Theory of Constraints: A Review on its Evolution and Adoption.
Transcript of Theory of Constraints: A Review on its Evolution and Adoption.
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Theory of Constraints: A Review on its Evolution and Adoption.
Dr.Nishant Kumar1Mohammad Talha Siddiqui
2 Mohammad Suhail
3
1Department of Business Administration, University of Lucknow, Lucknow, India. E-mail: [email protected].
2Department of Business Administration, University of Lucknow, Lucknow, India. E-mail: [email protected]. 3 Department of Building Engineering and Management, School of Planning and Architecture, New Delhi, India.E-mail:
Abstract
This study attempts to present an analysis of the evolution of Theory of Constraints over last three decades.This work is based on
analysis of various research papers, articles, books and testimonials of practicing consultants. From the studies it is found that
TOC is in its evolution stage only. Starting from the production area it has spread to various other disciplines like supply chains,
retail, marketing, services, strategy and other complex environments. The main contribution of the study are: (1)presenting the
evolution of TOC through literature review.(2)discussing the various tools of TOC available for various disciplines(3) assessing
the benefits of adoption of TOC by Indian firms.
Keywords: Theory Of Constraints (TOC), Critical Chain Project Management (CCPM), Drum Buffer
Rope (DBR), Thinking Process (TP)
Introduction
Theory of constraints(TOC) was conceived by an Israeli physicist Dr. Eliyahu M Goldratt. Theory of
constraints is a management philosophy which focuses on removing the weakest point in the operation of
the system. The concept started in the 1970's, when Goldratt and his team were working on a
programming software to optimize the production systems, they called it Optimized Production
Technology(OPT).(Goldratt et al., 1984) The name TOC slowly evolved and was put forth by Goldratt in
the novel ― The Goal‖ in the year 1984. The book focused on some concepts and phenomena that were
applicable in manufacturing and also proposed the concept of Process of ongoing improvement and
decision making for organisations.(Goldratt et al., 1984) Since then, the application of TOC has
broadened to various areas, such as supply chain,(Gupta & Andersen, 2018; S Rahman, 2002;
Simatupang et al., 2004) projects,(Goldratt, 2001; Leach, 1999; Luiz et al., 2019; Steyn, 2001)
marketing,(Lowalekar & Basu, 2019) services(Motwani et al., 1996)and retail(Gardiner, 1993; Goldratt,
1994). TOC philosophy considers all processes in system as rings of the same chain, they all are
dependent on each other. As a weak ring can break the whole chain, similarly a weak process can put the
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system on hold.(Cox J.F. & Schleier, 2010)Therefore, TOC philosophy focuses on the weakest
ring(process) of the chain (system). The concept of Theory of Constraints can be summarised as follows:
● Every system has at least one constraint, i.e. there is no system without a constraint. If this was
not true, then system would make infinite profit which is impossible. A constraint therefore, ―is
anything that limits a system from achieving higher performance versus its goal‖ (Goldratt, 1988)
● Constraints are good for the system, seems ironic. But TOC considers it as positive not
negative.(Shams ur Rahman, 1998) Because of constraint there is always opportunity for
improvement in the system.
There are two major components in the Theory of Constraints. First component is the philosophy that is
behind the working of TOC. It consists of five steps that focus on ongoing improvement: DBR(drum-
buffer-rope) scheduling methodology and the buffer management information system usually called as
―logistics‖ paradigm. The second component of the TOC is the Thinking Process(TP), it is a generic
approach for investigating, analyzing and solving complex problems.(Shams ur Rahman, 1998)
Philosophy
The principle of TOC focuses on continuous improvement process. The system can be improved by
focusing on the constraints. There is a series of five focusing steps.(Goldratt, 1990b)The steps of TOC are
generic in nature, they can be applied to various areas like manufacturing, services, marketing etc. The
five focusing steps(5FS)of the principle are:
I. Identify the constraint(s) in the system. A system can only be improved after knowing the
problematic point. Therefore, the first step in the improvement process is to find the constraint
that is limiting the performance. Only when the constraint is known then only one can design the
control mechanism for the constraint.
II. Exploiting the system constraint. To have a constraint in the system is the opportunity to make
the system more efficient. After identifying the constraint the focus should be there to remove the
constraint so as to make increased throughput.
