Does Working From Home Work?

Evidence from a Chinese Experiment

Introduction

Marissa Meyer’s ban on working from home (WFH) at Yahoo in 2013 caused a media storm over the costs and benefits of this rapidly growing practice. Is it encouraging employees to “shirk from home”? Or is it one of the major benefits of portable computing?

In the United States, the proportion of employees who primarily work from home has more than tripled over the past 30 years, from 0.75% in 1980 to 2.4% in 2010. At the same time, the wage discount from primarily working at home has fallen, from 30% in 1980 to zero in 2000. WFH now spans a wide spectrum of jobs, ranging from sales assistants and realtors to managers and software engineers.

Internationally, WFH also appears to be common. In a telephone survey we ran on more than 3,000 medium-sized manufacturing firms in 2012-2013, we found that the share of managers allowed to WFH during normal hours in the US, UK and Germany is almost 50%. The share in many developing countries is also surprisingly high, at 10% or 20%.

Is WFH a useful management practice for raising productivity and profitability? Even within a single industry, practices often vary dramatically. For example, call-center employees at JetBlue Airlines all work from home, American Airlines does not allow any WFH, and United Airlines has a mix of practices. Another issue is the potential of WFH to address concerns over work-life balance.

To address these issues systematically, the authors of this paper worked with Ctrip, China’s largest travel agency, to run a scientific experiment.

The Experiment

Ctrip, which has 16,000 employees and a NASDAQ valuation of nearly $10 billion, was interested in the potential of WFH to reduce its high office rental costs and annual staff turnover of 50%. At the same time, managers worried that allowing employees to work away from the direct oversight of their supervisors would lead to a large increase in shirking.

Given the uncertainty surrounding the effects of WFH in the research literature as well as in practice, Ctrip decided to run a randomized controlled trial. The authors assisted in designing the experiment and, whenever feasible, our recommendations were followed by management. We had complete access to the resulting data, as well as to data from surveys conducted by the firm. We also conducted various surveys ourselves and numerous interviews with employees, line supervisors and senior management.

In this nine-month experiment, Ctrip asked the 996 employees in the airfare and hotel departments of its Shanghai call center whether they would be interested in WFH four days a week, with the fifth day in the office. Approximately half of the employees (503) were interested, particularly those who were married, had children and faced long commutes. Of these, 249 were qualified to take part in the experiment by virtue of having at least six months’ tenure, broadband access and a private room at home in which they could work. After a lottery draw, those employees with even-numbered birthdays were selected for WFH, while those with odd-numbered birthdates stayed in the office to act as the control group.

Office and home workers used the same IT equipment, faced the same work order flow from a common central server, carried out the same tasks and were compensated under the same pay system, which included an element of individual performance pay. The only difference between the two groups was the location of work. This allows us to isolate the impact of WFH versus other practices that are often bundled alongside this practice in attempts to improve work-life balance, such as flexible work hours. Importantly, individual employees were not allowed to work overtime outside their team shift. In particular, eliminating commuting time did not permit the treatment group to work overtime, so this is not a factor directly driving the results.

This experiment is, we believe, the first randomized experiment on WFH. As such, it also provides causal evidence to supplement previous case-study and survey research. It is also unusual in that it involves a randomized controlled experiment within a large firm. Moreover, we were also granted exceptional access not only to data but also to Ctrip management’s thinking about the experiment and its results. This was because one of the co-authors of this paper, James Liang – the co-founder and current chairman and CEO of Ctrip – was a doctoral student at Stanford GSB while we were working on the project.

Results

We found several striking results. First, the performance of the home workers went up dramatically, increasing by 13% over the nine months of the experiment. This improvement came mainly from a 9% increase in the time worked during their shifts, due to reductions in breaks, time off and sick days. The remaining 4% improvement came from an increase in productivity per minute. The wages of the WFH group also rose by 9.9%, equivalent to about ¥250 ($40) extra a month from higher bonus payments.

In interviews, workers attributed the increase in time worked to the greater convenience of being at home (for example, the ease of getting lunch or using the toilet). The WFH group started work more punctually, avoiding the impact of events like bad traffic or the heavy snow. They could also schedule personal matters, such as doctor’s appointments, in the time they saved by not commuting. The increased output per minute was attributed to the relative quiet at home. This suggestion matches the psychology literature, which has shown that background office noise can reduce cognitive performance.

Second, there were no negative effects on the employees left working in the office. Comparing the control group to similar workers in Ctrip’s other call center in the city of Nan Tong, which was not involved in the experiment, we see no performance drop despite the control group’s having lost the treatment lottery. (The group winning the treatment lottery saved themselves nine months of commuting time and costs, worth about 17% of their salary.)

Third, rates of staff turnover fell sharply among the home workers, dropping by almost 50%. (For policy evaluation we would ideally adjust for the fact that no other Shanghai call centers offered WFH – if all firms introduced WFH the reduction in quit rates would presumably not be as dramatic.) Home workers also reported substantially higher work satisfaction and less ‘work exhaustion’ in a psychological attitudes survey.

Fourth, one downside of WFH appears to be that, conditional on performance, it was associated with reduced rates of promotion of about 50%. We found that employees performed substantially better at home but did not get promoted any faster, suggesting some offsetting negative impact of being at home. One story that is consistent with this is that home-based employees are “out of sight, out of mind” – the perception of promotion ‘discrimination’ led some employees to return to the office. Another possibility is that WFH employees lack opportunities to develop interpersonal skills and therefore are less likely to be promoted. A third explanation is WHF employees do not apply for consideration for promotion because they do not want to return to the office. This might be especially the case among more productive, better paid home workers, who have less to gain from promotion.

