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Thinking from the field — on operational improvement, sourcing discipline, leadership, and the work of making change stick. Each piece stands on its own. Read in any order.
When Expertise Isn't Enough
Not all consultants are created equal. That is a good thing.
The better question for a leader is not always, "Which consultant is best?" The better question is often: what kind of help does the organization need right now, and is the team ready to convert that help into measurable improvement?
At tbr ChangeWorks, we help companies move from discovery to implementation. We work with leaders and teams to understand what is really happening in the work, clarify the problem, organize the evidence, align stakeholders, design practical countermeasures, and support execution until improvement becomes part of the operating rhythm.
In some cases, that means we facilitate the improvement work ourselves, including focused improvement events. In other cases, we help a company prepare for highly specialized expertise — whether that expertise comes from lean practitioners, technical advisors, transaction specialists, attorneys, niche technologists, or other deep domain experts.
"Both needs are real. Both require discipline."
When it works — and what makes it work.
Some of the most effective lean practitioners create value with very little theater. They may show up without laptops, polished decks, or prepackaged answers. The classroom is the place where the work happens. The tools may be a flip chart, an easel, the process itself, and the people who own the work. Through disciplined questions, they help the team see the current condition, expose gaps in thinking, and create a practical path for problem solving.
That kind of engagement can be powerful. But it works best when the organization is ready. The evidence must be clear. The process must be visible. The team must understand the problem it is trying to solve. The current condition cannot be hidden in disconnected reports, vague assumptions, or competing narratives. That is where preparation protects value.
How complex organizations manage change at scale.
For larger organizations with existing workstreams, lean infrastructure, or a portfolio of concurrent initiatives, preparation becomes even more important. Companies with mature improvement programs have often managed change through a constellation of internal leaders, operators, project managers, lean experts, and external advisors. That model allows complex supply chain, operational, and commercial problems to be addressed concurrently — while employees remain focused on running the business, serving customers, and leading their teams.
"A structured problem statement, aligned stakeholders, and a disciplined scope of work help ensure the expert is focused on the work only they can do."
Between strategy and execution.
- Clarify the business problem and current condition
- Translate evidence into visual, actionable insight
- Facilitate improvement events and implementation work
- Prepare teams for high-value expert engagement
- Structure requests, workstreams, and scopes of work to reduce wasted time
- Build internal ownership so improvements survive after the engagement ends
- We have led from inside operations. Our perspective comes from direct operational and people leadership across industries, not only from advisory work.
- We connect improvement methods to measurable business outcomes. Our background was tied to customer experience, risk reduction, operating performance, and results visible in the ledger.
- We build capability, not dependency. Our role is to help clients improve the work, strengthen the team, and sustain the gains.
We are not the right answer for every problem. No consultant is. But when leaders need to understand what is really happening, mobilize people around evidence, improve the process, and convert expert input into executable work — that is where we are built to help.
Is this the kind of help you're looking for?
Book an Intro CallBeyond the Five Whys —
Toward Understanding
Why the most important question in problem-solving isn't "Why did this happen?" — and what to ask instead.
The Five Whys is one of the most widely taught problem-solving tools in Lean and Kaizen environments — and for good reason. Its intent is sound: understand problems deeply enough to prevent recurrence. But in practice, many organizations unintentionally weaken the method by moving too quickly from observing an abnormality to explaining it.
tbr ChangeWorks provides hands-on support beyond consulting, helping organizations improve performance through Lean, Kaizen, process improvement, strategic sourcing, and operational risk while building the skills to sustain gains. The approach described in this article — observation before explanation, systemic understanding before corrective action — reflects the guiding principles applied across tbr ChangeWorks engagements.
A defect appears. Someone asks "why?" An answer surfaces. Another "why?" Another answer. Very quickly, teams drift toward conclusions that feel actionable — operator error, lack of training, a missing inspection step. Sometimes those findings are correct. Sometimes they are simply the first explanations that allow the organization to restore motion and move on. That distinction matters more than most improvement systems acknowledge.
"Defects are often less dangerous than normalization. Once teams silently adapt around instability, the system begins hiding its own weaknesses."
The central challenge of sustainable improvement
Modern operations are shaped by combinations of people, automation, machine drift, software, environmental conditions, workload variability, and timing — with constant adaptation happening inside the process itself. Failures in those environments rarely emerge from a single isolated cause. They emerge from interacting conditions.
