Authors (Names and Percentages): Meihan He 100%
Because of the fast-changing working environment and consultants’ high demand for a more flexible working time, I suggest doing a 12-month study to see if giving consultants flexible working hours (FWH) can increase their productivity and employee satisfaction. We aim to see a 10% increase in productivity and a 5% increase in employee satisfaction rate. By doing this, we can put ourselves at the top of this industry, increasing revenue while satisfying all workers in the company.
The study will contain 100 participants; the study will begin on January 1st, 2025; the length of the study will be 12 months, and it will be split into two periods. From January 1st to June 30th is the pre-treatment period. All participants will work in the office from 9 a.m. to 5 p.m. on weekdays, just like their normal working schedule. From July 1st to December 31st is the post-treatment period (FWH program), all participants will be sent to the FWH program, which means they can choose to work flexibly and choose their desired location to work. Productivity and employee satisfaction will be recorded at the end of each period.
There are two main objectives for this study. First, comparing to the data recorded in the pre-treatment period, we expect to see a 10% increase in average revenue in December 31st after the post-treatment period. Second, we expect to see a 5% increase in employee satisfaction rate during the FWH program. Satisfaction surveys will be given when each period ends.
To best reduce bias, we use the same participants for both periods of the study to improve the credibility. We will be using pair t-tests using R to see the increase in revenue and employee satisfaction rate. We are using R because it gives really useful tools and accurate data for analysis.
The potential benefits in our company are significant. A 10% increase in revenue can greatly increase the company’s overall revenue, strengthening our current position in the market. Increasing the employee satisfaction rate by 5% makes the consultants engage more, it decreases the chance of turning over, and it makes a better culture in the company. In addition, the study will provide empirical evidence to help further studies as well as guide future policies on flexible working arrangements.
To make sure that the study is successful, we have to clarify some operational considerations. Training will be provided to the participants before the FWH program so that they can get all the resources they need to work at their best productivity level. Data security will be implemented to protect company information, such as using VPN and following all IT policies. The study will also meet ethical standards. Everything we do is agreed upon by participants.
We hope to get your consent to this study and request the allocation of necessary resources. This includes IT support, such as access to remote work tools. Also, we are requesting to allow participants to adjust their work time if needed during the post-treatment period. Third, we ask you to give us financial support with any extra costs related to the study.
Implementing flexible and remote work hours can not only potentially increase our consultants’ work productivity and satisfaction rate but also position our company as a leader in the industry. This study offers a chance for us to achieve those benefits, and it can make substantial impacts on future working policies.
Authors (Names and Percentages): Meihan He 100%
Nowadays, society is undergoing a big transformation in the workplace: flexible and remote working has been trending. Technology improvements and high worker expectations have made all companies think about changing the traditional working schedule to a new one. In the consulting industry, productivity and employee engagement are the keys to success. Accepting the new working model gives both opportunities and challenges.
Our consulting company follows the traditional working time, which means consultants work from 9 a.m. to 5 p.m. from Monday to Friday. Although this structure maintains constant performance levels, many people are worried that it is not the way to maximize people’s productivity level and maintain satisfaction. Many people even think rigid working schedules can hinder them from doing their best performance.
To tackle this problem, we propose to implement a 12-month study to see whether remote and flexible work hours (FWH) rather than traditional working schedules are beneficial to the company and to consultants themselves.
Rationale: By estimating every consultant’s important metrics like their revenue and their satisfaction level, the study can help compare with the traditional working-in-office model whether FWH can increase people’s well-being and productivity. Additionally, it positions the company in a working environment that is employee-centered, attracting more talent and fostering a culture that is balanced between working and life.
Authors (Names and Percentages): Meihan 100%
The rise of remote working and flexible working arrangements, especially after the VOVID-19 pandemic, has led the organization to research these trends to increase productivity and employee satisfaction. This literature review talks about how FWH and remote working can affect employees’ productivity and satisfaction level, highlighting the consulting industry’s benefits, challenges, and research gaps.
Some research shows that arranging working time flexibly can help increase productivity and employee satisfaction levels. Jannat et al. (2024) found that during the pandemic, Bangladeshi women only worked from home, and because of that, they felt less stressful while satisfying with their job more, which improved their overall working performance. It can be implied that people adjusting their working schedule based on their needs can better balance between work and life, enhancing their motivation.
Also, Mohiya (2024) reported that in Saudi Arabia, a flexible working schedule provides a better satisfaction level. Benefits include avoiding traffic jams, managing family responsibilities, and in control of their own working time. And this is closely correlated to having a greater productivity.