III. Subordinate everything to support the above change.Everything has to be aligned with the
decisions in the above step. Every other operation should be adjusted towards eliminating the
constraint. That means that all the non constraints should be centered towards optimizing the
constraint(thus entire system) ,not their individual performance.
IV. Elevate the constraint. At this point, after going through the above three steps if the constraints
still exists, it is the time to improve the constraint itself. This step is quite expensive as it requires
adding resources to remove the constraint. The resources can be like man, material, money,
machine, etc.
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V. Return to the first Step. After the aforementioned constraint is removed, new constraint may
develop in. So the quest is to remove the new constraint. To remove the new constraint the above
steps are repeated once again.
Literature Review
People are mistaken that theory of constraints can only be applied to production management but the case
is a bit different. Over the years TOC literature has seen many evolved concepts. The same TOC thinking
process that brought DBR( Drum-Buffer-Rope ) has created a whole new array of the TOC solutions,
such as critical chain project management(CCPM), Mafia offers, Simplified drum buffer rope(S-DBR)
management, Reliable Rapid replenishment and others(TOC Applications - Theory of Constraints
Institute, n.d.). Theory of constraints has quite a wide range of applications asit has beenused in many
management disciplines like project management(Goldratt, 2001; Leach, 1999; Luiz et al., 2019; Steyn,
2001), supply chain(Gupta & Andersen, 2018; S Rahman, 2002; Simatupang et al., 2004),
retailing(Gardiner, 1993; Eliyahu M Goldratt, 1994, process improvement and in other production
environments(Lambrecht & Segaert, 1990; Raban & Nagel, 1991), sales and marketing(Lowalekar &
Basu, 2019), research and development accounting(Şimşit et al., 2014) and so on.
There are various definitions of Theory of Constraints given by different researchers according to their
usage but the main idea of ToC is centric towards the constraint. The aim of any organisation is to
increase profits and anything that limits the profit of the organisation is a constraint. Studies have
suggested that TOC techniques could result in increased profits at the same time decreasing both
inventory and cycle time(Watson et al., 2007). Numerous studies have validated that systems using TOC
techniques have shown increased performance compared to those systems using Manufacturing Resource
Planning(MRP), Just-in-Time(JIT) approach Lean and Agile manufacturing(Dave et al., 1991; Davies et
al., 2005; Watson et al., 2007).
Many fortune 500 companies like 3M, Amazon, Ford motor company, Delta Airlines, Boeing, Lucent
technologies and general motors have disclosed publicly their improvements after deploying TOC. There
are many other companies who have not disclosed their improvement due to competitive reasons.
Applications of Theory of Constraints is not only limited to profit-organisations but they have also proved
equally beneficial for non-profit-organisations such British National Health Service, United Nations,
United States Department of Defence, NASA, Habitat for humanity.(Watson et al., 2007)
Despite great improvements in various organisations achieved by TOC, it is not widely accepted in
mainstream moreover implementation appears to be least mature as compared to other methodologies.
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Several authors - Davies et al., 2005; Ikeziri et al., 2019; Kim et al., 2008; Shams ur Rahman, 1998;
Watson et al., 2007; Xu & Xu, 2010; have given detailed review of published literature on TOC. In order
to comprehend the evolution of TOC, Watson et al.‘s five era structure has been used in the present paper.
1) The Optimised Production Technology Era
2) The Goal era
3) The Haystack Syndrome Era
4) The It's Not Luck Era
5) The Critical Chain Era
The Optimised Production Technology Era
The beginning TOC is quite unspectacular. It started with a small request for help. In late 1970‘s a
neighbour of Goldratt asked for assistance from him. Goldratt helped him by developing a program that
increased the production multifolds within a short period of time.
Goldratt introduced that solution as Optimised Production Timetables. Later it was renamed to optimised
production technology or OPT. The Process of OPT was first described by Fry et al in 1992. OPT
consisted of 4 components- BUILDNET, SERVE, SPLIT and OPT.
Although OPT was showing tremendous results in the firms where it was being applied but academicians
did not pay enough attention towards it. However there were several studies which talked about OPT. In
1983 Jacob explain how it can give good results in scheduling and production planning, in 1984 Fox
explained basics of OPT and investigated bottlenecks on the factory floor, in 1985 Harrison tried to
explain the concept of OPT in terms of goals of manufacturing organisations, in 1985 Agrawal
benchmarked MRP, JIT and OPT and discussed these inventory control systems. In that studies
comparative analysis was done and they tried to explain how these techniques can complement each
other. In 1990 Ronen and Starr discussed that OPT can be used with DBR.
