Wednesday, March 25, 2026

If You Can't Measure Productivity in a Large Organization at the Individual or Department Level, What Do You Do?

It is nearly impossible to granularly know which employees and departments in any large organization really contribute to firm outcomes.


Since we cannot really measure such contributions, brute force layoffs might be the only way to find out how efficient any large organization really can be, as hard as that is on workforces.


The “attribution problem” in large organizations will be familiar to anybody who has had to assess rewards based on actual firm results when no single department actually can claim credit for most financial outcomes.


In large firms, value is rarely created by a single employee or department working in isolation. Product launches, involve research and development,, engineering, marketing, logistics, sales, legal compliance, and customer support. 


When the launch succeeds, how much credit belongs to each? When it fails, who bears responsibility?


The assessment problems (rewards, for example) are significant:

  • Incentive misalignment. If individual contributions cannot be cleanly attributed, performance-based pay systems break down as heroes and free riders alike are in the same category

  • Resource misallocation. Budget committees and executives tend to reward departments that can demonstrate value legibly (sales, manufacturing) while others are hard to evaluate (compliance, infrastructure, knowledge management)

  • Strategic distortion. Firms may over-invest in activities whose productivity is visible and under-invest in activities whose productivity only shows up indirectly or with long lags. (research, culture-building, and organizational learning).


Small firms can rely on direct observation and social norms to attribute effort. But large entities have interdependencies that increase nonlinearly while political dynamics increasingly shape who gets credit. 


The result is that large firms have measurement costs that scale faster than the firm itself.


Study / Work

Authors

Year

Core Argument

Key Finding on Attribution

Production, Information Costs, and Economic Organization

Alchian & Demsetz

1972

The firm exists to monitor team production where individual contributions are inseparable

Joint production makes metering individual inputs prohibitively costly; hierarchy is an imperfect but necessary solution

Moral Hazard in Teams

Holmström

1982

Optimal contracts under joint output are necessarily inefficient

No budget-balanced contract can achieve first-best effort when output is jointly produced; someone must absorb the residual

Pay and Organizational Performance

Milgrom & Roberts

1988

Influence activities consume resources when attribution is ambiguous

Workers invest in lobbying for credit; firms respond with rigid rules that reduce gaming but also reduce flexibility

The Balanced Scorecard

Kaplan & Norton

1992

Firms rely too heavily on financial metrics that obscure true value drivers

Single-metric systems systematically misattribute productivity; multidimensional scorecards partially address but don't solve the problem

Knowledge-Creating Company

Nonaka & Takeuchi

1995

Knowledge is produced collectively and tacitly across departments

Tacit knowledge creation is inherently non-attributable; firms that try to credit individuals destroy the collaborative conditions needed for it

Measuring and Managing Performance in Organizations

Austin

1996

Measurement systems alter behavior in dysfunctional ways

The more precisely you measure a subset of outputs, the more workers optimize for measured outcomes at the expense of unmeasured ones (a formalization of Goodhart's Law)

Why Firms Differ

Nelson

1991

Organizational routines are the unit of productive capability, not individuals

Productivity resides in collective routines that cannot be decomposed into individual contributions without destroying the routine itself

Incentives vs. Control in Organizations

Prendergast

1999

A comprehensive survey of incentive design under imperfect attribution

Subjective performance evaluation introduces favoritism; objective metrics introduce gaming; no system cleanly resolves joint production

The Knowing-Doing Gap

Pfeffer & Sutton

2000

Firms systematically misidentify what drives performance

Attribution errors lead firms to copy visible practices (structure, perks) while ignoring invisible ones (culture, trust) that actually drive productivity

Social Capital and Value Creation

Tsai & Ghoshal

1998

Inter-unit resource exchange creates value that no unit can claim individually

Network ties between departments generate productivity gains that appear in no unit's performance metrics

Team Incentives and Worker Heterogeneity

Hamilton, Nickerson & Owan

2003

Empirical study of a garment manufacturer's shift to team production

High-ability workers joined teams despite lower individual pay, suggesting team attribution problems are partially self-selected but still persist

Paying for Performance: A History of Compensation

Milkovich & Wigdor

1991

Review of compensation system effectiveness across firm sizes

Attribution ambiguity grows sharply with firm size; large firms revert to tenure-based pay as a second-best solution

Multitasking and Soft Information

Baker

1992

When agents perform multiple tasks, incentivizing one distorts effort on others

Firms with complex interdependent workflows face a fundamental tradeoff: reward measurable tasks and lose unmeasured effort

Corporate Budgeting is Broken

Jensen

2001

Budget processes in large firms produce systematic gaming

Attribution uncertainty incentivizes sandbagging and internal negotiation over actual productivity improvement

Hidden in Plain Sight: Productivity and the Org Chart

Weil

2014

Fissured workplace structures (outsourcing, franchising) obscure which entity drives productivity

As production is fragmented across legal entities, attribution becomes structurally impossible even in principle


The point is that in large organizations,  it will be difficult to impossible to know with certainty how much individuals and whole departments actually contribute to firm outcomes, with or without AI


Few of us are perhaps happy that significant layoffs are happening, or will happen, in many large firms in many industries. On the other hand, none of us can actually “prove” that all those workers, in all those areas, are actually contributing to outcomes we can measure. 


This might be one of those instances where all we can do is act, see what happens, and then adjust if necessary.


