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How do you make sure you have the right amount of inventory to service your commitments, without tying up any more cash than you need to? This problem lies at the heart of distribution and replenishment. Luckily, there’s an unconventional solution.
[Listen to audio version, read by David Hodes]
If you’re out of stock, you can’t produce, repair, overhaul or sell, unless you spend more than you budgeted on expediting—if that’s even a possibility. Alternatively, too much stock, often of the wrong type, incurs costs in management attention, storage, writedowns to sales discounts, perishment or obsolescence.
You have a distribution problem when consumption locations are remote from the production location and the tolerance time of the buyer or end-user is much shorter than the time it takes to make the product available at the point of consumption. How can we solve this dilemma? Build a better crystal ball? Forecasting demand down to the item and the location it is required is as complicated as predicting the weather. It’s very challenging to know who will need what, where and when.
If we assume you are part of a for-profit organisation, then the organisation’s goal is likely to be to maximise profits now and in the future. To state the obvious, you must protect sales and, at the same time, reduce costs. To protect sales, your instinct is to hold high inventories, mostly because replenishment time is long, you cannot accurately predict demand and supply is unreliable. However, to reduce costs, you have the competing impulse to reduce inventory because of its effect on your cash balances, operating expense and write-offs.
In most distribution systems, the compromise is to choose a time interval and determine a target level for each product according to the forecast consumption over that interval. Often, the selected interval is adjusted according to the resulting total investment in inventory the organisation calculates it can afford. When this prevalent idea is applied, the accountants usually report the full value of inventory and relate it to the number of times stock turns in a year. So, for example, you could get a statement like: ‘We’re holding $20 million in inventory, about three weeks’. The trouble is, this could be zero stock for some fast-moving items and enough for a year or more for others. Anyone who has ever had the dubious joy of doing a stocktake has come across the aged, the comatose, the dead and the fossilised classes of inventory.
“Forecasting demand is as complicated as predicting the weather”
It stands to reason that you should target the level of investment in inventory according to the maximum forecast consumption within the average replenishment time, factored by the level of the unreliability of the replenishment time. Given this heuristic, the prime parameters used to determine the inventory target are, therefore:
The higher the level of service you require, the more emphasis you should place on the variability. However, the really big leverage resides in correctly understanding replenishment time. So, how does replenishment time impact the level of inventory in the system? The consumption point should order inventory to the target: consumption within the replenishment time. As a result, the distribution system has, on the way from the production point, inventory equal to the forecast consumption within the supply lead time. Also, at the point of consumption, it will have inventory equal to the forecast consumption within the order lead time, minus the ongoing sales.
The really big leverage resides in correctly understanding replenishment time.
Both the rate of consumption and the replenishment time have a direct impact on the inventory target, but replenishment time also has an indirect effect. The forecast accuracy deteriorates with the length of time of the forecast. Thus, the longer the replenishment time, the higher the variability in consumption is likely to be. Also, in many environments, the longer the replenishment time, the higher the variability in replenishment time, as more things could go wrong. This compounding of complexity means that doubling the replenishment time more than doubles the inventory target.
Since the replenishment time is the critical factor in determining a suitable inventory target, let’s take a closer look at some of the ramifications of paying insufficient attention to bad practice when it comes to addressing replenishment times.
Point-of-consumption batching: Often, producers will offer a lower price for goods if you, the consumer, order large quantities. Also, it is usually quite complex and requires a lot of management attention to determine what to order from whom and when, so you tend to batch your orders. Compare what you currently do to the unconstrained case where you would reorder every time you consumed or sold a unit. No minimum order quantity for production, shipping or storage—simply use one, buy one. Doing the thought experiment does not say that you can turn your world into the unconstrained one, but it does bring to the front of mind how much batching is going on at the point of consumption.
Production batching: Production people like to run large batches. They tend to do this because they can improve their production efficiencies by saving setups. They will accumulate sales orders until large ‘economic’ quantities have been reached, and only then will they start producing.
Transport batching: Shipping containers filled with product is less costly, on a per-unit basis, than using a truck or ship half-filled with air. Thus several orders are often combined to achieve the goal of minimising transport costs.
It’s easy to see that not only do we create more inventory than we need in our systems when we take the above three types of batching into account, but we also make the whole logistics puzzle far more challenging to solve, with each node in the network looking to optimise its piece of the puzzle at the expense of the whole. It does little to address the main problems: being out of stock of what you need, and having too much stock of what’s not required.
