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Reason to think

David Hodes

How structured is your thinking? No less a figure than W Edwards Deming made the theory of knowledge one of four pillars in his System of Profound Knowledge. And yet, in my experience, very little structured thinking goes on in our modern workplaces.

[Listen to audio version, read by David Hodes]

This is Part 1 of our series on the Logical Thinking Process: Part 1 | Part 2 | Part 3 | Part 4 | Part 5

Without a doubt, there is an enormous and ever-increasing amount of analytics performed in our digitising business environments. But how do we come to know what questions to ask of our immense sets of data? And, even if we knew all the powerful questions, not all knowledge is reducible to bits and bytes. For that knowledge which we cannot contain in a computer program, how do we construct our arguments, test them for logical coherence and then communicate the results?

Having a means of thinking in a logical and structured way is not to say that all decisions can be made based on reason alone. Difficult choices often don’t lend themselves to binary answers derived from cause and effect logic. We cannot possibly know everything about a given situation. Additionally, we all have our prejudices, often based on an emotional response to a given situation. Further, it is not always clear that parties to an argument share the same goal. Therefore, what appears to me to be sound reasoning may be intolerable to you.

Advocating for change

Notwithstanding these caveats, neglecting to develop a substantial capability in critical thinking seems to me to be one of the root causes of the difficulty we all encounter when advocating for change. Imagine for a moment that you or one of your team was well versed in the available means of persuasion. How much more could you accomplish? How many more rounds of innovation could you achieve while your competitors get lost in incoherent argument? How much more glide and how reduced the friction if you take the science and art of critical thinking seriously?

The Logical Thinking Process from the Theory of Constraints (TOC) provides a logically structured means of developing rhetorical muscle. It endeavours to do for TOC what Hoshin planning does for the Toyota Production System (Lean). The logic trees from the Thinking Process were designed initially to comprehensively answer the three critical questions of any change initiative: What to change? What to change to? How to change? There is a suite of five logic trees used to examine each of those questions: the goal tree, current reality tree, evaporating cloud, future reality tree and transition tree. But, before diving into the use of the trees, we would be better served by first studying Goldratt’s rules of rhetoric, which he calls The Categories of Legitimate Reservation, but which I prefer to simplify and call ‘logic checks’.

“Is what’s being said true, and what data
backs up the truth of its existence?”

Goldratt’s rhetorical test kit provides six logic checks: clarity, causality existence, additional cause, concurrent cause, missing intermediate effect and predicted effect. Getting to know these checks well is a little like learning a new language, but it can pay big dividends once mastered. With practice, you can start to pick out the logic flaws in your colleagues’ arguments as they speak. When constructing an argument of your own, you can ensure you have covered all that is necessary and sufficient to make it watertight. Let’s take each in their turn, with an example.

Clarity. Are the logical statements about reality clear in what they are saying? Can anyone involved in the system understand and readily share what is being said?

Example: ‘Johnny is upset because of sales’. We don’t know if Johnny is upset because sales are up and he has no more inventory, market prices are down, along with profits, and he thus won’t get his bonus, or logistics has screwed up and failed to get the product to the customer on time and in full, meaning the revenue can’t be brought to book.

Entity existence. Is what’s being said true, and what data backs up the truth of its existence?

Example: ‘The pump is broken’. If we incorrectly connected the wiring for the motor that drives the pump, it might be that the pump is in good working order, but it is unable to perform its function of circulating fluids because of the faulty wiring of the motor.

Causality existence. When connecting a chain of cause and effect, what are the assumptions underpinning the linkage? Can these assumptions be altered without the logic breaking down?

Example: ‘The project failed because we were over budget and behind schedule’. Being over budget and behind schedule were the effects of poor project management and not the actual cause of project failure. Improve project management and the cost and schedule outcomes will improve.

Additional cause. Is there another entity, which on its own would have the same effect and which, when combined with other causes, may have an amplifying effect. Alternatively, if we remove the original cause, the additional cause will still play its part in keeping the undesirable effect in place.

