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The concept of performance management is used by most of the organizations to ensure that either they are going on the right path or not. For managing the performance the organizations are required to know about the performance indicators. This paper explores the key performance indicators (KPIs) and impact of these KPIs on the overall organizational performance in manufacturing sector in Pakistan. The data for present study collected from the top level management of the 84 best manufacturing organizations in Pakistan by using a structured questionnaire and the impact of KPIs on the overall performance of the manufacturing organizations were evaluated. The results show that the manufacturing organizations put more focus on the customer satisfaction and Delivery reliability in terms of performance measurement. And measuring the performance in terms of cost, financial, quality, time, flexibility, delivery reliability, safety, customer satisfaction, employees’ satisfaction and social performance indicators have positive significant impact on the overall organization’s performance. This paper puts together all important performance indicators used by organizations in a single list and check their impact on the overall performance indicator index of the Organizations. As Pakistan is among the developing countries, this study will serve as a valuable guideline for several manufacturing organizations operating in other developing countries of the world.
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Qual Quant
DOI 10.1007/s11135-013-9945-y
The key performance indicators (KPIs) and their impact
on overall organizational performance
M. Ishaq Bhatti ·H. M. Awan ·Z. Razaq
© Springer Science+Business Media Dordrecht 2013
Abstract The concept of performance management is used by most of the organizations to
ensure that either they are going on the right path or not. For managing the performance the
organizations are required to know about the performance indicators. This paper explores the
key performance indicators (KPIs) and impact of these KPIs on the overall organizational
performance in manufacturing sector in Pakistan. The data for present study collected from
the top level management of the 84 best manufacturing organizations in Pakistan by using a
structured questionnaire and the impact of KPIs on the overall performance of the manufac-
turing organizations were evaluated. The results show that the manufacturing organizations
put more focus on the customer satisfaction and Delivery reliability in terms of performance
measurement. And measuring the performance in terms of cost, financial, quality, time, flex-
ibility, delivery reliability, safety, customer satisfaction, employees’ satisfaction and social
performance indicators have positive significant impact on the overall organization’s perfor-
mance. This paper puts together all important performance indicators used by organizations
in a single list and check their impact on the overall performance indicator index of the Orga-
nizations. As Pakistan is among the developing countries, this study will serve as a valuable
We’re thankful to Mr. Khuram Bukhary for his research assistantship and constructive comments to improve
the quality of the paper.
Z. Razaq was a former student of Institute of Management Sciences, Bahauddin Zakaria University, Multan,
Pakistan.
M. Ishaq Bhatti
CBE, King Abdulaziz University, Jeddah, Saudi Arabia
M. Ishaq Bhatti (B)
FBEL, La Trobe University, Melbourne, Australia
e-mail: i.bhatti@latrobe.edu.au
H. M. Awan
Director Air University, Multan Campus, Multan, Pakistan
e-mail: drhayat@mail.au.edu.pk
Z. Razaq
e-mail: zahidrazaq@live.com
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M. Ishaq Bhatti et al.
guideline for several manufacturing organizations operating in other developing countries of
the world.
Keywords Performance management ·Production management ·Process ·
Performance indicators ·Manufacturing
1 Introduction
In order to get and keep competitive advantage over other market players in the same industry
the manufacturing organizations must produce the quality products at lower cost with rapidly
increasing variety. These are the few among many valuable objectives of the organizations. In
order to get confirmations regarding the fulfilling of their objectives and goals organizations
have to keep check over their performance (Ghalayini and Noble 1997). In order to achieve
these purpose organizations must have to use the performance management systems. Simply
the performance management is done by the organizations in order to confirm that either they
are going in right direction or not. For measuring, managing and comparing the performance
the organizations are required to know about the performance indicators.
The performance indicators can be defined as the physical values which are used to mea-
sure, compare and manage the overall organizational performance (Gosselin 2005). The
performance indicators may include the quality (De Toni and Tonchia 2001;Gosselin 2005;
Heckl and Moormann 2010;Badri et al. 1994;Neely and Platts 2005), cost (De Toni and
Tonchia 2001;Neely and Platts 2005;White 1996), financial (Parmenter 2009;White 1996),
flexibility (De Toni and Tonchia 2001;andWhite 1996), delivery reliability (Heckl and
Moormann 2010;White 1996), employees’ satisfaction (Leong et al. 1990;Mapes and Szwe-
jczewski 1997;Parmenter 2009), customer satisfaction (Ittner 1998 and Neely and Platts
2005;Parmenter 2009), safety (Flin and O’connor 2000;Mearns et al. 2003;Parmenter
2009), environment/community (Neely and Platts 2005;Parmenter 2009;White 1996), and
learning and growth (Parmenter 2009;Sadler-Smith and Chaston 2001;Utterback 1975).
These are the performance indicators which are given in the literature and most of the orga-
nizations use these performance indicators for measuring and managing their performance.
The measures are the factors which are used to determine the organization performance in
terms of performance indicators (Browne et al. 1997;Gosselin 2005;Heckl and Moormann
2010). There could be tradeoffs between the performance indicators, which means that if
one indicator’s value increases the other’s value decreases (i.e) the major tradeoff could be
between the quality, cost, time, delivery reliability and flexibility (Mapes and Szwejczewski
1997). This paper revolves around three questions. First, which are the important indicators
and sub-indicators of performance? Second, do these performance indicators have any rela-
tionship with each other and with overall performance index of the organizations? Third is
there any impact of these performance indicators upon the overall performance of the orga-
nizations? This study is descriptive in nature which has used the survey research method
and some statistical techniques in order to find the answers of questions discussed above.
The results of the study reveal that the manufacturing organizations put more focus on the
customer satisfaction and delivery reliability in terms of performance indicators. Measur-
ing the performance in terms of cost, financial, quality, time, flexibility, delivery reliability,
safety, customer satisfaction, employees’ satisfaction and social performance indicators have
significant positive impact on the overall performance of organizations.