The nine OPT rules(Goldratt & Fox, 1986) given by Goldratt are given below:
1. Balance flow, not capacity.
2. Level of utilization of a non-bottleneck is determined not by its own potential but by some other
constraint in the system.
3. Utilization and activation of a resource are not synonymous.
4. An hour lost at a bottleneck is an hour lost for the total system.
5. An hour saved at a non-bottleneck is just a mirage.
6. Bottlenecks govern both throughput and inventory in the system.
7. A transfer batch may not, and many times should not, be equal to the process batch.
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8. The process batch should be variable, not fixed.
9. Schedules should be established by looking at all of the constraints simultaneously. Lead times are a
result of a schedule and cannot bepredetermined.
The Goal Era
As discussed earlier Goldratt was not getting much response from the industry practitioners. To attract the
attention of the practitioners, Goldratt made change in his strategy and wrote a book ―The Goal‖ with Jeff
and Cox in the year 1984. The Goal was a manufacturing novel about how Alex with the help of Jonah
saves his plant. The Goal was written to educate workers about employing OPT in the manufacturing
facilities. The strategy of Goldratt worked and soon ―The Goal‖ became the business best seller. This
elevated response from the practitioners as many of them tried to implement the concept found in the
book.
The Goal was the forerunner of TOC. It explained the heuristics and techniques that later became
foundation of Theory of Constraints. The Goal outlines 5 focusing steps of TOC. These 5 focusing
steps(5FS) later evolved as POOGI( Process Of On-Going Improvement). POOGI consists of 7 steps- five
of which are 5FS, which are discussed earlier and two prerequisites of implementation(Goldratt et al.,
1984). These two preliminary steps are:-
1. The Goal of the system.
2. Determination of global measures to achieve the goal.
In the same book the concepts of Drum Buffer Rope(DBR) is also discussed. DBR is a scheduling
technique of Theory of Constraints. It is focused on increasing the flow by identifying and leveraging the
Drum(Constraint).
The concept of DBR is explained in Goal with the example of boy scouts going on a hike. Later in the
book Race also, Goldratt explained this concept with the help of soldiers marching on the drum beat.
In DBR, Drum is the constraint. A constraint is something that limits the pace of the operation just like a
drum which controls the marching soldiers. It becomes very important to handle the constraint, as the
output of the system is just the output off constraint. DBR ensures that the constraint is 100% utilized, it
should not remain idle. To ensure that constraint is working on its full limit, additional buffers are
assigned to it.Buffer makes sure that that the constraint is not in ―starving‖ condition.
The concept of rope is like giving the one end of rope to the slowest soldier and other end to the first
soldier. It will ensure that all the soldiers will move with the same speed. This concept is also applied in
organisations.All the processes should be aligned with the speed of the most limiting constraint. In
facilities, this rope concept will help to keep an eye over unwanted work -in- process inventory, as all the
processes/machines are working with speed of constraint(Drum).
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Therefore, DBR ensures that facility/machines are working on the beat of the Drum i.e. constraint.
DBR methodology can be summarised as follows(Cox J.F. & Schleier, 2010):
1. Developing MPS(Master Production Schedule) compatible with the constraint.
2. Safeguard the throughput of the system from fluctuations by using buffers at the critical
points(Constraint).
3. Restrict the production of each facility to the Drumbeat(Rope).
Haystack Syndrome Era
The book ‗Haystack Syndrome‘ by Goldratt was written in 1990. The issue of data and information
incongruency has always been a critical issue for any company. In this book Goldratt examined data in a
new way and presented it very beautifully that how misinterpretation of these concepts can affect the
quality of decision making.
Most companies measure performance on ROI and Net Profit but there is also another measure which is
important-data found in the cash statements. Goldratt focused upon removing the overlap between
inventory and operating expenses. Traditional view on inventory is that it is considered as an asset but
Goldratt had a different view on this. According to Goldratt, cost accounting is enemy to the
productivity(Watson et al., 2007). TOC always called for change in the standard absorption cost
accounting systems. Goldratt said that when traditional cost accounting principles are applied to estimate
local performance measures, capital investment and product cost decisions provide deceiving outcomes
which may result in implementation of some policies that can result in fatal strategic misfit.(Goldratt,
1990a)
Goldratt was not the only one who opposed traditional cost accounting.Authors like Kaplan, and Johnson
have also felt that traditional accounting principles do not fit in highly flexible manufacturing systems. To
remove this incongruence Kaplan and Johnson developed activity based costing.(Johnson & Kaplan,
1987; Kaplan, 1983, 1986).On the other hand to remove this incongruence between TOC and Cost
accounting principles, Goldratt with others led to the development of process centered performance
measurement called Throughput Accounting (TA).