Example: ‘I can’t believe I failed to qualify as a coded welder when I got such a good grade for the exam’. To qualify, there were two necessary conditions: complete a supervised workplace assessment and pass the exam. A failure to satisfactorily do either, even when the other is done exceptionally well, results in an inability to qualify.

Concurrent cause. Is there a cause that needs to combine with another before it’s sufficient to create the observed effect?

Example: ‘We wouldn’t have been so late if the supervisor had given us a better estimate of how long his tasks would take’. To get a better estimate, you would need input from the supervisor, the specialist and the tradie performing the work. Leave out any of the three of them, and it becomes more likely that estimates miss their mark.

Missing intermediate cause. The proverbial ‘long arrow’ statement in which the distance between cause and effect is so great that one can intuit a connection, but to provide clarity, must be articulated as a full chain of cause and effect.

Example: ‘We failed to deliver on time and budget because we had a poor plan’. What had to happen after we developed the plan for us to succeed in achieving our goal? For example, how was the plan communicated? How was that communication connected to the organisational goal? What measures were put in place to help everyone know how they were travelling relative to the goal? How did we go about making any needed course corrections?

Predicted effect. This check is the tool of the diagnostician, who says if we deem the cause to be something in particular, then it could have multiple effects. The absence of any predicted effect eliminates the possibility of the hypothesised cause.

Example: ‘Because of the tight control we had on our contract labour, production costs for the month ran at a record low’. For the claim to be valid, we would predict that the variable costs of material inputs and all other operating expense beside contract labour remained the same.

I have found that one of the most significant benefits of using a structured approach to critical thinking is how it creates a possibility to avoid either ad hominem attacks or a singular claim for all the credit. It demands that the person who develops the logic has a degree of empathy for the subjects who are part of the analysis and understands the difference between blame, credit and cause. Having a grammar for the application of logic allows the team to share a safe way of examining assumptions and exploring, through dialogue, better ways to do better work.

Given these essential building blocks for the development of compelling logical argument, how can they be used? In my next article, I will start with some tips on how to develop the Goal Tree.
____________________________

This is Part 1 of our series on the Logical Thinking Process.

Part 1: Intro to the Logical Thinking Process
Part 2: Setting your goal
Part 3: Mapping your current reality
Part 4: Deciding with the evaporating cloud
Part 5: Realising the future
____________________________

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:

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  • MedTech

Validating medical device concepts before major investment

David Hodes

Concept validation

A concept can look convincing in a presentation and still make an important task harder. A patient may misunderstand an indicator. A clinician may need information the design does not provide. A promising workflow may depend on support unavailable in the intended setting.

These problems become more expensive when the organization discovers them after committing to architecture, tooling or a launch plan.

We must ask how effectively concepts are validated before significant resources are committed. Patient Centered Design treats this as a learning discipline: turn ideas into testable solutions rapidly using low fidelity prototyping, put them in front of relevant users and gather evidence about whether they improve the outcomes that matter.

“A convincing presentation shows what the team hopes will happen. A useful test reveals what people actually do.”

Begin with a question that can change the decision

A prototype without a learning objective can generate interesting comments while leaving the key decision unresolved. Start by identifying what must be true for the concept to succeed.

Does the patient intuitively understand the required action without explanation? Can the professional recognize when the result is ready to use? Does the proposed approach fit the work surrounding the task? Will people take meaningful steps toward adoption?

State the assumption and the evidence needed to assess it. Agree what would support proceeding, what would require revision and what could make the concept unviable. Gather quantitative data along with qualitative verbal feedback.

Prioritize questions with substantial consequences for the investment. An attractive enclosure deserves less attention than an unresolved issue that could prevent safe or practical use of the whole solution.

