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Staying sharp depends on consistently doing the fundamentals well. JD Solomon Inc. provides practical solutions.
Staying sharp depends on consistently doing the fundamentals well.

Staying sharp depends on consistently doing the fundamentals well. Experience may create the illusion that we’ve moved beyond the fundamentals, but in my work with organizations of all sizes, I see that these basics remain the foundation for effectiveness. They’re easy to overlook, but always essential.

 

A Story From the Batting Cage

Trying to Hit a Baseball

Years ago, I had moved into coaching upper‑tier showcase baseball. These were talented fifteen‑year‑olds who already had strong mechanics and a solid grasp of the fundamentals. At that level, coaching becomes a matter of fine points—small adjustments, subtle timing cues, and situational awareness. Fundamentals fade into the background because everyone assumes they’re already mastered.

 

One afternoon, after a long practice, we still had a few minutes left in the indoor facility. I stepped into the batting cage, partly out of curiosity and partly out of pride. If I had been coaching these players on the finer points, surely my own swing would have improved along the way.

 

It took only a few pitches to realize the truth. I couldn’t hit the ball. Not even close.

 

Doing the Fundamentals Well

After a dozen humbling swings, I stepped back and laughed at myself. Then I did what every coach eventually tells a struggling player: get back to the fundamentals. I focused on one thing—watching the ball all the way to the bat. No fancy mechanics. No overthinking. Just eyes on the ball and hands to the ball.

 

And just like that, the problem disappeared. The fundamentals had never stopped working; I had simply stopped using them.

 

A Recent Board Meeting

Not long ago, I returned to work with a small client I hadn’t assisted in nearly a decade. The assignment was to help the board work through a strategic issue. I’ve facilitated hundreds of board meetings, but walking into that first session, I had a flicker of nerves. It took me a moment to understand why.

 

The stakes were personal.

 

These weren’t corporate executives buffered by layers of staff and process. These were neighbors, parents, volunteers—people who would see each other at the grocery store the next morning. Their decisions didn’t just affect budgets or timelines; they affected kids, families, and community trust.

 

So, before the meeting began, I reminded myself of what I had told myself in the batting cage: focus on the fundamentals.

 

Little League Board Meetings

Years ago, when I served on a Little League board, the conversations were always grounded in what mattered most to the families. Playing time. Balanced teams. Costs. Safety. Getting kids to the next level. No one wanted to waste time, and no one wanted decisions made in a vacuum.

 

Those meetings taught me that the fundamentals of small‑organization governance are as much human as procedural.

 

Board Meetings These Days

Most of my business-related board work now happens on a bigger stage—regional authorities, statewide commissions, major infrastructure decisions. The fine points of Robert’s Rules of Order often dominate the conversation. Procedure matters, but it can easily overshadow purpose and human perspective.

 

Yet even in those settings, when the pressure rises, the fundamentals kick in. They always do.

The Fundamentals of Small‑Organization Board Meetings

For community‑embedded boards, service is personal and visible. The meeting leader must shift from being a formal presiding officer to becoming a strategic facilitator. That is someone who keeps the group aligned without silencing the voices that need to be heard.

 

1. Trust Is the Real Currency

Trust is built slowly through transparency and lost instantly through silence or surprise. In small communities, trust isn’t abstract. Trust is built on relationships.

 

2. Meetings Must Respect the Human Stakes

Every agenda item carries consequences for real people. That awareness should shape tone, pacing, and decision‑making.

 

3. Emotional Steadiness Matters as Much as Expertise

Technical knowledge helps, but emotional steadiness is what keeps discussions productive when issues become personal.

 

4. Legitimacy Before Authority

Formal authority means little if the board doesn’t feel ownership of the process. Legitimacy is earned through clarity and consistency.

 

5. Role Clarity Protects Relationships

Clear boundaries between governance and operations prevent personal conflicts from becoming organizational problems.

 

Doing the Fundamentals Well

I’ve always believed in doing, not just talking. Writing about what I see helps me stay grounded. Leading small‑organization boards does the same. Early in my career, a small contractor once told me, “I may be little, but I give you all I’ve got.” That line stuck with me.

 

When everything is a little smaller, everything is a little more personal. And that’s exactly why and when the fundamentals matter most.

 

Empathy. Ethics. And above all, staying sharp by doing the fundamentals well.



JD Solomon Inc. provides solutions for program development, asset management, and facilitation at the nexus of facilities, infrastructure, and the environment. Visit our Facilitation page for more information related to all types of facilitation.

JD Solomon is the founder of JD Solomon, Inc., the creator of the FINESSE Fishbone Diagram®, and the co-creator of the SOAP criticality method©. He is the author of Communicating Reliability, Risk & Resiliency to Decision Makers: How to Get Your Boss’s Boss to Understand and Facilitating with FINESSE: A Guide to Successful Business Solutions.