The goal of the TOC system is to make money now and also in the future. In order to examine whether
the company is achieving that goal or not, three global measures are used- Net Profit(NP), Return on
Investment(ROI) and cash flow(CF). TOC also uses these measures for global performance.But at
subsystem levels/plant levels Goldratt and Cox have introduced different measures - Throughput(T),
Inventory(I) and Operating Expense(OE). Goldratt also introduced three measures at the process level -
Throughput dollar days(T$D), Inventory dollar days(I$D) and local operating expense. Apart from these
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nine measures, another important concept of TOC also evolved,e.g, Contribution Per Constraint Per
Minute(CPCM). CPCM has wide use in make or buy decisions(Watson et al., 2007).
It’s not luck era.
‗It‘s not luck‘ is a book written by Goldratt in the year 1994. This book is the sequel to ―The Goal‖. In
this book Goldratt proposed a way and a set of logical tools for analysing the situation and handling
constraints. This logical tool was called Thinking Process(TP). Thinking process consists of five logical
tools which act as a framework for the decision making process. TP focuses on the three basic questions
of TOC: What to change? What to change to? How to cause the change? The tools which help in
answering these questions are: Current Reality Tree(CRT), Conflict Resolution Diagram(CRD) or
Evaporating Cloud(EC), Future Reality Tree(FRT), Prerequisite Tree(PRT) and Transition
Tree(TRT)(Dettmer, 2007; Goldratt, 1994)
Figure 1. Thinking Process. Source: Dettmer, 2007
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Current Reality Tree
CRT is a series of cause and effect relationships that start from undesirable effects down to few root
causes. CRT helps to identify what in the system needs to be changed.
Conflict Resolution Diagram
After CRT the next step in the TP is Conflict Resolution Diagram(CRD) or Evaporating Cloud. It is a
necessity-logic tool. As the name suggests CRD is used to resolve conflicts. The purpose of EC is to
surface the conflict and provide ideas of what can be changed to resolve the problem and create a win-win
situation.
Future Reality Tree FRT
It begins with the outputs from CRT and EC. FRT provides a blueprint to eliminate deviations identified
in CRT(Dettmer, 2007)Unlike CRT, FRT is a bottom up approach. It begins with the identification of the
actions and conditions that lead to the desired outcomes(Cox J.F. & Schleier, 2010; Dettmer, 2007)and to
check whether or not new UDEs(Undesirable Effects) arise from the actions(Kendall, 1998)
PRT and TRT
PRT seeks to identify obstacles or conditions that may hinder the achievement of desired outcomes and to
create new Intermediate Objectives(IO) to overcome identified obstacles. On the other hand TRT is a step
by step sequence of implementing the change. It is used to identify the tasks and actions needed to meet
the Intermediate objectives of PRT(Cox J.F. & Schleier, 2010)
Critical Chain Era
In 1990 at International Jonah Conference, a method based on TOC called critical chain project
management(CCPM) was introduced.(Watson et al., 2007) This method has time management focus to
schedule and control projects. The concept of CCPM is based on two premises. The first basic premise is
that better time management offers benefits to scope and cost management. The second premise is that
adding safety time at the end of each activity is the root of the problem(Goldratt, 2001). As a solution to
this problem, safety elements(buffers) in CCPM are allocated at the last of task(Raz et al., 2003).
According to CCPM projects fail due to some behaviour of the teams. These behaviours are student
syndrome, Parkinson‘s Law and poor multitasking(Robinson & Richards, 2010).CCPM starts with the
network diagram of various tasks-activities with their estimated durations. CCPM identifies the critical
chain(set of activities that take the longest time). Critical chain provides project conclusion date(Rand,
2000). CCPM manages uncertainity by allocating buffers at the end of the critical path. Buffers proposed
by CCPM are project buffers, feeding buffers, resource buffers(Herroelen & Leus, 2001; Leach, 1999).
