How much inventory and which items should a company hold, overall and at each stocking location (each DC, store, stockroom, salesperson’s vehicle, service depot, etc.)? When to replenish and how many? To the uninitiated, these seem like relatively straightforward daily decisions. But they are anything but simple and can make the difference between a highly profitable vs. out-of-business company.
Over the years, sophisticated formulae and algorithms have been developed to calculate and make inventory decisions. These are great tools and tremendous improvements over past methods. But algorithms alone are not enough. There are many forces and factors beyond what those tools can encompass. What is needed is a holistic approach that incorporates the full breadth of inventory’s ‘multiple personalities.’
The ‘Multiple Personalities’ of Inventory
In most companies, there is a tug-of-war between the different forces and functions and third parties that have a role in decisions and execution regarding what inventory to carry where. Each has a different perspective. A classic example is sales chronically over-forecasting (because they are rewarded for revenue, not forecast accuracy) and then manufacturing creating their own forecast, because they never trust the sales forecast.
This is why a holistic approach is key. There is no single right or wrong answer, but all of these competing objectives need to be synthesized into an optimal holistic approach that encompasses:
- Industry Characteristics/Optimization Objectives
- Business Model
- Trading Partner Relationships
- Product/Market Characteristics
- Risk Management
- Visibility and Technology
- Strategic Performance Alignment
Industry Characteristics/Optimization Objective
The characteristics and optimization objectives of a company’s industry segment have a big influence on inventory policy (see Figure 2 below). A capital intensive firm, such as a semiconductor foundry, where each fab1 costs anywhere from $2B to $5B to build, has their whole focus on achieving a good ROA (Return-on-Asset). Factory utilization is a critical metric for them — keep those billion dollar lines running! Contrast that with a product-focused design firm, like a fabless semiconductor company. They are a bunch of engineers that design chips. They don’t own any plants and their focus is time-to-market with a differentiated product. Other firms have a supply chain agility objective: postpone differentiation until the last moment, when demand is more accurately known. Thus the over-riding optimization objective of the firm informs their inventory strategy (and many other aspects of their operation).
A key aspect of a business model is who owns the inventory — i.e. when does title change hands as goods flow through the supply chain, and who makes the stocking and replenishment decisions. Ideally this is based on whatever creates the best outcome for the supply chain. For example, a manufacturer has knowledge of casual factors impacting demand of their product2 whereas the retailer has the actual demand/purchase data in their POS system and understands the broader promotions going on in their stores. Ideally they will collaborate together to make the best planning and replenishment decisions.
Then there is the question of inventory ownership. In traditional business models, the manufacturer or retailer owns the safety/buffer stock in their factory, or DC, or store, and makes the replenishment decisions. In VMI and similar business models, the supplier typically owns the safety stock and makes those decisions (see Figure 3). This places additional burdens on the supplier, as they are now carrying the inventory longer, and that inventory is spread out across many different customer locations, rather than only in the central pool of inventory within their DC. In theory, when the supplier ‘feels the pain’ of this inventory and has better visibility into actual demand, they will do a better job in planning their own production. However this requires that they have the systems and expertise; a different set of forecasting and inventory management skills. Often, especially when the customer is large and powerful, these decisions about inventory ownership and control are mandated by the customer.
We did in-depth research into the high tech industry’s transition to a VMI model, that revealed much about this aspect of a firm’s business model (see The Truth About VMI: Revelations and Recommendations).
Trading Partner Relationships
The relationship between trading partners can be viewed along several dimensions:
- Human relationships (person-to-person) — the foundation for collaboration and information sharing.
- Process relationships (workflows, formal and informal decision processes, system-to-system) — these should be re-examined on a regular basis.“We’ve always done it that way” prevents badly needed improvements.
- Contractual relationships — the purpose of the contract is to encapsulate the rules of the relationship, in a flexible way, that generates well-understood, deliberate commitments from both sides.
All three of these must be considered in taking a holistic approach to inventory management. One example for building flexibility into the relationship is the structured contract (see Figure 4 – Example of Structured Contract below). The buyer forecasts the range of expected demand and then asks the supplier to bid, providing pricing appropriate to the lead times and quantities of each tranche of expected demand. The buyer would expect a discount in exchange for longer lead times and firmer commitments for the base portion of demand, which they are highly confident in. The middle portion of demand would be close to normal market prices and lead times. For the upper end scenario, which will only materialize if demand is higher than expected, the buyer is willing to pay a premium in exchange for some commitment from the supplier to reserve the capacity and/or inventory stocks needed to deliver those quantities with short lead times. Thus the buyer communicates the degree or range of uncertainty in demand, and the supplier puts a price on providing the flexibility required to handle that range of uncertainty. The result is better inventory management on both sides. Structured contracts are described in more detail in “Surviving the Upturn: Ensuring Continuity of Supply in Allocated Markets.”