Paulišić et al. (2024) noted that a workplace’s flexibility can increase satisfaction through being in control of the working environment and working schedule; in this way, employees can have better loyalty to the company by being satisfied with their working place and time, thus contributing more to the company.
However, challenges do appear; Paulišić et al. (2024) highlighted some drawbacks, such as diminishing team morale and feeling a sense of loneliness. Also, lacking face-to-face engagement may hinder communication and cooperation. Jannat et al. (2024) acknowledged that by not clearly differentiating working and personal life can cause boredom, and some people might need organization support to maintain their work-life balance.
There is a notable research gap in the consulting industry. Consulting companies heavily rely on group cooperation, client interaction, and collaboration to solve problems, and this might be affected by the remote and flexible working model. Few studies are done about how to affect consultants’ satisfaction level positively, because satisfying consultants can provide a better service through them, giving the most contribution in the company. This study: giving a 12-month FWH program testing on consultants’ productivity and satisfaction rate, aims to address this gap and solve the problem. It will provide empirical evidence to only the consulting industry by using a within-subject design measuring outcomes before and after the program’s implementation
Authors (Names and Percentages): Yaqi Hou 100%
Will introducing a six months remote and flexible work hours (FWH) program for a consulting company increase their average revenue per consultant by 10 percent within the program period?
In order to investigate this question, we are going to examine the productivity of 100 consultants in two different six-month periods: for the pre-treat, which we called the pre-treatment, from January 1st to June 30th, consultants will follow the regular office time. For the second part of the treatment, which we called the post-treatment, from July 1st to December 31st, consultants will participate in remote and flexible work hours (FWH) program. The metric of performance, productivity, will be measured based on the total income made per consulter during each treatment period.
Null Hypothesis (H0): There’s no significant difference between average revenue per consultant in pretreatment period and the average revenue per consultant in post-treatment period. H0:μpost=μpreH0:μpost=μpre
Alternative Hypothesis (HA): Introducing a six months remote and flexible work hours (FWH) program for a consulting company will increase their average revenue per consultant by 10 percent within the program period.
Will introducing a six months remote and flexible work hours (FWH) program for a consulting company increase their employee satisfaction by 5 percent within the program period?
To study this question, we are going to examine the employee satisfaction rate at the end of both pre and post treatment period. Employee satisfaction will be measured by using a validated survey instrument. The survey will examine employee satisfaction rate from different areas, topics like the overall satisfaction of their work-life balance, autonomy and working conditions will be included in the survey.
Null Hypothesis (H0): Introducing a six months remote and flexible hours (FWH) program will not effect employee satisfaction in the consulting company within six months(the program period).
Alternative Hypothesis (HA): Introducing a six months remote and flexible hours (FWH) program will increase employee satisfaction in the a consulting company by 5 percent within six months (the program period).
Revenue per Consultant: this variable represents the total revenue made per consultant in every six-month period. This is a continuous variable that uses currency (e.g., dollar) as a unit, and this variable is the direct index of personal productivity.
Employee Satisfaction rate: this variable shows each employee’s (consultant’s) level of satisfaction for work. This variable will be collected by employee responses to a standardized survey (responses to a standardized survey (e.g., the Job Satisfaction Survey) on a Likert scale ranging from 1 to 5. the Job Satisfaction Survey) on a Likert scale ranging from 1 to 5. It reflects employee’s subjective evaluation of their work-life balance, autonomy and work conditions.
Work Arrangement (Time Period):The independent variable is the different types of work arrangements that employees participated in each treatment period.
Pre-Treatment Period: Standard in-office work hours (January 1st to June 30th).
Post-Treatment Period: Remote and flexible work hours program (July 1st to December 31st).
By having the same group of consultants participate in both time periods, the study avoids the chance of differences between people that could affect the results. This makes the findings more reliable. Moreover, by studying the same group of consultants before and after the FWH program, it’s easier to make direct comparisons of how their performance and satisfaction change.
Since the yearly growth rate in the consulting industry usually ranges from 3% to 5%, a 10% increase in revenue per consultant within 6 months is significant. Get this notable improvement in just six months would suggest that the FWH program may boost productivity a lot. This could be because consultants can work during their most productive hours and spend less time commuting, which allow them to focus more on their work.
Siimilarly, a 5% increase in employee satisfaction is also a meaningful result because it helps both employee and the company. Satisfied employees are often more motivated, perform better, and feel more committed to their company’s goals. This improvement support findings from other studies about how flexible work arrangements can have a positive impact on job satisfaction.
