Article 3: Part of the Beyond the Buyer series.
One of the most persistent problems in developing a supply chain business case is deciding what to do with benefits that are clearly real but difficult to express in dollars.
The maintenance manager may know that equipment repairs have declined since a new pallet program was introduced. The logistics director may see fewer disputes with carriers. The operations team may find that the distribution centre simply runs more smoothly. Yet when someone asks how much those improvements are worth, the conversation often stalls.
That leaves decision-makers with two unsatisfactory choices. They can leave hard-to-measure benefits out of the business case, even though everyone knows the analysis is incomplete. Or they can assign those benefits loosely supported dollar values that experienced reviewers are likely to challenge. We would propose that increasingly, as technology becomes more sophisticated, there is a better approach.
The first step is to recognize that benefits can be difficult to measure for different reasons. Sometimes the necessary data already exists but has not been gathered from the departments that hold it. Sometimes the connection between the investment and the result is difficult to prove. In other cases, the benefit is obvious, but there is no widely accepted method for quantifying it in dollar terms. Those are not the same problem, and they should not be treated the same way.
Key Takeaways
| Measure what you can defend | Benefits supported by operating data and a reasonable financial calculation belong in the business case. |
| Acknowledge the rest | Benefits that cannot yet be priced reliably should be described rather than ignored. |
| Avoid false precision | An unsupported dollar estimate can weaken an otherwise credible business case. |
| The boundary can move | Better operational and IoT data can turn some hard-to-measure benefits into measurable ones over time. |
Two Tiers of Benefits
The Multi-Stakeholder Benefit Attribution Model, or MBAM, separates benefits into two broad groups.
Tier A benefits can be supported with observable data and a reasonable method for converting the result into money. Gathering the information may require work across procurement, operations, maintenance, claims or other departments, but the necessary data and calculation methods are available.
Tier B benefits are economically meaningful, but they cannot yet be converted into a reliable monetary estimate. The evidence may be incomplete, the connection to the original investment may be too difficult to isolate, or the conversion method may be too uncertain.
The distinction is not between benefits that matter and benefits that do not. Both matter. The distinction concerns how confidently they can be measured.
Tier A benefits should be included as monetary estimates, with their data sources and assumptions clearly explained. Tier B benefits should be acknowledged and described, but not given a convenient dollar value simply to make the business case look stronger.
This produces an analysis that is both more complete and more credible.
What Can Be Measured Today
Consider an IoT-enabled durable pallet program. Several important benefit streams can usually be measured using information already available in ordinary business systems.
Asset loss reduction
An IoT-enabled pallet records its location, showing how many assets disappear from the system and how the loss rate changes after tracking is introduced. The calculation is relatively direct. The organization compares the loss rate before and after deployment and applies the replacement cost of the assets. Because the tracking system generates the location data itself, this can be one of the strongest and most defensible benefits in the business case.
Replacement savings from greater durability
The financial effect of a longer service life can be calculated from procurement records. The required information includes the purchase price, expected service life, replacement frequency and number of pallets in the program.
This is essentially a Total Cost of Ownership calculation. It is not technically difficult, but organizations sometimes weaken the analysis by using a short payback period rather than comparing the alternatives over their full expected lives.
Better fleet utilization
Tracking data can also show how much of the pallet fleet is actively moving through the supply chain and how much is sitting idle, lost or waiting to be retrieved. If improved visibility allows the company to support the same volume with fewer pallets, the reduction in required fleet size represents a measurable capital saving. Dwell-time and location records can help explain where assets are being delayed and where recovery efforts should be concentrated.
Fewer damage claims
Claims systems and insurance records can show changes in the number and cost of product-damage incidents.
The information may already be recorded, but it is rarely connected directly to pallet selection. Making that connection requires analysts to compare claim patterns before and after the change and determine how much of the improvement can reasonably be attributed to the new pallet program.
The monetary estimate can include both the value of damaged product and, where data is available, the labour required to investigate and process each claim.
Lower maintenance labour
Broken pallets, loose boards, protruding nails and debris can damage conveyors, lift trucks and other warehouse equipment. Maintenance systems may already record the resulting service calls, repair times and labour costs.
Reviewing those records can help identify incidents related to pallet condition. The estimate may not carry the same confidence as directly observed asset-loss data, but it can still be defensible when the organization clearly explains the records examined and the assumptions used.
Less housekeeping work
Wooden pallet debris creates a recurring cleaning requirement in many warehouses and distribution centres. The cost is real, but it seldom appears in a pallet business case.
Facilities records and short observational studies can help establish how many labour hours are spent removing boards, splinters, nails and other pallet debris. A comparison after the introduction of a more durable pallet can then show whether that requirement has declined. This type of benefit does not require sophisticated technology to measure. It requires someone to recognize that the work is connected to the pallet decision and to collect the appropriate information.
Together, these examples create a much more complete business case than purchase price alone. They also remain grounded in operational records that reviewers can examine.
What Should Not Yet Be Given a Dollar Value
Other benefits may be equally real but much harder to measure reliably.
Health and safety
Fewer pallet failures should reduce exposure to splinters, protruding nails, unstable loads and debris around handling equipment. The direction of the benefit is clear. The measurement problem is attribution. Most organizations do not record injuries and near-misses in enough detail to determine confidently how many resulted from a particular pallet type or specification.
