Gartner analyst Paul Lord has developed a framework to better understand inventory trade-offs by categorizing those decisions according to the objectives they are meant to achieve: structural, operational and situational.
Many companies struggle with decisions such as “How many days of sales or inventory turns per year should we target? or “How can we reduce inventory and improve our balance sheet?”
These are good questions, Lord says, but getting to the next level of analysis requires categorizing inventory so that both the company’s goals and the drivers impacting inventory can be better understood and addressed. Lord says that while three broad categories of inventory - structural, operational and situational - can overlap, each category should first be examined separately (Supply Chain Leaders Must Orchestrate Three Decision Categories for Inventory Excellence, 9 April 2018, Paul Lord).
Structural inventory is a direct result of design choices. Lord says simply, “Design choices create constraints with structural and inventory costs.”
These can be product design choices, such as when building an electrical product whether to make the power cord and plug an integral part of the initial product or to add it on later at the region (e.g., North America, Europe, …). Postponing that step could allow for faster fulfillment and more flexible inventory at the regional level, but could also significantly increase production and logistics costs.
They can also be network design choices, such as where to locate a warehouse. Longer network distances create lead times that require additional transit stock. Facility and production property, plant, and equipment (PP&E) choices determine cycle times that impact work in process (WIP) inventory. And single sourcing may reduce unit cost and inventory, but significantly increase structural risks.
Lord says that structural inventory, strictly speaking, should not be optimized. Instead it should be a strategic decision guided by balancing three objectives: delivered cost (direct supply cost), agility (inventory write-offs) and resiliency (supply interruption cost).
Operational inventory is discretionary inventory associated with additional cycle stock and safety stock that is employed to maintain service levels. It includes replenishment decisions (quantity, timing, location, buffering), production decisions (quantity, sequencing, allocation, scheduling) safety stock, and purchase decisions (quantity, timing, vendor, location). Supply planning and scheduling practices can also result in additional transit stocks and work-in-process.
Lord says that simple resupply frequency and reorder point rules of thumb don’t work in this environment, but requires inventory optimization (MEIO) to optimize buffer size, lot size and stage optimization.
Lord has developed a thought-provoking approach for tailoring supply and inventory tactics depending on the characteristics of the business and the inventory. His analysis uses two axes of segmentation, gross margin and demand variability. Based on Lord’s analysis, the interaction between these two variables drives the optimum approach to managing your inventory.
For instance, he says low margin and low demand variability businesses should “hard wire” their production and supply to churn out product at a consistent rate, maximizing resource utilization and production efficiency. High margin and high demand variability businesses are where Lord says the power of inventory optimization technology is most critical. It can orchestrate safety stock and other levers to provide the optimized buffers to address the demand variability while not only avoiding added cost, but often reducing excess inventory holdings and overall supply chain cost structure. In this segment, customer service comes not from the forecast, but from inventory. Variable demand, intermittent or long tail demand are all served by inventory. (For more on this analysis technique see Segmenting Your Inventory by Gross Margin and Demand Variability).
Situational inventory is used to anticipate events and opportunities and to deal with long lead time supply commitments or capacity utilization constraints. Lord breaks it into two groups; anticipation stock for preparing for potential demand events such as promotions, and hedging stock for addressing supply risks. These decisions often require balancing added inventory to buffer uncertainty with residual obsolescence risk.
Lord points out that due to the psychology of risk, these decisions are usually not purely deterministic. “Prospect theory” as described by Nobel Prize winning psychologist Daniel Kahneman shows that humans over-emphasize lost sales and under-emphasize product obsolescence. Lord says that the solution to counter this bias is adopting analytics and modeling techniques that remove this bias or at least require decision makers to consider it in an objective framework. For more on this interesting topic see Nobel Prize-winning economist's four steps to minimize forecast bias.
A final key point to remember: In the end there is only one set of inventory serving all three needs. It helps to make the structural decisions first (often in the strategic planning and S&OP processes) and then optimize the total inventory in a semi-automatic way using a good inventory optimization system.
Click below for a short whitepaper on how to make intelligent inventory trade-offs: