The Carrefour Department Store Operations in Abu Dhabi Essay

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Introduction

Headquartered in France, the Carrefour Department Store in Abu Dhabi is a subsidiary of the Carrefour S.A., which was established fifty-eight years ago. The Carrefour Department Store is a very successful supermarket store that serves more than three thousand customers in a day. The store is arranged into four departments to pool goods with similar purchasing trends. The departments are Bakery, Food and Groceries, Clothing, and Electronics.

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These four departments are served by 20 cashiers besides an extra cashier in the special service line that serves customers who purchase less than ten items. The store is associated with providing a variety of products all under one roof at very competitive pricing. The Carrefour Department Store is well positioned within the external environment as a result of diverse products, high economies of scale due to a large number of customers, and a well-developed supply chain channel. However, the suppliers have very high power owing to the fact that most of the goods sold in the supermarket originate from independent suppliers. The supermarket also faces the challenge of competition from many stores and mall retailing the same goods and services.

From the analysis, it is apparent that the Carrefour Department Store offers very affordable and competitive pricing for the products it retails. Besides, the store has a well-structured service charter that stresses quality and timely service. However, the Carrefour Department Store is current faced by poor service delivery due to an imbalance between the workforce and the number of customers. Apparently, the current number of cashiers is not enough to serve customers in a timely manner. Therefore, there is a need to remodel the current operations management in service delivery to increase the continuum value of service delivery.

Organization Service OM Analysis

The Carrefour Department Store functions on the pillar of the total quality management system. The supermarket is proactive in safeguarding assets and resources, sustaining efficiency in operations, and ensuring completeness in the management strategies. These strategies support communicational culture, efficiency, and optimal resource use in its service delivery to customers (Escrig-Tena, Bou-Llusar, Beltran, & Roca-Puig 2011). The business has integrated a corporate disclosure and system of litigation variables that are connected at a central point by strategic planning. The flexible service approach adopted by the Carrefour Department Store is comprehensive of the exploratory perspectives, for example, the specialized procedure of comprehension of the operations and legitimate utilization of measurable devices. These devices are basic in checking and dealing with the logistics behind the business capacities (Witcher & Chau 2010).

Operation Management Activities

The OM activities strategies of the Carrefour Department Store are to ensure long-term and sustainable operations. For the implementation of the strategy, the management balances both the short-term and long-term consideration towards decision making (Escrig-Tena et al. 2011). Management that ensures long term obligations is fulfilled. They consider the role played by planning for resources in technology, continued innovations in the production of new products, and conducting researches in the market to identify market niches within the customers (Witcher & Chau 2010).

For instance, the long-term expansion and further market penetration have been integrated through a series of beneficial partnerships, performance evaluation, and proactive innovation in the services to meet the demands of its diverse customers. Although operations management systems experience constant metamorphosis as a result of short-term, mid-term, and long-term goal planning, the store cannot operate efficiently without quality system functioning (Powell 2011).

At the Carrefour Department Store, there are systems in place to measure success as a component of the existing operational structure. Generally, this quality operations management system satisfies requirements within the budget and time schedule without disintegrating the initial goal projections. However, the current changes in the weights of labor cost and operating costs have substantially altered the final weighted average rating for the store (Escrig-Tena et al. 2011). The quality operations management system performs optimally via the integration of appropriate scientific factors of production.

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To enrich artistic managerial talents, a balance in the factors of production comes in handy to not only magnify the margins of success but also to ensure a smooth transition of an idea or an event after another, as is the case at the store. Besides, to avoid an imminent failure, the current operations management system at the store is focused on a defined edge in balancing the labor and operation costs (Witcher & Chau 2010). Therefore, the Carrefour Department Store has put in place stringent measures and strategies aimed and monitoring expansionary modules within feasible levels. These measures include techniques that are in use at the store to monitor sustainability by application of the scientific management strategies to balance the factors of the production matrix (Escrig-Tena et al. 2011). The measures have been successful, despite the current challenges facing the Carrefour Department Store.