Systems thinking helps you connect, inform, and build rapport with decision makers.  JD Solomon Inc. provides practical solutions for project development and communication.
Systems thinking helps you connect, inform, and build rapport with decision makers.

Effective communication is rarely about isolated elements. Perfect wording, flawless visuals, or an eloquent speaker are not required. What matters most is the seamless interaction of multiple components working together. Systems thinking transforms communication from a disjointed process searching for perfection into a well-orchestrated system that produces confidence.

 

Understanding Communication as a System

A system is a collection of related parts that create an outcome greater than the sum of the individual components. In communication, these parts include structure, clarity, medium, feedback, and the context in which the message is delivered.

 

A car’s engine, wheels, and transmission must work in harmony to move forward. Communication elements must function together to achieve effectiveness.

 

You Don’t Have to Be the Most Attractive or Best Spoken

The key takeaway from systems thinking is that individual perfection is unnecessary. A car does not require an ideal tire pressure or every cylinder running at peak efficiency to function effectively. Likewise, in communication, one does not need to be the most articulate speaker or the most skilled writer.

 

What matters most is that all communication components work together.

 

The FINESSE Approach: A Systems Thinking Model for Communication


The FINESSE framework is an example of systems thinking applied to communication. FINESSE stands for Frame, Illustrate, Noise Reduction, Empathy, Structure, Synergy, and Ethics. Each of these components plays an individual role. However, the true power comes from their interaction.


  • Frame: Setting the context ensures the message is understood correctly.

  • Illustrate: Using visuals or examples makes abstract concepts concrete.

  • Noise Reduction: Filtering out unnecessary information prevents confusion.

  • Empathy: Understanding the audience’s needs fosters engagement.

  • Structure: Organizing information logically aids comprehension.

  • Synergy: Ensuring all elements complement one another enhances clarity.

  • Ethics: Communicating truthfully builds trust and credibility.

 

FINESSE helps professionals create messages that drive action by treating communication as a system.

 

FINESSE in Action

The FINESSE Fishbone (cause-and-effect) Diagram produces an easy mental model to help recall the necessary system components. The FINESSE Checklist provides a concise tool for developing and checking the communication. Both are available at the JD Solomon Inc website under the Resources tab.

 

The Input-Process-Output (IPO) Model in Communication

Another practical tool from systems thinking is the Input-Process-Output (IPO) model. This model breaks down communication into three critical aspects.

 

Inputs

Data, reports, expert insights, visuals, and audience insights are the basic raw materials for effective communication. High-quality inputs lead to more effective communication.

 

Processes

This aspect involves shaping inputs into a meaningful message. It includes selecting the right medium, structuring content, and refining delivery.

 

Outputs

The final message should align with the intended outcome. That’s true whether it’s a report, a presentation, or a conversation.

 

The IPO Model in Action

The pressure is on as you start to develop a presentation for the Board of a senior executive. Begin by defining what action the decision maker should take. Next, frame what inputs are in and which are out.

 

Systems Thinking in Action

Frame the problem and streamline the information using the IPO model (expressed as the F as Frame in FINESSE). Next, structure the delivery using the FINESSE Fishbone Diagram and the FINESSE Checklist. Make sure each bone of FINESSE is sufficiently addressed, but the perfection of each component is not required.

 

Winning over Decision Makers

The power of systems thinking lies in recognizing that effectiveness comes from integration, not perfection. Professionals can craft messages that are understood and drive action by focusing on how elements interact rather than individual components. Effective communication is produced by how all the parts work together.



Solomon, J. D. (2025, March 6). How to use systems thinking to win over decision makers. Communicating with FINESSE. https://communicatingwithfinesse.substack.com/p/how-to-use-systems-thinking-to-win



JD Solomon writes and consults on decision-making, reliability, risk, and communication for leaders and technical professionals. His work connects technical disciplines with human understanding to help people make better decisions and build stronger systems. Learn more at www.jdsolomonsolutions.com and www.communicatingwithfinesse.com.

Leaders need to know whether uncertainty is a knowledge gap (fixable) or a natural variability (not fixable). JD Solomon Inc. provides practical solutions for addressing environmental risk and uncertainty.
Leaders need to know whether uncertainty is a knowledge gap (fixable) or a natural variability (not fixable).

In large, complex systems, uncertainty is a technical reality that must be classified, measured, and managed. The most useful distinction is between epistemic uncertainty, which reflects limits in our knowledge, and aleatoric uncertainty, which reflects inherent variability in the world itself. Serious quantitative modeling depends on knowing the difference, because what can be reduced must be pursued and what cannot be reduced must be designed for. The uncertainty that cannot be eliminated must be effectively managed and communicated.