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The key performance indicators (KPIs) and their impact
2 Literature review
The phenomenon performance measurement is used by the organizations in order to ensure
that they are going in right direction, achieving targets in terms of organizational goals and
objectives. The performance measures are used to evaluate and control the overall business
operations. They are also used to measure and compare the performance of different orga-
nizations in the industry, plants, departments, teams and individuals (Ghalayini and Noble
1996;Mapes and Szwejczewski 1997;Parmenter 2009). Thus the beginning of the perfor-
mance measurement starts from the identification of performance indicators that allow for
a detailed specification of process performance. Many authors have suggested many cate-
gories of indicators for different approaches of performance measurement. There are two
main groups of indicators which are used to determine the organizational performance. One
is called the financial or cost based measures of performance and the other is called non-
financial or non-cost based measures of performance. The costs / financial, quality, time,
delivery reliability, flexibility are largely accepted indicators of organizational performance
(White 1996). But several authors have defined other indicators as well on the basis of
their case study researches. Sinclair and Zairi (1995) have found the customer satisfaction,
quality, delivery reliability, employee factors, productivity, financial performance, safety
and environment / social performance as the indicators of business performance used by
many organizations. Parmenter (2009) has identified the customer’s satisfaction, employees’
satisfaction, environment/community, financial, internal process performance and learning
and growth as performance measurement perspectives. Browne et al. (1997) has identified
that the different organization uses different measures for their performance, like gener-
ally they measure performance of the organization by breaking up the overall business into
processes. And the most organizations measure their performance by allocating the indi-
cators to individual processes. Rolstadås (1998) has identified that the performance mea-
surement of an organization is a complex interrelation criteria between the effectiveness,
efficiency, quality, productivity, quality of work life, innovation, and profitability. In order
to be successful, each organization has to determine performance indicators and, subse-
quently, performance measures and performance figures that are strategically relevant to
its respective situation (Leong et al. 1990;Mapes and Szwejczewski 1997). Following are
the eleven perspectives or dimensions of overall business performance which are found in
literature.
2.1 Quality
Quality is the key to success of every organization. Now a days the customers are demanding
quality products and the organizations that are able to produce quality products at lower cost
win the game. The quality is checked mainly at three levels input, output and throughput or
process quality. Most of the organizations focus on quality because they have made promises
to their customers about quality of their services and products (Heckl and Moormann 2010;
Badri et al. 1994). White (1996) has discussed eight dimensions of quality which are: fea-
tures, reliability, conformance, durability, serviceability, aesthetics, and perceived quality. In
between these dimensions, conformance has the empirical evidence with quality. Gosselin
(2005) has discussed customer satisfaction, input quality, output quality, cost quality and
number of customer complaints as the measures of quality. De Toni and Tonchia (2001)have
discussed machine reliability, reworks, quality system costs, customer satisfaction, returned
goods, input and output quality, product reliability, and machine reliability as the quality
measures. According to Neely and Platts (2005) performance, features, reliability, confor-
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M. Ishaq Bhatti et al.
mance, technical durability, serviceability, aesthetics, perceived quality, humanity, and value
are the measures of quality.
2.2 Flexibility
Flexibility is defined as the ability of the organizations to perform multiple tasks at given
level of resources like, labour, machine etc (Zhang et al. 2003). Neely and Platts (2005)
has discussed material quality, output quality, new product, modified products, deliverabil-
ity, volume mix and resource mix are the most valid measures of flexibility. De Toni and
Tonchia (2001) have identified volume flexibility, mix flexibility, product modification flexi-
bility, process modification flexibility and expansion flexibility as the measures of flexibility
performance. White (1996) has identified perceived flexibility, flexibility relative to competi-
tors, process flexibility relative to competitors, perceived relative product flexibility, plant
response time to product mix changes, product cycle time, set-up time, time to replace tools,
change tool, assemble or move fixture, percentage increase in average number of set-ups
per day, perceived relative volume flexibility, ability to perform multiple tasks efficiently,
percentage programmable equipment, percentage of slack time for equipment, labour, per-
centage products using pull system, disruption caused by breakdowns and vendor lead time as
the strategy related measures of flexibility performance of the manufacturing organizations.
2.3 Time
Time is a very important determinant of the manufacturing performance of the organizations.
The time based manufacturing is an important concern for the manufacturing organizations in
the world; in order to achieve competitive advantage over their competitors (Koufteros et al.
1998). De Toni and Tonchia (2001) have identified the manufacturing lead time, delivery lead
time, due date performance, frequency of delivery and rate of production introductions as the
measures of time performance in their article. Neely and Platts (2005) have identified time
to market, distribution lead times, delivery reliability (to clients), supply lead times, supplier
delivery reliability, manufacturing lead time, standard run time, actual run time, wait time, set-
up time, move time, inventory turnover, order carrying out time and mean(flexibility) as the
measures of time indicator. White (1996) has used lead time, cycle time, time from customer’s
recognition of need to delivery, order processing time, response time, percentage on-time for
rush jobs, paperwork throughput time, material throughput time, distance travelled, decision
cycle time, time lost waiting for decisions, percentage first competitors to market, breakeven
time, time from idea to market, average time between innovation, number of changes in
projects and engineering time as the strategy related measures of time. White (1996)has
named time indicator as the speed in his research.
2.4 Safety
In recent years there has been a realization that the reliability of complex work systems
in achieving organizational goals safely depends on work structures as well as technical
arrangements (Mearns et al. 2003). Parmenter (2009) has identified in his book that the level
of risk and safety perceived, accident rate, level of employees’ cooperation, safety attitude
of managers and employees, level of employees’ physical risk on work place and the level of
safety information as the key measures of safety. In UK the leading measures of the safety
performance are lost time on accident, and accident rate (Flin and O’connor 2000;Mearns
et al. 2003).
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The key performance indicators (KPIs) and their impact
2.5 Financial performance
Historically financial measures are the best measures to evaluate the company’s performance,
such as the physical values of sales and profits or percentage return on equity and assets.
