Stanford Study on Working From Home [PDF]

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Can IT improve work-life balance? Evidence from a Chinese field experiment Nick Bloom (Stanford) James Liang (CTrip) John Roberts (Stanford) Zihchun Jenny Ying (Stanford) September 10 2011 Very Preliminary


Most US employers offer little workplace flexibility

Source: CEA work-life balance report (2010)


Do this matter? To date almost no casual evidence on impact of WLB on firms or employees despite being a recurrent policy and business issue • For example, the Obama’s 2010 CEA report on work-life balance (WLB) stated in the Executive Summary

• Literature is divided between supporters relying on casestudies and surveys (HRM researchers) and opponents arguing firms are profit-maximizing so will adopt good measures anyway


So running a field experiment on home working Working with one of China’s largest travel-agents with over 12,000 employees and worth about $7bn on NASDAQ Opportunity arose because the firm wanted to pilot this, and their Chairman and founder is a Stanford PhD student

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Shanghai based, but a founder previously worked for Oracle in the US, so somewhat US management style


The firm operates two large call centers, where employees are allocated to ≈ 15 person groups

Average age is 23.2, 68% are women, and all have high school but only 39% have tertiary education. Only 15% are married, 9% have children.


Individuals randomized to be allowed to work from by date of birth (even allowed home, odd not)

Lottery over even/odd treatment choice

Working at home

Working at Home

Working at Home


Impact on Individual Performance

Impact on Employees

Firm Impact and Longer-run Research


The experimental details • Experiment takes place in airfare and ticket departments in the Shanghai office. They take calls and make bookings • Employees work 5-shifts a week in teams of about 15 people plus a manager. Hours are fixed by team in advance • Treatment gets the option to work 4 shifts a week at home and one shift a week (all at the same time) in the office. • Of the 996 employees, 508 wanted to take part. Of those 255 qualified (had own-room and 6+ months experience) • Then ran the lottery and even birthdays won. So from the 255 even worked at home and odd were the control group.


Employees that were older, married, with kids, and longer commute more generally wanted to WFH


My prior for the impact on worker performance was negative, in part because of stories like this


And the perception of working from home in the US also seems poor - e.g. top Google image search


In fact performance was significantly better at home

Note: Performance z-scores defined as performance measures which for each group of employees (phone-call takers or order bookers) has been normalized by the pre-experiment standard-deviation and mean. Hence, these are ≈ N(0,1) performance measures


Figure 1. Treatment group performance was higher than the control group for most weeks

Start of the experiment

Performance z-scores defined as performance measures which for each group of employees (phone-call takers or order bookers) has been normalized by the pre-experiment standarddeviation and mean. So pre-experiment mean is zero


Figure 2. This difference between treatment and control was typically significant, even on a weekly basis


Figure 4. And quality measures – like the conversation rates or random call quality assessment scores – did not change Conversion rates (sales/calls)


In terms of magnitudes, working from home led to about 15% more calls, 4% from more calls taken per hour and 11% from more hours


Calls taken per hour went up apparently because it was quieter at home • Employees reported they often got distracted in the office or had problems hearing what the customer said • At home it was quiet and they found it easy to concentrate, increasing their productivity by about 4% • Interestingly, employees reported that for the week around Chinese New Year this positive effect reverses as being at home meant visiting relatives could bug them….


Hours worked rose due to employees working more hours per day (less late arrivals, sick breaks etc) and from more days (less sick days etc)

Notes: Column (2) onwards uses only the Airfare group data as we currently have no leave data for the Hotel group. Standard errors clustered by individual. Excludes long-term sick (employees with more than 1 week continuous sick), with impacts including these even larger.


Impact on Individual Performance

Impact on Employees

Firm Impact and Longer-run Research


Figure 5. It appears (at least some) employees seem to value working from home as attrition is significantly down


Other self-reported (survey) welfare measures are positive, although typically not significant

Airfare and Hotels group employees were administered a survey before (October 2010) and 9 months into the experiment (August 2011)


Psychologists have also been collecting selfreported (survey) ‘work attitude’ data, also showing apparently positive impacts

Work-exhaustion based on Maslach’s Burnout Inventory Survey, from Maslach and Jackson (1970). Employees asked to evaluate their emotional exhaustion on 6 questions like “I feel used up at the end of working day” [feel this way every day, most of the time, sometimes….]. Positive/negative attitudes based on Clark and Tellegen (1988) survey which asks feelings about 16 items. For example, “Cheerful” or “Jittery” [“not at all” (1)…..”extremely” (5)]


Impact on Individual Performance

Impact on Employees

Firm Impact and Longer-run Research


Experiment so successful that the firm is rapidly rolling out WFH and piloting other WLB measures • Results suggest large increases in profits from lower costs of labor, rent and turnover (less hiring and training) • The firm so positive on this that in August 2011 they decided to roll out to the Control group in Airfare and Hotel • Planning in 2012 to roll-out to other groups in Shanghai, and then to groups in their larger call center in Nantong • Also considering pilots of other measures: part-time working, shift-switching and remote working (regional cities) • We will continue to collect data over time and measures


Begs question why they did not do this earlier? • The profit impact appears so large that wonder why this did not happen sooner (it has been possible for a few years)? • The firm only recently started even thinking about this - no other firm in China has put call-center workers at home • So firm was initially unaware of this, and then prior to the experiment unsure of impact (why they ran the experiment) • Consistent with our India evidence (Bloom, Eifert, Mahajan, McKenzie and Roberts 2011) that informational issues part of the slow adoption of modern management practices


Conclusion • Working from home has been enabled by modern IT technologies (they need broadband and cheap PCs) • To date (9 months of data) appears to have improved both firm profitability and apparently worker welfare – improvements sufficiently large firm is now rollling-out • Continuing to monitor the experiment over time and across groups to evaluate larger and longer-run impacts • Also interesting as an example of the spread of one type of modern (IT enabled) management practice


Back Up


US working hours are very long by international standards, almost 50% more than the French in this sample of manufacturing firms


Work-life balance pressures seem to be rising as more households are full-time working

Source: CEA work-life balance report (2010)


In the experiment we found no evidence of any other (short-run) effects – for example spillovers onto other team members



Home-based work background facts (source: Oettinger, 2010 JHR) • About 5 million primary home-based US workers by 2000, growing rapidly from 2.5 million in 1980 (Census) – About 20 million that do some work at home (CPS) • Wages also rising – wage discount of 30% in 1980s for home working appears to have gone by 2000 • Wage and employment increases appear to be largest in occupations that have had the faster increase in IT use • Suggests that IT is improving both numbers and quality of home-working jobs


We visited Jet Blue in Salt Lake City, which is very progressive in terms of home working • Jet Blue allows impressive flexibility of home-working for its call center employees • The reason is this allows it to access highly skilled employees (often college educated women with schoolage kids) that would otherwise not work in call centers • While this is not cheaper than office (or overseas) call centers, it means employees are far higher quality, which given Jet Blue’s quality focus is a big advantage for them


Jet Blue – Office working


Jet Blue – Home working


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