“analytical review of bullwhip effect in ......bennett, 2001). supply chains should respond...

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International Journal of Management (IJM) Volume 11, Issue 9, September 2020, pp. 1318-1335, Article ID: IJM_11_09_127

Available online at http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=9

ISSN Print: 0976-6502 and ISSN Online: 0976-6510

7DOI: 10.34218/IJM.11.9.2020.127

© IAEME Publication Scopus Indexed

“ANALYTICAL REVIEW OF BULLWHIP

EFFECT IN MANUFACTURING AND SERVICES

SUPPLY CHAIN: ANALYZING HOW

WORKLOAD CREATES BULLWHIP IN

SERVICE SECTOR”

Muhammad Zain

Research Associate, University of Management and Technology,

Lahore, Pakistan

Zakee Saadat

University of Management and Technology,

Lahore, Pakistan

Majid Ali Khan

Research Assistant, University of Management and Technology,

Lahore, Pakistan

Khalil A Arbi

University of Management and Technology,

Lahore, Pakistan

ABSTRACT

The current study examines the effect of the Bullwhip phenomena in both

manufacturing and services industry based on a literature survey. The cause and impact

of the bullwhip effect have been determined, besides the methodology is determined to

mitigate this effect. For this purpose, Mcdonald’s case has been considered to better

understanding the reasons for the bullwhip for the product. The way forward has been

proposed to cope with the bullwhip problem. The study also reviews the literature on

the service sector, especially in the health sector. Moreover, the difference between the

services and manufacturing industry is determined in this study so that both kinds of

firms can get benefit by making it part of their system to mitigate the bullwhip effect.

The study concludes by pointing out the roadmap for future studies based on the

previous reviews done in this regard.

Keywords: Bullwhip Effect, Service Sector, Supply Chain, Manufacturing, Analytical

Review

Muhammad Zain, Zakee Saadat, Majid Ali Khan and Khalil A Arbi


Cite this Article: Muhammad Zain, Zakee Saadat, Majid Ali Khan and Khalil A Arbi,

“Analytical Review Of Bullwhip Effect in Manufacturing and Services Supply Chain:

Analyzing How Workload Creates Bullwhip in Service Sector”, International Journal of

Management, 11(9), 2020, pp. 1318-1335.

http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=9

1. INTRODUCTION

The bullwhip effect is defined as the uncertainty caused as an inflow of information between

upstream and downstream in the supply chain (Ryu et al., 2009). Forecast of demand is not

reliable as it follows the rigorous pathway to upwards from users to suppliers by passing

through retailers, wholesalers and manufacturers (Farrington 2006).

The bullwhip effect was initially identified by Simon (1952) and Forrester (1961); later on,

Blanchard, Blinder, Kahn, and Sterman contributed to the concept. The bullwhip effect has

been well recognized as a concept and practice in the area of operations management. Simon

(1952) and Forrester (1961) proposed identifying the bullwhip effect through a role-playing

beer distribution game developed at MIT. Beer game emphasized the inventory or materials

management process by following the four-stage supply chain model. It is appropriate for

achieving the single-step change for meeting the finalized product demand (Sterman, 1984).

Significant fluctuation in demand implies the firms pile up the inventory whereas, a better

forecast system tends to manage inventories for more efficient supply chain system effectively.

This variation and uncertain situation flow the inappropriate information and result in the

bullwhip effect (V. Padmanabhan, Seungjin Whang, Hau Lee; 1997). The variation of orders

increases as we go through the upstream in the supply chain process from retailer to the

manufacturing. More variations in orders lead to adverse bullwhip effects. One of the

assumptions about demand variation in the manufacturing sector follows that consumer sales

do not vary so much. Still, there exists variation in the retailer’s demand to the wholesaler as

well. To make things more complicated, the wholesaler’s order to the suppliers' level further

adds to the variation in demand, enhancing the bullwhip effect. Therefore, this variability at

each level causes the bullwhip effect.

The bullwhip effect can be costly for the firms because of extra inventory, unsatisfied

customer services and variable production planning. Lee et al. (2004) analyzed efficient

consumer response (ECR) and efficient foodservice response (EFR) and founded that bullwhip

as a challenging phenomenon for the efficient supply chain system.

The objective of supply chain management is to balance the inventories between the

requirements of customers and production capacity. Operations management has to set the

policies and meet the fluctuation in demand to reduce the shortages of stock (Riddalls and

Bennett, 2001). Supply chains should respond quickly, efficiently and effectively to forecast

and accommodate the fluctuations in the market by ensuring minimum reasonable inventory

(Towill, 1994). It implies the appropriate quantity of stock in the supply chain to fulfill the

need. (Novack et al., 1993).

Ultimately, the supply chain tends to improve the process of accommodating the bullwhip.