Because external groups of stockholders are strongly concerned with these sort of perfor-
mance measures and they put pressure on companies to use financial measures for their
internal performance measurement (White 1996). Many researchers and organizations use
different measures for evaluating and measuring their financial performance. Here, we have
adopted the financial measures suggested by Parmenter (2009) in his book “the key perfor-
mance indicators (KPIs)”. He suggested cost of goods sold / sales, scrap cost as %age of
total sales, A/c Receivable turnover, cash flows, days in inventory, days sales in receivables,
net income, sales, number of profitable customers, return on equity, sales by product, sales
growth rate, return on assets and return on capital employed as the measures of the financial
performance of the organizations.
2.6 Cost
The external stakeholders have more concern with the cost based measures of the perfor-
mance, so that is why the organizations use cost accounting system which include measures
of efficiency and effectiveness, represent an effort to relate internal performance measures to
external ones (White 1996). Neely and Platts (2005) has identified the manufacturing cost,
value added cost, selling price, running cost and services cost as the measures of the cost
performance. White (1996) has identified cost relative to competitors, perceived relative cost
performance, manufacturing costs, capital productivity, labour productivity, machine pro-
ductivity, total factor productivity, total product cost as a function of lead time, direct labour
cost, indirect labour cost, percentage improvement in labour, relative labour cost, labour
productivity, labour efficiency, material cost, inventory cost, scrap cost, repairing cost, cost
of quality, design cost, relative R&D cost, distribution cost, overhead and transactions per
product as strategy related measures of cost. De Toni and Tonchia (2001) have identified
the material cost, labour cost, machinery energy cost, machinery material consumption cost,
inventory cost, machine saturation, total productivity, working capital productivity, value
added productivity and value added productivity/employee costs as the measures of cost
performance of the organizations.
2.7 Employees satisfaction
The employees’ satisfaction is the key to success for every organization. If the employees
are satisfied then there will be satisfied customers and overall organizational performance
will boost up (Leong et al. 1990;Mapes and Szwejczewski 1997). Parmenter (2009)wasof
the view that analysis of absenteeism, %age of staff working flexible hours, turnover rate,
new recruits which are employee’s referrals, employees’ satisfaction per survey, employees’
complaints resolution effectiveness, empowerment index and length of service of staff who
has left are the measures to check the employees satisfaction in any organization.
2.8 Learning and growth
Leaning and growth provides the organizations with competitive advantage over their com-
petitors. It happened because the learning organizations keep training their employees with the
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M. Ishaq Bhatti et al.
new technological advancements (Sadler-Smith and Chaston 2001). Parmenter (2009)men-
tioned in his book that the %age of managers having IT literacy, %age of employees having
required education, employees terminated for performance this year, employees certified for
skilled job function or position, investment for training, number of internal promotions, man-
agers who have performance management training, number of new staff, times in training
(days/year) and number of research paper generated are measures by which the organizations
can check their performance in terms of learning and growth. The more the leaning organi-
zations involve in innovativeness the more they develop new product development projects
(Utterback 1975;Sadler-Smith and Chaston 2001).
2.9 Environment/social performance
The organizations owe something to the society in which they operate and the realization of
this liability is actually the social responsibility or we call this as corporate social responsibil-
ity. The socially responsible organizations actually take steps for the welfare of the society in
which they operate (White 1996;Neely and Platts 2005). Parmenter (2009) has mentioned in
his book that the discharge from production into the environment, waste and scrap produced,
dollar donated to community, percentage of local residence in total workforce, number of
media coverage events, number of photos in papers, number of sponsorships undertaken by
organizations, number of environment complaints received in a year, %age of current projects
that are environment friendly and the environment safety awards are the true measures of the
environment/social performance of the manufacturing organizations.
2.10 Customer satisfaction
The higher customer satisfaction improves financial performance by increasing the loyalty
of existing customers, reducing price elasticity, lowering marketing costs through positive
word-of-mouth advertising, reducing transaction costs, and enhancing organization repu-
tation (Ittner 1998 and Neely and Platts 2005). According to Parmenter (2009) stock outs,
revenue gained from top customers in a week, number of complaints, customer loyalty index,
customer lost, new customers, number of customer referrals, market share in term of cus-
tomers, on time delivery, product quality, number of quality service guarantee issued and
order frequency are the measures of the customer satisfaction.
2.11 Delivery reliability
White (1996) has proposed the perceived relative reliability, reliability relative to competitors,
percentage on-time delivery, due date adherence, percentage increase in portion of delivery
promises met. Percentage of orders with incorrect amount, schedule attainment, average
delay, percentage reduction in lead time per product line, percentage improvements in output,
percentage reduction in purchasing lead time and percentage reduction in average service
turnaround per warranty claim as the measures of the delivery reliability. There is little
discrepancy between researchers about the measures of delivery reliability.
In summary, there are many indicators available in literature that can be applied for mea-
suring the organization’s processes performance. During the late twentieth century, most of
the organizations focus more upon the efficiency, and lesser upon the effectiveness. Perfor-
mance measurement serves to reduce cost rather than to improve the organization’s profit
related issues. In order to avoid misguiding management the organizations should focus on
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The key performance indicators (KPIs) and their impact
the selection of performance indicators which are mostly related to their strategy. The other
thing which should be in the minds of managers during the selection of indicators is that they
should link these selected indicators to their business vision, mission and objectives. This
will result in strategic performance indicators that support senior management in indicating
toward the desired strategic direction. Hence, the indicators are highly dynamic, and the
selection of advantageously important performance indicators is related to the concept of
“critical success factors”. In order to be successful, each organization has to determine per-
formance indicators and performance measures that are strategically relevant to its particular
situation (Heckl and Moormann 2010).
3 The methodology and model
In this article survey research method is used. For this study a structured questionnaire is
used in order to get primary and qualitative data on the topic. The likert scale was used in the
questionnaire of study and it is filled by the top management of the sampled organizations.
The sample size of 84 respondents were randomly selected from four different manufacturing
industries of Pakistan. The respondents were asked to fill the questionnaire on the basis of
their organizations’ practices and their personal experiences. Then the data collected from
these questionnaires was entered into the SPSS 17 database for analysis. To prioritize the
different performance indicators we use analytical hierarchy process (AHP). The indices of
the eleven broad indicators are calculated on the basis of global priority weights. Correlation
analysis is used to check the impact of various performance indicators indices on each other
and the overall performance index to know how they are helping each other and in which
direction. At the end we run the simple regression in order to check the impact of these eleven
indicators indices on the overall performance indicators index.
3.1 Research model
The 4-stage research model for this study is given in Fig. 1. In this research model the
number of items (sub indicators) in each performance indicators EPI and IPI (as 2nd stage)
are recognized as the qualitative part of the study and the final number of dimensions are
determine by factor analysis (stages 3 and 4). Overall performance index is calculated (as 1st
stage) by using AHP’s given global weights of the performance indicators.
4 The findings
Rolstadås (1998) has identified that performance measurement of an organization is a com-
plex interrelation criteria between the effectiveness, efficiency, quality, productivity, quality
of work life, innovation, and profitability. In order to be successful, each organization has
to determine performance indicators and, subsequently, performance measures and perfor-
mance figures that are strategically relevant to its respective situation. Different organizations
use different performance indicators with respect of their competitive strategy. The organiza-
tions, which have cost based competitive strategy focus more on the cost based measures of
performance and the organizations with responsive competitive strategy focus more on the
quality and other non cost based measures. The financial measures are equally important for
all sort of organization, even the organizations put more focus on Non-financial measures of
performance (Leong et al. 1990). This study is conducted to assess the relative importance of
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M. Ishaq Bhatti et al.
Performance indicators Overall Performance
EPI IPI
FlexCS Cost QualSPDR Time EP Safety L&GFP
CS
Factor
DR
factors
SP
factors
Cost
factors
Qual
factors
Flex
factors
Time
factors
EP
factors
FP
factors
Safety
factors
L&G
factors
Fig. 1 The Research model for performance indicators and overall performance index
these performance indicators in manufacturing sector of Pakistan. This study will be helpful
for manufacturing organizations in Pakistan in order to select the KPIs for their performance
management.
4.1 Analytical hierarchy process (AHP)
In order to achieve the first objective of the study, which are the important performance indi-
cators used by the organizations, we have applied the AHP. AHP is a multi-criteria decision
making (MCDM) method. MCDM is a well known class of decision making that was first
introduce by Wind and Saaty (1980). The AHP actually converts respondents’ preferences
into ratio-scale weights that are pooled into linear additive weights for the alternatives. These
resultant weights are used to rank the alternatives and thus assist the decision maker in mak-
ing a strategic decision (Forman and Gass 2001). The three primary functions of AHP are the
structuring complexity, measurement on a ratio scale and synthesis. By understanding these
functions one can understand that why the AHP should be considered as a general methodol-
ogy that can be applied to a variety of problems. The first function of AHP technique is that it
is used to face problems in the way humans deal with complexity: the hierarchical structuring
of complexity into homogeneous clusters of factors. Wind and Saaty (1980) pointed that the
large range of organizations are mostly hierarchical in structure, which means that they are
divided into functions which are sub-divided into sub-functions. The hierarchical sub division
is not a strange phenomenon for the human organizations. The second function of AHP is that
it uses the ratio scale to rank different factors. The need to have a mathematically approved,
patently obvious methodology caused Saaty to use paired comparisons of the hierarchical
factors to derive ratio-scale measures that can be interpreted as final ranking weights. The
third main function of AHP is that it synthesis or putting together the parts into a whole.
As complex decisions involves many factors which need to synthesize manually. Although
the AHP facilitate the complex decision making by synthesize the multitude factors into a
hierarchy. We don’t know of any other methodology that facilitates synthesis as does the
AHP (Forman and Gass 2001).
The respondent were asked about different performance indicators which are arranged in
the form of eleven broad categories like, cost, quality, delivery reliability, flexibility, time,
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The key performance indicators (KPIs) and their impact
customer satisfaction, employees satisfaction, financial indicators, safety, organization per-
formance in terms of its contribution in environment and community and the organization
learning and growth which are also the first degree performance indicators. The respondents
were required to give their response in terms of many performance indicators arranged in dif-
ferent categories. A detailed analysis is done in order to develop a hierarchical index based
on the global priority weights of sub-indicators for performance management (Table 1),
which indicates the relative importance toward selecting these indicators as the KPIs for the
manufacturing organizations in Pakistan.
Results from AHP given in Table 1illustrate the relative importance of these sub-indicators
or measures provided by the top level management of different organizations from overall
manufacturing sector (OMS) of Pakistan and the selected manufacturing industries. The
results indicates that for the manufacturing organizations in Pakistan product quality is the
most important performance indicator which also reveals that the manufacturing organiza-
tions in Pakistan focus more on the product quality (Global weight=0.571) as compare to
other performance indicators. The organizations focus more on dollar donated to community
(Priority weight=0.519) as the second important factor and the conformance to commu-
nity as the third important factor (Priority weight= 0.444). The results indicate that for the
automobiles organizations in Pakistan the conformance to customer perception is the most
important performance indicator which also reveals that the manufacturing organizations in
Pakistan focus more on the product quality according to the customer perceptions (Priority
weight= 0.684) as compare to other performance indicators. The automobile organizations
in Pakistan focus more on dollar donated to community (Priority weight= 0.541) as the sec-
ond important factor and the a/c receivable turnover as the third important factor (Priority
weight= 0.450). In our study sample, there were eight electronics organizations from Pak-
istan. The respondent from these organizations were also asked the same question regarding
performance indicators either these are being used in their organizations or not. The results
about the electronics organizations suggest that the electronics organizations in Pakistan
are more concerned about material costs (priority Weight= 0.634) as performance indicator,
which is on top among other performance indicators. Other indicators are respectively the
conformance to customer perception (priority Weight= 0.509) which is second important
indicator of performance, product performance (priority Weight= 0.427) as third important
indicator, dollar donated to community (priority Weight= 0.422) as fourth important, per-
centage of local residence in total workforce (priority Weight= 0.422) as fifth important
performance indicator etc. These results suggest that the sports organizations in Pakistan
are more concerned about A/c receivable turnover (priority Weight= 0.629) as performance
indicator, which is on top among the other performance indicators. The other sub-indicators
are the dollar donated to community (priority Weight= 0.564) as second important, confor-
mance to customer perception (priority Weight= 0.401) as third important, material costs
(priority Weight= 0.398) as fourth important, product quality (priority Weight= 0.392) as
fifth important, products performance (priority Weight =0.342) as sixth important, reliability
relative to competitors (priority Weight= 0.323) as the seventh important indicator of per-
formance (etc). At the end, results for the textile organizations in Pakistan show that the
product quality is the most important performance indicator which also reveals that the tex-
tile organizations in Pakistan focus more on the product quality (Priority weight=0.520) as
compare to other performance indicators. The other part of the results show that the textile
organizations focus more on A/c receivable turnover (Priority weight= 0.472) as the second
important factor and the conformance to customer perception as the third important factor
(Priority weight = 0.422). A detailed analysis is made in order to develop a hierarchical indices
of performance indicators based on the global priority weights of sub-indicators for perfor-
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M. Ishaq Bhatti et al.
Tab l e 1 AHP based ranking of performance indicators
Indicators Sub indicators Global weights
OMS Auto Elect Sports Textile
Cost Labour costs as %age of T. Sales 0.1980 0.1474 0.1779 0.2135 0.2020
Cost relative to competitors 0.2821 0.2704 0.2409 0.2206 0.2651
Cost of quality 0.2815 0.2704 0.2409 0.2206 0.1235
Overhead cost 0.0692 0.1431 0.2262 0.2506 0.2490
%age of total manufacturing cost 0.1152 0.0999 0.0606 0.0255 0.1102
Service cost / warranty 0.0253 0.0291 0.0266 0.0348 0.0250
Scrap cost as %age of T. sales 0.0283 0.0394 0.0266 0.0341 0.0250
Material costs 0.2676 0.3174 0.6344 0.3983 0.3931
Distribution cost 0.1731 0.2085 0.1009 0.2180 0.1233
Value added cost per unit 0.3450 0.1006 0.1009 0.1086 0.1406
Running cost per unit 0.0510 0.1961 0.0680 0.1002 0.1568
Cost of goods sold/sales 0.1630 0.1773 0.0955 0.1747 0.1860
Financial A/c receivable turnover 0.2856 0.4500 0.2948 0.6297 0.721
Cash flows 0.4322 0.3788 0.2948 0.2281 0.2268
Days in inventory 0.2355 0.1297 0.3551 0.0626 0.2606
Days sales in receivables 0.0465 0.0413 0.0551 0.0794 0.0404
Net income 0.2535 0.2170 0.1927 0.2147 0.2392
Sales 0.1934 0.2306 0.2752 0.2403 0.1707
No. of profitable customers 0.0863 0.0673 0.1114 0.0613 0.1035
Return on equity 0.1136 0.1706 0.1114 0.1264 0.1497
Sales by product 0.0660 0.0541 0.0545 0.0503 0.0478
Sales growth rate 0.0713 0.0642 0.0950 0.1398 0.1260
Return on assets 0.1463 0.1420 0.1379 0.1329 0.1308
Return on capital employed 0.0693 0.0540 0.0215 0.0340 0.0319
Quality Products performance 0.3123 0.3480 0.4277 0.3425 0.3632
Products features 0.1126 0.1015 0.1830 0.1062 0.1565
Products reliability 0.1596 0.2286 0.1302 0.1198 0.1218
Machine reliability 0.1070 0.0748 0.0641 0.1198 0.0671
Out put quality 0.1541 0.0999 0.0898 0.1586 0.1455
Input quality 0.1541 0.1470 0.105 0.1528 0.1455
Conformance to customers 0.4444 0.6840 0.5099 0.4010 0.4226
Technical durability / expected life 0.2366 0.0950 0.2118 0.2327 0.1647
Serviceability 0.0855 0.0950 0.0826 0.0887 0.1743
Perceived quality by customer 0.2332 0.1258 0.1955 0.2775 0.2383
Time Cycle time 0.1338 0.3823 0.2206 0.2826 0.1901
Order processing time 0.1569 0.1734 0.1138 0.2055 0.1746
Response time 0.2056 0.0867 0.1526 0.0987 0.2261
Move time 0.0508 0.0486 0.0588 0.0489 0.0474
Wait time 0.0597 0.0610 0.1113 0.0634 0.0529
Order carrying out time 0.0642 0.0709 0.0711 0.1287 0.0525
Time to market 0.1966 0.0610 0.0859 0.0913 0.1538
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The key performance indicators (KPIs) and their impact
Tab l e 1 continued
Indicators Sub indicators Global weights
OMS Auto Elect Sports Textile
Breakeven time 0.0341 0.0500 0.1009 0.0402 0.0498
Throughput time 0.0979 0.0655 0.0846 0.0402 0.0525
Flexibility performance Volume flexibility 0.1706 0.2301 0.1469 0.1624 0.1760
Mix flexibility 0.0908 0.1570 0.0894 0.0865 0.0918
Product modification flexibility 0.1177 0.0789 0.1226 0.1276 0.1067
Expansion flexibility 0.1290 0.0982 0.1385 0.1388 0.1643
Ability to perform multiple tasks 0.1288 0.1355 0.1385 0.1431 0.1501
Labor flexibility 0.1896 0.1473 0.1385 0.1425 0.0759
New product developments 0.1004 0.1143 0.1385 0.1425 0.1433
Job classification 0.0380 0.0191 0.0538 0.0285 0.0735
Lot size flexibility 0.0345 0.0191 0.0327 0.0275 0.0181
Delivery reliability Reliability relative to competitors 0.2396 0.3204 0.2035 0.3233 0.2400
Perceived delivery reliability 0.1151 0.0754 0.1869 0.0733 0.0743
On time delivery percentage 0.1426 0.1485 0.0889 0.0870 0.1488
Average delay 0.2063 0.1960 0.0889 0.0978 0.1814
%age of incorrect orders 0.0379 0.0740 0.0531 0.0596 0.0470
%age reduction in lead time 0.0386 0.0412 0.1137 0.0969 0.0779
%age improvements in output 0.0417 0.0412 0.1137 0.0969 0.0409
%age on-time delivery 0.0675 0.0750 0.1008 0.0725 0.1077