Before we solve this batching issue, let’s get some insight into the variability component of the inventory target. Below is an illustration representative of most supply chains. Manufacturers produce goods and deliver to a distribution point. From there, there is a V-shape reaching out to several supply points which branch out further to the ultimate consumption points. The consolidation point could be a national staging hub, the supply points the regional warehouses and the consumption points the individual stores or local warehouses.
If we focus on the consumption points and map the demand for product over time, we might get something that looks like the diagram below.
The orange horizontal line associated with each consumption point represents the average demand from each consumption point. It would be challenging to address all of this variability in each one of the endpoints of this supply chain. If you have decided to hold inventory to the average consumption, then some days you’ll be sold out and will miss production or revenue, and on other days you’ll have too much.
But, what if we go down to the supply point, and have a look at how the demand from each of the consumption points is aggregated? You’ll notice that the demand over time is far less volatile and thus makes managing the inventory much easier. On a given day when a consumption point has a high demand, another consumption point is likely to have low demand, and the net effect is a far more steady flow of product. What counts, then, is the lead time it takes to go from the supply point to the consumption point: the shorter that lead time, the less inventory required at each of the consumption points. By the same reasoning, if there’s also a rapid replenishment time from the consolidation point to the supply point, the overall inventory held in the system is reduced. If production can quickly resupply the consolidation points, then all the better for the system as a whole.
The underlying principles of the Theory of Constraints (TOC) replenishment solution therefore demand that you keep inventory as deep down in the ‘V’ as you can, giving you the benefit that aggregation provides against local uncertainty. But, at the same time, you do everything possible to reduce the batch-sizing and hence delays in lead time caused by the ordering, production and transport processes.
It is very counterintuitive to hold inventory away from the consumption points. But, if you apply the principles of Constraint Accounting, you can come to understand the business benefits of doing so. You may incur some marginal additional costs associated with more frequent and smaller shipments, but what you gain in the reduction of inventory and improvement in due date performance will usually dwarf the downside.
To recap, the essentials of the TOC replenishment solution include:
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What’s next?
The change from standard thinking to Theory of Constraints (TOC) is both profound and exhilarating. To make it both fun and memorable, we use a business simulation we call The Right Stuff Workshop.
We’d love to run it with you. To learn more:

[Background image: Fulfilment at work, Shutterstock]
“May the power of aggregation be with you.”
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Healthcare professionals are central to the patient’s progress from awareness of a therapy to successful long-term use. They identify risk, interpret evidence, diagnose conditions, discuss options, perform procedures, provide training and monitor outcomes.
Yet many medical device development programs treat healthcare professionals primarily as users to be trained or customers to be persuaded.
HCP-Centered Design takes a wider view. It examines the work healthcare professionals must perform, the system in which they perform it and the constraints that limit their ability to move suitable patients through the care pathway.
“If patient flow depends on a healthcare professional, that professional’s available capacity may determine how many patients ultimately receive the therapy.”
A medical device patient journey commonly depends on several healthcare professionals:
Each professional governs a transition in the flow of patients.
If one transition lacks sufficient capacity, information or clarity, the whole pathway slows. More marketing, sales activity or production capacity will not compensate for a shortage of specialist time or a burdensome diagnostic process.
This is why HCP-Centered Design is not simply about making an interface easier to use. It is about enabling the system of care to perform.
A healthcare professional’s work depends on information and actions supplied by others. They may rely on referrals, patient histories, pathology, imaging, electronic records, clinical guidelines and the availability of equipment or trained colleagues.
After reaching a decision, they may need to explain it, document it, arrange authorization, coordinate treatment and prepare the next person in the pathway.
A technically strong solution can still create difficulty if it:
The relevant design question is not merely, “Can the HCP use this product?”
It is, “Does this solution improve the HCP’s ability to complete important clinical work within the conditions in which care is actually delivered?”
“HCP” is not one persona.
A general practitioner, specialist, interventional physician, nurse, technician and clinical administrator encounter different stages of the pathway. Each has different responsibilities, authority, expertise and exposure to risk.
Even within a profession, context matters. An experienced specialist in a major hospital may approach the same task differently from a professional who encounters the condition infrequently or works without immediate specialist support.
Useful HCP personas distinguish factors that influence work:
These personas clarify who performs each job and what support each person requires.
The HCP journey often begins before the visible clinical procedure.
It may include receiving a referral, gathering information, forming an initial view, ordering investigations, interpreting results, deciding whether the patient is eligible, discussing treatment, obtaining authorization, preparing for the procedure, delivering care and arranging follow-up.
At each stage, ask:
The resulting journey map should distinguish processing time from waiting time. A decision may require only minutes of specialist attention while patients wait weeks to access that attention.