If we assume that, for most firms, higher costs are not a good thing, then lower costs, with same or higher output, are preferable, generally speaking.


And if we cannot measure the impact of contributions, then the equivalent of pruning a plant might not be irresponsible. 


Generative AI vs Agentic AI vs AI Agents


Read on Substack

Sunday, March 22, 2026

"It Depends" Might be the Answer to the Question of "Can We Reduce Workweeks to 4 Days"

Some tests of a four-day workweek suggest output can be maintained, compared to a five-day workweek, at least in a test. Some skeptics might wonder whether the stable output, 20 percent less work time pattern can be maintained in a permanent, post-test environment, as studies in the past have shown that output improves when people are in a test situation. 


That Hawthorne effect refers to a behavioral observation that people change (usually improve) their performance or behavior simply because they know they are being observed, studied, or given special attention, and not because of the actual intervention being tested. 


For example, medical personnel hand washing increased 55 percent when personnel were in a test of hand washing. 


The point is that we cannot generalize from the results of limited-time tests because there is a significant possibility that output or behavior actually improves simply because people know they are being watched and evaluated. 


The principle was first discovered in the Hawthorne Works experiments (1924–1932) at a Western Electric factory in Cicero, Illinois. Researchers tested variables such as lighting levels, rest breaks, shorter days, and work structure changes on relay-assembly workers. 


Productivity rose in almost every condition (even when lighting was dimmed), and it often fell back to baseline once the study ended. 


Analysts later concluded the gains stemmed from the workers feeling noticed by researchers and supervisors, forming a cohesive “special” group, receiving sympathetic oversight, and the sheer novelty of being part of an experiment.


And that is the issue: it is not clear that a permanent four-day workweek would permanently sustain the “same productivity or output” as a five-day week, as we know that awareness of scrutiny can temporarily boost output, temporarily. 


We might also argue that employee well being is enhanced, but that productivity might not be similarly improved. It is hard to evaluate the productivity implications of “burnout,” for example. Many of us might note casually that many workers do not seem to produce as efficiently on Friday as at the beginning of the workweek, for example. 


In other words, the marginal output on day five might be low enough that a shorter workweek might possibly not damage overall productivity very much. 


There also is the Pygmalion Effect (also called the Rosenthal effect or teacher expectancy effect), a psychological phenomenon where higher expectations from one person (a leader, teacher, or supervisor) lead to improved performance in another through a self-fulfilling prophecy. 


It operates via subtle behavioral changes: when expectations are raised, the "expecter" provides more support, opportunities, feedback, encouragement, and trust; the "expectee" internalizes this, boosts self-efficacy and motivation, expends greater effort, and ultimately performs better, often confirming the original high expectations.


The Hawthorne Effect is a legitimate reason to view short-term pilot results with healthy skepticism. On the other hand, accumulating evidence from longer follow-ups, real-world scaling (Iceland), and high continuation rates indicates that genuine efficiency gains, reduced fatigue, and better focus from the shorter schedule are also at work. 


One might argue that if output over a four-day week remains at least the same as was seen with a five-day week, then the prior level was substantially suboptimal and inefficient, involving waste, fatigue-driven drag, and diminishing (or even negative) marginal returns on the fifth day or later hours.


The law of diminishing marginal returns applies to labor hours just as to other inputs. Adding hours beyond 35 to 48 per week (context-dependent) yields progressively less additional output per hour, as fatigue, errors, and disengagement rise. 


The point is that longer working hours might lead to output-per-hour falling as total hours climb. 


In trials, workers might have achieved the same (or more) total output in 20 percent less time by becoming more focused and rested. Also, less procrastination, fewer unnecessary meetings, and less "performative" busyness might also have occurred. 


In that view, the fifth day wasn't "producing" proportionally; it was often recovery from the first four. Hidden costs (burnout, sick days, turnover) made the five-day model less efficient societally. In other words, we weren't as productive as we thought, we were just working more.


Long-term, recovered workers sustain higher innovation and lower error rates.


Of course, in some cases there is an opportunity cost. In theory, that fifth day could fund deep work, skill-building, research or development collaboration, or innovation sprints that compound future output far beyond maintenance. 


A hyper-optimized culture might squeeze even higher total production by treating every hour as investment rather than default leisure.


Much could hinge on the type of firm; the outputs; employee commitment and other inputs. Dysfunctional firms are unlikely to suddenly be transformed into high-performance firms simply by reducing hours. 


It might be the case that ‘working smarter” outperforms grinding longer, at least for firms that are well run; have high worker buy-in; good management; are highly dependent on creativity and have other hallmarks of high-performing organizations.


There are likely meaningful differences in how a four-day workweek affects different types of firms. 


Creativity or insight-dependent organizations such as R&D labs, research institutes, artistic/creative agencies, design firms, innovative tech/product development might benefit more directly. 


Firms whose output is standardized or routinized, such as customer service contact centers, routine manufacturing or assembly, standardized professional services like basic admin or call handling, retail operations, or shift-based public services like certain nursing or police functions might be more likely to see lower output, as they are a function of “hours available.”


The point is, there might not be one universal answer to the question “can we reduce workweeks from five to four and still maintain present output.”


If You Can't Measure Productivity in a Large Organization at the Individual or Department Level, What Do You Do?

It is nearly impossible to granularly know which employees and departments in any large organization really contribute to firm outcomes. Sin...