Authors (Names and Percentages): Yawen Ren 100%
This study will focus on full-time consultants. The participants need to be have been working at least one year to ensure they have sufficient working experience in the company. Additionally, their job needs to be conducive to both in-office and remote work settings. These requirements ensure that participants are representative of the firm’s consulting staff and capable of participating in both phases of the study.
Authors (Names and Percentages): Yawen Ren 100%
There are 100 participants included in the study. Because the research employs a within-subject design, the individuals will be observed during both the pre-treatment and post-treatment periods. This approach controls the differences between individuals and enhance the reliability when comparing between the two working arrangements. All participation is voluntary and informed consent will be obtained from all participants before the study
Authors (Names and Percentages): Yawen Ren 100%
The study spans 12 months, divided into two phases:
Pre-Treatment Phase (January 1st - June 30th): Participants need to work in the office from 9 a.m. to 5 p.m., from Monday to Friday. During this period, data on revenue generated by each consultant and employee satisfaction levels will be collected. At the end of this phase, participants will need to complete a survey of job satisfaction to assess baseline of satisfaction levels.
Post-Treatment Phase (July 1st - December 31st): Participants will transition to the remote and flexible working time program. They will be allowed to work remotely and arrange their working time themselves if they can meet the program deadline and regularly communicate with their team. Additionally, before it starts, there will be a training session to help consultants familiarize themselves with their remote work technologies.
Throughout the study, researchers need to minimize their interference with participants’ daily activities to avoid influencing their behaviors. Researchers will schedule regular checks to address any concerns and ensure smooth of data collection processes.
Authors (Names and Percentages): Yawen Ren 100%
December (Prior to Start): Recruitment of participants, obtaining informed consent and initial briefing sessions.
January 1st - June 30th: Pre-treatment phase with standard in-office work hours, baseline data will collect at the end of this period.
Late June: Training on remote work tools and flexible work policies prepare for the post-treatment phase.
July 1st - December 31st: Post-treatment phase with remote and flexible work hours; last data collection at the end of this period.
January (Following Year): Data analysis and preparation of findings.
Authors (Names and Percentages): Yawen Ren 100%
Revenue data are from the internal financial records, which captures the total revenue every consultant generates during both six-month periods. Employee satisfaction will be measured using standardized survey instrument, such as the Job Satisfaction Survey (JSS). The survey assesses will be administered at the end of each phase electronically. The survey assesses working satisfaction in various metrics, including working condition, autonomy, work-life-balance, by a Likert scale.
Authors (Names and Percentages): Yawen Ren 100%
All data collected will be treated with strict confidentiality. Personal identifiers will be removed, every participant will be assigned a unique code to anonymize data. Additionally, electronic data will be stored in a safe and encrypted servers that are only accessible to the research team. Responses of survey will be collected through qualified secure platforms. The study will adhere to ethical guidelines, ensuring that all information will only be used for research purposes and follow that participants’ privacy is safeguarded.
Authors (Names and Percentages): Yawen Ren 100%
Revenue per Consultant: This variable reflects the total revenue every consultant generates during each six-month phase. This is a continuous variable measured in monetary units (e.g., USD) as an objective indicator of individual productivity.
Employee Satisfaction rate: This ratio is derived from the survey responses, which reflect the overall working satisfaction from each consultant. It is measured on a Likert scale (e.g., 1 to 5), with higher rate indicating better satisfaction. The survey collects various subjective evaluation metrics, such as flexibility, workload, and workplace environment.
Authors (Names and Percentages): Yawen Ren 100%
Work Arrangement: The independent variables are the working arrangement for the participants in each research phase:
Standard In-Office Work Hours: Standard in-Office Work Hours: Fixed working time in the office, from 9:00 a.m. to 5:00 p.m.
Remote and Flexible Work Hours: Participants can work in remote, arrange their work time with flexibility provided they meet professional tasks.
Authors (Names and Percentages): Yawen Ren 100%
To control for potential confounding factors, Additional data will be collected in the analysis for the first question:
Years of experience: Number of years each consultant has been employed by the firm, limited to 1 - 10 years of working experience.
Client type: Whether they are doing a consultation for small, medium or large companies.
Additional data will be collected in the analysis for the second question: - Age: Consultants’ age in years, restricted between 25 to 40. - Role: Whether they are junior or senior staff. - Years of experience: Number of years each consultant has been employed by the firm, limited to 1 - 10 years of working experience.
Collecting these variables allows for more nuanced analysis and helps ensure that any observed effects can be more confidently attributed to the change in work arrangement rather than other factors.