It also refers to the phenomenon whereby the variance of demand can be adjusted effectively

as the orders proceed through each level of a supply chain (Lee et al., 1997). In this context, it

is critical to understand the causes of the bullwhip effect. It is majorly occurred due to four

primary reasons, weak demand forecast, non-optimized batches ordering, price variation and

shortages. The organizations could accommodate the bullwhip effect could be minimized by

ensuring the following assumptions as studied by V. Padmanabhan et al. (1997):

Updating the forecast (make a forecast for a shorter time)

http://hbr.org/search/V.%20Padmanabhan/0

http://hbr.org/search/Seungjin%20Whang/0

http://hbr.org/search/Hau%20Lee/0

http://hbr.org/search/V.%20Padmanabhan/0

“Analytical Review Of Bullwhip Effect in Manufacturing and Services Supply Chain: Analyzing How

Workload Creates Bullwhip in Service Sector”


Centralizing information from downstream to upstream

Directly selling to the customer

Increasing the operational efficiency to reduce lead time and variable costs

Price stability to avoid stockpiling

Coping with the shortages

Elimination of generous return policies for retailers

This study attempts to provide a more depth review of the bullwhip effect in both the

merchandise and services industry by identifying the significant causes of the bullwhip effect.

In the first part, the study demonstrates the supply chain process and the methodology by

considering the case of Macdonald’s, which helps to understand the phenomena of mitigating

the bullwhip effect in the supply chain process. Moreover, in the later stage, the literature

describes the theoretical model and the selected studies are from the health sector. The findings

will help to develop the procedure which will exhibit the systematic approach to eliminate the

bullwhip effect.

The conception of the bullwhip effect requires discussing the inventory policy primarily. In

this regard, Disney et al. (2005) emphasized that inventory management requires an order-up-

to approach based on adequate inventory variances and customer services. For this purpose, it

is crucial to managing the inventory through a suitable forecasting technique effectively. This

variance can differ based on the calculations methods used. The different systematic ways have

varying calculation methods based on which the results can also vary. For example, three

different forecasting techniques, autoregressive (AR), moving average (MA) and

autoregressive moving average (ARMA), have different results while calculating the same

inventory level for the demand process. Disney et al. (2005) also demonstrate that high

customer services and a stable inventory system do not increase the cost of inventory. There

are two kinds of stock replenish systems; continuous-time, fixed and periodic ordering systems

(Magee, 1956 and Rao 2003). Fixed order system ensures the availability of resources in the

same quantity over multiple times. Whereas, periodic ordering variations in the inventory over

different intervals. Deziel and Eilon (1967) studied a variant of the OUT policy with a separate

order of events than those considered here and the analysis was conducted via computer

simulation.

1.1. Problem Statement

The bullwhip effect is the problem facing by the operations department of every organization

and has a great impact on the firm’s effectiveness and efficiency. The literature lacks the

presentation of comparison for the bullwhip effect in both manufacturing and services industry.

The trend is moving towards the services worldwide and facing the bullwhip effect in their

operations. Therefore, there is a need to explore more knowledge for the reasons behind the

bullwhip effect for both services and manufacturing industry.

2. LITERATURE REVIEW & FRAMEWORK

2.1. Introduction of Bullwhip Effect

The bullwhip effect is defined as “the amplification of demand variability from a downstream

side to an upstream site” (Lee et al., 2004). The bullwhip effect was described by Forrester

(1961), and his research work was later promoted by Buffa and Miller (1979). A methodology

for controlling production and inventory, presented by Burbidge (1961), was inherently linked

to the problem of demand amplification. This term promoted by Lee et al. (1997a) and Tang



(2000) while observing the retailers' orders to their suppliers. There was a more considerable

difference between customer demand and retailers' orders. This demand variation adds up to

amplified at each level up. Croson & Donohue (2006) also defined a bullwhip effect caused by

increasing the number of orders in the supply chain. Viswanadham & Gaonkar (2005) study the

behavior of Integrated Manufacturing and Service Network (IMSN), which is a network, consist

of both product and service supply chain. The success of such a network depends on the level

of integration of both chains. The bullwhip effect can cause when there is a lack of coherence

between both the manufacturing and service systems. The excellent flow of information and

between both chains would increase the profitability and decrease the bullwhip effect. It has

been tried by many researchers to measure and give evidence of the Bullwhip Effect in real-life

business environments and to find out its causes and to propose remedies.

The pure demand variations amplification effect and the rogue seasonality effect are the two

distinct effects expressed in the context of demand variation. The absence of a stable seasonality

pattern is referred by demand variation, with demand peaks and valleys alternating with no

customer-driven periodicity (Towill 1997). For both theoretical and empirical purposes,

measuring the Bullwhip Effect is an issue of great importance. The most widely used measure

is variance-ratio to detect the BE. Variance ratio is defined as the ratio between the demand

variance at the downstream and the upstream stages; when this ratio is greater than 1, then we

have bullwhip at that stage. Sometimes intensive measures are used: for instance, Metters

(1997) used the seasonality coefficient or Fransoo and Wouters (2000) and Dejonckheere et al.

(2003) used the coefficient of variation.

To determine the causes of the Bullwhip Effect is another elementary stream. Two schools

of thought are prevailing here, System Thinking School and Operations Managers School.