Schedule attainment 0.1102 0.0278 0.0501 0.0922 0.0817
Safety Level of risk and safety perceived. 0.2219 0.2029 0.2256 0.1740 0.3026
Accident rate 0.3957 0.3083 0.2256 0.2764 0.3026
Level of employees cooperation 0.1140 0.2393 0.2256 0.2764 0.0678
Safety attitude of employees 0.0853 0.0722 0.2256 0.1135 0.1623
Level of physical risk on work place 0.0476 0.0433 0.0321 0.0437 0.0471
Level of safety information 0.1354 0.133 0.0653 0.1156 0.1172
Customer satisfaction Customer loyalty index 0.3181 0.2405 0.25 0.2421 0.2247
Product quality 0.5716 0.3871 0.25 0.3923 0.5207
quality service guarantees 0.0493 0.1732 0.25 0.1788 0.1224
Order frequency 0.0607 0.1991 0.25 0.1866 0.1319
Stock outs 0.2280 0.1958 0.1276 0.1866 0.3518
No. of complaints 0.0919 0.3291 0.2947 0.2845 0.3518
Customer lost 0.0924 0.0856 0.0942 0.0947 0.0592
New customers 0.1266 0.1068 0.1985 0.1376 0.0653
Number of customer referrals 0.1567 0.0535 0.0785 0.0528 0.0419
Market share in term of customers 0.0976 0.0996 0.0785 0.1158 0.0618
On time delivery 0.0924 0.1292 0.1276 0.1277 0.0678
Employees satisfaction Analysis of absnteeism 0.2687 0.3110 0.2746 0.2219 0.1565
%age of staff working flexible hours 0.1045 0.0815 0.1617 0.1012 0.1653
Turnover rate 0.2735 0.2374 0.2502 0.1759 0.2171
New employees referral recruits 0.0896 0.0966 0.0559 0.1134 0.0913
123
M. Ishaq Bhatti et al.
Tab l e 1 continued
Indicators Sub indicators Global weights
OMS Auto Elect Sports Textile
Employees satisfaction per survey 0.1202 0.1613 0.1216 0.1892 0.2016
Complaint resolution effectiveness 0.0298 0.0333 0.0312 0.0447 0.0658
Empowerment index 0.0366 0.0333 0.0522 0.0308 0.0271
Tenure of staff who has left 0.0765 0.0452 0.0522 0.1225 0.0750
Social Dollar donated to community 0.5199 0.541 0.4229 0.5644 0.3676
%age of locals in total workforce 0.3027 0.2850 0.4229 0.2304 0.4012
Number of media coverage events 0.0802 0.0770 0.0495 0.1133 0.1543
Number of photos in papers 0.0472 0.0484 0.0522 0.0459 0.0384
Sponsorships undertaken 0.0498 0.0484 0.0522 0.0459 0.0384
Iste discharge into environment 0.3759 0.4149 0.2557 0.2557 0.2
Iste and scrap produced 0.4227 0.2576 0.2557 0.2557 0.2
Yearly environment complaints 0.0539 0.0725 0.2557 0.2557 0.2
Environment friendly projects 0.0644 0.0786 0.0561 0.0561 0.2
Environment safety awards 0.0828 0.1762 0.1765 0.1765 0.2
Learning and growth Managers having IT literacy 0.1816 0.1812 0.2383 0.1793 0.2432
Employees with required education 0.2566 0.2397 0.2383 0.2469 0.2432
Employees certified for job position 0.3823 0.2397 0.2383 0.2469 0.2432
Managers with PM training 0.0866 0.2748 0.2604 0.2662 0.2432
No. of research paper generated 0.0927 0.0645 0.0245 0.0605 0.0270
Yearly fire outs for performance 0.1542 0.1871 0.2347 0.2465 0.2557
Investment for training 0.2546 0.4347 0.3854 0.3186 0.2557
Number of internal promotions 0.2934 0.1923 0.1875 0.2211 0.2557
Number of new staff 0.1778 0.0635 0.0560 0.0571 0.0561
Times in training (days/year) 0.1197 0.1222 0.1362 0.1565 0.1765
mance management, which indicate the relative importance toward selecting these indicators
as the KPIs for the manufacturing organizations in Pakistan. We learn from the descriptive
statistics in the Table 2. That the means’ value of overall indicators index for overall manufac-
turing sector and the electronics industry is 2.0913 and 2.2448. This difference is significant
(p= 0.15). The differences between the overall manufacturing sector and electronics indus-
try (p= 0.07), sports (p= 0.02) and textile (p= 0.04) are significant. The social performance
and learning and growth are the best performance indicators among all other performance
indicators in all industries, where as the quality and financial performance indicators are the
quite less important performance indicators in all industries.