Problem Identification

Despite the quality in its operations management, the Carrefour Department Store faces the challenge of delayed customer service due to inability of the current workforce of twenty cashiers. Many customers often complain of long queues and sometimes take more than ten minutes to be served at the counter, despite the Carrefour Department Store’s promise of efficiency and timely services. Although the Carrefour Department Store has added a new service line consisting of a cashier designated to serve customers who buy less than ten items to minimize the queuing, the seems to be very minimal impact in the overall efficiency in customer service since the complaints have not ceased (Escrig-Tena et al. 2011). Specifically, the situation becomes dire during the weekends when there is high traffic of customers in the store since the bakery, clothing, electronics, and food sections are always busy.

Proposed Solution

Decision Analysis

The store should hire four more cashiers to reduce the customer waiting time. The viability of this proposal is discussed as follows. The model is based on the assumption that the service time follows an exponential distribution. The number of servers is multiple. Also, the waiting room is unlimited. Thus, the supermarket can hold unlimited number of customers. Further, the arrival time is estimated at 160 customers per hour. The service rate is 200 customers per hour. Also, the salary for each cashier is estimated at AED3, 000.

Waiting Lines, Queuing Models and transportation model

The table below shows calculation of waiting time for customers when the company employs 20 cashiers.

Inputs
Unit of timehour
Arrival rate (l)200customers per hour
Service rate (m)160customers per hour
Number of identical servers (s)20Servers
Outputs
Mean time between arrivals0.040
Mean time per service0.166666667Hour
Traffic intensity0.833333333Hour
Summary measures
Average utilization rate of server83.3%
Average number of customers waiting in line (nl)3.10074Customers
Average number of customers in system (ns)7.26740Customers
Average time waiting in line (tl)0.12403Hour
Average time in system (ts)0.29070Hour
Probability of no customers in system (P0)0.00988(this is the probability of empty system)
Probability that all servers are busy62.0%(this is also the “percentage who wait in queue”)
Probability that at least one server is idle38.0%(this is also the “percentage who don’t wait in queue”)
Distribution of number of customers in system
n (customers)P(n in system)
30.119068
Distribution of time in queue
t (time in queue)P(wait > t)
0.250.177675
hour
Cost of cashiers20 * 3,000AED60,000

Thus, the average waiting time in the line is 0.12403 while the average time in the system is 0.29070. The total cost of the cashiers is AED60, 000. The table shows calculation of waiting time for customers when the company employs 25 cashiers.

Inputs
Unit of timehour
Arrival rate (lambda)200customers per hour
Service rate (mu)160customers per hour
Number of identical servers (s)25Servers
Outputs
Direct outputs from inputs
Mean time between arrivals0.063Hour
Mean time per service0.05Hour
Traffic intensity0.4
Summary measures
Average utilization rate of server40.0%
Average number of customers waiting in line (Lq)0.15238customers
Average number of customers in system (L)0.95238customers
Average time waiting in line (Wq)0.00952Hour
Average time in system (W)0.05952Hour
Probability of no customers in system (P0)0.42857(this is the probability of empty system)
Probability that all servers are busy22.9%(this is also the “percentage who wait in queue”)
Probability that at least one server is idle77.1%(this is also the “percentage who don’t wait in queue”)
Distribution of number of customers in system
n (customers)P(n in system)
10.342857
Distribution of time in queue
t (time in queue)P(wait > t)
0.3333333330.000077
Cost of cashiers25 * 3,000AED75,000

An increase in total number of cashiers reduces the average waiting time in the line to 0.00952 while the average time in the system reduces to 0.05952. The total cost of the cashiers increases to AED75, 000.

Forecasting

The table presented below shows a summary of the forecasting results from addition of cashiers.

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20 cashiers25 cashiersPercentage change
Average waiting time0.124030.00952-92.32%
average time in the system0.290700.05952-79.53%
Total cost of the cashiersAED60,000AED75,00025.00%

The summary in the table above shows that the percentage decline in average waiting time (92.32%) is greater than the percentage increase in cost of cashiers (25%). This implies that the benefits of adding cashiers exceed the cost. This indicates that the company will gain by adding the cashier. Therefore, based on the cost benefit analysis, the company should add cashiers.