Choose the simplest useful representation

A picture is worth a thousand words. A simple user experience prototype is worth a thousand pictures. Choose artifacts that maximize learning with the least effort. The appropriate artifact depends on what the team needs to discover.

A sketch may help users explain how they interpret a proposed interaction. A physical mock-up may expose handling difficulties. A simulated interface can support a sequence of tasks. A more complete prototype may be necessary to examine timing, feedback or combined interactions.

Build enough realism to test the assumption accurately. Excessive detail can consume resources without improving the evidence, while insufficient fidelity can conceal the issue being investigated.

Make limitations clear to participants and observers. A manually simulated function may help test an experience, but it does not establish that the technology can deliver that function reliably.

Recruit people who represent the intended use

Patients and healthcare professionals can differ in experience, confidence, physical ability, responsibilities, and access to support. Those differences influence whether the concept helps them complete the job.

Define the participants and contexts relevant to the test. Include people whose circumstances could expose difficulties the development team has overlooked.

A familiar expert may work around a confusing interface that challenges a new user. A clinician from a highly supported center may assume resources unavailable elsewhere. Research needs to reveal these dependencies.

Match the study to its purpose. Exploratory sessions can identify problems and guide iteration. They do not automatically establish population-wide performance or replace the evidence required for later design validation.

Create an Experience Café around real tasks

An Experience Café gives participants a structured opportunity to encounter concepts and talk about their experience. Its value comes from the quality of the scenario, observation and follow-up questions.

Set up situations that reflect what the person is trying to accomplish. Let participants interact with the artifact rather than rely solely on a demonstration by its designer. Build rough and rapid.

Assign roles to facilitators and observers. Agree how comments, actions and difficulties will be captured. Keep the session focused on learning rather than defending the proposed solution. Hold a conversation around the prototype. “Can you show me how you would use this?” “Tell me what you are thinking here.”

Ask participants to explain what they believe is happening and what they would do next. Observe where the concept supports that understanding and where they hesitate, improvise or seek help.

Listen without teaching away the problem

A facilitator can unintentionally make a weak concept appear successful by explaining each step or supplying missing information.

Use neutral prompts and allow participants to reveal their interpretation. When assistance is necessary, record it along with the point at which the person became stuck.

Follow observations with questions about purpose and reasoning. What did the participant expect? Which information did they look for? Why did they choose that action?

Separate a preference from evidence about task performance. “I like this one” may reflect appearance or familiarity. Successful completion, appropriate interpretation and manageable effort provide a stronger basis for assessing whether the concept addresses the need.

“Every explanation the facilitator must supply is a question about what the design expects the user to know.”

Examine the complete experience

The product interaction belongs within a wider job. Test preparation, readiness, execution, monitoring and what follows, wherever these activities affect the concept’s value.

A device may work well once configured while setup introduces avoidable complexity. A result may be easy to view while the professional still needs to transfer it manually before acting.

Include relevant dependencies on caregivers, staff, information and other systems. Investigate whether the concept reduces burden for one participant by increasing it for another.

Use realistic scenarios appropriate to the development stage. Important exceptions and recovery steps deserve attention alongside routine success. An incomplete or interrupted task can reveal weaknesses that a carefully guided demonstration leaves hidden.

Make cognitive burden visible

Ease of use involves what a person must notice, understand, remember, decide and physically do. A tidy interface can still demand substantial mental effort.

Human performance depends on limited attention, working memory and feedback. Examine how the concept supports those processes during a task.

Does it make the relevant information perceptible? Can the user understand its meaning? Is the next action clear? Can they recognize whether that action succeeded?

Look for unnecessary steps, demands to remember information across screens and alerts that interrupt without helping a decision. The best change may simplify a sequence or improve feedback rather than add another feature. Confirm its effect through observation and appropriate measures.

Measure effort alongside task success

Choose measures that reflect the priority outcome and the study’s purpose. These may include completion time, errors, requests for help, repeated actions or failure to notice important information.