This reveals the practical relationship between HCP capacity and patient flow.
The Theory of Constraints directs attention to the factor limiting the performance of the entire system.
In some pathways, the constraint may be the number of qualified interventional specialists. In others, it may be diagnostic capacity, physician confidence, authorization effort, operating room access or the time required to train patients.
The constraint may also be hidden inside the HCP’s working day.
A specialist supporting a therapy must still manage other clinical duties, administration, meetings, documentation and urgent cases. The question is not simply how many specialists exist. It is how much of their usable capacity is available for the activities upon which patient flow depends.
“The scarcest resource may not be the healthcare professional. It may be the few hours of focused capacity available for the critical work.”
Improvement away from this constraint can make performance worse. Sending more referrals to an already overloaded specialist increases the queue. Adding information may increase cognitive burden. Creating another approval may consume the capacity required to treat patients.
HCP-Centered Design seeks to protect and expand the capacity that governs flow.
Policies and procedures describe how clinical work should happen. Observation reveals how it actually happens.
Healthcare professionals routinely compensate for missing information, awkward interfaces and unreliable handovers. These workarounds may become so familiar that nobody reports them as problems.
Gemba research should examine:
The purpose is not to judge the healthcare professional. It is to understand the system surrounding the work.
“A workaround is often evidence that the system has failed to support the person doing the work.”
Healthcare professionals do not simply use devices. They use them to make progress in clinical work.
An HCP may need to identify risk, reach a confident diagnosis, select an intervention, perform a procedure safely, explain options, monitor progress or recognize deterioration.
A structured job map divides this work into eight stages:
This wider view prevents the product team from concentrating exclusively on the procedure.
The greatest value may come from reducing preparation, improving decision confidence, clarifying an exception, simplifying documentation or improving the handover to follow-up care.
Comments such as “the interface is difficult” or “we need better information” indicate dissatisfaction, but do not provide sufficient direction for design.
They should be translated into measurable outcome statements, such as:
“Minimize the time required to identify which clinical information is missing before making a treatment decision.”
Or:
“Reduce the likelihood that a clinically significant change goes unrecognized between scheduled reviews.”
A broader population of healthcare professionals can then assess the importance of each outcome and their satisfaction with their current ability to achieve it.
Highly important and poorly satisfied outcomes provide a rational basis for prioritizing innovation.
“Adoption follows when a solution makes important clinical work safer, clearer or easier to complete.”
The five-step FOCUS process creates a practical improvement cycle.
Find the constraint. Determine which HCP activity or resource currently limits patient flow.
Optimise for it. Protect the constraint from avoidable work, missing information, interruptions and rework.
Collaborate around it. Align upstream and downstream teams so patients, information and resources arrive when required.
Uplift it. Add capacity, redesign responsibilities, improve technology or remove restrictive policies.
Start Again. Identify the new constraint once flow improves.
This approach allows the organization to distinguish activity from value. It also turns HCP engagement into an ongoing management discipline.
HCP-Centered Design must connect clinical reality with patient needs, technology, regulation and business strategy.
A Value Management Office can help coordinate these perspectives across the product lifecycle. Its role is to ensure that projects, resources and stage-gate decisions remain connected to patient flow and business value.
The organization should be able to show:
The goal is not simply a device that healthcare professionals can operate. It is a solution they can confidently incorporate into care and a delivery system capable of getting that solution to more patients.
Use the HCP-Centered Design assessment to determine how well your organization understands clinical work, HCP capacity and the constraints governing patient flow.
The resulting evidence should guide product design, process improvement and investment toward better products, delivered faster, with more lives changed for good.
Medical device companies devote enormous skill and investment to developing safe, effective products. Yet a technically successful device changes no lives while suitable patients remain unable to reach it.
Between a patient becoming aware of a therapy and receiving its intended benefit lies a pathway of referrals, consultations, diagnostics, approvals, procedures, training and follow-up. Every step consumes time. Between the steps, patients wait. At some points, they become confused, discouraged, ineligible or lost to the process.
Patient Centered Design must therefore address more than the design of the device. It must improve the performance of the entire system through which patients reach, receive and live successfully with the solution.
“A life-changing therapy changes no lives while patients remain trapped in the pathway leading to it.”
A typical medical device journey may include:
Companies often manage these stages as separate functions. Marketing works on awareness. Medical affairs supports clinicians. Market access addresses reimbursement. Sales works with specialists. Clinical teams gather evidence. Training teams support adoption.
The patient, however, experiences one journey.
