Improving the Quality of The Housekeeping Management Process for Stay at Bridge Suites Hotel

ABSTRACT This research paper studies the housekeeping services in Stay Bridge Suites Hotel, which deals with challenges in managing the Quality of Service (QoS). Since there is no standard procedure for serving customers and the staff is required to perform manual tasks, miscommunications between staff present lead to long waiting times. This problem results in frequent complaints regarding the services, which leads to a bad reputation, low customer retention, and improper utilization of resources. The project aims to identify the root causes affecting the QoS and standardize the housekeeping management process. To achieve these objectives, DMAIC (Define, Measure, Analyze, Improve, and Control) methodology was accomplished. As a result, some of the significant factors that affect the waiting time are manual task allocation, seasonal workload, and lack of supervision. Therefore, a preventive automated solution was proposed regarding the scheduling procedure to decrease the service waiting time.


INTRODUCTION
According to the most recent statistics, the hotel service industry represents 38% of the total value in the World Economic Community. Hundreds of millions of dollars are spent yearly to improve service quality. Furthermore, the poor performance of services is responsible for 30% to 40% of operational costs in the service sector (LE, 2010). Therefore, one of the features of a successful hotel business is the continuous improvement of high-quality services that exceed guests' expectations in every manner, from pre-booking until post-stay. Since customers are much more demanding than ever when it comes to Quality of Service (QoS), understanding their expectations and needs is becoming more critical. This allows the hotel to know how the QoS is defined from a customer point of view, helps to formulate customer satisfaction surveys, and influences visit repetition and word-of-mouth suggestions. To sustain the hotel's current position and thrive in the future, it is vital to offer high-quality services to retain old customers and attract new customers. Some of the main concerns for hotel industries are to be aware of guest expectations, have a standard working procedure, and have skilled staff that delivers high-quality services to guests. Therefore, manual allocation tasks are the major issue to be focused on for causing a long service waiting time. On the other hand, the two factors: high guest waiting time and low QoS had the highest number of ingoing arrows, consequently, they are the main outcomes. Thus, the manual allocation task needs to be eliminated to reduce the service waiting time and increase the QoS.

Eliminating Non-Value Adding Activities
The 5-Whys analysis method was used in this phase to find the root cause of the nonvalue adding activity, which is the manual task allocation as illustrated in the above interrelationship diagram. The 5-Whys technique is an iterative, team-driven procedure that interrogates a problem by repeatedly asking "Whys" to find the root cause of a specific issue.
The number five refers to that five iterations of asking why are usually sufficient to identify the root cause (Harrington & Voehl, 2016). However, in some cases, it may take more or fewer whys, depending on the depth of the root cause (Harrington & Voehl, 2016). This method was used to obtain preventive actions for the non-value-adding activities.
Non-value-adding activity: The HK manager manually allocates the human resources (staff) to services in papers every morning.
To find the root cause: 1. Why? The system does not have the feature of assigning resources.
2. Why? There is no visibility on staff availability status.
3. Why? The system has limited access to the managers and the front office only.
Root cause: The HK staff do not have access to the hotel's system to update their status.
Corrective action: The HK manager and the front office department should all be integrated with the staff inputs in the system to develop an auto-scheduling process that eliminates the manager's manual allocation, resulting in a reduction in the HK services waiting time.

Room cleaning services VS. Other HK services
Providing services to customers represents a deep concern in the housekeeping department, especially room cleaning services, as they consume more effort from HK staff and long-time duration than other services. To illustrate the fact that room cleaning services have the longest waiting time, the average waiting for the time duration of the room cleaning services compared with other services in HK that are sensitive to customer needs or demand such as ordering inventory items (e.g., bed sheets, towel, shampoo) and additional guest requests (customized services).   Table 1 below, the team should select one room and cleaning type to calculate and compare with other HK services. Thus, the lowest standard duration was determined for comparison, the "Daily Cleaning for 1B" equal to 20 minutes.
Compared to the standard time, the graph shows that additional 15 minutes on average were spent in the room cleaning service, which is considered additional waiting time. As the standard duration for the other two services is 15 minutes, approximately two to nine minutes on average are considered as waiting time. Consequently, the graph highlights that room cleaning services have the highest variation compared to the standard time. Hence, the room cleaning service's waiting time should be considered to enhance the QoS of the housekeeping.

Service types VS. Customer waiting time
To investigate more about the relation between the service type and the waiting time, the following hypothesis was tested: H0: Service type does not affect the customer waiting time.