Subjective workload measures can complement observed performance. NASA Task Load Index can help structure participants’ assessment of workload, while PURE provides an expert assessment of the effort required to complete tasks. Satisfaction ratings on a Likert scale can be used to compare concepts directly with each other and a baseline solution.

Do not treat one measure as a complete account of usability. Faster completion may accompany misunderstanding. A participant may complete the task correctly while reporting effort that makes repeated use impractical.

Interpret results together and examine the conditions under which they occurred. Record the limitations so decision makers understand what the test has established.

Test demand separately from technical feasibility

Pretotyping examines whether people take meaningful action toward using or adopting an idea before the full solution exists. It addresses a different question from whether a working product can be engineered.

A clearly described concept, service simulation or expression-of-interest process may provide evidence about engagement. The strength of that evidence depends on the action required and the conditions surrounding it.

A click demonstrates less commitment than a substantive implementation conversation. Neither establishes clinical efficacy or successful device use.

For medical concepts, keep representations accurate and make the test status clear. Interpret behavioral evidence alongside clinical appropriateness, access requirements and the responsibilities of the people making adoption decisions. Interest alone cannot establish that the solution should proceed unchanged, particularly when workflows in the clinical setting are involved.

Refine the value proposition with evidence

A value proposition explains which customer the concept serves, the job it supports and the difficulties it intends to reduce. It should connect directly with the outcomes identified through research.

Compare that proposition with the evidence from concept tests. Did participants experience the intended benefit? Did another difficulty become more important? Did the concept require assumptions that the intended setting cannot support? Did the concept do something better than a competitor’s current solution?

Capture both positive and negative findings. Use them to revise the concept, the proposition or the team’s understanding of the need.

Then test the important changes. Iteration should answer a question left open by the previous round. Repeating sessions without changing the artifact or research objective can accumulate comments while leaving uncertainty untouched.

Keep early findings within their proper limits

Early concept validation supports decisions about direction and investment. It does not establish all the evidence needed for a finished medical device.

Technical performance, reliability, clinical benefit and intended-use safety require appropriate subsequent work. A convincing simulated experience may depend on functions the team has not yet demonstrated.

Make these boundaries visible in the decision record. State who participated, what was tested, the conditions, findings and unresolved issues. Explain how those findings affect the next commitment.

Overall, having a “winning concept” in hand, backed by user Experience Café data along with user needs in the form of outcome statements formally structured with a direction of improvement and unit of measure, sets a development team up for success. The outcome statement user needs provide a solid foundation for the design history file.

Rapid prototype experience testing gives the team answers to key decisions and sets a target to pursue early on. This results in faster development cycles, more robust regulatory submissions, and better returns on investment spending.

A Value Management Office can connect this learning with resources and stage decisions. Testing should help the organization commit at a pace justified by evidence and concentrate effort on the uncertainties that govern progress.

“Early validation creates value when it changes the concept or the commitment before an unresolved assumption becomes expensive.”


What comes next

Examine one proposed investment. Which assumption could defeat the concept, and what is the least costly credible way to test it?

Prepare an appropriate artifact, involve representative users and observe meaningful tasks. Review the evidence, revise the concept and record the next learning decision. This gives Patient Centered Design a practical route toward solutions people can successfully use and organizations can responsibly develop.

READ MORE

  • MedTech

Developing medical device concepts around patient needs

David Hodes

A development team can become committed to a concept before it has seriously considered an alternative. The idea is familiar, a senior sponsor favors it or an available technology makes it attractive. Detailed engineering begins while the reason for choosing that approach remains largely untested.

Concept engineering provides a more disciplined basis for commitment. It develops several viable approaches, compares them against important needs and combines their strongest elements where doing so improves the solution.

Within Patient Centered Design, the purpose is to identify a concept that can help patients and healthcare professionals accomplish their jobs successfully. Question 2.1.1 examines the effectiveness of that work.

“A winning concept earns its place by addressing important needs and surviving comparison with credible alternatives.”

