Inventory concepts

Inventory concepts

The Inventory Delimma
A few years ago I conducted a workshop for the operating committee of one of the world’s largest industrial conglomerates. The heads of operations for each business unit plus the company’s COO participated. We had a question and answer session at the end of the workshop. The COO asked the first question. “Dr. Frazelle, we have quite a bit of conflict in these meetings. Especially lately. Why is that?” I asked him what the charter of the group was. He said, “We have two main objectives. The first is to reduce inventory. The second is to lower our unit costs.” I said politely, “You just answered your own question. Your main methods of reducing unit cost, global sourcing from cheap labor sources and buying in large quantities to receive discounts, increase your inventory levels. Your objectives are at odds with one another so you are at odds with one another.” He asked me what they should do about it. I encouraged them, like I encourage all our clients, to take a step back and reconsider their objectives and their approach. I suggested that their objectives would preferably be to maximize return on invested capital (ROIC), improve perfect order percentage, spend whatever was required in total supply chain cost to support those objectives, and invest in whatever inventory level was required to accomplish those objectives. Sometimes that inventory level will be higher and sometimes it will be lower. Inventory is not an end in itself; it is a means to an end.

We encounter this conflict in nearly every client situation. In all but the wisest and most mature organizations, highly qualified professionals are required to do the impossible; respond to a barrage of typically uncoordinated and irreconcilable initiatives from across the organization. Those initiatives normally include many of the following. Increase SKUs. Increase customization. Increase inventory availability. Reduce customer response times. Reduce transportation costs. Reduce purchase costs through global sourcing. Reduce manufacturing costs. Mitigate increasing supply chain risk with multiple sources. All of these naturally work to increase inventory levels. Yet, facing prevailing lean thinking, they are still required to reduce inventory.
Inventory Malfunctions
The inventory conundrum is exacerbated by many complicating factors. Those factors can be categorized into five major malfunctions:
• Data Discrepancies
• Inadequate Training & Education
• Problematic Perspectives
• Misaligned Metrics
• Poisonous Paradigms

Data Discrepancies
1. Base Data Errors. In many companies the base data used to control and plan inventory and to support inventory decision making is just plain wrong. In a recent project with one of the world’s most prominent HVAC firms we discovered that more than 50% of the MRP, bill of materials (BOM), and on-hand inventory records were wrong. In a recent engagement with a large engine manufacturer we found that inventory planners were regularly manipulating historical demand, set points and parameters to conjure the turn rate they wanted.
2. Un-vetted Changes. It is not unusual to find hundreds of people, qualified and unqualified, with and without accountability, making un-vetted changes to schedules, demand, supplier data, and MRP data. We recently came across a client situation where more than 500 people had access to make changes to multi-million dollar assembly schedules. With a large retailer we found that more than 300 people had clearance to modify multi-million dollar store order replenishment schemes.

Inadequate Training & Education
3. Untrained Planners. Based on my experience I estimate that less than 30% of inventory planners and analysts working with inventory systems have any formal education in inventory management. During a recent project I asked to see the resumes of the inventory planners. Less than 10% had any formal training in the decisions they were making. Many people pulling inventory triggers don’t know how to use the gun.
4. Faulty Fundamentals. Because so few inventory planners and managers have inventory training and education, there is widespread misunderstanding and misapplication of inventory management fundamentals. During a recent engagement with a large healthcare company I asked about their inventory accuracy. They said that it was well above 98%. I was suspicious, so I asked them how they defined inventory accuracy. They said it was the portion of demand shipped from inventory. I explained that that was fill rate, not inventory accuracy. I then asked what their inventory accuracy was. They didn’t know.

Problematic Perspectives
5. Conflicting Perspectives. Every inventory decision impacts financial, service, and operational performance. However, very few individuals understand all three and very few decision support tools consider all three. As a result, different inventory levels appear high or low depending on the glasses you are wearing. Those views need to be reconciled; a major point and objective of this book.
6. Irreconcilable Interdependencies. Decisions made in customer service, inventory management, manufacturing, sourcing, transportation, and warehousing all work interdependently to impact inventory levels. However, very few individuals understand those interdependencies and very few decision support tools consider them.
7. Operations Myopia. Inventory is typically viewed as an operational or tactical outcome. It is rarely viewed as a strategic contributor to an overall supply chain strategy which in turn serves as a part of an integrated business strategy.
8. Misplaced Accountability. Many people influence inventory levels but often no one is accountable. I like to ask our clients early on who is accountable for inventory. The answer is revealing and quickly highlights the organizational and measurement root of inventory and/or supply chain issues.
9. No Microscopes. Every SKU has a unique demand pattern, supply pattern, and dimensional profile. Individual SKUs are bought, sold, and slotted. Yet, most companies resist individual SKU inventory optimization and planning. Even in cases with 100,000+ SKUs we have developed individual SKU strategies and rolled those up into category and business unit inventory strategies. Inventory strategy is a top-down AND bottom-up endeavor. Wide angle lens AND microscopes are required and available.