The characteristics of the product being sold make a huge impact on inventory strategy. For example, postponement, or differed differentiation, can be used to create more effective inventory management. One form of this is build-to-order of a configurable product. Many different SKUs share pools of common components, which are not assembled until you have a firm order for a specific SKU in hand. It is much easier to forecast aggregate demand across all of those SKUs. By pooling common components, a manufacturer can hold less inventory (while achieving higher service levels) than if they built out each unique configuration ahead of time, before receiving orders. However, this type of configurability — the ability to actually differ the differentiation — must be designed into the product. So, the supply chain group may brainstorm with the engineering group on ways to achieve differed differentiation. In this case, the product’s design characteristics are being specified with the explicit goal to support more effective inventory management.
Another example of product characteristics is seeing where each product fits on the ‘Uniqueness-Commodity Spectrum.’ On one end of the spectrum, a retailer of high fashion items may create exclusivity and uniqueness by carrying only one of each size of a particular dress. It would be ridiculous to do that with a highly commoditized article, such as paper towels. In the latter case, you never want to run out of stock, or else the customer will buy another brand (bad for the manufacturer) or, if they are brand loyal, will go to another store (bad for the retailer). Thus the characteristic of the product and the market must be considered in any inventory strategy.
The lifecycle of the item is another product characteristic that plays a major role in inventory management. If the lead time from the supplier is greater than the lifecycle of the product (from launch to end-of-life), then the buyer is forced to buy their entire stock before seeing any of what the actual demand will be. This creates a huge risk of shortages and excess inventory. Using postponement and similar strategies, the lifecycle characteristics can be changed, allowing the buyer to observe and understand demand before placing the final order (see Figure 5 – Product Lifecycle Types, Characteristics). For more details on how this is done, see “Demanding Times: Part Four – Lifecycle Planning.”
Replenishment decisions must also take into account risks — such as what are the consequences of an out-of-stock, and what is the level of inherent risk in the supply network. The consequences of an out-of-stock may vary dramatically. Consider two items with the same lead time and demand variability — standard formulas may tell you to keep similar levels of safety stock. But, suppose running out of one item means you simply have to juggle some production schedules until it arrives, whereas running out of another item shuts down your entire production line, costing millions per day. Obviously that must be considered when deciding how much of each item to carry. In addition, one item may have alternate sources available or a highly reliable source, whereas the other has only a single source, and that supplier has many vulnerabilities (these could be the financial, geo-political, natural disaster risks, etc.). This risk information also should be incorporated into inventory decisions. Often risk management is considered a separate discipline and organization from inventory management, but in fact the two should be working together closely.
Visibility and Technology
Many companies have separate ‘islands of visibility’ into what inventory they are holding where (see Figure 6). For example, many companies manage e-Commerce inventory completely separately from store inventory, thus loosing opportunities for pooling that inventory. This topic and how to achieve an end-to-end view is explored in “Omni-Channel Inventory: Getting the Big Picture.”
Beyond visibility, of course technology can help tremendously with forecast accuracy and replenishment decisions. But these replenishment formulas are only as good as the input data. For example, it takes work to find out the real lead times for all your items. People will often take a short cut and enter the same lead time for all items (or all of a class of items), resulting in incorrect replenishment calculations and decisions by the system’s algorithm. No matter how great the replenishment algorithm and technology are, they will give wrong answers if the input data is wrong.
Strategic Performance Alignment
Each organization has a set of strategic goals. Ideally the whole organization, including inventory management, is aligned to meet those goals. However, many parties influence a company’s inventory strategy (remember the tug-of-war depicted in Figure 1 – Inventory’s Multiple Personalities) and the metrics and compensation incentives for those various parties are not always aligned to the strategic goals. Those metrics and incentives should be reviewed on a regular basis to understand the underlying causes that create behaviors that may be counter-productive to achieving the goals. For example, perhaps a portion of the salesperson’s bonus should be based on forecast accuracy and/or profitability of the sale, instead of solely on revenue generation.
What Successful Companies Are Doing
The drivers of inventory policy and strategy are dynamic. Successful companies are constantly reassessing yesterday’s policies and decisions to see if they still make sense today — everything from replenishment algorithms to competitive dynamics to changing product characteristics. Further, they are able to bring together all of the intelligence across the organization to make smarter decisions. They align individual metrics to the strategic goals. They have flexible supplier arrangements to more successfully accommodate both downside and upside demand scenarios that materialize. They have end-to-end visibility into their inventory, across the chain. They incorporate risk management into their inventory strategy. In short, they take a holistic approach to more successfully manage their inventory.
1“Fab” is industry lingo for a semiconductor fabrication plant which makes the dies (i.e. the circuitry of the chip) which can be put into various application-specific packages. — Return to article text above
2For example, a manufacturer of mosquito repellent may keep track of rainfall and the amount of standing water in each region it sells into, since that impacts the mosquito population and hence demand for their product. It is not possible for the retailer to know and track that level of detail for the tens of thousands of SKUs they stock.– Return to article text above
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