CCPM controls project progress using buffer management(BM). When the actual time of the project
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exceeds the forecasted time the surplus is used from the buffer. The evolution of the CCPM can be
categorized into three stages(Luiz et al., 2019). The first stage is the ―Conceptual‖stage, evolved over the
period 2000-2005. In this stage various articles were published that focused on the basic foundation of
CCPM and its comparision with other traditional project management approaches. The second stage is
―Deepening of Applications‖ stage, evolved over the period of 2006-2010. In this stage most of the
studies addressed buffer management. Also CCPM was used for emperical studies in various
sectors(Bevilacqua et al., 2014) like construction(Rogalska & Hejducki, 2007) and electronics(Kuo et al.,
2009). The era after 2011 is called as ―Methodological Maturity‖stage. In this stage the application of
CCPM has expanded to multiprojects management. Various mathematical modelling techniques for
CCPM evolved in this stage like-Multi Objective Optimization method(Wang et al., 2014), Evidence
Reasoning approach(Yang & Fu, 2014), algorithms based on Multi-agent systems(Zhang et al., 2014) and
Fuzzy theory(Roghanian et al., 2017)
Application of Theory Of Constraints by Indian Firms
In India many organisations have benefitted by using TOC in their organisations. There are very few
consulting firms in India that are working on TOC with their clients. Among the very few firms-Goldratt
India and Vector Consulting have worked with many organisations and have helped them to grow both
top line and bottom line with the help of TOC.
Companies like Jindal Steel and Powers, Godrej, Paharpur, Airtel, Eicher and many more have
overhauled their operations with the help of TOC. These companies have substantially improved their
operations by reducing lead times, reducing work in process, reducing finished goods inventory, and also
reducing receivables.
According to Goldratt India, their clients have achieved some or all of the following after implementing
TOC (Theory of Constraints Consulting | Goldratt India, n.d.-a):
● Quantum improvement in On Time In Full (OTIF): Clients have been able to improve their
On Time Delivery from less than 10% to over 95%.
● Substantial Reduction in lead-time: Clients are able to shrink their lead-time by a factor of 2 to
6.
● Reduction in Finished Goods Inventory: Finished Goods reduction achieved ranges from 20%
to 50%.
● Reduction in Work-In-Process (WIP): Clients have reported WIP Reduction in the range of
30% to 80%.
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● Reduction in receivables: Typical reduction achieved in receivables is 20% to 30%.
TOC applications are not confined to manufacturing or operations only, they have wide applications in
other streams also. Mishra & Palo, 2014in their research paper have discussed the applications of Theory
of Constraints in the realm of Indian Administrative Services. The writers have discussed how constraints
figured out using cause and effect relationships and also discussed the course of action taken by the
officers to eliminate the constraints.
To have the actual picture of how organisations in India havebenifitted after applying Theory of
Constraints, testimonials of various top level executives was analysed. These testimonials were written by
Chairmans,CEOs and Directors of organisations to the consulting firm that helped them to implement
TOC tools in their oraganisations. In the present study, data from select testimonials written for Goldratt
Indiais taken. After content analysis of the testimonials, the key points are summarized in the table-1.
Table 1. Improvements in various organisations after implementing TOC.
S.No. Company/Year Outcomes of the Implementation of TOC Tools
1) Jindal Steel & Powers ● Improved cash through reduction in receivables,
inventories, export incentives etc.
● Reduction in gross working capital by Rs 2500 in 2015-
16.
● Reduction in gross working capital by Rs 1100 in 2016-
17.
● Overall reduction of gross working capital by 56%
● EBITDA increased by 16% in 2015-16 and 17% in 2016-
17.
2) Paharpur Cooling
Towers
● OTIF(On Time In Full) helped in increasing timely
despatches.
● Weekly review concept helped a lot.
● TOC solution DBM helped in reducing blocked money
and maintained efficient inventory levels.
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3) Airtel ● Used the concept of Conflict Cloud to make processes
customer friendly.
● Performance increased manifold in areas of project
delivery.
4) Flexistuff ● Month end syndrome was reduced.
● Weekly planning was helpful in production planning,
dispatch scheduling and receivable collection.
5) Samtel Color ● Procurement, inventory management, payment terms with
customers were improved.
● Cash blocked in receivables and inventories was reduced
to 43 crores from 89 crores in the span of 9 months.
6) Sheela Foam(2008) ● In the financial year 2007-08 the company grew by more
than 30% on the top line and more than 70% in the bottom
line.