Academicians raised System Thinking School with a strong background in Systems Theory.

This thinking school is intensely focused on the ‘‘systemic’’ nature of the supply chain and

reflected a general perception of the causes of the BE. In opposition, the second school of

thought is much more enthusiastic about confronting single and isolated factors whose

existence could generate the BE. This school is much closer to the attitude of managers.

J.W. Forrester is the most ascribed author within System Thinking School. He discussed

the complexity, feedbacks and the non-linear nature of supply chains as the leading causes for

the BE. Forrester (1980) said that ‘‘symptoms, action and solution are not isolated in a linear

cause-to-effect relationship, but all change takes place within the control of feedback loops.

Growth, goal-seeking and oscillation are consequences of feedback loops dynamics’’. Towill

(1982) and Sterman (1989) have followed the same approach. Senge (1990) and Senge and

Sterman (1992), also reinforced the same concept and described the BE observed in the supply

chain to the lack of ‘‘systems thinking’’.

The Operations Managers school of thought is keener to concentrate on single element,

whether it belongs to the hardware or to the software of the supply chain, whose occurrence

may cause the BE. Blackburn (1991) concentrated on time delays as an essential factor to be

avoided. Demand uncertainty and incorrect forecasts as a feasible explanation of BE

concentrated by Naish (1994). A contribution by Lee et al. (1997) has become the interpretative

standard for this phenomenon.

2.2. The Bullwhip Behavior in Manufacturing

In manufacturing, the bullwhip effect happens due to the amplification of demand at each stage

of the supply chain. The chain interlinks, the difference in demand when entering the process

dramatically varies when coming out of the process (Sterman, 2000). There are several reasons

for the bullwhip effect in product supply chains. Forrester (1961) reveals that managers need

time to observe a change in demand and develop a strategy to react to that change. Any delay




in reaction would act as a cause of the bullwhip effect. Simon (1991) gives attention to

rationality. It found that people responsible for calculating the demand and order placement see

their job difficult and observed in Beer Game (Croson & Donohue, 2006). There is a lack of

correct usage of information and not remembering the order placement part, which leads to the

bullwhip effect. The list given by Lee et al. (1997b) identified four causes of the Bullwhip effect

in manufacturing; the interpretation of the order, promotions tactic, supply shortage way and

order batching.

2.3. The Bullwhip Behavior in Services

Research is going on the topic of the bullwhip effect in the service supply chain. Ackermans

and Vos (2003) study reveals that the bullwhip effect also exists in the service chain. Anderson

et al. (2005) elucidate that the amplification effect in the service chain is because of variation

in demand and information sharing. In the service chain, due to varying demand, an increase in

demand and backlog uncertainty exists. Therefore, it is recommended that the backlog adjust,

as it has no access to goods. It suggested that there is both similarities and difference between

service and product supply chain. It is measured in terms of nature and causes of the bullwhip

effect. In the supply chain, the backlog factor is calculated instead of inventory. It discussed a

connection between workload and quality, which causes the amplification (Akkermans and

Vos, 2003). Anderson et al. (2005) determine the reasons for the bullwhip effect in services. It

is observing the causes of amplification in orders. It is determined that there is an exchange

between reducing backlog variation and increasing capacity. It is argued that the reduction in

backlog in one stage will increase the capacity variation.

3. ROOT CAUSES OF BULLWHIP EFFECT

3.1. Root causes of the product bullwhip effect

Lee et al. (1977a, 1997b) determined four significant reasons of the Bullwhip Effect in

manufacturing: (1) individuals wrongly anticipating (the demand); (2) artificially arouse need,

(3) order batching; (4) supply shortages, which also lead to artificial demands.

3.1.1. Demand forecast updating

In the product supply chain, an increasing number of orders will lead toward more demand

prediction; thus, more charges will place. It also works in a reverse way when, due to some

reason, customer demand decreases. The supply chain, in return, reduces the order placement.

This situation creates a bullwhip effect.

3.1.2. Order batching

Placement of orders usually not comes after inventory consumption. There may be several

reasons behind it, i.e., fixed cost. For instance, a company places an order once a week. In this

case, it would show more variation in demand than the actual demand that is another color of a

bullwhip. The reduction in batch size and higher-order placement will decrease this effect.

3.1.3. Price fluctuations

The promotion tactic varies the price of products. When the product price decreases, a customer

buys more when it increases vice versa. This artificial increase in demand increase and decrease

would create a bullwhip effect. However, stabilizing the price and minimizing the promotion

tactics will reduce the bullwhip effect.



3.1.4. Rationing and shortage of gaming

It happens when the demand for the product increases the supply. At this time supplier needs

to ration its product. It is because customer sometimes orders more than they need. After

sometimes, there will be no shortage. The rational methods should be base on past sales.

3.2. Root causes of the service bullwhip effect

3.2.1. Delays and work backlogs

Forrester (1958) claimed that the bullwhip effect occurs due to the lack of managerial decisions.