By the time an observable defect appears, the system may already contain accumulated drift, hidden compensations, stacked tolerances, inspection gaps, and interaction effects between processes that individually appear acceptable. Every contributor in that chain usually believes their step was not the one that failed — not because people are dishonest, but because operational systems are framed around local responsibility and local visibility.
Stacking "why" questions on top of incomplete observation doesn't move teams closer to solvable root causes. It creates cleaner narratives around incomplete understanding.
Commercial aviation, nuclear operations, and transportation safety investigations evolved well beyond linear root-cause narratives because the consequences of misunderstanding causation were too high. Organizations like the NTSB rarely investigate failures through a straight-line search for blame.
Instead, they reconstruct sequences, weak signals, failed barriers, operational drift, and interacting conditions — a methodology consistent with researchers like Jens Rasmussen, Nancy Leveson, and Erik Hollnagel, whose work moved systems thinking toward resilience engineering and drift analysis.
This depth of thinking is notably consistent with the spirit behind the Toyota Production System's "go see" mindset — observational before it is explanatory.
The gap between sustainable improvement and recurring problems often comes down to which pattern a team defaults to when something goes wrong.
The Traditional Pattern
Problem is detected
Team immediately asks "why?"
First plausible answer becomes root cause
Fix is implemented quickly
Team moves on
Drift remains — problem returns
The Observable Deviation Approach
Abnormality is detected
Team goes to observe directly — no blame
What changed from the last stable state?
When was the deviation first detectable?
Drift and interactions are identified
Causes are tested, system is fixed at source
The difference isn't just procedural. It changes the atmosphere of the investigation before it starts. When the goal is observation rather than explanation, conversations become less defensive. The team is no longer working to identify who caused the problem — they're working to understand the dangers and weaknesses emerging inside the system itself.
Observation Before Explanation — Seven Steps to Systemic Understanding
The following seven-step approach is designed to be practiced as a repeatable rep — a discipline that pairs with, rather than replaces, other improvement behaviors like standard work, layered audits, and visual management. Novices will find concrete starting points; experienced practitioners will recognize that the depth at each step scales with the complexity of the system.
Before any analysis begins, the abnormality must be clearly named. This is not about blame or explanation — it's about disciplined perception. What, specifically, is outside of the expected condition?
- What is the observable difference between what is and what should be?
- Who first noticed it, and how?
- Is this abnormality contained, or is it moving downstream?
Go to the place where the work happens. Engage the people closest to the process — not to assign responsibility, but because they hold observational data no report can capture. The goal is collective intelligence, not confession.
- What does the process look, sound, or feel like right now versus normal?
- What have operators noticed but perhaps not escalated?
- What workarounds or compensations are currently in place?
Defects do not appear in stable systems without something changing. The question is not "why did it fail?" but "what is different from the last time this process ran well?" Change is the most reliable entry point into system drift.
- What changed in materials, methods, machines, people, or environment?
- What changed in volume, timing, or sequence?
- What changed that no one formally documented?
Defects visible at final inspection rarely originate there. Tracing backward to find the earliest point at which the deviation was detectable — even subtly — is often where the real leverage for prevention lives.
- When did the first detectable signal appear, and where?
- What was the lag between first signal and detection?
- What inspection points existed between origin and detection — and what did they miss?
Without a clear standard or stable prior condition, "deviation" has no meaning. This step anchors the investigation in something measurable. It also reveals whether the standard itself is current, understood, and actually achievable.
- What is the documented standard for this process, output, or condition?
- How did actual performance deviate from that standard?
- Is the standard itself still valid, or has the process drifted from it over time?
This is where the investigation expands beyond single-cause thinking. Most failures in complex operations are the outcome of multiple conditions interacting. Each of the four domains may contain contributing drift.
- People: What adaptations or informal compensations have developed over time?
- Process: Where has the sequence, timing, or method drifted from standard?
- Machine: What equipment drift, calibration shift, or wear exists?
- Environment: What conditions — temperature, shift timing, volume — may have interacted?
A proposed root cause is a hypothesis until tested. Before implementing a countermeasure, validate it: can you reproduce the defect by recreating the conditions? Can you prevent it by changing one specific thing? This discipline separates lasting improvement from well-intentioned patching.
- Can we reproduce the failure under controlled conditions?
- Does removing the proposed cause prevent recurrence?
