Showing posts sorted by relevance for query productivity paradox. Sort by date Show all posts
Showing posts sorted by relevance for query productivity paradox. Sort by date Show all posts

Saturday, December 12, 2020

Work from Home and the Solow Productivity Paradox

It is easy, but perhaps wrong, to attribute many types of change to “Covid-19” or the responses made to the pandemic. To be sure, the prevalence of work-from-home, learn-from-home modes required by governments to slow the spread was a precipitating event. It arguably speeded up trends already in place and convinced larger numbers of people and firms to consider joining trends, such as substituting Zoom video conferences for older meeting formats. 


With good reason, increased amounts of work from home are viewed as a permanent shift in venues where many types of work are done on a routine basis. The conventional wisdom is that hybrid models will dominate, with more workers spending parts of the week working from home, rather than “in the office.”


source: Researchgate  


But it is worth noting that this “remote work” trend has been in place and growing for more than 50 years, though we used to call it “telecommuting.” 


source: Federal Reserve Bank of St. Louis 


The point is that forecasters have expected a huge increase in remote work patterns for quite some time. 

Source


So it might be safe to say that belief in permanent change of remote work arrangements will happen. But the change might be more gradual than some believe. 


There might be unexpected barriers in the form of cost issues, as has proven true in the past, for at least some firms. 


More importantly, it is hard enough to measure office worker productivity at all. It will be devilishly difficult to determine what impact on productivity remote work in large doses might produce. 


Obviously, at some level of productivity (higher, same, lower), many types of work can be performed remotely, at home. 


source: McKinsey


But productivity is an issue. To be sure, most of us assume that higher investment and use of technology improves productivity. That might not be true, or true only under some circumstances. 


Investing in more information technology has often and consistently failed to boost productivity.  Others would argue the gains are there; just hard to measure.  There is evidence to support either conclusion. 


Most of us likely assume quality broadband “must” boost productivity. Except when it does not. The consensus view on broadband access for business is that it leads to higher productivity. 


But a study by Ireland’s Economic and Social Research Institute finds “small positive associations between broadband and firms’ productivity levels, none of these effects are statistically significant.”


“We also find no significant effect looking across all service sector firms taken together,” ESRI notes. “These results are consistent with those of other recent research that suggests the benefits of broadband for productivity depend heavily upon sectoral and firm characteristics rather than representing a generalised effect.”


“Overall, it seems that the benefits of broadband to particular local areas may vary substantially depending upon the sectoral mix of local firms and the availability of related inputs such as highly educated labour and appropriate management,” says ESRI.


Most of us are hopeful about the value of internet of things. But productivity always is hard to measure, and is harder when many inputs change simultaneously. Consider the impact of electricity on agricultural productivity.


“While initial adoption offered direct benefits from 1915 to 1930, productivity grew at a faster rate beginning in 1935, as electricity, along with other inputs in the economy such as the personal automobile, enabled new, more efficient and effective ways of working,” the National Bureau of Economic Research says.  


There are at least two big problems with the “electricity caused productivity to rise” argument. The first is that other inputs also changed, so we cannot isolate any specific driver. Note that the automobile, also generally considered a general-purpose technology, also was introduced at the same time.


Since 1970, global productivity growth has slowed, despite an increasingly application of technology in the economy overall, starting especially in the 1980s. 

 

A corollary: has information technology boosted living standards? Not so much,  some say. The absence of huge productivity gains has created what economists call the “productivity paradox.”


Basically, the paradox is that the official statistics have not borne out the productivity improvements expected from new technology.

 

Still, the productivity paradox seems to exist. Before investment in IT became widespread, the expected return on investment in terms of productivity was three percent to four percent, in line with what was seen in mechanization and automation of the farm and factory sectors.


When IT was applied over two decades from 1970 to 1990, the normal return on investment was only one percent.


This productivity paradox is not new. Information technology investments did not measurably help improve white collar job productivity for decades. In fact, it can be argued that researchers have failed to measure any improvement in productivity. So some might argue nearly all the investment has been wasted.


Some now argue there is a lag between the massive introduction of new information technology and measurable productivity results, and that this lag might conceivably take a decade or two decades to emerge.


Work from home trends were catalyzed by the pandemic, to be sure. Many underlying rates of change were accelerated. But the underlying remote work trends were there for decades, and always have been expected to grow sharply. 


Whether that is good, bad or indifferent for productivity remains to be seen. The Solow productivity paradox suggests that applied technology can boost--or lower--productivity. Though perhaps shocking, it appears that technology adoption productivity impact can be negative.

Thursday, February 20, 2025

We All Believe Computing is Prodcutive, But Struggle to Measure It

Though virtually everybody would agree that computing technologies are useful, enabling and productivity-enhancing, we still find it difficult to precisely quantify the gains.


For starters, the U.S. Bureau of Labor Statistics, which tracks productivity, does not break out the actual “causes” of productivity change by source. It studies “total factor productivity” only, so all we can say is that all information technology likely contributes a non-zero amount to productivity change.

source: Economic Strategy Group 


Also, the U.S. Bureau of Labor Statistics, measures employee productivity by calculating “output per hour” of work. That’s a measurement problem because we have to create proxies for “output.” And most quantitative measures you might think of might, or might not, also represent “productive output.” 


