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All improvement is change, but not all change is an improvement. We can optimise sales, or marketing, or manufacturing, or supply chain, or HR, or IT. Indeed, you can optimise any subsystem of your organisation. But how will it affect your business outcome?
[ Listen to audio version, read by David Hodes]
This is Part 4 of our series on The 5-Step FOCUS: Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6 | Part 7
To optimise the system constraint we have to take a step down from the lofty heights of theory and operating philosophy and engage with the suite of the three pragmatic methodologies Goldratt invented, covering the requirements of projects, production and supply chain replenishment. These three approaches are sometimes called the “proven solutions” as there is an abundance of evidence that they deliver results which would otherwise seem unreasonable and impossible. The three are Critical Chain Project Management (CCPM), Drum-Buffer-Rope (DBR) production management and Dynamic Buffer Management (DBM) for the supply chain replenishment solution.
“When you focus on the constraint,
you can improve the system as a whole”
The full power of CCPM as an optimisation engine becomes apparent when you have to solve the complexity of running multiple projects off a single resource pool. We typically find these types of environment in, amongst others, product development businesses, consultancies, engineering functions and businesses and software developers and integrators. But, before going into optimisation for the portfolio, we should have a quick think about the individual project.
What prevents a project from being completed in no time and at no cost? Sound like an absurd question? Not if you’re looking for the constraint. What constitutes the time dimension? It would have to be the duration of the longest sequence of tasks that cover all the required scope, from initiation to completion. This longest sequence is the idea behind the concept of the critical path. And, what of the zero-cost part? Unless your project has free labour and materials, you’re unlikely to get away with zero cost. So, to come as close as you can to the ultimately optimised project, you have to consider what the tasks are, what sequence they’re in, who’s going to do them and what materials they’re going to use.
Suppose you make the simplifying assumption that there are no spatial or access constraints to any given work front and that there is no uncertainty associated with the known timing of any of the tasks. In that case, you can derive a deterministic lead time and expected completion date for your project. But, life’s not like that, is it? Who has an infinite number of resources and doesn’t have to deal with contention between them? And whether it’s a physical production space or access to a unit of software code, it’s infrequent that queues don’t form behind an active packet of work.
“Who has an infinite number of resources and
doesn’t have to deal with contention between them?”
CCPM does the job of optimisation by considering the longest sequence of tasks after levelling the load across all tasks, given the number of resources you make available to the project. The CCPM method also addresses the issue of task uncertainty by reducing the duration of each task, followed by aggregating and storing their individually held contingency in carefully placed buffers. At the end of the planning process, we have an optimised schedule, which explicitly takes into account both resource availability and task uncertainty.
But, planning is for getting you into things – you have to get yourself out. We cannot say that we have genuinely optimised a project until the method used for execution is itself optimal. In execution, the CCPM method calls for the measurement of progress along the critical chain relative to the amount of buffer, that is, the aggregate contingency consumed. Monitoring this critical ratio provides project managers with the wherewithal to focus their efforts on those few or even single task which needs management attention and prioritisation of resource allocation.
In the multi-project environment, we once again predicate optimisation on finding the constraint. Imagine we have prepared a portfolio of projects using the CCPM method for single projects. We then stack them up, one above the other, all starting on the same day. We measure in daily vertical slices what the load is by specific resource type and compare that to the capacity we have available.
On each day, there will be one resource type whose ratio of load to capacity is higher than any other. The load will be less than the available capacity for some of those resource types, whereas, for others, the opposite will be true. In simple terms, based on what your budget allows, given a relevant time horizon, one resource type will be more loaded than any other.
To optimise, we then have a choice. We can either accept our resource constraints and extend the overall duration of the portfolio by shuffling the pipeline of projects sufficiently to the future to eliminate the resource constraints. Or, we can add additional resources until we eliminate the given bottleneck and discover what the next one is, as it emerges from our calculations.
Once we have optimised the pipeline in the planning phase, we once again use the signalling system as per the case of the single project outlined above. Depending on the value of the critical ratio, that is chain completed versus buffer consumed, we can plot all of our projects on a single control chart to visualise which project most urgently requires focus.
Since it is axiomatic that constraints govern the rate of portfolio completion, it is also the case then that non-constraints have capacity available. We therefore achieve optimisation when unconstrained resources subordinate to the needs of the constraint. But, that’s a topic for our next article on the third focusing step – Collaborate around the proposition that the constraint is the rate-determining step in the creation of value.