- What does the standard need to look like to hold the gain?
- How will we know if drift begins again before a defect reappears?
Problem-solving at this level is not an event. It is a capability built through repetition — the way any physical or cognitive skill develops. Teams that apply this framework consistently, even on smaller issues, develop something no single training session can deliver: better instincts about when a system is drifting before a defect becomes visible.
This is what made the difference on production floors where quality performance improved not because of one breakthrough investigation, but because the team collectively became more attuned to weak signals. People surfaced abnormalities earlier. Conversations became less defensive. The team developed stronger awareness of how the system behaved under stress, variation, and drift.
"The most important question is not 'Why did this happen?' — it is 'When did the system first begin drifting away from stable operation?'"
The shift from reactive fixing to systemic understanding
The Five Whys is a valuable starting point. It orients teams toward curiosity over reaction, and that instinct is exactly right. The Observable Deviation Approach doesn't discard that instinct — it deepens it. By placing observation before explanation, comparison before conclusion, and validation before implementation, teams develop the kind of systemic understanding that makes improvement sustainable rather than cyclical.
Not because the method is sophisticated. Because it builds the habit of seeing systems clearly — and that habit, practiced repeatedly, is what lasting improvement actually runs on.
END · Continuous Improvement Series · tbr ChangeWorks
Ready to build this capability in your team?
Book an Intro CallProcurement as a CEO Lever
Two value stories. One function at the center. Moving margin and earnings quality.
I launched tbr ChangeWorks after spending more than 30 years at GE across manufacturing, procurement, quality, and financial services. That experience shaped a simple belief: a few disciplines — Lean, strategic sourcing, and change management — consistently separate companies that scale well from those that struggle. One lesson feels especially relevant right now: procurement is a CEO lever.
Procurement isn't just about buying. It directly shapes earnings — and how reliable those earnings are.
"Are you treating procurement as a buying desk — or as a value engine that shapes margin, earnings durability, and customer trust?"
AI and analytics are making cost, supplier performance, contract leakage, and utilization far more visible — to you, your customers, and your suppliers. Technology and SaaS spend keep growing. Those investments can either scale the business or quietly introduce waste and risk. Procurement increasingly determines which path you're on.
- Organizations can now see price variance, supplier performance, contract leakage, and software utilization like never before
- Customer expectations for reliability and transparency are rising
- Suppliers are using analytics to sharpen pricing, capacity allocation, and negotiation posture
- Technology investment can unlock productivity — or create tool sprawl, renewal creep, and contract risk
Direct materials, components, outsourced production, logistics, and quality failures drive cost. Procurement shapes the margin directly.
Sectors: Manufacturing · Retail & Distribution · Construction · Transportation
Technology, professional services, outsourcing, SaaS, and contingent labor drive cost. Procurement shapes the efficiency ratio and earnings quality.
Sectors: Professional services · Software · Healthcare · Financial services
| Sector | COGS Range | OpEx Range |
|---|---|---|
| Manufacturing | ~50–80% | ~12–30% |
| Retail & Distribution | ~60–75% | ~15–30% |
| Construction | ~70–85% | ~6–15% |
| Transportation | ~60–80% | ~10–25% |
Enterprise value impact of a single 1-point EBITDA margin increase for a $100M company — at typical sector valuation multiples.
| Sector | COGS Equivalent | OpEx Range |
|---|---|---|
| Professional & Business Services | ~40–70% | ~15–35% |
| Information & Software Services | ~20–50% | ~25–45% |
| Healthcare Services | ~45–70% | ~15–35% |
| Banks (efficiency ratio) | Commonly ~50–70% | |
| P&C Insurers (expense ratio) | Often ~25–35% | |
Potential equity value increase for banks and insurers from a 1% reduction in operating expenses as a share of revenue.
"Treat procurement as a leadership system, not a buying desk."
As you think about your business — where does procurement have the most influence in your model? Which spend decisions truly shape customer experience and reliability? Where might one point of improvement change the conversation?
Want to explore this lens for your business?
Book an Intro CallExperience, Age & the Work of Staying in Motion
What the research says — and a practical strategy for the second half of a long career.
In the United States, many forms of discrimination are prohibited because history showed us that bias, when left unchecked, can become normalized, institutionalized, and even defended as reasonable. Age discrimination sits in that uncomfortable space. It is legally constrained, publicly disapproved, and yet still difficult to prove — especially when it operates through preference, perception, coded language, or silence.