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Journal of Advances in Humanities Research 32 H1: Service type affects the customer waiting time.
A random sample of 12 consecutive days that were exceeding their standard duration was taken to analyze their service waiting duration (day 1 = Monday)

a) Room cleaning service
A regression line has been plotted to study the relationship between the type of service (room cleaning service) and the waiting time, as shown in Figure 4.
The regression equation of the plot is: Y= 41.60 -1.666 x (1)

FIGURE 4: REGRESSION LINE.
From Figure 4, the waiting time of cleaning services on days 4, 5, and 6 increased since these were the weekend days and the demand on the hotel and the cleaning services are much higher on the weekends.
The correlation is equal to -0.627, which indicates a strong negative relationship.
Additionally, as shown in Figure 5, the P-value equals 0.039, which is less than 0.05.

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Hence the H0 will be rejected. Therefore, the room cleaning services affect the customer waiting time.

b) Additional guest requests
The second type is additional guest services, which means more customized services in responding to the guest requests. This type represents the main concern since staff should be highly responsive to the guest's demands. A regression test was accomplished to study the relationship between the additional guest requests service and the waiting time.
The regression equation of the plot is: Y= 24.67 -0.5385x (2)

FIGURE 6: REGRESSION LINE.
As displayed in Figure 6 above, there are different durations plotted for the selected sample since the customized services vary depending on the guest's request. However, the standard time for the additional services should not exceed 15 minutes, and it appears that six points (services) exceed the standard time. Furthermore, there is a negative trend between this type and the waiting time, and the correlation is equal to -0.27, which indicates a weak negative relationship. Also, as indicated in Figure 7, the P-value equals 0.396, which is more than 0.05; hence the decision is failing to reject H0. Therefore, there is no relationship between the additional guest requests and the waiting time.

c) Inventory items order
A regression line has been plotted to study the relationship between the type of the service (Inventory items order) and the waiting time, as shown in Figure 8.
The regression equation of the plot is: Y=24.48-0.2028x (3)

FIGURE 8: REGRESSION LINE.
Figure 8 above illustrates that the waiting time is unstable, and it is due to the different inventory locations (nearest to the rooms) and the availability of the ordered items. Furthermore, the correlation equals -0.082, which indicates that the relationship is a weak negative relationship. Also, as shown in Figure 9 below, the P-value is greater than 0.05. Therefore, the decision fails to reject H0. Hence, there is no relationship between the inventory items order and the waiting time. The relationship between service types and waiting time is illustrated in Table 2

Room Cleaning Standard Duration Vs. Actual Duration
The previous analysis identified the room cleaning service as the highest contributing service type to the waiting time. Therefore, a random sample of 75 room cleaning services was collected from the data to plot a graph of the actual waiting durations versus the standard waiting durations. Since Stay Bridge Suites hotel has three types of rooms, the service duration depends on each type.

FIGURE 10: CLEANING STANDARD DURATION VS. ACTUAL DURATION.
In Figure 10 above, MS Excel was used to plot the actual duration versus standard durations to observe the deviation of the cleaning waiting time of this sample. For instance, the standard time of the two-bedroom in a daily cleaning type would take 30 minutes to complete the service, while with the improper scheduling, the range deviates between 30 to 55 minutes; therefore, the average for the range is 42 minutes of the service duration, and the increase will be 12 minutes increase.

Seasonal periods VS. Customer waiting time
The Interrelationship diagram in Figure 14 shows that the hotel's seasonal workload is a cause of high guest waiting time. As many hotels become super busy and hectic during seasonal periods such as Ramadan, Eid, National Holiday, etc. Furthermore, as the demand increase for the reservations, the guests will occupy most of the rooms. A poor QoS, high workload, and complicated scheduling process will be resulted since the same number of staff is used during the seasonal periods. In order to verify this, the regression relationship between seasonal periods and guest waiting time was investigated.

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The alternative hypothesis to be tested for the regression model is as follows: H0: There is no relationship between seasonality and the guest's waiting time.
H1: There is a relationship between seasonality and the guest's waiting time. Figure 11 below shows a regression line of 2-weeks average waiting time durations (in minutes) for room cleaning services to spot the seasonality and find the relationship between the seasonal periods and the guest waiting time for the room cleaning services.