4.2 Correlation
Correlation analysis is used to check the impact of various performance indicators indices on
each other and the overall performance index to know how they are helping each other in for-
mulating the overall performance index and in which direction, which is also used to answer
our second research question. The Pearson correlation coefficients (R) between performance
123
The key performance indicators (KPIs) and their impact
Tab l e 2 Weighted indices of all performance indicators
Indicators indices overall manufac-
turing sector
Automobile Electronics Sports Textiles
Mean SD Mean SD Mean SD Mean SD Mean SD
Cost 2.196 1.035 1.944 .626 2.272 1.018 2.229 1.192 2.178 .9487
Financial 1.660 .4621 1.532 .462 1.695 .3992 1.681 .4839 1.648 .4690
Quality 1.807 1.080 1.406 .399 2.118 1.321 1.897 1.074 1.702 1.090
Time 1.832 .5710 1.615 .432 2.075 .7583 1.886 .5865 1.754 .5234
Flexibility 1.958 .5504 2.073 .765 1.677 .3140 1.963 .5731 2.002 .5476
Del reliability 2.270 1.231 3.183 1.69 2.142 1.269 2.198 1.098 2.265 1.299
Safety 2.563 1.673 2.069 1.95 1.951 1.324 2.961 1.721 2.387 1.647
Customer satisfaction 2.062 .8377 2.343 .742 2.003 .6936 2.122 1.017 1.990 .7049
Employee satisfaction 2.448 1.333 2.419 1.75 2.157 1.221 2.496 1.234 2.469 1.441
Social 3.152 1.635 3.189 2.09 2.425 1.601 3.382 1.620 3.100 1.628
Learning and growth 3.511 1.554 3.481 1.82 2.698 1.616 3.806 1.502 3.428 1.553
OPI 2.091 .4241 2.244 .486 2.015 .4733 2.120 .4245 2.049 .4636
Tab l e 3 Correlations coefficients between the performance indicators
Cost Fin Qual Time Flex DR Safety CS ES Social L&G OPI
Cost
R1
Sig.
N84
Fin
R .076 1
Sig. .489
N84 84
Qual
R.011 .282 1
Sig. .918 .009
N848484
Time
R .250 .427 .497 1
Sig. .022 .000 .000
N84848484
Flex
R.004 .474 .146 .247 1
Sig. .969 .000 .187 .024
N8484848484
DR
R.351 .139 .312 .015 .178 1
123
M. Ishaq Bhatti et al.
Tab l e 3 continued
Cost Fin Qual Time Flex DR Safety CS ES Social L&G OPI
Sig. .001 .206 .004 .893 .105
N84 8484 84 8484
Safety
R .211 .612 .267 .217 .449 .202 1
Sig. .054 .000 .014 .047 .000 .066
N84848484848484
CS
R.214 .191 .147 .071 .352 .069 .181 1
Sig. .050 .082 .183 .524 .001 .530 .100
N8484848484848484
ES
R .000 .434 .016 .070 .397 .254 .688 .412 1
Sig. .999 .000 .883 .525 .000 .020 .000 .000
N848484848484848484
Social
R .346 .125 .027 .069 .132 .042 .573 .096 .564 1
Sig. .001 .262 .808 .537 .238 .705 .000 .390 .000
N82828282828282828282
L&G
R .427 .111 .021 .163 .003 .002 .437 .013 .494 .845 1
Sig. .000 .319 .851 .145 .981 .985 .000 .907 .000 .000
N8282828282828282828282
OPI
R.052 .391 .576 .451 .360 .538 .404 .570 .347 .367 .329 1
Sig. .637 .000 .000 .000 .001 .000 .000 .000 .001 .001 .003
N848484848484848484828284
indicators are listed in Table 3for overall manufacturing sector. The results for correlation
show that the quality has a significant positive correlation with time, delivery reliability and
safety, which means that the increase in time, delivery reliability and safety will result into
the increase in overall quality performance of the organization. The time has a significant
positive correlation with flexibility and safety. It means that increase in the flexibility and
safety performance will result due to the increase in the time performance. The flexibility has
a significant positive relation with the safety, customers’ satisfaction and employees’ satis-
faction. These correlation values mean that the increase/decrease in the safety, customers and
employees’ satisfaction will result into the increase/decrease in the performance of the organi-
zation in terms of the flexibility. The delivery reliability has a significant negative correlation
with the safety and employees’ satisfaction. The safety has a positive significant relation
with employees’ satisfaction, social performance and learning and growth performance. The
customers’ satisfaction is positively correlated with employee’s satisfaction. The employees’
satisfaction is positively correlated with social and learning and growth performance. At
the end all the indicators other than the cost have a positive significant correlation with the
123
The key performance indicators (KPIs) and their impact
overall performance index. And if we write the results of Pearson correlation between all
performance indicators and overall performance index the most significant positively corre-
lated performance indicator is quality (p= .000, R= .576) followed by the customers’ satis-
faction (p= .000, R= .570), delivery reliability (p =.000, R =.538), time (p =.000, R =.451),
safety (p= .000, R= .404), financial (p= .000, R= .391), social (p= .001, R = .367), flexibil-
ity (p= .001, R= .360), employees’ satisfaction(p= .001, R = .347) and learning and growth
(p= .003, R= .329). The cost is negatively correlated (R= 0.637) with overall performance
indicator but their relationship is not significant (p= .637).
4.3 Regression analysis
In order to address third research question which was the impact of these performance indica-
tors upon the overall performance of the organizations? We have used the regression analysis
with the overall performance indicators index as the dependent variable and the eleven per-
formance indicators indices as the independent variables. The results of the simple regression
are given in the Table 4, which show that measuring the performance in terms of cost, finan-
cial, quality, time, flexibility, delivery reliability, safety, customer satisfaction, employees’
satisfaction and social performance indicators have positive significant impact on the over-
all performance of the organizations at 0.01 significance level. But the learning and growth
index has no effect on the overall performance indicators index. On the basis of beta coeffi-
cient the delivery reliability (beta= 0.591) has more impact on the overall performance index
followed by customers’ satisfaction (beta= 0.443), quality (beta= 0.232), cost (beta= 0.150),
employees’ satisfaction (beta= 0.143), financial (beta= 0.119), flexibility (beta= 0.108), time
(beta= 0.103), social (beta= 0.094) and safety (beta= 0.081). The R square (Coefficient of
determination) is 0.965 which is the degree of variation explained by the eleven indicators in
overall performance index. It means that these eleven performance indicators are explaining
the much of the variability in the overall performance of the organizations.
Tab l e 4 Regression coefficients for the performance indicators indices
Model Un-standardized coefficients Standardized
coefficients
tSig.
