Operation Management Report: PDCA Cycle, Industry 4.0 and Operations

This report delves into the core concepts of operation management, focusing on the application of the PDCA cycle for continuous improvement and the influence of Industry 4.0 on business processes. The first section analyzes a pilot project using the PDCA cycle, detailing the stages of Plan, Do, Check, and Act to optimize supplier relationships and customer satisfaction. The report then explores how Industry 4.0, with its emphasis on the Industrial Internet of Things, big data, and cybersecurity, is reshaping operations management. It examines the automation of data collection and analysis, the use of big data analytics for informed decision-making, and the importance of cybersecurity in protecting intellectual property and maintaining a competitive edge. The analysis highlights how these trends contribute to systematic and gradual improvements in organizational processes, ultimately enhancing efficiency and risk mitigation. The report concludes by emphasizing the importance of quality, innovation, and the strategic application of these methodologies to drive continuous improvement and achieve business prominence in a competitive market.

Running head: OPERATION MANAGEMENT 1
Operation management
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Table of Contents
Introduction.................................................................................................................................................2
Plan..............................................................................................................................................................3
Do................................................................................................................................................................4
Check...........................................................................................................................................................4
Act...............................................................................................................................................................4
Conclusion...................................................................................................................................................5
Question two...............................................................................................................................................5
Discuss how Industry 4.0 affects operations management.........................................................................5
Industrial internet of things.........................................................................................................................6
Conclusion...................................................................................................................................................7
References...................................................................................................................................................8

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Introduction
It is every investor’s wish and expectation to start a business and create a buzz in the
market within the shortest period possible. However, this is not often the case; some businesses
face it rough and unable to compete with other firms in the market for a couple of reasons. The
aim of compiling this document is to detail the critical cyclic circle of continuous improvement
of business operations.
Venturing in a new field is sensitive to the fact one is after generating income from his
hard-earned money but the risks involved in the entire process can shut this vision and mission
(Babbar, Behara, Koufteros, & Huo, 2017). Starting a business requires a detailed understanding
of what you are about to do as an investor, you, therefore, need to understand the entire process
of your business and strategize on possible means of improvement. Before paying attention to
the future of the business it is essential to lay a sound business foundation using the available
information on the investment either in the journals, media scholars and competitors. Where this
information is insufficient, it is recommendable that you set up a pilot program to test the waters
in the market like in the case at hand. Pilot businesses are advantageous since they enable the
investor to learn on the most proficient way to dominate the market as well as choosing most
proficient business partners and suppliers. To achieve the desired future of the business,
continued improvement is critical; this is best explained by the PDCA Cycle. The cycle entails:
Plan
Continuous improvement has much reliance on the strength of the plans developed. The
fact that the improvement process is cyclic, there stands chances for a review of the plans for
further improvement. The plan being the first phase of project improvement entails the

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development of literal plans by the teams involved (Glock, Grosse, Jaber, & Smunt, 2019). For
instance, it is pure planning to opt to set up a pilot small business. Also, the decision to work
with new suppliers is an outcome of pure planning. In this phase, the question, what is the core
problem comes first hence igniting ideas generation on how it can be done. Having known what
needs to be done to solve the current problem and how to solve it, the next question is on the
resources needed and evaluation of what resources are available out of the needed. Finally,
planning entails setting the solution on how to systematically solve the problem at hand as well
as highlighting on outcomes that will guide on the rating of the plan, whether successful or failed
(Babbar, Koufteros, Bendoly, Behara, Metters, & Boyer, 2020). The planning stage is only
complete when an opportunity or a problem has been identified and the hypothesis is developed
with a decision on which to test.
Do
Having developed a plan, the Do-stage follows. Do-stage entails the actual realization of
the plan at hand. After planning on initiating a pilot business and engaging business with new
suppliers, this stage now requires the set-up of the business and hiring of the suppliers. All this
methodology is applied to a pilot or sample to evaluate the practical shape of implementing the
set strategy (Fisher, Olivares, & Staats, 2020). It is important to note that other problems may
occur in this phase other than those noted in the planning phase and their solution is ready.
Occurrence or lack of these new problems is the decision-making point on whether the cycle
should proceed to the next level or something need to be altered for further improvement.
Basically, the stage is more of testing the viability of the plan generated on a small scale.

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Check
The check phase is argued by the experts to be the most critical phase of the cycle. A lot
of attention, therefore, must be paid as one evaluate the average performance of the plan. The
observation on performance in this particular case reveals that the plan to use the pilot business
and the new supplier is positive (Gibson, & Parkman, 2018). For clarity of the plan, recurring
problems are identified and eliminated while attention is paid on improving the plans’ strength
concurrently. The measurements collected in the do phase are used to either support or reject the
hypothesis generated at the planning phase.
Act
Having checked through the acting comes in as the last phase of the cycle. It is worth
noting that the application of the plan is based on the outcome projected on the check phase. It is
advisable to put a plan to work if only it projects a positive outcome. Otherwise, more time will
have to spend on the drawing board. The selected plan henceforth assumes to be the new
standard baseline. It is important to acknowledge that whenever a standardized plan is repeated,
all steps must be followed. The PDCA is a less complicated process but this attribute does not
refrain it from being a powerful tool for continuous improvement (Heizer, 2016). The tool plays
an important role in improvement, especially through reduced wastage. PDCA calls for a
commitment to the mandatory included repetitive process. The Cycle is also a subject to take
time hence patience is important (Matthias, Fouweather, Gregory. & Vernon, 2017). In the end,
with the application of the model, positive changes in efficiency are very likely. It is more of
implementing a successful solution.