Anderson et al. (2005) indicate that work backlog inconsistency is an effect of a bullwhip.

Further, control theory describes three types of delays: (1) information processing failure or

delay (determine the capacity) (2) decision-making failure or delay (decision regarding actions)

(3) implementation failure or delay (capacity modification)

3.2.2. Escalation of the frequency of customer contact

In the service sector, a customer brings business. The service sector establishes on customer

and service provider relationship. It observes that whenever there is a problem with services,

customers contact the service supply chain. It may be via email or call (Vargo and Lusch, 2004).

In the service sector, delay in response causes backlog, which leads to an escalation of the

frequency of customer contact (Akkermans & Voss, 2013).

3.2.3. Rework cycles and tipping points

In the service sector, another face of the bullwhip effect is variation in workload. For example,

suppose an individual perform ten tasks one day and might handle 12 with hard work. However,

if the workload increases, say 15 tasks per day, it might difficult for one to complete even seven

tasks a day. Further, it will also increase the quality problem. Hence, if the staff does not have

too much workload, then they can easily handle regular work and small variations in workload.

On the other hand, if the staff is overloaded with work, then it could cause a backlog of

work (Akkermans & Voss, 2013). This will lead to a quality problems and lower production.

This is known as the “rework cycle” (Oliva and Sterman, 2001). It goes along with “tipping-

point behavior” (Malcolm, 2000). It shows an increase in work with the time and then a sudden

change in behavior occurs.

3.2.4. Automation of services and the fallout effect

With time, there is increased usage of service automation. The examples can be taken from

banks, telecom and insurance companies. Now customers do many jobs done by employees of

a service provider, i.e., booking of flights. However, some quirks need to be handled by the

staff. The problem arises in quality when the number of queries increases but the human

resource is not available. It would cause “order fallout.” There will be an increase in workload

requirements (Akkermans & Voss, 2013). Akkermans and Vos (2003) found out more

fluctuation and amplification seen in the automated process than in other methods.

3.2.5. Lack of management data and understanding

It is not always compulsory that the bullwhip effect occurs because of any event. It is sometimes

caused by management. Firstly, a manager cannot observe backlog in a service chain. It is

because of insufficient data and information. It can also because they lack the insight into the

service chain.




3.3. Remedies to encounter Bullwhip effect

Remedies for BE can be divided into two parts. The first one, from the System Thinking School

that proposes investments in training programs so that the managers’ ability to recognize,

understand and adequately react to the non-linear, feedback oriented nature of supply chains

could be increased (cf. Senge and Sterman, 1992). The second stream reasonably deals with the

attitude of the Operations Managers School. The Operations Managers School suggests a more

operative list of remedies. The first contributor in this direction is Wikner et al. (1991), who

directed five courses of actions to be followed, and a simulation study shows their effectiveness.

The five steps are (i) Improvement of each stratum’s decision rules. (ii) Better tuning of rules

among different echelons. (iii) Reduction of time delays. (iv) Removal of some distribution

strata. (v) Better information flow along the chain.

4. A CASE OF MCDONALD’S.’

4.1. Background

McDonald’s is the world’s largest chain of fast-food restaurants spread in 112 countries of the

world. The total number of operating restaurants of McDonald’s is around 30,000. McDonald’s

is a global chain often gearing its products mainly towards children. McDonald's offers different

products, such as burgers, ice-creams, happy meals, fries, salads, etc. McDonald’s made an

entry in Pakistan in 1988 in Lahore city by being a part of the Lakson Group of companies.

Now McDonald’s has around 27 restaurants in 8 key cities of Pakistan. Today McDonald’s

earns a good position in the Pakistani fast-food market for the value it generates in the form of

best customer service, paramount quality and hygienic products and the right place for

youngsters to cherish their time.

4.2. Supply Chain

In a quest to deliver fresh and the best product to its ultimate consumers, McDonald’s manages

its supply chain efficiently. Sharma (2013) provides the general sketch of the supply chain of

McDonald is shown as:

Figure 1 supply chain of McDonald

The tier 1 suppliers of McDonald’s are all those suppliers who offer processed items like

burger patties, french fries, oil for frying. Tier 2 suppliers are all those suppliers who provide

unprocessed items to McDonald's like farmers who supply fresh vegetables, potato, milk, fruits

and those suppliers who offer coating material for Chicken Patties (Dimaculangan et al., 2010).



Apart from collaborating with suppliers of edibles, McDonald’s also purchased directly from

beverage distributors like coke, fanta, sprite, etc.

4.3. Inventory Management in Supply chain

McDonald’s deals with three types of stocks daily: raw materials, work in process and finished

goods. Raw materials of McDonald’s are burger patties, potatoes, salad ingredients, packaging

material, etc. Work in process inventory of McDonald’s is cooked chicken patties, pickles, cut

onions, grated cheese, etc. so that when the demand arrives, the employees just have to assemble

these things and reduces the lead time as well as a throughput time of its customers. Finished

goods are those items, which are ready to sell to customers like salad, cold drink, etc. The

inventory management goal of McDonald’s is to minimize waste from its supply chain by

accurately forecasting customer demand (Business Case Study). To ensure quality and

freshness, McDonald’s handles its stock on a First in First out (FIFO) inventory management

system.