B SE Beta
(Constant) .027 .067 .406 .686
Cost .064 .014 .150 4.699 .000
Financial .114 .032 .119 3.543 .001
Quality .100 .014 .232 7.320 .000
Time .079 .024 .103 3.329 .001
Flexibility .089 .023 .108 3.830 .000
Delivery reliability .212 .011 .591 19.990 .000
Safety .022 .012 .081 1.877 .065
Customers’ satisfaction .233 .015 .443 15.810 .000
Employees satisfaction .049 .015 .143 3.363 .001
Social .026 .014 .094 1.883 .064
Learning and growth .022 .014 .076 1.533 .130
123
M. Ishaq Bhatti et al.
5 Summary and conclusions
The performance management is an important factor for organization to get a competitive
advantage over their competitors. This is the only way for organizations to check either they
are going in right direction and achieving their targets in terms of their preset objectives and
goals or not. For this purpose, the performance measures are used to evaluate and control
the overall business operations. They are also used to measure and compare the performance
of different organizations both within the organization and outside of the organization. The
performance can be compared within the departments, sub departments, teams and individual
processes (Ghalayini and Noble 1996). This study is an attempt to know that which are the
KPIs used by the manufacturing sector of Pakistan? What is the relationship between these
performance indicators and overall performance index? And what is the impact of these KPIs
on the overall Organization’s performance Index in manufacturing sector of Pakistan?
Fernandes et al. (2006) has discussed four types of performance indicators like financial,
customer related, learning and growth and internal business process and he also discussed the
KPIs for these four types. Bernard et al. (2004) have discussed three perspectives of perfor-
mance measurement, which are the growth/renewal, efficiency and stability. Munir Ahmad
and Dhafr (2002) also explored three perspectives of performance measurement indicators
the financial performance indicator (business performance), technical performance indicator
(productivity measurement) and efficiency indicator (human contribution measurement).
The results of AHP analysis show that the overall manufacturing organizations put more
focus on the customer satisfaction and delivery reliability. The automobiles organizations put
more focus on the customer satisfaction and social performance. The electronics, sports and
textiles industries put more focus on the customers’ satisfaction and delivery reliability. On
the basis of regression analysis we can conclude that measuring the performance in terms
of cost, financial, quality, time, flexibility, delivery reliability, safety, customer satisfaction,
employees’ satisfaction and social performance indicators have positive significant impact
on the overall performance of the organizations, whereas the learning and growth index has
no impact over the overall performance of the organizations.
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In the recent world, making the proper decisions in business is challenging and complicated, especially on sales data. Sales are the most valuable part of a business. Only the sales report of a business is not enough for today’s business development. The activity needs to get an insight into sales using data because data-driven decision is more impactful. The purpose of the research is to develop an affordable and approachable model to deliver a business insight that helps you to understand your business and support to make business decisions faster. In this piece of research work, a model is proposed to develop an affordable simple sales data insight, helping with business intelligence technique and cloud database. This model uses a set of data, with ad hoc query, statistical analysis, some mathematical equations, and data visualization is a key component to gain a proactive and data-driven solution. Using such methodologies and approaches, our model generated certain key performance indicators and a quick snapshot of the sales situation, allowing company owners to see trends and predict sales process weaknesses. Not only that proposed model also provides geolocations sales state and cross ponding sales preview on a visualization mode.
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There are many fascinating headings that can be investigated. Newspapers, blogs, articles print a lot of content and depict a lot about a person’s positive and negative aspects. In this chapter, we have explained how we can estimate those numbers of positivity, negativity, or neutrality about the product or services provided by an organization. This is the way toward recognizing and arranging sentiments communicated in a bit of content, particularly to decide if an author’s disposition toward a point/item is sure, negative, or impartial. It is utilized to check how positive or how negative an announcement is. This analysis is like manner called sentiment mining or opinion AI, is the path toward deciding if a touch of making is sure, negative, or unprejudiced. A run of the mill use case for this development is to discover how people feel about a subject. Sentiment analysis is broadly connected to audits and internet-based life for an assortment of utilizations. Sentiment analysis can be performed from various perspectives. Numerous brands and advertisers use watchword-based apparatuses that arrange information as positive/negative/impartial. Social media platforms play an important role in providing real time streaming data for such analysis. In this chapter we have tried to provide the complete pathway to do social media analytics.
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Besides the broad changes in industry atmospheres and the increase in competition. Decision intelligence (DI) is one of the most imperative issues that contribute to strategic business planning (SBP), At present, a functioning business lacking a DI and SBP is like a session in the purchaser bench of your private business. In the long run, nevertheless, you meagerly watch as it tries unreliably or, further appalling, smashes and blisters. DI and SBP put you on a dynamic seat. SBP can attend as a context for the successful conclusion of business indicators. Commercial proprietors are in a loftier condition to understand their professional and become specialists in their industries. Also, helps superintendents understand the path in which their commercial is profitable by looking into past development and making variations to develop and produce. While, DI is the new development that transports a summary for best completes help the high-glassy managers in decision-making technique in the state of ambiguity since they are about upcoming and they are prolonged-term decisions that make administrations to retain on the path to see progress and economic goals.
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Measuring intellectual capital is on the agenda of most 21st century organisations. This paper takes a knowledge-based view of the firm and discusses the importance of measuring organizational knowledge assets. Knowledge assets underpin capabilities and core competencies of any organisation. Therefore, they play a key strategic role and need to be measured. This paper reviews the existing approaches for measuring knowledge based assets and then introduces the knowledge asset map which integrates existing approaches in order to achieve comprehensiveness. The paper then introduces the knowledge asset dashboard to clarify the important actor/infrastructure relationship, which elucidates the dynamic nature of these assets. Finally, the paper suggests to visualise the value pathways of knowledge assets before designing strategic key performance indicators which can then be used to test the assumed causal relationships. This will enable organisations to manage and report these key value drivers in today's economy.
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Business process re-engineering (BPR) is the latest addition to the armoury of management techniques available. BPR purports to produce quantum improvements in performance by radically redesigning organizational processes. There is, however, some confusion as to what exactly constitutes BPR and how, if at all, BPR should be integrated with other approaches such as total quality management (TQM) and benchmarking. Uses a survey of 65 organizations from different industrial sectors to examine the industry understanding and use of BPR, and its integration with other management techniques.
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