For many companies, safety improvement therefore remains a Tier B benefit. It should be discussed, but it should not be assigned a precise dollar value unless the organization has sufficiently detailed incident data. That classification is not permanent. Safety could move into Tier A if better records made the connection between pallet condition and incident frequency clear enough to support a reliable calculation.
Better decision-making
IoT data can help planners locate assets, identify delays, respond to exceptions and make better-informed inventory decisions.
The value builds through many decisions made across the organization. No single report is likely to show that better pallet data saved a specific amount of money. The effect is spread across planning, transportation, inventory management and customer service. That does not make the benefit imaginary. It means the benefit is too diffuse to convert confidently into one financial figure.
Organizational learning
A company that introduces an IoT-enabled asset system also develops experience with sensors, data management, dashboards and real-time operational analysis. Those capabilities may later support other applications. However, it is difficult to determine how much of that future value should be credited to the original pallet investment.
The capability has economic importance, but a precise monetary estimate would depend heavily on assumptions.
Brand and customer effects
Fewer damaged products and more dependable deliveries may improve customer satisfaction, shelf availability and the company’s reputation.
The connection is plausible, but the path from pallet selection to brand value is long. Many other factors affect customer experience and sales performance. Supply chain analysts should therefore be cautious about claiming a specific revenue or brand-equity benefit.
Stronger trading-partner relationships
Better information can reduce disputes over delays, losses and product damage. Shared visibility may also improve trust between supply chain partners.
Anyone who has worked in a difficult supplier, customer or carrier relationship can understand the potential value. The problem is not recognizing the improvement. It is finding a defensible way to price greater trust or fewer disagreements.
Benefits to the wider industry
Early adopters often generate knowledge that helps later users avoid mistakes and reduce implementation costs. That is a genuine benefit, but much of it accrues to companies outside the original investment.
It does not belong in the early adopter’s financial return calculation, even though it may be relevant to researchers, associations and the industry as a whole.
How to Present Both Tiers
A strong business case should not hide the difference between measured and unmeasured value.
Tier A findings should be presented as monetary estimates. For each one, the analysis should explain:
- what was measured
- where the data came from
- how the result was converted into money
- how confident the analyst is in the estimate
A benefit based on directly observed tracking data may receive a high confidence rating. A maintenance saving that requires reviewing service records and deciding which incidents were pallet-related may receive a medium rating.
The purpose of a confidence rating is not to weaken the business case. It allows reviewers to see which findings are strongest and which depend more heavily on judgment.
Tier B findings should be presented separately. The analysis should name the benefit, explain why it matters, and state why a reliable monetary estimate is not yet possible.
This avoids both common mistakes. The business case does not pretend that hard-to-measure benefits do not exist, and it does not undermine its credibility by attaching unsupported numbers to them. The Tier A total can then be described as a minimum defensible estimate of the value created. Tier B represents additional potential value that has been acknowledged but not included in the financial total.
The Boundary Can Change
A benefit does not necessarily remain in Tier B forever.
Some benefits are difficult to measure only because organizations are not yet collecting the right data. If safety records begin identifying the asset or equipment involved in an incident, the relationship between pallet condition and injury frequency may become measurable.
Retail shrink and product-availability effects could also become easier to quantify where suppliers and retailers share more detailed operating data.
IoT technology is helping move this boundary. Asset-level data can connect shock events with damage claims, dwell time with detention costs, location information with loss rates, and temperature records with cold-chain failures. As more observations become available, benefits that once depended on assumption can increasingly be tested against actual operating experience.
Other effects may remain difficult to monetize. Organizational learning, relationship quality and improved decision-making involve long causal chains and many contributing factors. Even better data may not produce a single dependable dollar value.
Why the Difference Matters
The goal of a business case should not be to make an innovation appear as valuable as possible. It should be to describe its economic effect as completely and honestly as the available evidence allows. Ignoring every benefit that cannot immediately be priced will undervalue many supply chain innovations. Assigning speculative dollar values to every possible advantage will make the analysis easier to challenge.
The Tier A and Tier B distinction offers a more balanced path. It allows organizations to count what they can defend, acknowledge what they cannot yet price, and show decision-makers where important value may still be missing from the total.
That approach may not produce the largest possible return-on-investment number. It should produce a number that purchasing teams, finance departments and operating managers are more likely to trust.
For the complete MBAM framework, practical examples and research agenda, visit the Beyond the Buyer resource hub or download the white paper, Beyond the Buyer: A Multi-Stakeholder Framework for Evaluating the True Economic Impact of Supply Chain Innovation.
For the full reference list and complete methodology, see the white paper at packagingrevolution.net.
Articles in this series:
Article 1: Why Total Cost of Ownership Isn’t Enough, And What to Do About It
Article 2: The Pallet Core Revenue Problem: Why Pallet Procurement Decisions Have Hidden Economics
Article 3: What We Can Measure, What We Can’t, and Why the Difference Matters
Rick LeBlanc, EMBA, is the founder and editor of Reusable Packaging News (subscribe to the free newsletter) and editor of Western Pallet Magazine. A supply chain journalist with more than 30 years of experience, he specializes in pallets, reusable packaging, material handling and related operations. Rick is co-author of Pallets: A North American Perspective and Pallets & Progress: A Collected History of Pallets and Palletized Handling 1922–1945. He is also an advisory board member of the Virginia Tech Center for Packaging and Unit Load Design. Read Rick’s full bio.