Misaligned Metrics
10. Traditional Accounting. Traditional accounting treats inventory strictly as an asset whereas operationally and philosophically inventory is popularly considered a liability.
11. Conflicting Metrics. Metrics used in the five supply chain logistics activities – customer service, inventory management, sourcing, transportation, and warehousing – often work at odds with one another and yield excess inventory.

Poisonous Paradigms
12. Procurement “Cost Avoidance”. In the name of “cost avoidance”, procurement is still looking for the cheapest first price that may cost much more in related excess inventory carrying costs.
13. Lean. Lean literature and previously idolized supply chain operators often veil the fact that their inventory turn advantages typically come at the expense of suppliers further up the chain.

Were it not for poor fundamentals, grasping for silver bullets, limited education, misaligned metrics, myopic perspectives, misplaced influence and accountability, misalignment with corporate strategy, and false prevailing paradigms: developing inventory strategy would be a piece of cake.

During a recent client workshop the chief supply chain officer noticed that I was becoming discouraged as they bemoaned their inventory ills. He said, “Dr. Frazelle, don’t get discouraged. We don’t. We just keep our heads down, keep making stuff, and hope it turns out OK in the end.” Fortunately he was joking. Unfortunately many live in a world with their heads down, making and buying stuff, and hoping it turns out OK in the end. There has to be a better way.

Inventory Maturity
In a recent project with one of the world’s largest and most critical healthcare providers I was stunned to learn that they did not even measure inventory accuracy, let alone know what it was or have on-going efforts to improve it. On a project with a prestigious industrial conglomerate I helped them uncover the fact that over 50% of their MRP and BOM data was just plain wrong. In a project with a global aerospace company we discovered that over 500 people, some with minimal credential requirements could make multi-million dollar changes to high level production schedules with little to no oversight. In a project with a major high tech equipment company we found that unqualified inventory “analysts” were “tweaking” major inventory set points and true demand in their service parts inventory system. The pre-meditated tweaks were un-vetted, un-supervised and made to guarantee that reported turns coincided with their personal turn targets. In a recent project with one of the world’s largest commodities companies the company balked at my suggestion that they even consider using the word “integrity” in reference to inventory because “integrity” sounded moral. In each case, the companies yearned for and nearly demanded the most sophisticated practices in inventory management, while struggling with, ignoring, flying in the face of, and/or naively overlooking the basis for all inventory improvements – integrity.

Integrity is the foundation for everything related to trust. Trust is the fertile cultural and technical soil required for true inventory optimization. Without it, each element of the supply chain hunkers down into their own inventory protection mode, commonly known as hoarding.

High levels of inventory integrity develop from high levels of inventory accuracy; reliable base data including leadtimes, MRP records and BOM records; measured and persistently improved forecast accuracy; and consistent, disciplined participation, follow-through, and accountability by key players in inventory decision making meetings and processes.

Once a high level of inventory integrity is established, the next phases of inventory management maturity are attainable. Level 2 is inventory stability, where predictable cause and effect outcomes are the rule as opposed to the exception in inventory behavior. Level 3 is inventory optimization, where the SKU portfolio, forecast, leadtimes, lot sizes, deployment, visibility, inventory carrying rate, inventory turn rate, and fill rate that meet required service levels and maximize financial performance are determined and implemented. Level 4 is inventory integration, where inventory optimization incorporates cross-functional participation in and accountability for inventory decision making. Level 5 is inventory collaboration, where sharing inventory levels, forecasts, and planning with key suppliers and customers is commonplace.