“Planning is for getting you into things—
you have to get yourself out”
We achieve optimisation in the production domain through the application of the Drum Buffer Rope (DBR) scheduling system. As the name infers, the drum, also known as the critically constrained resource (CCR) beats the rhythm of the production system and is akin to the concept of takt time in lean. In the perfect world, the rate of production at the drum exactly equals the rate of sales, with single-piece flow and no batching. The buffer is a store of inventory just upstream of the drum, placed to prevent any shocks to material flows from common cause variation. The rope is how we send a signal for the release of materials such that those materials arrive at the drum just in time for their scheduled operation at the CCR.
The DBR method is the TOC way to accomplish what operations people call finite scheduling. It’s difficult to imagine arriving at an optimum schedule without taking on the significant challenge of finite scheduling. As with CCPM, the first order of business is to level the load – what lean practitioners call heijunka. Typically you take all of your confirmed production orders for the next week or fortnight, depending on your scheduling horizon, and calculate the demand on each resource type.
For example, if you have production orders for several different models of widget, each of which takes varying amounts of time on lathes, grinders and welding, you would calculate the total time by work centre and find which one is the most constrained. That work centre then becomes the drum. The drum schedule is the very detailed, hour by hour schedule that allocates work to the drum such that the production system delivers the optimum outcome in terms of on-time performance.
In managing execution, we use buffer management to determine where we need to focus such that we have a very reliable drum schedule. In brief, to run buffer management, we split the time from material release to the allocated time for commencement of drum production into three, creating a green, orange and red zone. As the date with production draws closer, the planned work moves from the green to the orange and finally to the red zone.
“It’s difficult to imagine arriving at an optimum schedule without taking on the significant challenge of finite scheduling”
Once the planned work is in the red zone, you would hope that you would have met all conditions necessary and sufficient for production to start. These conditions might include materials, tooling, drawings, standard operating procedures, safety measures and the like. Buffer management allows you to make visible, ahead of time, any missing production requirements and to focus management attention on expediting their supply.
An additional component of the DBR system for optimisation is how we build continuous improvement into the system. If, for example, a particular production batch misses its scheduled slot, you can record the reason. After a while, you’ll have a statistically significant sample of reasons for non-adherence to schedule. We can arrange these reasons into a Pareto chart, and improvement efforts would then naturally focus on the most common cause for slippage.
The optimised supply chain is capable of squaring the circle of minimising investment in inventory while at the same time maximising customer service. These two goals appear to be at odds with each other unless you understand the principles of what drives the amount of inventory you must carry to achieve a given level of due date performance.
The TOC replenishment solution provides remarkable results, but as ever, it is counter-intuitive. Ask most people, and they will argue that we must keep as much inventory as close to the customer as possible. This strategy would, however, send us broke. Imagine a shoe shop having to stock every style, colour and size of shoe just in case someone walks in to buy a pair?
“The mathematics of the central limit theorem
comes to our rescue”
What factors then make for the optimum mix? It turns out that the amount of inventory we have to carry is a function of how long it takes to generate an order, how long to complete production, how long to ship and what the forecast demand is for the product. Further considerations include an understanding of the variability fo each of those metrics and the crucial concept of the tolerance of the customer for delay in instant gratification.
The variability part of the equation is quite discombobulating if we are to make accurate predictions for one product at a time. However, the closer we get to statistically meaningful sample size, the more the mathematics of the central limit theorem comes to our rescue. Simply put, the larger the sample size, the more predictable the aggregated result.
So, where is the place of highest aggregation? Think of a distribution system as a V, with the point of supply at the bottom and the consumption points at the top. The deeper you go down the V, the more aggregation there is. Thus, counter-intuitively, if you hold most of your inventory at the bottom of the V, you will be better prepared to address the volatility at the top. But, only if you place a great deal of emphasis on the velocity of your product from the bottom to the top.
The key to this optimisation idea is to reduce batching to an absolute minimum: purchase order batching, production order batching, and shipping order batching. And understand your customer. If I wear a size 13 shoe, I’m a lot more likely to be willing to wait for exactly the style I want than someone whose feet are right in the middle of the bell curve.
There is much to be said about how the three proven solutions from TOC, CCPM, DBR and DBM can help optimise your business. They have proven capable when competently applied, to time and again deliver not only outstanding results but also the means to have those results continuously improve.
This is Part 4 of our series on The 5-Step FOCUS.
Part 1: Identifying the System
Part 2: Setting the Goal
Part 3: Find the Constraint
Part 4: Optimise the Constraint
Part 5 : Collaborate Around the Constraint
Part 6 : Uplift System Performance
Part 7 : Start Again
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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: Mountain climbers, Charlie Hammond on Unsplash]
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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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