Linear Programming

Linear programming and sensitivity analysis are important statistical tools for making decision based on examining the interaction between different variable inputs to generate ideal output (Powell, 2011). Specifically, linear programming is significant in ensuring that optimal output is achieved by subjecting different input variables and constraints for the best solution at the least cost. In this case, the supermarket intends to add more service points denoted by X and Y. The store is aware that the cost of service point X is $10 and can be fitted in a floor space of 6 square feet to hold cash cabinet that are 8 cubic feet in depth. The cost of a unit of service point Y on the other hand is $20 and needs a service space of 8 square feet in order to hold cash cabinet that have a depth of 12 cubic feet.

The store has $140 to acquire service points X and Y to fit the service space that can accommodate cash cabinets within 72 square feet. In order to determine the number of each model of service points to be purchased to offer maximum storage capacity, the variables to consider are x; number of X model service points, and y; number of Y service points to purchase. Obviously, y > 0 and x > 0 since there is no way the store can make negative purchase of service point cabinet X and cabinet Y. The next step is to take into account the floor space and costs at maximum storage capacity. In this case, the floor space and costs are the constraints with the volume being the optimization equation as summarized below.

  • Cost: 10x + 20y < 140, or y < – (1/2) x + 7
  • Space: 6x + 8y < 72, or y < – (3/4) x + 9
  • Volume: V = 8x + 12y

The equation can be plotted in the linear graph inclusive of the two constraints as indicated below.

Linear Programming.

From the above graph, when the corner points are tested at (12, 0), (0, 7), and (8, 3), the maximum volume that can be obtained is 100 cubic feet through purchasing 3 units of service point cabinet Y and 8 units of service point cabinet X.

Statistical Quality Control and assignment model

There are several methods of carrying out sensitivity analysis, depending on the number of inputs and outputs to be calculated. Among the notable methods of carrying out sensitivity analysis include One-at-a-time (OAT), scatter plots, regression analysis, variance-based method, and screening. Under the OAT method, the strategy is to examine how variation in a factor at a time affects the output generated. For instance, a single input variable is moved while maintaining other normal variables at the baseline. The moved variable is then returned at the baseline after which another variable at the baseline is moved. The process is repeated depending on the number of variable inputs (Slack, 2012). In relation to the Carrefour Department Store in Abu Dhabi, the choice of service point being preferred by customer is assumed to be dependent on the variables of time of service and per service cycle by different cashiers in the store. A set of data was collected on the trend to represent the service counter preference of customers within the store cashier lines. The information was generated in a table to rank ten pairs of observations for x and y where x=seconds by cycle and Y=seconds per item. The data was then plotted in a graph below to indicate the results.

Statistical Quality Control and assignment model.
Cycle and Per Item Scatter Graph.

In order to carry out sensitivity analysis, there is need to establish the input variables (seconds per cycle and seconds per item) and output (preferred service line). The above data can be used to generate a scatter graph by randomly picking values and plotting against service per cycle and per item as indicated in the table below.

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From the scatter graph generated above, the sensitivity coefficient was established at 0.8308 by using the linear regression equation y=-0.5226x+84.436. Apparently, the choice of cashier counter is highly sensitive to the duration a cashier takes to complete a service cycle and passing each item over the cash point.

Discussion

From the findings of the quantitative examination, there is need to reorganize some of the operational strategies of the Carrefour Department Store in order to ensure that the current quality model is sustainable in the long terms. Since operations administration framework determines accomplishment of the business strategy, the Carrefour Department Store should create a small scale inspection unit for interior decision-making as opposed to depending significantly on full scale market environment, especially in implementing the proposal to increase the number of cashiers by four. For example, the strategy for balancing the cashier efficiency and correspondence as part of the administration standards in quality management should be credible (Powell 2011).

In addition, the part of restricting work and variables of creation will assume the most essential part in the operations administration system. This is a direct result of the part of social importance regarding dialect, inclination, and utilization that may be in the objective of the Carrefour Department Store. Choices made ought to be subject to accessible assets such as venture portfolio, work force size, experience, and proficiency for a particular task requiring particular capabilities. These outcomes would give a top to bottom estimation of circulation of success for future expected returns since increasing the number of cashiers will result in increased efficiency (Escrig-Tena et al. 2011). The specific recommendations for adjusting the current operations management through increasing the number cashiers is discussed below.