Inventory Management Maturity Phases

Inventory integrity and its elements including inventory accuracy, SKU record accuracy, putaway accuracy, forecast accuracy, and lead time accuracy are all measured, monitored, included in personnel incentive plans, and relentless improved via root cause analysis and corrective action.
Push or Pull
There are two conceptual models for inventory management – push and pull. The push inventory model is so called because the emphasis is on “pushing” speculative inventory, made-to-forecast (MTF) in response to forecasted demand, out the door to customers. The push model financially outperforms the pull model when manufacturing utilization is critical and the cost of production is high relative to inventory carrying cost and to the risk of obsolescence. We have recently helped successfully convert a variety of clients in the CPG, food, beverage, and confectioners industries to push models resulting in much higher profits, return on invested capital, market share, and customer satisfaction.

Definition: Sell what you make.
When: When keeping manufacturing utilization high is critical and the cost/risk of obsolescence is low.
Examples: Cigarettes, Dog Food, Candy

The pull inventory model is so called because true demand is said to pulling made-to-order inventory to customers on a just-in-time basis. The pull model financially outperforms the push model when the cost of inventory carrying cost and risk of obsolescence are high relative to production and postponement costs. Products such as high-end, highly configurable electronics and pharmaceuticals are examples of products that work best financially and operationally in pull-based systems.

Definition: Make/ship what you sell.
When: When inventory is very expensive, postponement is feasible, and there is high cost and risk of obsolescence.
Examples: Retail Apparel, Personal Computers

Over the years since the advent of pull-based systems like the Toyota Production System (TPS), Just-in-Time (JIT), and Lean – many demonstrative proponents of pull-based inventory and supply chain management have published and soap-boxed to the point where any other approach to inventory or supply chain management is considered second-class, immature, or old fashioned. Yet, when we work with our clients to compute true return on invested capital, profitability, and customer satisfaction for each of their SKUs moving through each node and link in their unique supply chains we are finding that an optimal mix of push and pull depending upon the product characteristics and transition point within the supply chain yields dramatically superior financial and service performance. That optimal mix is based on a wide variety of item characteristics including demand variability, item value, shelf life, and risk of obsolescence AND logistics characteristics including setup/PO costs and inventory carrying rates. A qualitative presentation of those factors and their impact on push-pull models is presented in the figure.

Push-Pull Decision Factors
Bullwhip Effect
The “bullwhip effect” in supply chain management is a reference to the increase in the variability of order sizes and the accompanying increase in inventory levels that occur moving backwards in the supply chain from consumers to retailers to wholesalers to manufacturers to suppliers. An example of the phenomenon is illustrated in the chart below.

Example Bullwhip Effect Diagram

There are many causes for the bullwhip effect including:

• If the retailer has a promotion, that may create a spike in demand. That spike proliferates through the system. Everyday Low Pricing (EDLP) is sometimes used to counteract the effect of promotions. Many mass merchants try to follow EDLP. They don’t incur these big demand spikes, inventory levels are lower, they can charge less for the product, and they can afford to execute Everyday Low Pricing. Usually the number one or number two retailers in a particular commodity can afford EDLP and the others have to offer promotions to get consumers into their stores and away from the people who are offering Everyday Low Pricing.
• Not every player in a supply chain closely follows consumer demand.
• Manufacturing, procurement, and transportation economies of scale work against smooth order and inventory patterns.
• Shortage gaming and false ordering throws off forecasting systems and creates blips in demand and ordering..
• Poor forecasting and limited forecast sharing create ordering and inventory peaks and valleys.

The bullwhip effect can be effectively counteracted by forecast sharing, collaborative planning, DRP, EDI communications, and total-supply-chain-cost decision making.

Merge-in-transit is a supply chain flow strategy made famous by Dell Computer. The basic merge-in-transit concept is to use the transportation function (vs. warehousing) to assemble the components of an order manufactured on demand in disparate locations.

Example Merge-in-Transit Flow

This logistics strategy at one time allowed Dell to achieve return on invested capital rates in excess of two times their closest competition. Some of the keys to success for them included:

• Direct internet sales
• Supplier owned inventory held less than 15 minutes away
• Supplier City with vendors on-site performing inventory management on Dell’s behalf
• The merge-in-transit flow concept
Inventory Optimization
An optimization statement is comprised of two components – an objective function and constraints. Isolated to inventory, the optimization becomes finding the inventory level that yields the best possible financial performance for the business and supply chain subject to fill rate, response time, shipping frequency, and storage capacity constraints.

