The Team Performance Puzzle: Why Building Great Teams Is Getting Harder — and Measuring Them Is…
November 5, 2026
The Team Performance Puzzle: Why Building Great Teams Is Getting Harder — and Measuring Them Is Harder Still
An Industrial and Organizational Psychology Perspective on Growth, Workforce Change, and Artificial Intelligence
A company can hire talented people, assemble them into teams, and still produce disappointing results. As organizations grow rapidly, expand geographically, introduce artificial intelligence, and welcome new generations of employees, building effective teams becomes increasingly complicated. Measuring their performance may be even more challenging.
The problem is not simply finding good people. It is understanding how individual capabilities, interpersonal relationships, organizational systems, and changing work environments combine to produce results. This is precisely where industrial and organizational (I/O) psychology offers practical, scientifically grounded solutions.
Individual Excellence Does Not Guarantee Team Excellence
Campbell and colleagues’ seminal research on individual job performance established that performance involves multiple behavioral dimensions, influenced by knowledge, skills, motivation, and other determinants.¹
At the team level, Salas, Sims, and Burke identified five essential teamwork components: team leadership, mutual performance monitoring, backup behavior, adaptability, and team orientation.²
The distinction matters. An organization can employ excellent individual performers who collectively achieve mediocre results. Five outstanding musicians playing five different songs do not constitute an orchestra.
Rapid growth magnifies this problem. Geographic expansion introduces coordination challenges, while changing workforce demographics and generational expectations complicate communication, supervision, and team development.
Research on psychological safety by Amy Edmondson further demonstrates that interpersonal conditions influence whether team members speak up, learn, and address mistakes.³
The Performance Measurement Trap
Traditional performance systems emphasize individual productivity, attendance, and supervisor ratings. These measures often overlook coordination, knowledge sharing, adaptability, and collective problem-solving. The result is a dangerous measurement gap: organizations know who is busy but cannot reliably determine whether teams are effective. I/O psychology addresses this through validated performance models, behavioral observation, structured assessments, and multilevel measurement.
Lessons from the Military and Construction
The U.S. Army provides an instructive example. Special Operations teams depend not merely on individual technical competence but also on trust, adaptability, coordinated decisions, and performance under uncertainty. Selection, collective training, and after-action reviews reflect applied I/O psychology principles, even when practitioners use different terminology.⁴
Construction faces comparable challenges. Project teams combine subcontractors, supervisors, engineers, and geographically dispersed specialists. Poor coordination can undermine productivity despite competent individual workers. Industry research emphasizes that labor shortages, fragmented workflows, and inadequate planning contribute to project performance problems.⁵
Both environments demonstrate a fundamental principle: team effectiveness is an organizational capability, not simply the sum of employee capabilities.
Management Problems Versus Cultural Change
Organizations must distinguish performance problems created internally from those associated with broader societal developments.
Unclear roles, poorly designed incentives, inconsistent supervision, and ineffective workflows are management problems. They are generally amenable to organizational intervention.
Generational shifts in communication preferences, changing expectations about employment, and broader technological transformations are contextual influences. They may require adaptation but should not automatically be blamed for poor performance.
Indeed, research cautions against exaggerated assumptions about generational differences in workplace attitudes.⁶
Blaming younger employees for dysfunctional systems is convenient. Unfortunately, convenience is not a validated performance measure.
Enter Agentic AI: A New Team Member
Agentic AI introduces another challenge: teams increasingly include autonomous digital agents performing scheduling, analysis, coordination, and decision-support activities. McKinsey describes emerging organizational models in which humans and AI agents work together across redesigned workflows.⁷
This development makes team performance measurement essential. Automating poorly coordinated processes may simply produce dysfunction faster.
I/O psychology can help establish appropriate human–AI roles, accountability, performance criteria, and supervisory controls.
Three Practical Interventions
Organizations should adopt three complementary approaches:
1. Measure both individual and team performance. Develop behaviorally anchored measures covering productivity, coordination, adaptability, and collective outcomes. Compare results across teams and locations while accounting for differences in resources and task complexity.
2. Institutionalize team diagnostics and feedback. Use validated surveys, structured observations, after-action reviews, and periodic team assessments to identify communication failures, role ambiguity, and ineffective leadership. Track improvement rather than merely administering another survey.
3. Redesign work before automating it. Apply I/O psychological work analysis to identify human–AI responsibilities, critical interdependencies, and appropriate performance indicators. Pilot new workflows and evaluate outcomes before scaling.
The Bottom Line
Tomorrow’s competitive advantage will depend less on assembling collections of talented individuals and more on developing teams that learn, coordinate, adapt, and deliver measurable results.
I/O psychology provides the scientific foundation for making that happen.
The management imperative is straightforward: Stop merely counting performers. Start measuring performance.
Footnotes and Sources
Academic research, industry publications, military doctrine, and business analysis
1. Campbell, J. P., McCloy, R. A., Oppler, S. H., & Sager, C. E. (1993). “A Theory of Performance.” In Personnel Selection in Organizations, pp. 35–70. Jossey-Bass. Seminal individual job performance framework. Wiley Online Library
2. Salas, E., Sims, D. E., & Burke, C. S. (2005). “Is There a ‘Big Five’ in Teamwork?” Small Group Research, 36(5), 555–599. Seminal team performance framework. Sage Journals
3. Edmondson, A. (1999). “Psychological Safety and Learning Behavior in Work Teams.” Administrative Science Quarterly, 44(2), 350–383. Empirical research involving 51 work teams. ERIC
4. U.S. Department of the Army (2024). Civil Works Review Policy, ER 1165–2–217, Section 8.5.3. Documents the Army’s use of after-action reviews to improve team performance. Defense Media
5. Associated General Contractors of America and NCCER (2026). “Construction Workforce Shortages Remain Acute Despite ‘Soft’ Market Conditions.” Industry survey documenting skills shortages and project delays. Associated General Contractors of America
6. Costanza, D. P., Badger, J. M., Fraser, R. L., Severt, J. B., & Gade, P. A. (2012). “Generational Differences in Work-Related Attitudes: A Meta-analysis.” Journal of Business and Psychology, 27, 375–394.
7. McKinsey & Company (2025). “The Agentic Organization: Contours of the Next Paradigm for the AI Era.” Examines human–AI collaboration and emerging organizational operating models. McKinsey
Contributor’s Note: Mark Wilson, Chief Analytics Officer and Senior Business Advisor. Comments, suggestions, reactions, examples, and questions are welcome. Reach me at mark.wilson@horizonperformance.com
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