Adopting the Flexible Monitoring System (FMS)

Business productivity reflects the ideal usage of distributed variables in creation of products at the most cost effective module. From the above refection, it is clear that the Carrefour Department Store should integrate the Flexible Monitoring System (FMS) to balance the quality variables that determine the magnitude of service delivery sustainability in the short-run and-long run (Witcher & Chau 2010). In spite of lower rates of return beneath the projection, the general impact of adopting the FMS is that the company will have advantages that will exceed its restrictions since the increased labor force will translate into increase customer service delivery. For example, when the FMS is completely embraced as proposed, the company will be in a position to manage costs as result of delays and logistics management.

Despite the fact that the value of the Carrefour Department Store is lower than often anticipated, the FMS will make it reasonable since it manages the element of costs in managing operations through ensuring that optimal productivity is achieved at the least possible cost, especially when integrated in the new cashier service charter (Escrig-Tena et al. 2011). In addition, the part of productivity as a consequence of FMS will push the generation logistics management towards manageability over a long period of time. Fundamentally, the prompt adjustment of the proposed FMS will contribute towards supportability in the part of cost, reliability, velocity, quality, and adaptability of the current operations management module. In particular, the increased productivity at the least cost will give room for development of different products lines with a labor force of 24 cashiers without expanding the physical production utilities in each of the four departments. More space means more products being created inside of same production lines.

Through enhanced flow in the customer service schedule, the Carrefour Department Store is set to quickly and considerably pick up from the unwavering quality perspective when contrasted with its rivals. Since customers will have the capacity to get their request inside of a shorter time, the organization stands to gain from consumer loyalty and referrals (Powell 2011). Since the length of time of conveyance will diminish by around 92.34% of its present rate when the FMS is integrated, the organization is equipped to profit from economies of scale because of expanded ability to create and disseminate inside of a brief timeframe will guarantee increased productivity for different product lines currently being retailed by the Carrefour Department Store.

Within the dynamics of the Abu Dhabi retail industry, the quality framework is guaranteed by the integration of the FMS system since the customer service structures are well placed. Subsequently, when the framework is arranged effectively, the whole chain organizing these fragments would bring about ideal operations at the Carrefour Department Store, in terms of timely services to customers. In spite of the fact that operations administration frameworks experience steady transformation as a consequence of short term, midterm, and long term goal setting, no organization can work productively without quality framework (Slack 2012). Accordingly, quality will evaluate ideal production sustainability and competitiveness to ensure that the Carrefour Department Store is not only profitable but also efficient in managing the entire operations management matrix in balancing the cost as a result of increased labor force and improved customer service time. Furthermore, the efficiency requirement as integrated in the FMS operations administration tracks implementers of business procedure with a specific end goal to exhaustively confirm reason for supporting current, anticipated, and real results for each complete customer service cycle, through a quality awareness framework.

Adopting the Six-Sigma

The Carrefour Department Store should consider adopting the six-sigma approach in quality control and certification in the logistics support after increasing the number of cashiers. Six-Sigma is an ordeal of operations administration that is utilized to create business operations, which guarantee productivity through ideal and convenient service cycles. Six-Sigma is embraced to accomplish huge impacts of creation effectiveness through occasional audit of the generation logistics network across the major departments in an organization (Witcher & Chau 2010). Really, Six-Sigma is an arrangement of business occasions which conveys positive yields and creates business point of dependability in the customer service chain. Six-Sigma guarantees that service functions are vital and enhanced through proactive administration of the components of production such as labor, time, and ideal efficiency timeline in each complete customer service cycle.

The Six-Sigma is intended to diminish wastage in the productivity resources that can create unstable service cycle and inadequate output from each resource input in the form of increased labor force. Quality control is generally used to advance nature of business productivity. Six-Sigma typically incorporate workers to give optimal productivity through self appraisal and proactive way to deal with efficiency in job performance (Powell 2011). Six-sigma is done to plan, synchronize, and deal with the diverse exercises of organization through productivity module that is designed to manage the performance of each employee (Escrig-Tena et al. 2011). By actualizing the six-sigma approach at the Carrefour Department Store, the organization can focus the future dangers and obstacles in the execution of any service activity and take appropriate measures for addressing the unforeseeable dangers such as avoidable delays in customer service.