The data tells us this is not paranoia.
AARP's national surveys consistently find that roughly three in four workers aged 45 and over have either witnessed or experienced age discrimination in the workplace.
A large field experiment published in the Journal of Political Economy — submitting more than 40,000 fictitious résumés varying only by age signals — found that callback rates fall measurably as applicants get older, with the effect more pronounced for women. That is not anecdote. That is documented behavior inside the very systems we are told to trust.
"Fluid intelligence declines slowly from early adulthood. Crystallized intelligence — judgment, vocabulary, pattern recognition, contextual reasoning — keeps rising well into the 60s and 70s."
Gary Klein's research on naturalistic decision-making shows that experts — who are, by definition, mostly older — recognize patterns faster and arrive at workable decisions with less deliberation than novices. In domains that reward judgment under ambiguity, accumulated experience is a measurable performance advantage, not a depreciating asset.
So, the contradiction is real: a body of evidence says older professionals can deliver, and another body of evidence says hiring systems often discount that. Both are true simultaneously. That contradiction is the strategic problem. And it cannot be solved by hiding age.
What proof am I creating that my experience is still moving?
The strongest signal is not the claim "I am adaptable." It is recent evidence: new tools learned, new problems solved, new content created. A 2023 Harvard / MIT / BCG study found that knowledge workers paired with generative AI completed tasks roughly 25% faster and at meaningfully higher quality. AI fluency is the single clearest "I am current" signal — and it compounds the judgment they already have. The résumé should not read like a museum. It should read like a working lab.
Where does my experience create unfair advantage rather than perceived risk?
Some roles will see seniority as cost, rigidity, or short runway. Other contexts need exactly what senior professionals bring: judgment under ambiguity, risk management, stakeholder navigation, crisis recovery, process discipline, mentoring, governance, transformation, client trust, pattern recognition. The work is not to convince every employer. The work is to find the environments where accumulated experience is needed, not merely tolerated.
Am I relying on systems that no longer see me clearly?
Mark Granovetter's foundational research showed that the majority of job moves happen through acquaintances rather than close friends or formal channels. Applicant tracking systems trained on keyword distance and recency biases are structurally less reliable for late-career profiles. The center of gravity must shift toward referrals, advisory conversations, fractional work, project-based proof, thought leadership, and communities where credibility travels through trust.
- Recent learning made visible — current AI tools, automation, digital workflows actively in use
- Present-tense evidence — current projects, ventures, pilots, podcasts, advisory work, writing, teaching
- A tightened historical record that keeps the strongest proof points without forcing the reader through every decade
- Experience framed as acceleration — "I recognize patterns faster, reduce avoidable mistakes, align stakeholders sooner"
- Demonstrated coachability and curiosity backed by examples
- Referrals treated as trust-transfer mechanisms, not last-resort favors
One concrete recommendation for senior professionals working through this transition: invest in a coach who understands what the market actually values in senior leaders — not in general "career advice."
I have been working with Chris Stambolidis, and his preparation was instrumental in helping me move through a recent seven-interview process and finish strongly. Chris spent more than a decade as an executive recruiter before moving into coaching, which means he understands the language, the gates, the decision criteria, and the unspoken expectations of executive search from the inside.
The deeper point: as you become more experienced, you have to put in more deliberate work, not less, to get results. The market does not reward seniority by default. It rewards seniors who can articulate their current usefulness with the same crispness as someone earlier in their arc. Coaching at this stage is not remediation. It is calibration.
Stop trying to look younger.
Start making your current usefulness unmistakable.
Sources: AARP, Workplace Age Discrimination surveys (2018, 2022). · David Neumark, Ian Burn, Patrick Button, "Is It Harder for Older Workers to Find Jobs?" Journal of Political Economy (2019). · Paul B. Baltes, Lifespan Development and the Brain (2006); Timothy A. Salthouse, longitudinal cognitive-aging research (2009–2020). · Gary Klein, Sources of Power (MIT Press, 1998). · Fabrizio Dell'Acqua et al., "Navigating the Jagged Technological Frontier," Harvard Business School Working Paper 24-013 (2023). · Mark S. Granovetter, "The Strength of Weak Ties," American Journal of Sociology (1973). · Laura L. Carstensen, Stanford Center on Longevity.
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