Authors (Names and Percentages): Nanshuo Wu 100%
Paired t-tests will be used to address both research questions. This test is appropriate because it compares the means of the same individuals or groups under two conditions—in this case, the same consultants measured before and after the FWH program. We will also simulate 1,000 experiments to test the reliability of the paired t-tests in detecting true effects.
For revenue per consultant, the paired t-test will compare the mean revenue generated during the standard in-office period (pre-treatment) with the mean revenue during the FWH program (post-treatment). Similarly, for employee satisfaction rate, the test will compare mean satisfaction rate obtained from surveys administered at the end of each period. Therefore, we chose the paired t-test because it is quite straightforward and aligns with the research questions which are focused on mean differences for both of the dependent variables.
Authors (Names and Percentages): Nanshuo Wu 100%
Sample Size and Statistical Power
For both research questions, sample size and statistical power are calculated using Cohen’s d effect size and the pwr.t.test() function from the pwr package.
For the first research question, the effect size was set to 10%, where we expected the mean difference of the average revenue per consultant is 10% of the pre-treatment $50,000. The 10% was based on our assumptions on the revenue differences in the consulting industry. We also assumed that the standard deviation of the revenue is $10,000. Based on that, Cohen’s d effect size is calculated as the ratio of the expected mean difference to the standard deviation. For the power test, we used the method of paired t-test, and the significance level of the test is set at 0.05. Similar to a typical threshold for the power analysis, the desired statistical power is set at 0.8, which means there is an 80% probability of detecting a true effect. The required sample size to achieve the power of 0.8 at a 0.05 significance level is approximately 33.36.
For the second question, the power test process is the same as the first question. The expected mean difference in satisfaction is set to 5 units, representing a 5% increase. While the standard deviation of satisfaction differences is set to be 10 units. This gives us the same Cohen’s d effect size, and by using the powered t-test for the power test, the suggested number of samples for the second hypothesis by R with power calculation is 33.36 as well.
However, our group has decided that in a consulting company setting, the consulting industry can exhibit high variability due to differences in consultants’ skills, client portfolios, and market conditions. A larger sample size (100) provides better coverage of this variability, ensuring the results are more representative of the entire population of samples in the company. We also want to reduce the risk of drop out by choosing larger sample sizes and increase our precision of the test. Moreover, we plan to account for several confounding variables, therefore, the sample size of 100 would be adequate for us to conduct our analysis and ensure a relatively accurate outcome for both research questions.
Authors (Names and Percentages): Meihan He 100%
If, according to our analysis, there’s no significant improvement in consultants’ revenue and employee satisfaction after implementing the 6-month remote and FWH plan, it’s recommended to maintain the current work arrangement in the office. This indicates that the FWH working mode cannot bring the expected benefits in the organization’s working environment. Based on this result, it’s suggested to explore other alternative strategies that can improve productivity, which could include but not limit to optimizing working process, investing in professional development programs, and introducing a performance-evaluating incentive system to motivate consultants. In terms of customer satisfaction, if we cannot observe significant improvement, it indicates that factors other than working arrangements are affecting employees’ attitudes towards work. Examining other factors through employee surveys and focus group investigations will be helpful. Collecting direct feedback from workers can help the organization find out underlying issues, such as workplace culture adjustments and career progression opportunities. Prioritizing solving these problems could improve employee satisfaction more than merely changing work schedules.
If the research reveals remarkable improvement in consultants’ revenue and employee satisfaction after the FWH program, considering launching the flexible working schedule in the long term will be beneficial. The positive result indicates that the FWH program can profoundly increase productivity and employee benefits. To support this adjustment, it’s necessary for the firm to develop strategies that can promote remote working. Some of them may include implementing relevant technologies, providing training for using remote-working tools, and formulating clear guidelines for communication and collaboration expectations. Highlighting the benefits of flexible working with employees can enhance the company’s branding image as an employer. Emphasizing the story of success and positive experiences can endorse the culture of work-life balance and employee autonomy. The firm can improve employee satisfaction by executing additional strategies like recognition of employee achievement, healthcare support, and career advancement to amplify FWH’s effectiveness. By captivating an environment that is not only productive but also satisfies employees, the organization can sustain more talented employees and business achievement.
Authors (Names and Percentages): Meihan He 100%
One important constraint is the possibility that employees may not completely follow the working arrangement. During the FWH program, some consultants may not fully utilize flexibility due to personal preference, lack of self-management, or inappropriate working environments in their family settings. In contrast, at the initial stage of treatment, some employees may use the flexibility improperly, disregarding the standard schedule. This personal violation of rules may blur the difference between the two periods, which may diminish the observable effects of the FWH program. Due to the variation in compliance, it will be risky to attribute changes in employee revenue and satisfaction solely to working arrangements.