4.4. Bullwhip Effect in Products

In the past, nearly the late 90’s, McDonald’s faces few colors of bullwhip effect in its supply

chain. The demand at the upstream of the supply chain is amplified unless of the actual product

demand. There are specific reasons for this. The first reason is that the procurement process of

McDonald’s is not efficient. McDonald’s introduce its fast-food chain to introduce American-

style burgers to the rest of the world. Still, their traditional way of procurement processes

jammed McDonald’s flight due to that bumpy ride. Mostly forecasting is the duty of a

franchisee manager who uses past weekly forecasting data as a methodology to order inventory

to its suppliers. For example, if last week the sales are 100 and there is an increment of 10% in

net sales, than the manager order inventory for 110 burgers (Business case study).

Nevertheless, this forecasting does not consider the effect of certain events like national

holidays, summer holidays, etc. Another appropriate reason for that amplification in product

demand is that the restaurant manager makes a little error while writing the demand forecast of

McDonald’s products. That thing will also create a whip in the supply chain and a large amount

of inventory is accumulated than demanded. Another reason for this demand amplification is

that (Dimaculangan et al., 2010) that McDonald’s does a lot of promotion at the inception stage

of its outlet by offering MC Toys in Happy meal. Similarly, the demand for Macfluries has a

seasonal trend. This drives demand fluctuations and poses a difficulty for managers to gauge

the accurate demand and result in more safety stock and excess cost in their supply chain.

To prevent the effect of bullwhip from its supply chain, McDonald’s started to take certain

measures like to use a centralized procurement hub known as the Restaurant Supply Planning

Department, whose purpose is to communicate with outlet managers and forecast by taking into

consideration of local events. This methodology of forecasting at McDonald’s is termed as

Manugistics (Dimaculangan et al., 2010).

4.5. Anticipatory Bullwhip Effect in Services

The whole literature provides a clear insight into the bullwhip effect in the supply chain of its

products. However, no one illustrates the concept of the Bullwhip Effect in the services of

McDonald’s. According to the study of Viswanadham et al. (2005), if a firm is in a business of

manufacturing as well as in services, then its product life cycle and its supply chain should be

modified accordingly. As the bullwhip effect occurs in the supply chain, it also affects the

services a firm provides to complete a value-generating transaction with its customers. With

inappropriate use, the perceived customer satisfaction is less and ultimately reduces the




customer visits and, in turn, the customer demand. Sometimes better service ramping up product

sales and boost customers' demand.

By walking on the research findings of Viswanadham et al. (2005), the bullwhip effect in

the supply chain of products will also affect the supply chain of its service by a supporting

example of the automobile industry. Likewise, McDonald’s provides services like sitting area,

home delivery of products, birthday party organizers and fun zone for children. With an

increase in bullwhip at one side of the supply chain for its product and suffer from accumulated

stock, on the other side, McDonald’s will also face a bullwhip effect in its supply chain of

services. McDonald’s than tries to increase its service capacity by ordering more stock to meet

the forecasted demand level by hiring and training more staff to deliver service and by ordering

more vehicles to ensure the fast delivery of customer orders to generate value. Therefore, the

cost boosts up due to the bullwhip effect not in the form of more safety stock, more waste, fewer

inventory cycles and a perishable inventory but in utilizing company resources to increase their

service capacity.

5. THEORETICAL MODEL IN SERVICES

In the service sector, there is a lot of variety in the workplace. Every customer demands different

service and there is no concept of mass production; instead, the principles of Just in Time (JIT)

are introduced. With the change in the external environment and constant pressure from

customers and competitors, organizations are working on quality standards; Value added

operations are used for the production of products and to deliver faster services, outsourcing

and offshoring of operations are commonly used. To cope with these changes, organization

workplaces are altering on a day-to-day basis (Askenazy & Gianella, 2000). These changes are

of different types like job rotation, reassignments, flextime and work autonomy (Askenazy,

2004; St-Onge, Audet, Haines, & Petit, 2004). All these things have an impact on employees'

work.

Changes in the design of workstations and the arrangement of work on employee’s desk

have an impact on workload (Sprigg & Jackson, 2006). Due to the lack of adequate resources,

employees are bombarded with work and backlogs started to increase (Ballet & Kelchtermans,

2009). In the Activity Analysis Model, Workload is defined as the constraints which happen

when a worker and situation have interacted with each other (Lamonde, 1992). Due to the

presence of different factors in the work situation, individuals or employees are suffered from

physiological and psychological effects of workload on them.



