Inventory optimization

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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. [1] 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." [2]

Contents

Inventory management challenges

In contrast to the traditional "binge and purge" inventory cycle in which companies over-purchase product to prepare for possible demand spikes and then discard extra product, inventory optimization seeks to more efficiently match supply to expected customer demand. [3] American Productivity and Quality Center (APQC) Open Standards data shows that the median company carries an inventory of 10.6 percent of annual revenues as of 2011. The typical cost of carrying inventory is at least 10.0 percent of the inventory value. So the median company spends over 1 percent of revenues carrying inventory, although for some companies the number is much higher. [4]

Also, the amount of inventory held has a major impact on available cash. With working capital at a premium, it is important for companies to keep inventory levels as low as possible and to sell inventory as quickly as possible. [5] When Wall Street analysts look at a company's performance to make earnings forecasts and buy and sell recommendations, inventory is always one of the top factors they consider. [6] Studies have shown a 77% correlation between overall manufacturing profitability and inventory turns. [7]

The challenge of managing inventory is increased by the "Long Tail" phenomenon which is causing a greater percentage of total sales for many companies to come from a large number of products, each with low sales frequency. [6] Shorter and more frequent product cycles which are required to meet the needs of more sophisticated markets create the need to manage supply chains containing more products and parts. [5] Hence, businesses need to understand how this affects their inventory and how they can seize the opportunities presented by such products. [8]

At the same time, planning frequencies and time-buckets are moving from monthly/weekly to daily and the number of managed stocking locations from dozens in distribution centers to hundreds or thousands at the points of sale (POS). This leads to a large number of time series with a high level of demand volatility. [9] This explains one of the main challenges in managing modern supply chains, the so-called "bullwhip effect", which often causes small changes in actual demand to cause a much larger change in perceived demand, which in turn can mislead companies to make bigger changes in inventory than are really necessary. [10]

Non-optimized approach

Without inventory optimization, companies commonly set inventory targets using rules of thumb or single stage calculations. Rules of thumb normally involve setting a number of days of supply as a coverage target. Single stage calculations look at a single item in a single location and calculate the amount of inventory required to meet demand. [11]

Deterministic vs. stochastic

Inventory optimization models can be either deterministic—with every set of variable states uniquely determined by the parameters in the model – or stochastic—with variable states described by probability distributions. [12] Stochastic optimization takes supply uncertainty into account that, for example, 6 percent of orders from an overseas supplier are 1–3 days late, 1 percent are 4–6 days late, 5 percent are 7–14 days late and 8 percent are more than 14 days late. [13]

Stochastic optimization also accounts for demand volatility which is a top priority among the challenges faced by supply chain professionals. [14] For example, management predicts a 65 percent probability of selling 500 units, a 20 percent probability of selling 400 units and a 15 percent probability of selling 600 units. High service levels can be achieved with cost overruns, excessive inventory and firefighting, but higher profitability can be achieved by understanding the sources of volatility and planning appropriately. The result is a better understanding of the inventory requirements than with a deterministic approach. [15]

Single vs. multi-echelon

Single-echelon location problems are single-type problems such that either the material flow coming out or the material flow entering the facilities to be located is negligible. In multiple-echelon problems, both inbound and outbound commodities are relevant. This is the case, for example, when distribution centers (DCs) have to be located taking into account both the transportation cost from plants to DCs and the transportation cost from DCs to customers. In multiple-echelon problems, constraints aiming at balancing inbound and outbound flows have to be considered. [16]

A sequential single-echelon approach forecasts demand and determines required inventory for each echelon separately. Multi-echelon inventory optimization determines the correct levels of inventory across the network based on demand variability at the various nodes and the performance (lead time, delays, service level) at the higher echelons. [17]