Start with a problem the team agrees on

Concept work begins with a concise problem statement and an agreed objective. Both should describe the progress the intended users need, rather than assume the answer.

An illustrative problem might concern a clinician’s difficulty identifying whether the information needed for a treatment decision is complete. “Build a new dashboard” commits to one response before exploring the problem.

Clarify the users, operating context and desired outcome. Review the patient journey and the clinical work surrounding the interaction. Establish which unmet needs the concept must address.

Resolve major differences in interpretation before the selection exercise. A mechanical engineer, clinician and commercial leader can otherwise compare ideas while quietly applying different definitions of success. Shared language makes their conversation more useful.

Bring priority needs into the criteria

Concept selection needs criteria grounded in research and requirements. Include the outcomes patients and professionals consider important, particularly those existing approaches satisfy poorly.

Then identify necessary capabilities and constraints. Relevant considerations may include safety, reliability, usability, manufacturing, service requirements, implementation and the resources available to develop the solution.

Separate mandatory conditions from characteristics that permit tradeoffs. A concept that cannot satisfy a necessary safety condition needs resolution or rejection; attractive performance elsewhere cannot compensate for that failure.

Define the criteria clearly enough for consistent comparison. “Easy to use” leaves the team guessing. The number of required actions, time to complete an activity or ability to recognize readiness can provide more concrete grounds for conversation, depending on the need.

Generate options before narrowing the field

Concept engineering encourages broad idea generation, with constraints applied more deliberately during selection. This gives the team room to consider alternatives before familiar solutions dominate.

Use sketches and short descriptions to make ideas visible. Invite different functions to contribute approaches, concerns and connections the team might otherwise miss.

The concepts should represent meaningful alternatives. Several versions of the same preferred design may leave the underlying assumptions untouched.

Explore how the required function could be achieved differently. Could information arrive earlier? Could preparation become simpler? Could a service change remove work the proposed product was intended to automate?

Make concepts understandable enough to compare

A concept should communicate its operating principle, important interactions and dependencies. A simple drawing can expose differences that remain hidden in a verbal description.

Explain what the patient or professional would do, what the system would provide and what supporting resources would be required. Include the activities before and after the visible product interaction.

Build enough detail to support the decision at hand. Early concept selection does not require complete engineering specifications, but an appealing image alone gives little basis for comparison.

Record what is known and what is assumed. If one idea appears stronger because its description omits difficult tasks, the matrix will reward an incomplete account of the solution. Consistent descriptions support a fairer evaluation.

Use a simple comparison matrix

The Pugh matrix provides a structured way to compare concepts. List the criteria as rows and the candidate concepts as columns. Choose a reference concept, known as the datum, against which alternatives will be assessed.

For each criterion, judge whether a concept is better than, similar to or worse than the datum. The simple notation is positive, same or negative.

Discuss the basis for each rating. Record supporting evidence and unresolved questions. The matrix makes differences visible and gives the team a shared place to examine them.

Totals can help identify promising candidates, but they should not make the decision automatically. The significance of a weakness depends on the criterion involved. Several small advantages may leave a concept unable to address its most important requirement.

“The matrix is useful when it exposes the reasoning behind a choice and the evidence still needed to defend it.”

Match the method to the available evidence

Early conversations often rely on incomplete information. Simple comparisons can be more useful than elaborate scores that suggest a level of precision the team does not possess.

Weighted methods may help when criteria genuinely differ in importance. Paired comparisons can support more structured judgments about relative priority. When measured engineering performance is available, use those data directly in the evaluation.

Choose the method for the decision and evidence, rather than adding complexity by default. Explain how weights or ratings were established and which assumptions could change the result.

Check whether the leading concept remains attractive under reasonable changes to uncertain judgments. A decision that reverses after a minor rating adjustment deserves closer examination before the organization makes a substantial commitment.