From the patient’s perspective, a delay between two organizational functions remains a delay. A repeated test remains repeated work. An unclear handover creates uncertainty regardless of which department owns it.
Patient Centered Design begins when the organization sees and manages this journey as a connected system.
Every step contains some necessary processing time. A consultation takes time. A diagnostic test takes time. An authorization must be assessed. A procedure must be performed.
The patient’s total lead time, however, also includes the waiting between these activities.
A consultation may take 30 minutes, but the patient could wait six weeks for it. A diagnostic test may take an hour, followed by another delay before a specialist reviews the result. Prior authorization may require little actual work while adding weeks to the pathway.
This distinction matters because organizations often improve processing time while leaving the larger queues untouched. Saving five minutes during an appointment produces little benefit if the patient waits months to reach it.
Patient Centered Design therefore asks:
The answers reveal the true performance of the patient system.
Theory of Constraints teaches that the performance of any system is limited by a constraint. Improving a part of the system that is not constraining flow may create more activity without increasing results.
If diagnostic capacity is the constraint, generating more awareness may simply produce a longer queue for diagnosis. If specialist capacity is the constraint, accelerating authorization may move patients more quickly into another wait. If training after first use is inadequate, increasing procedures may produce poor experiences and avoidable follow-up demand.
“More activity at a non-constraint creates work in process. More capability at the constraint improves the system.”
The constraint is not always a physical resource. It may be a policy, an eligibility rule, missing evidence, a fragmented handover, an information delay or the cognitive burden placed on the patient.
The most important question is therefore not, “How do we improve every step?”
It is, “What currently limits the flow of suitable patients to successful use of the therapy?”
Numbers show where patients are lost. Patient research helps explain why.
Two patients with the same diagnosis may respond very differently. One may actively seek new treatment options. Another may delay action until symptoms become severe. A third may want help but lack confidence in navigating the healthcare system.
Meaningful patient segmentation considers characteristics that influence behavior:
These differences affect whether patients enter the pathway, remain engaged and successfully adopt the solution.
The Gemba is the place where work actually happens. For patients, this includes the home, clinic, hospital and all the places where they manage their condition between formal encounters.
Interviews alone may miss important evidence. People normalize inconvenience, forget workarounds and simplify their past decisions. Observation allows the development team to see what patients actually do.
Good research combines three activities.
Observe. Watch how patients obtain information, prepare, use the solution and respond when something goes wrong.
Immerse. Understand the physical, emotional and practical conditions surrounding the experience.
Engage. Ask open questions that allow patients to describe their goals, fears and frustrations in their own language.
The purpose is to discover the patient’s reality before asking them to evaluate the organization’s preferred answer.
Patients rarely want a medical device for its own sake. They want the progress it may enable.
They may want to recognize deterioration earlier, preserve independence, reduce pain, avoid repeated visits, return to work or prevent a disease from controlling daily life.
A useful job map examines eight recurring stages:
This reveals opportunities beyond the immediate use of the device. The most valuable improvement may involve helping patients prepare, confirm readiness, recognize an exception or understand what happens next.
Stories create understanding, but investment decisions require structured evidence.
Patient observations and comments should be converted into outcome statements that identify:
For example:
“Minimize the time required to recognize that my condition has changed sufficiently to require clinical help.”
Patients can then assess the importance of each outcome and their satisfaction with their current ability to achieve it.
Highly important and poorly satisfied outcomes represent genuine opportunities. This prevents teams from prioritizing attractive features that do not materially improve the patient’s life or progress through the pathway.
“Innovation becomes valuable when it improves an outcome that matters and remains poorly served.”
The Patient Centered Design pathway can be improved through a repeating discipline:
Find the constraint. Identify what currently limits patient flow or successful use.
Optimise for it. Make the best possible use of existing constraint capacity.
Collaborate around it. Align functions and partners so their actions support the constraint.
Uplift it. Add capability, remove restrictive policies or redesign the pathway.
Start Again. Once the constraint moves, identify and address the next limiting factor.
This prevents improvement from becoming a collection of disconnected initiatives. It directs scarce resources toward the factor that most strongly governs the result.
Patient insight should influence more than early product design. It should shape clinical evidence, regulatory strategy, reimbursement, manufacturing, education, market development and post-market support.
The organization should be able to show:
The goal is not simply to place the patient at the center of a diagram. It is to organize the enterprise around delivering better products faster, so that more lives can be changed for good.
Use the Patient Centered Design assessment to determine how well your organization understands its patient journeys, priority outcomes and constraints to patient flow.
The result should be more than another collection of patient opinions. It should provide evidence that directs strategy, investment and execution toward the changes that matter most.
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