventory's value and direct expenses, since that money could be used for other purposes. When there are no transaction costs for shipment, carrying costs are minimized when no excess inventory is held at all, as in a just-in-time production system.

Channel coordination aims at improving supply chain performance by aligning the plans and the objectives of individual enterprises. It usually focuses on inventory management and ordering decisions in distributed inter-company settings. Channel coordination models may involve multi-echelon inventory theory, multiple decision makers, asymmetric information, as well as recent paradigms of manufacturing, such as mass customization, short product life-cycles, outsourcing and delayed differentiation. The theoretical foundations of the coordination are based chiefly on the contract theory. The problem of channel coordination was first modeled and analyzed by Anantasubramania Kumar in 1992.

Merge-in-transit (MIT) is a distribution method in which several shipments from suppliers originating at different locations are consolidated into one final customer delivery. This removes the need for distribution warehouses in the supply chain, allowing customers to receive complete deliveries for their orders. Under a merge-in-transit system, merge points replace distribution warehouse. In today's global market, merge-in-transit is progressively being used in telecommunications and electronic industries. These industries are usually dynamic and flexible, in which products have been developed and changed rapidly.

Petrolsoft Corporation (1989–2000) was a supply chain management software company with a focus on the petroleum industry. Petrolsoft Corporation was founded at Stanford University in 1989 by Bill Miller and David Gamboa as Petrolsoft Software Group. It was later incorporated in 1992. Petrolsoft introduced demand-driven inventory management to the petroleum industry.

Inventory management software is a software system for tracking inventory levels, orders, sales and deliveries. It can also be used in the manufacturing industry to create a work order, bill of materials and other production-related documents. Companies use inventory management software to avoid product overstock and outages. It is a tool for organizing inventory data that before was generally stored in hard-copy form or in spreadsheets.

Inventory optimization refers to the techniques used by businesses to improve their oversight, control and management of inventory size and location across their extended supply network. It has been observed within operations research that "every company has the challenge of matching its supply volume to customer demand. How well the company manages this challenge has a major impact on its profitability."

Retail back-office software is used to manage business operations that are not related to direct sales efforts and interfaces that are not seen by consumers. Typically, the business processes managed with back-office software include some combination of inventory control, price book management, manufacturing, and supply chain management (SCM). Back-office software is distinct from front-office software, which typically refers to customer relationship management (CRM) software used for managing sales, marketing, and other customer-centric activities.

References

  1. "Supply Chain Optimization". Exforsys Inc. 3 September 2007. Retrieved 8 December 2012.
  2. Garcia, Daniel J.; You, Fengqi (2015). "Supply chain design and optimization: Challenges and opportunities". Computers & Chemical Engineering. 81: 153–170. doi: 10.1016/j.compchemeng.2015.03.015 .
  3. Schueneman, Herbert. "Overpackaging: Throwing Away Money and Clogging Landfills in the Name of Safe Product Delivery" (PDF). Westpak, Inc. Retrieved 25 February 2013.
  4. Kokoris, G., Supply Chain Optimization - Hidden Opportunities to Increase Cash Flows and Working Capital, Supply Chain Management Review, 29 November 2011, accessed 6 July 2022,
  5. https://www.tibco.com/glossary/what-is-supply-chain-optimization