The accuracy of the collected data can be affected by potential errors in measurement. Although each consultant’s revenue is an objective metric, it can also be influenced by other external factors that are out of personal control; possible factors include market fluctuations, client availability, and project cycle. These aspects can cause revenue changes that are not due to working arrangements. Employee satisfaction is evaluated by self-reports, which are easily influenced by social bias. Participants may give out their responses based on socially desirable expectations rather than reflecting their real feelings, in turn affecting the soundness of the satisfaction data.
Findings from our research have limited generalizability to other industries and organizations. Specific culture, operational practices, client base, and internal dynamics in consulting firms play an important role in shaping the effects of the FWH program. Methods that are proven effective under this unique environment can result in different outcomes in companies with different structures, industries with different needs, and cultures with different attitudes towards remote working. As a result, it should be really cautious to apply the study’s result to broader contexts without considering other unique traits in different environments.
Measurements of uncontrolled variables can also influence the research results. External economic conditions, such as economic recession or industry downturn, can affect revenue independently from working arrangements. Additionally, consultants’ personal factors, such as health issues, family responsibilities, and significant life occasions, will also affect their productivity and satisfaction, but these cannot be quantified or adjusted in the analysis. Team dynamics and the level of management support may also differ during two periods, which further makes it complicated to attribute observed changes to the FWH project.
Although we strengthen the study result by using the within-subject design to control individual variation, it cannot rule out the possibility of confounding variables. The designed time range of the study’s implementation means that anything else that happens within the same period as the FWH project can affect the result. For example, during the research period, organizational reconstruction, leadership rearrangements, or the introduction of new technologies can also influence productivity and satisfaction. Therefore, it needs to be cautious if causality is attributable merely to the FWH program. The study’s result shows a relationship but cannot prove that FWH is the detrimental causation of any observed changes.
Recognizing these constraints is crucial for understanding and analyzing the research result. We need to ensure the conclusion is fair and genuine by assessing the potential measurement errors, limiting generalization, uncontrolled variables, and precise interpretations. In future experiments, more controlled groups from other organizations can be included to increase broader application, a longer experimental period can be launched to alleviate temporal effects, and a mixed-method approach can be employed to understand employee experiences more deeply. Though certain challenges arise from this study, the result provides valuable insights to help provide strategic information to organizations in need of flexible working schedules.
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Jannat, H., Saif‐Ur‐Rahman, K., Noor, I. N., & Begum, A. (2024). Job satisfaction and performance among employed Bangladeshi women working from home during COVID‐19 pandemic: A cross‐sectional study. Health Science Reports, 7(8), e2306. https://doi.org/10.1002/hsr2.2306
Mohiya, M. (2024). An investigation into employees’ factors of flexible working hours (FWH) for productivity in Saudi: A mixed qualitative triangulation. Humanities & Social Sciences Communications, 11(1), 440. https://doi.org/10.1057/s41599-024-02929-2
Paulišić, M., Vizjak, M., & Elhawari, M. M. (2024). Workplace Flexibility: Identifying New Trends and Directions from the Grey Literature Sources. Organizacija, 57(2), 127–138. https://doi.org/10.2478/orga-2024-0009
Social Impact
The result of study could impact more than just our organization. Showing that remote and flexible work improve productivity and employee satisfaction might encourage other consulting firms to do the same practices, which could help promote a better work-life balance across the industry, and can lead to happier and healthier employees. Besides that, flexible work models can address all kinds of employees’ needs, such as helping employees with caregiving responsibilities or health challenges, which make it easier to support diversity and inclusion. This study provides valuable insights into how flexible work can benefit employees and organizations. These findings could shape workplace standards in the industry. Moveover, it can inspires more companies to create policies that care for employees’ well-being and make workplaces more supportive and inclusive for everyone. Sustainable Improvements If the FWH program proves successful, it could lead to long-lasting changes within our organization. Flexible work arrangements might become a normal part of our culture, help us attract top talent and stand out as a great place to work. Continued improvement in productivity and employee satisfaction can encourage innovation, make the company more flexible, and cann help us handle future challenges.
By trying out and adopting new work models, we show that we are forward-thinking and adaptable. This not only benefits employees by improving their work experience, keeps clients happy with better service, and helps set new standards in the consulting industry, but also shows that we are not just meeting today’s needs but also preparing for the future of work.