There are some obvious concerns with these results. First, was quality sacrificed for quantity by the home workers? Using two different quality metrics, we found no impact on quality of WFH. Second, perhaps our results are driven by attrition bias. It turns out that in fact our results probably are biased by attrition, but biased downwards, so the true impact of WFH is probably substantially larger.

The overall impact of WFH was striking. The firm improved total factor productivity by between 20% to 30% and saved about $2,000 per year per WFH employee. About two thirds of this improvement came from the reduction in office space and the rest from improved employee performance and reduced staff turnover.

This success led Ctrip to offer the option to work from home to the entire firm. It also allowed members of the treatment and control groups to re-select their working arrangements. Surprisingly, more than half of all the employees changed their minds. In particular, two thirds of the control group (who had all volunteered for WFH 10 months earlier) decided to stay in the office, citing concerns over loneliness. In addition, half of the treatment group changed their minds and returned to the office – especially those who had performed relatively badly at home, but also those who found the lack of social contact particularly costly.

This learning and re-selection caused the longer-term impact of WFH on employee performance to rise to 22%, almost double the direct experiment effect of 13%. The reason was strong selection effects: WFH workers who performed worse over the nine-month experiment period returned to the office, while those who performed well stayed at home. This highlights how selection effects and learning by both the firm and employees can influence the impact of management practices. Both groups were initially unsure about the impact of WFH, and the nine-month experiment and subsequent roll-out process were essential for their ability to evaluate it.

Conclusions

How do our findings compare with previous research? This paper connects to three strands of literature. First, there is a long literature that links the puzzling dispersion of productivity between firms to differences in management practices. Our paper suggests that uncertainty about the efficacy of new practices may play a role in the slow diffusion of these practices, including those addressing issues of work-life balance such as WFH.

The second strand of literature is on the adoption of workplace flexibility and work-life balance practices. It is based primarily on case studies and surveys across firms. These tend to show large positive associations of WFH adoption with lower employee turnover and absenteeism, and higher productivity and profitability. However, most of these studies are hard to evaluate because of the non-randomized nature of the programs.

There is also a connection to the urban economics literature. Reducing the frequency of commuting will reduce vehicle miles travelled, lowering emissions, but also reducing population centrality as people move out to the suburbs. WFH is also part of the wider impact of IT on firm fragmentation arising from the increasing ease of long-distance communicating. Ctrip has now set up regional offices to employ workers in lower-wage, inland Chinese cities using the same WFH technology used in this experiment.

Why did Ctrip not introduce WFH earlier? First, the firm believed that the private benefits of WFH would be short-lived (if it was successful), as rivals would copy the scheme and use it to drive down commission margins in the travel agency market, while the costs of experimentation would be borne entirely by Ctrip. Second, Ctrip’s senior managers were primarily motivated by career concerns, with limited bonus or equity compensation. As a result, they gained little from a successful experiment, but risked career damage if it failed. James Liang, the chairman and co-founding CEO, played a major role in persuading Ctrip executives to run the experiment. Both factors – risk aversion among senior managers and the threat of imitation – are likely to deter process innovations in other large firms.

What does our experiment tell us about what other firms can expect if they allow WFH? We should note that the job of a call-center employee is particularly suitable for telecommuting. It requires neither teamwork nor in-person face time. Quantity and quality of performance can be easily quantified and evaluated. The link between effort and performance is direct. Yet many occupations have these characteristics, such as writing code, technical support, telesales and basic accounting. Moreover, the lessons of increased productivity from the peace and quiet of home, and large drops in quit rates from greater employee job-satisfaction are likely relevant to most jobs.

This experiment highlights how complex the process of learning about new management practices is. For Ctrip, the lack of precedent in terms of similar Chinese firms that had adopted WFH led them to run this extensive field experiment. Given their success, other firms are now likely to copy this practice. More generally, the large impact on firm performance – about $2,000 per employee improvement in profit and a 20% to 30% increase in productivity – also provides a management-practice based explanation for heterogeneous firm performance.

Our advice is at the very least firms ought to be open to occasional WFH to allow employees to focus on individual projects and tasks. Often opportunity presents itself such as bad weather, traffic congestion from road works or major events (such as the London Olympics) to trial this out for a week or two.

We think WFH can be a win-win for the company and its employees, as Ctrip showed. More firms ought to try it.

“Does Working from Home Work? Evidence from a Chinese Experiment” is published on TAP by permission from its author, Professor Nicholas Bloom. It is based on an article by the same title, researched and written in collaboration with James Liang, D. John Roberts, and Zhichun Jenny Ying.

Nicholas (Nick) Bloom is the William Eberle Professor of Economics at Stanford University, a Senior Fellow of SIEPR, and the Co-Director of the Productivity, Innovation and Entrepreneurship program at the National Bureau of Economic Research. His research focuses on management practices and uncertainty. He previously worked at the UK Treasury and McKinsey & Company.

He is a Fellow of the American Academy of Arts and Sciences, and the recipient of the Alfred Sloan Fellowship, the Bernacer Prize, the European Investment Bank Prize, the Frisch Medal, the Kauffman Medal and a National Science Foundation Career Award. He has a BA from Cambridge, an MPhil from Oxford, and a PhD from University College London.