Look for stronger combinations

Hybridization is a central part of concept engineering. A concept with several strengths may also have a weakness another option handles well.

Examine whether the useful elements can be combined into a stronger approach. For an illustrative monitoring solution, one concept may support straightforward preparation while another provides clearer feedback when a connection fails.

A hybrid might preserve both benefits, but it needs its own evaluation. Combining features can introduce new interfaces, added complexity or conflicting operating requirements.

Redraw the combined concept and reassess it against the criteria. Investigate whether it actually removes the weakness or merely moves the burden elsewhere. The aim is a coherent design whose interactions work together, rather than an accumulation of everyone’s favorite features.

Manage disagreement as a source of learning

Concept selection brings technical judgment, professional experience and organizational interests into the same conversation. The quality of that conversation affects the outcome.

Agree on meeting ground rules and use a team with relevant expertise across functions. Ensure that a strong personality or senior title does not become a substitute for evidence.

When disagreement cannot be resolved, capture the question and define an action. Assign an owner, the evidence required and a completion date. An independent facilitator can help when team dynamics obstruct useful comparison.

The method can make judgments more transparent, but it does not eliminate subjectivity. Leaders should expect the team to explain its reasoning and show how important uncertainties will be resolved.

Test the assumptions that could defeat the concept

The leading idea may depend on uncertain technical performance, user behavior, supplier capability or implementation conditions that significantly affect time to market. Identify those dependencies before detailed development absorbs significant resources.

Plan focused experiments, research or prototypes to address them. Match each activity to a question that could change the selection decision.

If a concept depends on clinicians adopting a new preparation routine, a technical bench test will not establish that assumption. If it depends on a material performing under particular conditions, user enthusiasm will not resolve the engineering question.

Prioritize uncertainties with serious consequences for the concept’s viability. Early learning should help the team avoid expensive redesign while preserving options until the relevant evidence is available.

Select a direction with a clear explanation

At this point in the design process, using patient and healthcare professional journey mapping satisfies the Empathy stage of Design Thinking. Understanding the jobs to be done and desired outcomes satisfies the Define stage of Design Thinking. Concept engineering at its core is a practice that ensures the best solution direction is chosen before significant expense is incurred and satisfies the Ideate stage of Design Thinking.

With a selection of “winning concepts” in your pocket, complete the Design Thinking stages by rapidly prototyping and testing solutions with customers to gather data on which concepts your customers desire most. The Design Thinking stages provide an explanation of why a solution is preferred and a record of why alternatives were not chosen.

Retain the criteria, important comparisons, hybridization decisions and unresolved risks. This record helps future teams understand the consequences of a proposed change.

Selection establishes a direction for further learning and development. It does not prove that the solution meets user needs or performs safely in practice. Concept validation and subsequent engineering evidence must support those conclusions.

Keep the relationship with the original needs visible. A chosen architecture can gradually lose important benefits as specifications and implementation choices evolve. Traceability helps the team notice when a tradeoff undermines the reason the concept was selected.

Connect concept decisions with enterprise priorities

The Voice of Business and Voice of Technology should inform selection alongside customer evidence. A concept needs a realistic development route and an operating environment capable of supporting it.

A Value Management Office can connect these choices with resources and portfolio priorities. Systems thinking helps the team examine whether the proposed improvement addresses a constraint governing patient access or successful use.

Evaluate the complete contribution. A technically impressive device can introduce training, service or clinical work that limits its benefit in the wider pathway.

“Concept engineering should leave the organization with a reasoned choice, a manageable learning plan and a clear connection to patient benefit.”


What comes next

Review one current concept decision. Can the team show credible alternatives, agreed criteria, the basis for selection and the assumptions requiring further evidence?

Bring the relevant disciplines together, compare options and examine stronger combinations. Then test the uncertainties that could change the decision. That is how Patient Centered Design builds a defensible route from important needs to better products.

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    We’ll only use your email address for this newsletter. No sales calls

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