Multi-echelon inventory optimization looks at inventory levels holistically across the supply chain while taking into account the impact of inventories at any given level or echelon on other echelons. For example, if the product sold in a retailer's outlet is received from one of its distribution centers, the distribution center represents one echelon of the supply chain and the outlet another one. It should be clear that the amount of stock needed at the outlets is a function of the service received from the distribution center. The better the service that is provided upstream, the smaller the protection that is needed downstream. The goal of multi-echelon inventory optimization is to continually update and optimize safety stock levels across all of these echelons. [6]

Multi-echelon inventory optimization represents a "state of the art" approach to optimize inventory across the end to end supply chain. Modeling multiple stages allows other types of inventory, including cycle stock and prebuild along with safety stock due to time phased demands, to be more accurately predicted. [18] As part of inventory optimization, supplier performance, customer service and internal asset metrics should be continuously monitored to enable continuous improvement. [19]

Inventory optimization engines

Scheuffele and Kulshreshtha refer to inventory optimization engines or IO engines, whose function is to analyze inventory data using a holistic approach across the supply network. They note growing interest in their use and application in specific inventory fields, such as plant operations, assembly lines, and within transportation. [1] : 4–7 

Benefits

Companies have achieved financial benefits by employing inventory optimization. A study by IDC Manufacturing Insights found that many organizations that utilized inventory optimization reduced inventory levels by up to 25 percent in one year and enjoyed a discounted cash flow above 50 percent in less than two years. [5] For example:

See also

Related Research Articles

<span class="mw-page-title-main">Supply chain management</span> Management of the flow of goods and services

In commerce, supply chain management (SCM) deals with a system of procurement, operations management, logistics and marketing channels, through which raw materials can be developed into finished products and delivered to their end customers. A more narrow definition of supply chain management is the "design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronising supply with demand and measuring performance globally". This can include the movement and storage of raw materials, work-in-process inventory, finished goods, and end to end order fulfilment from the point of origin to the point of consumption. Interconnected, interrelated or interlinked networks, channels and node businesses combine in the provision of products and services required by end customers in a supply chain.

<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 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 in distribution channels 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.

Service management in the manufacturing context, is integrated into supply chain management as the intersection between the actual sales and the customer point of view. The aim of high-performance service management is to optimize the service-intensive supply chains, which are usually more complex than the typical finished-goods supply chain. Most service-intensive supply chains require larger inventories and tighter integration with field service and third parties. They also must accommodate inconsistent and uncertain demand by establishing more advanced information and product flows. Moreover, all processes must be coordinated across numerous service locations with large numbers of parts and multiple levels in the supply chain.

Yield management (YM) 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."

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.

<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.

In business, a demand chain is the understanding and management of customer demand, in contrast to a 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".

Supply-chain optimization (SCO) aims to ensure the optimal operation of a manufacturing and distribution supply chain. 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.

Revenue management (RM) is a discipline to maximize profit by optimizing rate (ADR) and occupancy (Occ). In its day to day application the maximization of Revenue per Available Room (RevPAR) is paramount. It is seen by some as synonymous with yield management.

<span class="mw-page-title-main">Supply chain network</span> Evolution of the basic supply chain

A supply-chain network (SCN) is an evolution of the basic supply chain. Due to rapid technological advancement, organizations with a basic supply chain can develop this chain into a more complex structure involving a higher level of interdependence and connectivity between more organizations, this constitutes a supply-chain network.

Material theory is the sub-specialty within operations research and operations management that is concerned with the design of production/inventory systems to minimize costs: it studies the decisions faced by firms and the military in connection with manufacturing, warehousing, supply chains, spare part allocation and so on and provides the mathematical foundation for logistics. The inventory control problem is the problem faced by a firm that must decide how much to order in each time period to meet demand for its products. The problem can be modeled using mathematical techniques of optimal control, dynamic programming and network optimization. The study of such models is part of inventory theory.

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.

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.

Reactive destocking in supply chain management is a reduction of the inventory when expected demand goes down. When a company is only doing reactive destocking, the desired inventory to sales ratio, remains unchanged. Reactive destocking in general is done by operational managers of the logistical activities, without additional instructions. The inventory can include finished products, raw materials and/or goods in process.