FIGURE 11: REGRESSION LINE.
The regression equation of the line is as follows: Y = -0.394x + 20.067 (4) The scatter plot in Figure 11 represents the average cleaning duration's pattern in the original data period, which is five months. The fitted line in Figure 11 indicates that the pattern is somehow constant (has a slight negative slope), except for July month, since there was Eid Al-Adha holiday (14/7/2021 -24/7/2021), demonstrating that the waiting time rate was significantly higher than usual.
As shown in Figure 12, the Analysis of Variance (ANOVA) indicates that the H0 should be rejected since the P-value is less than the significance level of 0.05. It can be concluded that are seasonal periods affect the guest's waiting time for services.

DEVELOPING AN AUTOMATED SCHEDULING SYSTEM
Murakami, Tasan, Gen, and Oyabu (2011) stated that managers require automated assistance in order to make successful human resource allocations (Murakami et al., 2011). By investigating the situation and based on the analysis above, the manual resource allocation is a factor in the increased guest waiting time, thus affecting the quality of housekeeping performance. At Stay Bridge Suites hotel, the HK manager allocates the human resources manually per each service using checklists and WhatsApp messages between the front office and HK department to circulate the guests' requests. Accordingly, to reduce the manual allocation without immediate effect on the HK QoS, an automated web-based system will be developed.
To construct the system, there are certain steps that should be follow as the following: Step 1: Understanding the current situation and identifying the need.
As mentioned in section II the problem statement.
Step 2: Determine an appropriate system Since the current situation at the Stay bridge hotel necessitates adopting a proper webbased management system between the HK manager, employees, and front office to reduce waiting time, the Application Express system (APEX) will be utilized. The APEX system is a multi-model relational database management system primarily intended for enterprise grid computing and data warehousing. It offers a software solution for managing database operations, ranging from personal to enterprise-level applications (Monger et al., 2009).
Moreover, APEX mainly consists of two major programming languages, Structured Query Language SQL, and JavaScript, familiar to the team members.
Why is APEX used?
a. Because the circumstance necessitates three main stakeholders, the system's access will be restricted for more privacy.
b. The APEX system supports uploading/downloading Excel sheets that are extracted from the hotel's system, which will facilitate the process of scheduling services.
c. It is a world-class technology service that provides the required features to support the current situation (e.g., Database, User interface, algorithms (several programming languages)) all in one more efficient system. D. Easy to use and adapt to future changes and improvements.
Step 3: Designing the new process In designing the model, the APEX system features will be utilized extensively to enhance the current process and eliminate non-added value activities. The website consists of three main stakeholders: the HK manager, staff, and the front office. The HK manager can view the requests, needed services, and available staff in each shift. The ability to make auto scheduling. Also, check the schedule of the staff who is available and who is busy, and the details of each staff work.
The second stakeholder is the front office, which can check the services' reports and assign the guest's request in the system with more details (e.g., room type, date, time, room number). Another feature is the ability to view the database and the accomplished reports done by staff. The third one is the staff; the staff can access the system to view the assigned tasks ordered by the HK manager set the start time and end time of the service. This will eventually increase the staff's commitment to accomplishing the task in minimum time. Additionally, if a delay occurs, the staff should mention the reason behind this delay so that the HK manager can check and take corrective action later. Figure 13 illustrates the flow chart of the system. Step 4: Building Database tables SQL will be the programming language used in the APEX system database because it was the most resilient and not limited the number of entries accepted among the other options.
The system mainly needs five connected tables using different relations and dependencies. Figure 14 shows the initially designed tables.

FIGURE 14: THE INITIAL TABLES.
Before the pilot test, the data of the services and guest requests collected from the hotel system, Opera, should be in an Excel sheet in a format that the APEX system can read. So that the system can enter accurate data, avoid misunderstandings of assigned tasks, and have a substantial positive impact on the HK process.
Comparing this plan according to the specifications, it noticed that good coordination between stakeholders, delivering services in less time, and providing more efficient services are met by this plan. Also, the resource to accomplish the alternative is available. The solution is applicable, feasible, and user-friendly regarding the constraints. It does not violate the hotel's regulation and can be completed within seven months.

CONCLUSION
The hotel will improve itself in several ways by implementing the recommended solutions. The team has successfully identified the root causes of the waiting time, developed criteria to detect staff performance, developed plans to oust the current process and set strategic actions to bypass long waiting times in the future. Furthermore, the solution will assist in be preparing for unexpected reservations while effectively maintaining the hotel's reputation and the level of services provided to customers. Moreover, the Stay Bridge hotel will be impacted by these actions and their competitor, the industry, and local businesses. As a result, highquality performance value will have a favorable impact in various sectors.