7) Godrej ● Significant improvement in online delivery, lead times and
despatches.
● Increased customer satisfaction.
8) Indo Asian ● The turnover in the second half of the financial year
increased by 30%.
● Cash generation and profits increased.
● TOC encouraged teamwork and changed the attitudes of
the members of Indo Asian.
9) Salora International ● Reduction in Lead time from 5 days to 1 day.
● Reduction in WIP inventory by 80%.
● Reduction in finished goods inventory by 30%.
● Reduction in raw material inventory by 10%.
10) Nat Steel ● Ontime deliveries increased from 5% to 95%.
● Lead times reduced from 13 weeks to 2 weeks.
● Order inflow rate increased by 25%.
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● Sales up by 25%,
● Receivables down by 33%.
● Inventories down by 33%.
● Suppliers payments from over 3 months to 1 month.
● Bank Borrowing reduced by 40%
11) Eicher(2003) ● In the first half of the year grew by 29% of the last year.
● Planning and cash control improved.
● Better teamwork.
12) Eicher(2004) ● 57% increase in net sales in one year.
● 43% increase in throughput.
● Operating expenses were under control with only 1% rise.
13) Hari Machines(2005) ● Company undergoing heavy losses became profit making
company.
● In 2004-05 Hari Machines achieved a turnover of 125
crores, which is about 30 times the turnover of 1999-2000.
14) Fleetguard(2006) ● Throughput increased by 35% and profit doubled within 6
months of using TOC.
● The company achieved the performance without any
additional investment or any increase in fixed expenses.
15) Natsteel(2007) ● Manufacturing despatches increased by 53%.
● Ontime despatches.
● Weekly throughput increased by 48%.
● Profits increased by 200% over the last year.
16) Natsteel(2008) ● Manufacturing despatches increased by 72%.
● Ontime despatches.
● Weekly throughput increased by 96%.
● Profits increased by 400% over the last year.
17) Paharpur 3P(2007) ● Within 3 months of implementing TOC, loss making firm
started earning profits.
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● Within 13 weeks throughput increased by 30%.
● Weekly review process was very helpful.
18) Paharpur 3P(2008) ● Throughput increased by 27%.
● Delivery period and on time delivery improved
significantly.
● Inventories decreased substantially despite increase in
volume by 25%.
19) Sona Okegawa(2009) ● Throughput increased by 41%.
● Receivables days reduced from 157 days to 48 days.
● Profit increased by 129%.
● OTIF tool was very helpful in planning.
20) Paharpur(2016) ● OTIF was very helpful in increasing the timely
despatches.
● Weekly review system has reduced month end syndrome
for factory despatches.
● TOC supply chain solution-DBM improved the quality of
inventory while reducing the blocked money.
Source:Theory of Constraints Consulting | Goldratt India, n.d.-b
Conclusion
Through research and analysis of various research papers, articles and books, the present study has tried
to analyse various transitional stages of TOC. Although TOC started with a production scheduling
software but now it has evolved as an integrated management philosophy that is being used in various
disciplines.
Various practitioners and researchers have empirically observed the benefits of implementing TOC in
theirorganisations. These benefits are not only confined to operational and financial performance
enhancement onlybut also reflect in ameliorated teamwork and motivational levels of workers. As the
implementation of TOC has not been universally adopted by business firms, there are some gaps in its
usage across industries. There are few practitioners who have not accepted TOC concepts. They argue
that TOC only gives feasible solutions, not the optimal solutions. Practitioners are also not able to
associate TOC concepts with the newly emerging areas like Internet of Things, Industry 4.0, Smart
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Factory, etc.But in the bigger context, results of TOC implementation present a positive evolutionary
trend. Implementation of TOC in firms has shown notable improvements. One thing that need to be
highlighted is that these notable improvements have come in those systems which were already very
efficient in nature. Organisations like Ford, NASA, Godrej, Jindal Steels and others were already using
other scheduling and controlling tools for years and had made their systems effective and efficient and yet
application of TOC tools in these firms made their systems more efficient.
References
Bevilacqua, M., Ciarapica, F. E., & Mazzuto, G. (2014). Critical chain and theory of constraints applied to yachting shipbuilding:
a case study. International Journal of Project Organisation and Management, 6(4), 379.
https://doi.org/10.1504/ijpom.2014.066411
Cox J.F., I., & Schleier, J. G. (2010). Theory of constraints handbook. McGraw-Hill.