The RightStock™ model uses a menu of objective functions for inventory decision optimization. They are all related to financial performance, and include the impact of inventory and fill rate on revenue, expense and capital. (This is a major departure from most supply chain philosophies, tools, and metrics which typically only consider the impact of decisions on expenses or operational performance indicators.) RightStock™ objective functions include maximizing Return on Invested Capital (ROIC), maximizing Inventory Value Added™ (IVA), minimizing Inventory Policy Cost (IPC), and maximizing Gross Margin Return on Inventory (GMROI). There will be a much more comprehensive explanation of these objective functions in section 2.6.

Inventory Constraints

If all we had was an objective function, optimization would be easy. Admittedly facetious, but regrettably common, here’s a storyline that is played out in many companies. Let’s consider each of the total logistics cost components, independently. First, transportation. Transportation has become so expensive and complex that we may just decide to stop trying. Fuel costs. Regulatory hassles. Poorly performing carriers. The list goes on. Second, warehousing. All the JIT, Lean, and Six Sigma books suggest that warehousing is non-value added, and just plain bad for business. Let’s close the warehouses. Third, inventory carrying. Even though inventory is still an asset in accounting, we all know it’s a liability (borderline illegal in some companies) and politically incorrect in the current JIT, Lean, Six Sigma environment. We need to stop carrying inventory. Since there is no inventory, there will be no customers, so lost sales cost is eliminated. These all work together to completely eliminate total logistics cost and the inventory that goes with it. We win, right? Wrong!

Total Logistics Cost Elements for Optimization

In addition to common sense, what should prohibit an organization from going down that road to ruin? A customer service policy (CSP). A RightChain™ Customer Service Policy is segmented by channel, ABC customer class within a channel, commodity, and SKU class within a commodity (Figure 1.4). The CSP establishes targets which must be met for fill rate, response time, delivery frequency, delivery quality, packaging, and any other stipulated dimension of customer service. Those requirements serve as constraints in supply chain logistics optimization. An example supply chain logistics optimization statement from a recent service parts client follows.

Multi-Channel Customer Service Policy

Objective Function
• Minimize Total Logistics Cost

1. Fill Rate > 90%
2. Response Time < 96 Hours
3. Delivery Frequency = 3x per Week
4. Shipping Accuracy > 99.7%

An illustration of the optimization is below. Note that the customer service policy yielding the lowest total logistics cost is a response time of 3 days and a fill rate of 99%. (That is not always the case and just happened to be for one particular SKU for this particular client.) The tricky part is that as fill rate increases, inventory carrying cost, warehousing costs, and potentially transportation costs increase while lost sales costs decrease. Those dynamics and interdependencies are reflected on one axis. As response time decreases, transportation costs, warehousing costs, and potentially inventory carrying costs increase (depending on whether the response time requirement is met via more expensive transportation or more warehousing close to the customer); but lost sales cost decrease. Those dynamics and interdependencies are reflected on the other axis.

Supply Chain Logistics Optimization Surfaces

A strictly inventory optimization statement would include one or more of the following objective functions and one or more of the following constraints. (Each will be explained in much more detail as we proceed through the book.)

Inventory Objective Function Candidates
• Maximize Gross Margin Return on Inventory (GMROI)
• Maximize Inventory Value Added™ (IVA)
• Minimize Inventory Policy Cost™ (IPC)

Inventory Optimization Constraints
• Fill Rate > Target
• Response Time < Target
• Shipping Frequency > Target
• Inventory < Storage Capacity

Determining and implementing the inventory level that satisfies the required constraints and yields the best financial performance is inventory optimization.
As a part of the National Science Foundation’s Japan Technology Evaluation Center I had the unique privilege to lead a major study for the U.S. government comparing U.S. and Japanese logistics systems. During the study I interviewed business and supply chain executives in many large Japanese organizations. Not surprisingly, one of those was Toyota. I spent significant time with the developers of the Toyota Production System and their professor. One of the stories they shared explains more about the Toyota Production System than all the books I have ever read on the topic.

The Toyoda (the company name was created from the family name) family was a rice farming family. They became wealthy when they invented mechanical harvesting equipment for rice. At some point they decided that if they could make rice harvesting equipment, they could also make cars. Unfortunately the production concepts did not translate very well and the auto making venture almost bankrupted the family. The head of the family decided to hire a new engineer from outside the family and gave him one year to develop a new way to make cars. To make a long story short, that young man came up with a way to profitably make cars in an island nation (self-contained), with few natural resources (no waste), limited habitable land (no space), and locust-like industrial congestion (perfectly orderly). The Toyota Production System was born out of those unique geographic, business, and cultural conditions.