Figure 2 Detail workload Model

Prescribed Workload is defined as the tools and resources which are required by a worker

to achieve his/her job goals and to reach specific objectives (Montmollin, 1986). The prescribed

workload is not about job descriptions, but about those resources that enable a worker to

perform particular job demands. The resources are financial resources, human resources,

equipment, software and directives from the management. Suppose these resources are not

available to workers, then it appears as a constraint and hampers their ability to perform

according to the job expectations. Thus, it results in workload creation.

Resources refer to as an individual capacity that drives from his psychological and

physiological nature to accomplish a specific task. It can be in the form of his experience,

training, age, fatigue and social characteristics (F. Lamonde & Montreuil, 1995).

The actual workload is the efforts done by a worker to come as near as possible to the

work objectives by taking into account the factors prevailing in the organization, available

resources and prescribed workload (Guérin et al., 2006). The actual workload contains all of

the late work, suspended, or that is not performed due to the constraint in the organization (Y.

Clot, 1999). The actual workload is all those things or activities done by workers to accomplish

their work tasks. The perceived workload is the extent to which individuals sense their

workload in prescribed workload and organizational constraint. It introduces the element of

employee satisfaction or employee dissatisfaction in the specific workplace.

Administrative Processes are the regular changes in employee working procedures and

work activity due to the changes in organization and working procedures. Due to organizational

transformation, organizational processes continue to change (B. M. Bass, 1999; M. B. Bass,

1985). Consequences arise when a worker tries to adjust his available resources with the

organizational constraint to perform his tasks. The first consequence can be that a worker can

utilize resources and perform a task or vice versa.

On the other hand, it may change the organization’s work expectations. This paper aims to

apply the model to nurses and see it equally feasible in the health sector as it is in the service

sector. Greenglass (2003) indicated that in hospital staff, the workload has increased, especially

on nurses.




Nurses are the “backbone” of our healthcare system; it can be said that nurses act as an

essential pillar of the hospital. The increased workload of nurses in a hospital may prove a

critical problem for the care system. There are four fundamental reasons due to which nurses

are suffering from higher workloads, i.e., (1) amplified demand for nurses, (2) insufficient

supply of nurses, (3) condensed staffing and enlarged over time, and (4) reduction inpatient stay

time (Pascale, 2008).

At first, the aging factor of the population cause increase in the demand for nurses. Second,

to meet the existing order, the number of nurses required is insufficient, and the deficiency is

expected to become more severe as upcoming demand increases. As the scarcity of nurses

occurs, it automatically put the workload on those nurses who are performing their duties. At

third, nurses have been reduced by the hospitals as the cost of health care increased since the

1990s, and policies of fixed overtime are executed to fulfill unpredictably high demands, due

to which the workload of nurses is expressively increased. A fourth, considering the increasing

pressure of cost, it has been decided by the hospitals to lessen the length of stay of a patient. As

a result, hospital nurses today take care of patients who are sicker than in the past; therefore,

their work is more intensive.6 Their workload is multifaceted and complex. A significant factor

in workload stress for hospital and community nurses is work intensity, which has increased

due to shorter hospital stays and more complex health problems per patient. Work intensity

escalates when hospitals are filled beyond capacity (Judith, 2002). A study in North American

Hospital conducted results that situations which require a greater ratio of nurse per patient

increase the risks of death after surgical treatment (Tauton et al., 1994). Estimations showed

that the rise of one patient per nurse increases the death rate with 7 percent.

5.1. Concepts of Nursing Workload

Four levels of measures to depict the workload of nurses: (1) unit level, (2) job level, (3) patient

level, and (4) situation level (Pascal et al., 2005). These measures can be organized into a

hierarchy. The situation- and patient-level workloads are embedded in the job-level workload,

and the job-level workload is embedded in the unit-level workload. In a clinical unit, for

example, numerous nursing tasks need to be performed by a group of nurses during a specific

shift (unit-level workload). The type and amount of workload of nurses are partly determined

by the kind of unit and specialty (e.g., intensive care unit nurse versus general floor nurse),

which is the job-level workload. When performing their job, nurses encounter various situations

and patients, determinants of the situation- and patient-level workloads.

5.1.1. Workload at the Unit Level

The most commonly used unit-level workload measure is the nurse-patient ratio. The nurse-

patient rate can be used to compare units and their patient outcomes concerning nursing staffing.

Previous research provides strong evidence that high nursing workloads at the unit level have

a negative impact on patient outcomes (Lang TA et al., 2004, Dimick JB et al., 2000, Mattke

S, et al., 2002). These studies’ suggestions regarding improving patient care are limited to

increasing the number of nurses in a unit or decreasing the number of patients assigned to each

nurse. However, it may not be possible to follow these suggestions due to costs and the nursing

shortage. The major weakness of this type of research is that it conceptualizes nursing workload

at a macro level, ignoring the contextual and organizational characteristics of a particular health

care setting (e.g., physical layout, information technology available) that may significantly

affect workload. Research should examine the impact on the nursing workload of work factors

in the health care micro-systems.

