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Dodgy data dulls your senses and leads to poor decision-making. Why? The purpose of your information system is to help you do two things: make sense of what is happening in your environment and support effective decision-making.
[ Listen to audio version, read by David Hodes]
This is part 1 of the series. For more on this, see Part 2 | Part 3 | Part 4 | Part 5
Every transaction and every bit of data gathered from sensors gives a unique record, at any given moment, of the state of play of your enterprise. Sometimes what happens next is automated; sometimes it waits for a person to act, based on a process, a business rule, analysis or intuition.
For illustration, let’s look at a simple slice through an organisation, from CEO to the shop floor:
– The CEO presses an approval button for the establishment of a contract for the expansion project, and the workflow opens the floodgates to the raising of purchase orders.
– Engineering produces bills of material from the computer model of the project and collates them according to when they are due, how long their delivery will take, and then further batch them by vendor.
– Supply , under the umbrella of the contract, takes care of procurement for all the products and services the engineering project team has itemised. Finance keeps score of how much has been spent against what has been budgeted and approved.
– An RFID tag scans across a reader and inventory is recorded as received into a warehouse. The finance system raises an asset on the balance sheet and a matching liability against a vendor.
– The contractor engaged in helping out in the warehouse swipes in and immediately starts counting up the dollars earned for hours worked.
– The project coordinator requisitions a part from the warehouse as the schedule indicates it’s going to be needed the following day.
– The fitter calls over the rigger assigned by the system, and both of them go to fit the item according to the drawings they have from the engineering model. Once done, they scan the barcode on the item which updates the model, along with the finance, maintenance and work management systems.
– Operations turns some dials and flick some switches to start the process, and monitor an array of simulated dials displayed on a monitor.
– A temperature sensor detects that the safe set-point has been exceeded and a signal goes to open a valve to relieve pressure until the system can once again operate within limits.
– The system doesn’t return to a safe operating level and at the same time as the operator shuts it down, a manager tasks a planner with expediting delivery of a spare, as well as assembling an emergency crew to get it fitted.
– All the while, a sensor monitors the production volume and sends the results to the reporting system. Everyone knows the CEO has a particular interest in those production numbers, using them to determine whether or not the business is going to meet its goal.
Now, that’s a pretty simple scenario outlined above. It’s just a thin slice through a hypothetical day in a typical industrial environment. But what’s going on there besides my assertion in the first paragraph? Isn’t it all about sense-making and decision-making?
When all those systems were designed, built, tested and deployed, there was likely at least a business analyst, a developer and a business owner, amongst others, scoping out requirements based on business needs. Someone from the team would have been in charge of the data, determining what fields went in which tables. They’d be thinking about how the master data would be used with the transaction data to make sense of the processes the information system was managing. In the team’s scope were, for example, the process flows, the business rules, security settings, permissions as to who could create, read, update and delete records. You get the picture.
The system goes live, and a catalogue of errors cascades through the organisation:
– The wrong account is attached to the CEO’s press of the button, and all the resulting financial data goes walkabout.
– The engineers were in a rush to get the bills of material out and thought it unimportant to complete the delivery fields diligently, with the result that everything had a lead time of a week.
– The supply team was so busy negotiating the master contracts and raising purchase orders with their vendors that, even though they spotted the error on the lead times, they did what was expedient: increase them universally by a week.
– The materials managers were given a spreadsheet by one of the vendors which had the wrong mapping of the RFID fields. How were they to know they were capturing a code for a pump when the description was for a motor?
– The warehouse contractor swipes in, but the learning management system has him registered as a coded welder. For every hour he works, the system books it out at the stored rate for a coded welder, which is twice the dollars than should be the case. And although the guy works at the top of the warehouse racking, 10m above ground, the system fails to note that his ‘work from heights’ certification needs renewal.
– The schedule has not been updated in a week and the part requisitioned by the coordinator actually should have been there two days prior. An expeditor is sent to the stores to get back in time to be done during the day shift.
– The fitter and rigger wait in the crib until they’re notified that the part has been delivered to the work location. When they get there, they can’t quite believe that a pump has been provided instead of a motor.
– Finally, the right piece of equipment is fitted, and the ramp-up sequence can start. But, the commissioning team used the wrong specs to calibrate the IoT sensors and thus the system had to be shut down, despite them learning later that the instrumentation was giving a false negative.
– The false-negative doesn’t prevent the manager from tasking the planner with expediting the delivery of a spare and assembling an emergency crew to get it fitted. They don’t find out about the perfectly good, but supposedly faulty piece of equipment until it’s too late.
The CEO, meantime, sitting way above this comedy of errors, cannot have any real sense of what is going on in his business. Therefore any decision they makes would be as effective as the throw of a die would be to answering a multiple-choice exam question.
Processes and data seem to have a particular propensity for decay—it’s as if the gods maliciously choose to configure their quotient of entropy such that they cause the most harm.
There are two remedies for the problem.
The first involves leadership around the reason why it is essential to maintain true data. When you consider the enormous amount of effort people spend doing their work, wouldn’t it be the sensible thing to do to ensure that as little of that effort as possible is wasted on correcting the effects of bad data? Can you as a leader clearly articulate the opportunity cost of the wasted time not only on business outcomes, bit also on engagement, motivation and a sense of accomplishment?
The second, which can only be achieved once the first is done, is to commit to such a high level of operating discipline that these effects of false data become increasingly rare and less consequential.
In one of Eli Goldratt’s lesser—read books, The Haystack Syndrome, the fascinating introductory chapter talks about the difference between information and data. Specifically, how to find the needle of information in the haystack of data. Since its publication in 1990, the book’s subtitle, ‘sifting information out of the ocean of data’ has, besides mixing metaphors, become even more relevant in our age of big data and machine learning.
‘Information,’ wrote Goldratt, ‘is the answer to the question asked of the data.’ You have to ask good questions. Crucially, too, the data has to be reliable. From an operational perspective, I’ve found one need only ask about six measures :
• How much throughput is the system generating?
• What operating expense are we consuming to generate that throughput?
• What investment have we made in generating the profit arising from the difference between the throughput and the operating expense?
• How long is what the system’s doing going to take—that is, what’s the lead time or turn-around time?
• How reliable is system performance—that is, what is delivery to promise?
• What quality does the system produce—that is, how much product or service is either rejected or reworked?
Maintaining true data means having a reliable system of record that can provide timely answers to these questions. After all, the purpose of information is to assist in sensemaking within and across the enterprise. Having a reliable system of record ensures that we use the best possible sensemaking information to support effective decision-making.
Understanding and insight come from knowledge. We build knowledge from information. Information is the answer to the question you ask of the data.
If you want better understanding and insight, maintain true data.
This article is part of our series: Five commandments for high-performance execution
Part 1: Maintain True Data
Part 2: Work Fully Kitted
Part 3: Control Work Release
Part 4: Resolve Issues Rapidly
Part 5: Act by Priority
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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: Playing cards on table, Jack Hamilton 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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