Epistemic Uncertainty

Epistemic uncertainty is defined as those uncertainties due to simplifying model assumptions, missing physical data, or our basic lack of knowledge. Some examples include the way we express inputs or relationships to describe natural phenomena, the inputs we chose to put in (or leave out), and certain types of numeric errors (such as those related to precision or significant figures).

 

Epistemic uncertainty is limited by our understanding of what we know (knowledge) and to the choices we make in applying the knowledge (judgement).

 

Aleatoric Uncertainty

Aleatoric uncertainty is defined as those uncertainties that are inherent to a problem or to an event that cannot be reduced by additional knowledge. Additional runs (trials) of an experiment or additional observations may help to narrow the uncertainty, but there is a natural error of lack of clarity or precision that is present. Aleatoric uncertainty is also known as statistical uncertainty or irreducible uncertainty.

 

Modeling Example

Both kinds of uncertainties are present in Large Worlds. And they are usually overlapping.

 

For example, I began my career developing quantitative groundwater (hydrogeologic) models. The leading-edge quantitative models were developed with early generations of the control-volume finite-difference (CVFD) flow software MODFLOW and the solute transport and reactive solute transport software MT3D. Both software applications are still in use 20 to 30 years later, albeit with several generations of improvement. They are now officially endorsed by the United States Geological Survey (USGS).

 

Some of the issues with quantitatively assessing the uncertainty associated with some nasty chemicals and chemical compounds included: the assumed boundary conditions at the edges of the model; grid spacing (both model and field sampling points); relationships and inter-actions between known, and possibly unknown, compounds; geophysical conditions, such as aerobic or anaerobic environments, and the effect on chemical fate and transport; the type and precision of groundwater sampling that had been performed; the accuracy and reliability of analytical laboratories and field testing; and the accuracy and reliability of the models themselves.

 

All of this to say that there were many sources of uncertainty – some based on our then-current knowledge of the world and others related to the assessment approaches we had chosen, or were limited to using.

 

Uncertainty is Everywhere

Similar Large World examples can be found related to air quality assessments, atmospheric modeling, weather forecasting, climate change models, predicting wildfires, disease and epidemic modeling, biological assessments, nuclear engineering, and others.

 

The good news is that we are certainly much improved at quantitative prediction where variables behave independently, such as in many physical sciences.

 

The bad news is that we still have a long way to go when it comes to accurately predicting outcomes in which variables depend on and interact non-linearly, such as in biological processes and human behavior.


Uncertainty in Practice

The distinctions between epistemic and aleatoric uncertainty continue because they clarify what can be reduced versus what must be managed.


  • Epistemic uncertainty - reducible with more data, monitoring, research, or model refinement.

  • Aleatoric uncertainty - inherent variability that must be accommodated through design margins, resilience, or probabilistic methods.

 

Environmental agencies still rely on distinctions in epistemic and aleatoric uncertainty to justify monitoring programs, adaptive management, probabilistic risk assessments, and funding for data collection.

 

Uncertainty in Environmental Communication

Federal and state environmental agencies implicitly or explicitly use epistemic and aleatoric uncertainty logic in risk communication and hazard modeling.


Leaders need to know whether uncertainty is a knowledge gap (fixable) or a natural variability (not fixable). There are competing frameworks, but framing environmental issues using epistemic and aleatoric uncertainty remains powerful and intuitive.

 

The Limits of Eliminating Uncertainty

Reducing uncertainty and being more objective are certainly the right, noble things that should be done. However, the reality is that our knowledge of the future is not perfect and even the most quantitative models require subjectivity. Only statistical Frequentists, working in Small Worlds, believe or advocate otherwise.


Reduce uncertainty and subjectivity – yes.

Eliminate uncertainty and subjectivity – never.

Embrace uncertainty and subjectivity – always.

 

 

North Carolina State University’s Ralph Smith is an excellent source in the field of uncertainty quantification. For me, he is also an example that, although you may travel far for expert advice and guidance, sometimes you discover one of the best sources is in your own backyard. See G.L.S. Shackle for more on the nature of our knowledge. The US National Weather Service is an excellent reference for more details on quantitative modeling for weather forecasting, the USGS for quantitative hydrogeologic and geologic modeling, and the Centers for Disease Control (CDC) on quantitative and qualitative modeling related to diseases and epidemics.

 


This article was first published by JD Solomon on LinkedIn.

Solomon, J. D. (2018, October 29). Risk and uncertainty: Eliminating uncertainty. LinkedIn. https://www.linkedin.com/pulse/risk-uncertainty-eliminating-jd-solomon



JD Solomon writes and consults on decision-making, reliability, risk, and communication for leaders and technical professionals. His work connects technical disciplines with human understanding to help people make better decisions and build stronger systems. Learn more at www.jdsolomonsolutions.com and www.communicatingwithfinesse.com.

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