5.1.2. Workload at the Job Level



According to this conceptualization, the level of workload depends on the type of nursing job

or specialty (ICU nurse versus operating room nurse). For instance, Schaufeli and LeBlanc

(1998) used a job-level measure of workload to investigate the impact of workload on burnout

and performance among ICU nurses. Previous research linked job-level workload (a working

condition) to various nursing outcomes, such as stress (Crickmore, R. 1987, Matathia R, et al.

1991) and job dissatisfaction (Freeman T, 1998). Workload measures at the job level are

appropriate when comparing workload levels of nurses with different specialties or job titles

(Oates PR, 1996). However, the workload is a complex, multidimensional construct. There are

several contextual factors in a nursing work environment (e.g., performance obstacles and

facilitators) other than job title that may affect nursing workload (Hundt AS et al. 2005). In

other words, two medical ICU nurses may experience different levels of workload due to the

various contextual factors that exist in each ICU. The workload at the job-level

conceptualization fails to explain the difference in the workloads of these two nurses.

5.1.3. Workload at the Patient Level

This conceptualization assumes that the primary determinant of nursing workload is the clinical

condition of the patient. Several patient-level workload measures have been developed based

on the therapeutic variables related to the patient’s condition (Crickmore, R. 1987, Briggs BA,

et al. 1974, Keene AR, 1983) and have been extensively discussed in the nursing literature.

However, recent studies show that factors other than the patient’s clinical condition (e.g.,

ineffective communication, supplies not well-stocked) may significantly affect the nursing

workload. The previous two workload measures, patient-level workload measures, have not

been designed to measure the impact of these contextual factors on nursing workload.

5.1.4. Situation-Level Workload

To remedy the shortcomings of the three levels of measures explained above and complement

them, we have suggested using another way to conceptualize and measure nursing workload

based on the existing literature on workload in human factors engineering: situation-level

workload (Carayon P andGurses A.2005). In addition to the number of patients assigned to a

nurse and the patient’s clinical condition, the situation-level workload can explain the workload

experienced by a nurse due to the design of the health care micro-system. In a previous study,

we found that various characteristics of an ICU micro-system (performance obstacles and

facilitators)—such as a low physical work environment, supplies not well stocked, many family

needs, and ineffective communication among multidisciplinary team members—significantly

affect situation-level workload(Gurses & Carayon P. 2007). For example, sometimes, several

members of the same family may call a nurse separately and ask very similar questions

regarding the same patient’s condition. Answering all these different calls and repeating the

same information about the patient’s status to various members of the family is a performance

obstacle that significantly increases the (situation-level) workload of a nurse.

It is important to note that the impact of this performance obstacle on nursing workload

would not be apparent if we used a unit-level or patient-level workload measure. Compared to

workload at the job level, the situation-level workload is temporally bound: it explains the

impact of a specific performance obstacle or facilitator on nursing workload over a well-defined

and relatively short time (e.g., 12-hour shift), rather than using the overall experience of the

nurse in a given microsystem. The situation-level workload is multidimensional, that is,

different types of performance obstacles and facilitators affect other types of workload.

Whereas the distance between the patients’ rooms assigned to a nurse affects physical workload,

the condition of the work environment (noisy versus quiet, hectic versus calm) affects the

overall effort spent by the nurse to perform her job (Gurses AP., 2005). No prior study




investigated the impact of the microsystem characteristics on situation-level nursing workload

(Carayon P. and Gurses AP, 2005).

In summary, by studying workload at the situation level, researchers can identify the

characteristics of a microsystem that affects workload. This information is vital for reducing

nursing workload by redesigning the microsystem. In the last section of this chapter, a human

factors engineering approach based on the situation-level workload is described.

5.2. Prescribed Workload

According to the Canadian Nurses Association report (2000), nurses take care of a growing

number of patients without any change in their number. This became an ethical issue for nurses

on how to fulfill their job. It was admitted in a report that hospitals have a significant problem

with resource allocation. Varcoe and Rodney argued that the ideology of hospitals compelled

nurses to balance their work to attain maximum efficiency. The nurses are asked to give their

best with whatever they have. However, an increase in the workload of workers without any

sufficient support in the form of recourses leads the workers to think that their employers have

broken the agreement (Schaufeli & Enzmann, 1998). The findings of Greenglass (2003)

indicated that when the demand for the workload is unmanageable for the workers, it will affect

them both emotionally and physically. This kind of negligence on the part of the organization

would contribute to the stress of workers. In this case, nurses are the one who is being subject

to this problem.

5.3. Perceived workload

The working environment can create frustration and anxiety among the workers. It usually

occurs due to an increase in workload. When employees of any organization start perceiving

that she has to do a lot of work in a given time, it can introduce anxiety among employees.

According to the research, burnout can be seen among employees when they perceive that the

job demands more from them, where organizations provide fewer resources (Leiter, 1991).