You might measure the volume of emails generated, lines of code written or some other quantitative activity metric. But you probably are skeptical that such “inputs” are really “outputs.” And we are likely looking at correlations rather than causation in any case. In other words, higher IT investment might be correlated with higher outputs, but we cannot say for certain how much the IT investment “caused” or “lead to” the estimated productivity gains. 


Study

Key Findings

Measurement Method

Advanced Workplace Associates & Center for Evidence Based Management

Identified 6 factors correlating with knowledge worker productivity at team level

Analyzed academic databases for peer-reviewed research

Time on Task

Measures time spent on specific tasks (e.g., reading x-rays, answering support tickets)

Apps like RescueTime to track time in applications

Completed Intentions

Assesses number of intended tasks completed in a day

Self-reporting of task completion

APQC Research

Found average knowledge worker spends 8.2 hours/week on information-related tasks

Survey of knowledge workers

Qualitative Metrics

Focuses on how workers feel about their work

End-of-day questionnaires with agree/disagree statements

Empowered Productivity System

Trains workers to use workflow management system

Organizational implementation and observation

McKinsey Research

Explored productivity barriers in knowledge interactions

Daily logs of knowledge interactions from workers at multiple organizations

Situational Metrics

Develops metrics specific to type of work (e.g., software development cycle length, bug count)

Custom metrics for each knowledge work type

Modern Intranet Analytics

Measures intranet usage trends, content performance, and employee engagement

SharePoint analytics tools



If outputs are intangible and difficult to define, so are “results” produced by teams rather than individuals. 


And since we are measuring “output by hour,” that is an obvious problem where salaried employees are evaluated. The “hours” denominator is uncertain. The problem is worse with remote and mobile working. 


All that will be worth keeping in mind as artificial intelligence increasingly is deployed across industries and economies. We’ll be looking to measure output changes that might be quite subtle and subjective. 


Period

Labor Productivity Growth (Annual)

Trends

1980s

2.0%

Slowdown from previous decades 1

1990s

2.9%

Productivity surge, partly attributed to IT advancements 1,7

2000-2004

2.9%

Continuation of 1990s productivity growth 7

2004-2023

1.5%

Long-term decline in productivity growth 7

2023

2.7%

Recent uptick, approaching 1990s levels 7


If past experience provides any guide, it is that the actual net impact of AI will be very hard to measure, and might or might not actually produce an identifiable productivity boost in the near term. In the past,  positive productivity impact has often taken some time--as much as a decade--to correlate with higher productivity growth rates. 


Study

Date

Publisher

Key Conclusions

The Impact of Information Technology on Worker Productivity: Firm-Level Evidence

1999

The Quarterly Journal of Economics

Found a strong positive correlation between IT investment and labor productivity growth.

Does Information Technology Cause Productivity Growth?

2000

American Economic Review

Concluded that IT investment alone does not guarantee productivity gains; effective implementation and organizational change are crucial.

The Productivity Paradox: Are Computers a New Age of Diminishing Returns?

1999

Harvard Business Review

Explored the idea that early IT investments may not have yielded significant productivity gains due to factors like learning curves and organizational adjustments.

Measuring the Impact of Information Technology on Productivity Growth

2001

Brookings Institution

Examined various methodologies for measuring IT's impact on productivity, highlighting the challenges of isolating the effect of technology from other factors.

Information Technology and Productivity: A Review of the Literature

2002

Journal of Economic Literature

Provided a comprehensive review of existing research on IT and productivity, summarizing key findings and identifying areas for future research.

The Diffusion of the Internet and the Productivity Paradox

2004

Review of Economic Studies

Investigated the role of the internet in productivity growth, finding that its impact may be more significant in the long run as businesses adapt and integrate internet technologies.

Does IT Really Matter?

2005

MIT Press

Explored the broader societal and economic impacts of IT, beyond just productivity, considering factors like job displacement, income inequality, and social change.

The Productivity Paradox Revisited: Resolving the Debate

2006

Information Economics and Policy

Re-examined the productivity paradox debate, arguing that earlier studies may have underestimated the impact of IT due to measurement challenges and the time lag between investment and productivity gains.

The Impact of Information Technology on Economic Growth

2008

National Bureau of Economic Research

Analyzed the long-term impact of IT on economic growth, finding evidence that IT has played a significant role in driving economic growth in recent decades.

Measuring the Impact of Information Technology on Productivity Growth

2001

Brookings Institution

Examined various methodologies for measuring IT's impact on productivity, highlighting the challenges of isolating the effect of technology from other factors.

Information Technology and Productivity: A Review of the Literature

2002

Journal of Economic Literature

Provided a comprehensive review of existing research on IT and productivity, summarizing key findings and identifying areas for future research.

The Diffusion of the Internet and the Productivity Paradox

2004

Review of Economic Studies

Investigated the role of the internet in productivity growth, finding that its impact may be more significant in the long run as businesses adapt and integrate internet technologies.

The Economics of Information Technology

2010

Addison-Wesley

Provided a comprehensive overview of the economics of IT, covering topics such as investment, innovation, productivity, and market structure.

The Digital Revolution and the New Economy

2011

Oxford University Press

Explored the broader social and economic transformations brought about by the digital revolution, including the rise of the internet, e-commerce, and the gig economy.

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