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Conclusion
To sum up, it is essential to highlight that the quality of goods is a strong tool in
competition hence a potential route to prominence, all this is attributed to the soundness and
creativity of the team deployed. The cycle is oriented to help in the execution of the strategy,
therefore, the strategy must be available from the word go. There is sufficient evidence that the
methodology helps on improvement on the efficiency of the iterative processes thus the quality
of the service provided in the market. The methodology also helps in risk mitigation by avoiding
risks before they happen or by combating them once they show up.
Question two
Discuss how Industry 4.0 affects operations management
Before jumping on how industry 4.0 affects operations management, it is commendable
to note that; industry 4.0 is different from the fourth industrial revolution, it therefore wrong to
use the two terms interchangeably. Industrial 4.0 refers to the trends in data automation in
collection and analysis such that a computer system can collect and analyze data hence deciding
on a given entire line of production (Reid, & Sanders, 2019). This is realized through the latest
technologies in artificial intelligence, the internet of things, cloud computing and cognitive
computing. To better understand how industry 4.0 affects the operation management of the
organization it is recommendable to consider a trend at a time.
Industrial internet of things
Industrial internet of things refers to the capacity of the organization to distribute
intelligent devices to collect information from places, processes, and equipment that objects that

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cannot speak. The data collected is deeply analyzed hence making decisions based on facts and
figures. Automation of data collection allows the collection of data around the clock without
fatigue hence accuracy and reliability (Slack, 2018). This also ensures the management spots the
downtime in the operation with ease. The trend is automated to the level of collecting, analyzing
and making a decision on data without human hand. This saves human expertise time to focus on
the management of other operations that requires 100% human attention. The systems are
however very expensive and their benefit might not be realized if the organization lacks proper
management of the operations.
Big data and cyber security
Big data is also a major industrial 4.0 trend. This data is collected by machine owing to
the size of the data. Big data analytics is used in the analysis of big data aiming to point out and
aspect of the data that could have lost meaning if lost in the mass data (Spring, Hughes, Mason,
& McCaffrey, 2017). Big data analytics facilitates solid decision making hence efficiency and
thus an improvement in the overall operations.
Industry 4.0 focuses more on information security and protection of intellectual
properties than opposed to the physical properties of broken doors and so on. In fact, it is
claimed that information securities are hard to attack than physical security measures. Secured
organizational data assures easier retrieval and facilitating collection of big data hence
broadening the basis of making inference on a given phenomenon. Cyber-security trends have
also significantly contributed to the installation of measures to secure intellectual property
(Thomé, Scavarda, & Scavarda, 2016). Cyber security has improved privacy on sensitive
information making it hard for access by rivalry competitors hence maintaining the

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differentiating factor hence sound competition. The trends above have evolved over a long
period hence application in operations management has resulted in a systematic and gradual
improvement of processes in the organizations (Tsay, Gray, Noh, & Mahoney, 2018). The
history of big data analytics late back in the 19th century after the first successful digital data
storage in a magnetic tape. Operation management has henceforth experienced the impact of
these trends for a while, although the technologies gained buzz in the application market after the
evolution of the internet.
Conclusion
To wrap up on the effects of industry 4.0, it wise to conclude that it has brought many
benefits in operation management. It has enhanced the establishment of reliable data collection
methods and analysis hence forming a sound ground for decision making. The analysis depicts
small attributes whose impact is important in continuous improvement but could have not been
realized with traditional methods.

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References
Babbar, S., Behara, R. S., Koufteros, X. A., & Huo, B. (2017). Emergence of Asia and
Australasia in operations management research and leadership. International Journal of
Production Economics, 184, 80-94.
Babbar, S., Koufteros, X., Bendoly, E., Behara, R., Metters, R., & Boyer, K. (2020). Looking at
ourselves: Lessons about the operations management field learned from our top
journals. Journal of Operations Management.
Fisher, M., Olivares, M., & Staats, B. R. (2020). Why empirical research is good for operations
management, and what is good empirical operations management?. Manufacturing &
Service Operations Management, 22(1), 170-178.
Gibson, P., & Parkman, R. (2018). Cruise operations management: hospitality perspectives.
Routledge.
Glock, C. H., Grosse, E. H., Jaber, M. Y., & Smunt, T. L. (2019). Applications of learning
curves in production and operations management: A systematic literature
review. Computers & Industrial Engineering, 131, 422-441.
Heizer, J. (2016). Operations management, 11/e. Pearson Education India.
Matthias, O., Fouweather, I., Gregory, I., & Vernon, A. (2017). Making sense of big data–can it
transform operations management?. International Journal of Operations & Production
Management.
Reid, R. D., & Sanders, N. R. (2019). Operations management: an integrated approach. John
Wiley & Sons.

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Slack, N. (2018). Essentials of operations management. Pearson UK.
Spring, M., Hughes, A., Mason, K., & McCaffrey, P. (2017). Creating the competitive edge: A
new relationship between operations management and industrial policy. Journal of
Operations Management, 49, 6-19.
Thomé, A. M. T., Scavarda, L. F., & Scavarda, A. J. (2016). Conducting systematic literature
review in operations management. Production Planning & Control, 27(5), 408-420.
Tsay, A. A., Gray, J. V., Noh, I. J., & Mahoney, J. T. (2018). A review of production and
operations management research on outsourcing in supply chains: Implications for the
theory of the firm. Production and Operations Management, 27(7), 1177-1220.