Dave, U., Fogarty, D. W., Blackstone, J. H., & Hoffman, T. R. (1991). Production and Inventory Management (2nd Edition). The
Journal of the Operational Research Society, 42(10), 904. https://doi.org/10.2307/2583420
Davies, J., Mabin, V. J., & Balderstone, S. J. (2005). The theory of constraints: a methodology apart?—a comparison with
selected OR/MS methodologies. Omega, 33(6), 506–524. https://doi.org/10.1016/j.omega.2004.07.015
Dettmer, H. W. (2007). The logical thinking process: a systems approach to complex problem solving. ASQ Quality Press.
Gardiner, S. C. (1993). Measures of product attractiveness and the theory of constraints. International Journal of Retail and
Distribution Management 21, 7, 37–40.
Goldratt, E. M. (1988). Computerized shop floor scheduling. International Journal of Production Research 26, 3, 443–455.
Goldratt, E. M. (1990a). The Haystack Syndrome: Sifting Information from the Data Ocean?, 1st (ed). North River Press, New
York, NY.
Goldratt, E. M. (1990b). What is this thing called theory of constraints and how should it be implemented? North River Press.
Goldratt, E. M. (1994). It’s not luck. North River Press.
Goldratt, E. M. (2001). Critical chain. North River Press.
Goldratt, E. M., Cox, J., & Whitford, D. (1984). The goal : a process of ongoing improvement.
Goldratt, & Fox, R. E. (1986). The race. North River Press.
Gupta, M., & Andersen, S. (2018). Throughput/inventory dollar-days: TOC-based measures for supply chain collaboration.
International Journal of Production Research, 56(13), 4659–4675. https://doi.org/10.1080/00207543.2018.1444805
Herroelen, W., & Leus, R. (2001). On the merits and pitfalls of critical chain scheduling. Journal of Operations Management 19
(5), 559, 577.
Ikeziri, L. M., Souza, F. B. de, Gupta, M. C., & de Camargo Fiorini, P. (2019). Theory of constraints: review and bibliometric
analysis. International Journal of Production Research, 57(15–16), 5068–5102.
https://doi.org/10.1080/00207543.2018.1518602
Johnson, H. T., & Kaplan, R. S. (1987). The Rise and Fall of Management Accounting. IEEE Engineering Management Review,
15(3), 36–44. https://doi.org/10.1109/emr.1987.4306297
Kaplan, R. S. (1983). Measuring manufacturing performance: a new challenge for managerial accounting research. The
Accounting Review 58, 4, 686–705.
Kaplan, R. S. (1986). Accounting lag: the obsolescence of cost accounting systems. California Management Review 28, 2, 174–
199.
The International journal of analytical and experimental modal analysis ISSN NO:0886-9367
15
Volume XII, Issue IX, September/2020 Page No: 968
Kendall, G. I. (1998). Securing the future: strategies for exponential growth using the theory of constraints. St. Lucie Press.
Kim, S., Mabin, V. J., & Davies, J. (2008). The theory of constraints thinking processes: Retrospect and prospect. International
Journal of Operations and Production Management, 28(2), 155–184. https://doi.org/10.1108/01443570810846883
Kuo, T.-C., Chang, S.-H., & Huang, S.-N. (2009). Due-date performance improvement using TOC‘s aggregated time buffer
method at a wafer fabrication factory. Expert Systems with Applications, 36(2), 1783–1792.
https://doi.org/10.1016/j.eswa.2007.12.038
Lambrecht, M. R., & Segaert, A. (1990). Buffer stock allocation in serial and assembly type of production lines. International
Journal of Operations and Production Management 10, 2, 47–61.
Leach, L. P. (1999). Critical Chain Project Management Improves Project Performance. Project Management Journal, 30(2), 39–
51. https://doi.org/10.1177/875697289903000207
Lowalekar, H., & Basu, S. (2019). Theory of constraints based mafia offer for supply chains of deteriorating products.
International Journal of Production Research, 1–29. https://doi.org/10.1080/00207543.2019.1654629
Luiz, O. R., Souza, F. B. de, Luiz, J. V. R., & Jugend, D. (2019). Linking the critical chain project management literature.