Third-party logistics is an organization's long term commitment of outsourcing its distribution services to third-party logistics businesses.

Warehouse execution systems (WES) are computerized systems used in warehouses and distribution centers to manage and orchestrate the physical flow of products from receiving through shipping. Warehouses are storage facilities for raw materials and parts used in manufacturing operations; distribution centers (DCs) are facilities that store and distribute finished goods to retail locations, consumers, and other end customers.

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. 1 2 Scheuffele, G. and Kulshreshtha, A., Inventory Optimization: A Necessity Turning to Urgency, SETLabs Briefings, Volume 5, No. 3, July–September 2007, accessed 3 December 2023
  2. ↑ Yogesh Malik, Alex Niemeyer, and Brian Ruwadi, "Building the supply chain of the future", McKinsey Quarterly, January 2011
  3. ↑ King, Bill (11 January 2017). "Inventory Optimization & Its Role in Businesses". AvidXchange. Retrieved 26 April 2017.
  4. ↑ Marisa Brown, "Inventory Optimization: Show Me the Money," Supply Chain Management Review, July 19, 2011.
  5. 1 2 3 William Brandel, "Inventory Optimization Saves Working Capital in Tough Times," Computerworld, August 24, 2009.
  6. 1 2 3 Dan Gilmore, "Supply Chain News: What is Inventory Optimization?," Supply Chain Digest, August 28, 2008.
  7. ↑ Vijay Sangam, "Inventory Optimization," Supply Chain World Blog, September 2, 2010.
  8. ↑ "The Long Tail of Inventory... and 3 reasons why it's important". www.tradegecko.com. Retrieved 2015-11-24.
  9. ↑ P.J. Jakovljevic, "A Modern Tale of Long (Supply Chain) Tails — Part I," Technical Evaluation Centers Blog, July 2009.
  10. ↑ "Bullwhip Effect in Supply Chain," World News.
  11. ↑ Sean P. Willems, "How Inventory Optimization Opens Pathways to Profitability," Supply Chain Management Review, March/April 2011.
  12. ↑ Leslie Hansen Harps, "Optimizing Your Supply Chain: A Model Approach," Inbound Logistics, April 2003.
  13. ↑ "Are Your Inventory Management Practices Outdated," AberdeenGroup, March 1, 2005. Archived December 29, 2009, at the Wayback Machine
  14. ↑ Tim Payne, "Magic Quadrant for Supply Chain Planning for Process Automation", Gartner Research, ID Number G00200934. September 3, 2010.
  15. ↑ Aberdeen Group, Are Your Inventory Management Practices Outdated? published on 1 March 2005
  16. ↑ Introduction to Logistics Systems Planning and Control - Gianpaolo Ghiani, Gilbert Laporte, Roberto Musmanno http://onlinelibrary.wiley.com/book/10.1002/0470014040
  17. ↑ Noha Tohamy, "A User Guide to Network Design and Inventory Optimization Solutions", Gartner Research, Publication Number G00209211, December 8, 2010.
  18. ↑ Enslow, B., Are Your Inventory Management Practices Outdated?, AberdeenGroup, published 1 March 2005, accessed 4 December 2023
  19. ↑ "Inventory Optimization: Balancing the Asset versus Service Tradeoff," APQC Best Practices Report, 2011.
  20. ↑ Sarah Lafferty, "Handling Volatile Demand," Supply Chain Movement, Number 1, Quarter 1, 2012. Pages 36-38.
  21. ↑ Hallie Forcino, "Break on Through to the Other Side," Managing Automation, February 2005. Archived 2013-05-10 at the Wayback Machine
  22. ↑ Robert J. Bowman, "For Smiths Medical, Service Quality Is an Ever-Moving Goal," Supply Chain Brain, June 15, 2012.
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