Similar findings are supported in the case of hospital nurses (Greenglass, 2003). Canadian

Nurses Association's (2000) report depicts that the nurses expected to do the work of other

departments as well. The nurses feel that even though they decrease the workload of other

departments by increasing their work, they are not adequately rewarded for that. Perceive

workload introduces an element of job satisfaction among employees (M. B. Bass, 1985). North

American studies showed a strong relationship between stress and job satisfaction. So, the way

nurses perceive their work and evaluate themselves would create job dissatisfaction, causing

stress. The similar findings seen in the UK nurses (McNeese-Smith 1999) perceive work affects

job satisfaction where the focus is directly linked with the workload.

5.3.1. Actual Workload

Nurses have learned to work according to hospitals' requirements and their tasks Canadian

Nurses Association (2000). The actual workload is efforts done by the (nurses) to perform their

work in the available recourses and given job (Guérin et al., 2006).

5.4. Resources

Resources have an impact on the nurse’s workload, which sometimes creates backlogs. There

are specific resources described in the literature that comes to the surface and become the cause

of nurse workloads. Siswanto et al. did the study. (2014) shows that the number of workloads

in nurses can be controlled by ensuring that nurses have relevant training and experience and

this can be seen through their documents. The results of the study show that 52.2% of nurse’s

workload is higher who have incomplete documentation in the form of less training and less



experience. Hughes et al. (2008) reported that the nurse’s experiencing stress and fatigue are

not able to work correctly. They have their mind at one place and their physical body at the

other place. They are not able to work as they lack cognitive skills effectively; this thing creates

workloads and also intimidates patients' safety. Stress leads to nurses absenteeism, which will

cause additional workload on the remaining nurses in a hospital (Suresh et al., 2013). Hughes

et al. (2008) make it apparent that reduced staffing and increased overtime leads to fatigue in

nurses and results in their workloads. In ICU, there is a tremendous amount of stress, and

situational workload is present among nurses, so an authentic leadership style is required to

reduce this workload and nurses' stress. The study ( Pessoal & Tarabalho, 2009) suggests that

the more the workload required in ICU, the more significant, is the necessity for a directive

leadership style. According to Pascal et al. (2008), the shortage of nurses’ supply has increased

and this trend is growing with the passage of time and nursing schools could not cope the

increasing demand for education and training. Therefore, this shortage of training, instruments

and education increases the workload. Secondly, the healthcare cost has risen rapidly, which

causes the hospitals to reduce staff to become cost-effective. This downsizing has increased the

workload on the nurses, and quality has compromised.

One of the most crucial sector in the US in the health care industry. Health care services

require the patient-oriented and highly customized services and need continuous interaction of

patients and nurses (Li et al., 2002). Therefore, the executives of healthcare centers and

governments ensure the facilities, equipment and work-force up to standards and requirements.

Over the past decade, even as an aging population is consuming more health services, about

10% of US community hospitals have closed due to low occupancy rates and poor financial

performance (Ling et al., 2001). There is a need for a unique structural, strategic formulation

which emphasized on infrastructures, equipment, and staff, training facilities to cope with the

increasing demand for healthcare and to avoid the workload (Anonymous, 2001).

6. CONSEQUENCES

The limitation of resources and increasing cost resulted in poor management and affected the

patient’s health. Moreover, this workload increases the dissatisfaction and results in higher

turnover, which is also a cost for the hospitals. A 1998–1999 survey of more than 43,000 nurses

in five countries found that 17 percent to 39 percent of respondents planned to leave their job

within a year because of job over demands. Similarly, the workload may also reduce the time

spent by nurses collaborating and communicating with physicians, therefore affecting the

quality of nurse-physician collaboration. Poor working conditions like the wrong or

unfavorable working environment and job stress will have an impact on nurse’s job

dissatisfaction due to these nurses have a higher rate of absenteeism. This acts as a consequence

of the workload (Suresh et al., 2013; Davey et al., 2009).

7. DISCUSSION & CONCLUSION

The literature described above provides a sound basis to the research service sector, especially

the health sector. It tells us how workload affects the quality of work done, the resources and

consequences involved and the outcomes of an excessive workload. With global advancements,

organizations are getting larger and larger day-by-day. The research work lacks in the area

regarding the need for inter-departmental co-operation and the steps that should be taken to

cope with the demanding work environment, especially in the case of nurses. The nursing

environment seems to be dealing with the problems of workload and increasing the number of

staff is not the solution always. It is the need of the hour to discover what can be done to

decrease the workload of nurses and their ability to manage work stress. Nurse managers stay

responsible for the workload of their stations and strengthening the support system of their work




environment. Managing a suitable work environment is the task of nurses by effectively

managing workload at all levels.

Future studies call for measuring the situational workload in the nurses, identifying the

factors of workload and their contributions in creating the workload. The study will outline the

remedial steps that should be taken to overcome the problems of workload. The training and

development procedures followed to make nurses solve their issues of workload. The literature

suggests that hiring more work-force is not the proper solution for decreasing the workload.

Instead, solutions should be worked out to reduce the problems of workload by combining the

resources of the work-force, i.e., skills, experience and expertise, along-with the prescribed

workload, to reach the actual workload resulting in consequences in the form of services with

quality and minimum variability.

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