International Journal of Managing Projects in Business, 12(2), 423–443. https://doi.org/10.1108/IJMPB-03-2018-0061
Mishra, S., & Palo, S. (2014). Applying theory of constraints to the indian administrative services. Management and Labour
Studies, 39(2), 187–207. https://doi.org/10.1177/0258042X14558186
Motwani, J., Klein, D., & Harowitz, R. (1996). The theory of constraints in services: part 2 ‐ examples from health care.
Managing Service Quality: An International Journal, 6(2), 30–34. https://doi.org/10.1108/09604529610109738
Raban, S., & Nagel, R. N. (1991). Constraint-based control of flexible flow lines. International Journal of Production Research
29 (10), 1941, 1951.
Rahman, S. (2002). The theory of constraints’ thinking process approach to developing strategies in supply chains.
Rahman, Shams ur. (1998). Theory of constraints: A review of the philosophy and its applications. In International Journal of
Operations and Production Management (Vol. 18, Issue 4, pp. 336–355). https://doi.org/10.1108/01443579810199720
Rand, G. K. (2000). Critical chain: the theory of constraints applied to project management. International Journal of Project
Management, 18(3), 173–177. https://doi.org/10.1016/s0263-7863(99)00019-8
Raz, T., Barnes, R., & Dvir, D. (2003). A critical look at critical chain project management. Project Management Journal 34, 4,
24–32.
Robinson, H., & Richards, R. (2010). Critical Chain Project Management: Motivation & overview. In 2010 IEEE Aerospace
Conference. IEEE. https://doi.org/10.1109/aero.2010.5446879
Rogalska, M., & Hejducki, Z. (2007). TIME BUFFERS IN CONSTRUCTION PROCESS SCHEDULING. JOURNAL OF
CIVIL ENGINEERING AND MANAGEMENT, 13(2), 143–148. https://doi.org/10.3846/13923730.2007.9636430
Roghanian, E., Alipour, M., & Rezaei, M. (2017). An improved fuzzy critical chain approach in order to face uncertainty in
project scheduling. International Journal of Construction Management, 18(1), 1–13.
https://doi.org/10.1080/15623599.2016.1225327
Simatupang, T. M., Wright, A. C., & Sridharan, R. (2004). Applying the theory of constraints to supply chain collaboration.
Şimşit, Z. T., Günay, N. S., & Vayvay, Ö. (2014). Theory of constraints: a literature review. Procedia - Social and Behavioral
Sciences, 150, 930–936. https://doi.org/10.1016/j.sbspro.2014.09.104
Steyn, H. (2001). An investigation into the fundamentals of critical chain project scheduling. International Journal of Project
Management, 19(6), 363.
Theory of Constraints Consulting | Goldratt India. (n.d.-a). Retrieved March 9, 2020, from
https://www.goldrattindia.com/about.html
Theory of Constraints Consulting | Goldratt India. (n.d.-b). Retrieved March 9, 2020, from
The International journal of analytical and experimental modal analysis ISSN NO:0886-9367
16
Volume XII, Issue IX, September/2020 Page No: 969
https://www.goldrattindia.com/testimonial.html
TOC Applications - Theory of Constraints Institute. (n.d.). Retrieved March 12, 2020, from https://www.tocinstitute.org/toc-
applications.html
Wang, W., Wang, X., Ge, X., & Deng, L. (2014). Multi-objective optimization model for multi-project scheduling on critical
chain. Advances in Engineering Software, 68, 33–39. https://doi.org/10.1016/j.advengsoft.2013.11.004
Watson, K. J., Blackstone, J. H., & Gardiner, S. C. (2007). The evolution of a management philosophy: The theory of constraints.
Journal of Operations Management, 25(2), 387–402. https://doi.org/10.1016/j.jom.2006.04.004
Xu, J., & Xu, X. (2010). Notice of retraction: theory of constraints: a review of its applications in supply chain management.
2010 International Conference on E-Business and E-Government (ICEE 2010), 4977–4980.
https://doi.org/10.1109/ICEE.2010.1250
Yang, S., & Fu, L. (2014). Critical chain and evidence reasoning applied to multi-project resource schedule in automobile R&D
process. International Journal of Project Management, 32(1), 166–177. https://doi.org/10.1016/j.ijproman.2013.01.010
Zhang, J., Jia, S., & Diaz, E. (2014). A new buffer sizing approach based on the uncertainty of project activities. Concurrent
Engineering, 23(1), 3–12. https://doi.org/10.1177/1063293x14561871