Author: Andrei Bilog M.Sc., CAPM

In competitive environments like healthcare, biotech, and academia, professionals are constantly making decisions that shape their careers. But not all decisions are made for the same reason.

Some decisions are made to optimize outcomes and long-term impact.
Others are made to send signals to the outside world.

These two motivations—decision quality vs. external signaling—often compete with each other.

Understanding the difference can dramatically change how students choose internships, how scientists design projects, and how professionals evaluate career opportunities.

Decision quality refers to how well a decision is made given the information available at the time, not whether the final outcome happens to be good or bad. (Wikipedia)

Researchers studying decision theory emphasize that a high-quality decision usually includes several elements:

In other words, a decision can be high quality even if the outcome is uncertain, especially in fields like medicine or biotech where experiments and research involve risk.

For students entering healthcare or biotech, this distinction is important. A decision that maximizes learning, skills, or long-term opportunity may not look impressive immediately—but it may be the best decision available at the time.

External signaling comes from signaling theory, a concept widely used in economics and organizational research.

Signaling theory explains how individuals communicate information about their abilities or quality through observable actions—such as degrees, job titles, or institutional prestige—especially when outsiders cannot directly evaluate their true ability. (Wikipedia)

For example, people may choose:

These choices signal competence or credibility to employers, investors, or admissions committees.

In situations where information is incomplete, signals help others infer quality. Effective signals are often costly or difficult to imitate, which is why credentials and affiliations matter. (Wikipedia)

But signaling has a downside: sometimes decisions are made for appearances rather than substance.

The tension between decision quality and signaling appears everywhere in education and professional life.

Consider three common scenarios.

A student may choose:

The first option signals credibility.
The second option might produce far more technical learning.

For someone planning a career in research or process development, the smaller environment may actually produce stronger skill development—even if it looks less impressive on paper.

In academic labs, some students gravitate toward projects likely to produce publications quickly.

Others choose technically difficult work that may fail but teaches deeper experimental design.

Ironically, the second path often produces better scientific thinking, even if it takes longer.

Research environments constantly force scientists to choose between high-signal activities and high-learning activities.

Early professionals often choose jobs based on titles or brand recognition.

But in reality, the strongest career accelerators tend to be roles that provide:

In biotech companies, someone who runs part of a manufacturing process or analytical platform early in their career may gain more real expertise than someone with a more impressive title but limited responsibility.

When I was a student, I remember feeling pressure to pursue paths that looked impressive to others.

Like many students in science, I believed that success meant collecting recognizable signals:
prestigious institutions, well-known labs, impressive titles.

But over time—especially working in science and teaching anatomy and physiology—I realized something.

Many of the people who become excellent scientists, clinicians, or professionals are not necessarily those who optimized for signaling.

They optimized for learning environments.

They chose:

Sometimes those choices looked less impressive at first.

But five or ten years later, the difference in skill level became obvious.

Healthcare and biotech operate in complex, uncertain environments.

In these fields:

Because of this uncertainty, decision-making quality becomes extremely important.

Researchers and professionals must constantly evaluate evidence, update assumptions, and adapt their strategies. Studies in cognitive neuroscience even show that humans generate internal signals after decisions to monitor errors and adjust future behavior, highlighting how learning from decisions is essential to performance improvement. (PMC)

In other words:

Good professionals are not just good at looking impressive.
They are good at thinking carefully under uncertainty.

When evaluating opportunities, ask yourself two questions:

Examples:

Signals are useful. They help open doors.

But they are not everything.

Examples:

Capability compounds over time.

The best careers balance both.

Early on, it is tempting to optimize entirely for signaling. But the strongest professionals gradually shift toward optimizing for decision quality and capability development.

A good rule of thumb is:

Signals open doors.
Skills keep them open.

Students entering healthcare or biotech should remember that the most important decisions are not always the ones that look impressive today.

They are the ones that make you more capable tomorrow.

Disclaimer: This article was assisted by AI-based language tools (ChatGPT, OpenAI) for drafting and organization. All content was reviewed by the author, and all claims are supported by peer-reviewed sources.

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Connelly, B. L., Certo, S. T., Ireland, R. D., & Reutzel, C. R. (2011). Signaling theory: A review and assessment. Journal of Management, 37(1), 39–67.

Desender, K., et al. (2021). Understanding neural signals of post-decisional performance monitoring. eLife, 10, e67528.

Spetzler, C., Winter, H., & Meyer, J. (2016). Decision quality: Value creation from better business decisions. Wiley.

Spence, M. (1973). Job market signaling. Quarterly Journal of Economics, 87(3), 355–374.