Modification of the Variables in Performance Management

Keeping in mind the end goal to accomplish quality operations administration, the current performance management matrix should be occasionally moved up to track the various working service models such as proportion examination in operation administration, which is perfect in proactive management of the entire performance matrix in the short term and long term production activities. These variables are achievable through quality assurance, production expansion, and inventiveness as part of the performance management (Escrig-Tena et al. 2011). The modification of performance management variables as a strategy is fundamental in the specialty of operations administration at the Carrefour Department Store (Witcher & Chau 2010). Notwithstanding, having proficient operations administration framework will enable the Carrefour Department Store to completely track the component of checking advancement at miniaturized scale besides the large scale customer service cycle, especially during the weekends.

The second technique for reviewing the performance management variables for the cashiers at the Carrefour Department Store should be adjusted to correspond to quality assurance strategies across the departments such as logistics, human resource, production, research and development, and supply chain. In order to guarantee success in the performance management, the quality administrators at the Carrefour Department Store should adjust both the performance trackers and complete service cycles across different departments as independent entities. This proposal will ensure that the Carrefour Department Store is in a position to locate areas with efficiencies or inefficiencies. As a result, the quality management strategies that guarantee long term commitments are satisfied in the service cycle in each department (Jaisnkar & Mistra 2011). This is conceivable in light of the fact that this model of operations administration framework takes into consideration operations process aggressiveness as it manages the superfluous overhead expenses from waste and under utilization of production input in the form of increased labor force.

In accordance with the primary goal of estimating the completeness of the operation management matrix, it is of quintessence to reverberate upon the standards of relative execution of distinctive contending operation variables as a major aspect of the operations framework at the Carrefour Department Store. For consistency, the parameters and variables utilized should be adjusted to guarantee that quality model is accomplished inside contending service matrices since the Carrefour Department Store has series of department with different service cycles. Keeping in mind that the end goal is to address the hidden issues in stochastic instability estimation, the parameters should rotate on the fringe of pertinent data which is steady with the genuine and expected results from the quality model (Harrison & John 2010). When the proposal is implemented, the Carrefour Department Store will not only be in a position to create an ideal performance management network but also track the progress of the customer service support functions such as labor, supply chain, and efficiency (Witcher & Chau 2010).

Conclusion

The Carrefour Department Store has a generally stable operations administration framework. The company has quality and proficiency certification framework that specifically affects the operations station, as the procedure is comprehensive of key and reasonable decision science. In order to reduce the waiting time in the supermarket, the researcher computed the average waiting time and total cost of cashiers after increase based on estimated number of customers visiting the supermarket per hour. The results of the calculations show that the percentage decline in average waiting time (92.32%) is greater than the percentage increase in cost of cashiers (25%).

This implies that the benefits of adding cashiers exceed the cost. This indicates that the company will gain by adding the cashier. Therefore, based on the cost benefit analysis, the company should add cashiers. In order to effectively implement the proposed change, it is necessary for the store to make alterations in the effectiveness column through embracing the Flexible Monitoring System, Six-Sigma, and execution variable to guarantee maintainability in its business operations after increasing the number of cashiers to 25. These strategies will ensure that the store can track efficiencies and inefficiencies in customer service cycle in each department.

Reference List

Escrig-Tena, A, Bou-Llusar, C, Beltran, M, & Roca-Puig, V 2011, ‘Modeling the implications of quality management elements on strategic flexibility,’ Advances in Decision Sciences, vol.1, no.1, pp.1-27.

Harrison, J, & John, C 2010, Foundations in strategic management, South Western Cengage Learning, Ohio, Oh.

Jaisnkar, S, & Mistra, N 2011, Quantitative techniques for management, Bharathiar University, New Delhi, India.

Powell, T 2011, ‘Total quality management as competitive advantage: a review and empirical study,’ Strategic Management Journal, vol.16, no.4, pp.15–37.

Slack, N 2012, Operations and process management: Principles and practice for strategic impact, Pearson Education Limited, Alabama, Al.

Witcher, B, & Chau, V 2010, Strategic management: Principles and practice, Cengage Learning, Alabama, Al.

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