Evaluate the Process

Description of the Problem Statement In this assignment, the organizational problem that will be addressed is the operational

inefficiency in businesses. Business operations are the activities that keep on running in a

business. Thus, operations entail the work of managing the inner workings of a business to

ensure that it runs as efficiently as possible. Some of the processes that are involved in business

operations include production of the products, inventory management, selling of the final

products, and all the other necessary operations to make the production of goods a success.

Operational efficiency is a measure that is used to measure the relationship between the output

that is produced in a business and the input that is used to run the business (Saranga & Nagpal,

2016). When a business has operational efficiency, it has a high output to input ratio. On the

other hand, when a business had a low output to input ratio, it is termed as having a low

operational efficiency, or in short, operational inefficiency. Operational inefficiency affects

inventory management, the process and quality of the products produced by a company, and the

controlling and improvement of the production process.

Operational inefficiency is not desirable for a business. It leads to decreased profits,

decreased productivity, and at times low-quality products. That may lead to a business losing its

loyal customers, which would have a more adverse effect on the business (Invernizziet al., 2018).

Some of the common causes of operational inefficiency include improper planning, poor

scheduling, poor team quality control and supervision, and poor data management systems.

Operational inefficiency mostly begins during the planning stage of a project or when

setting the goals and objectives of an organization. Some activities such as the neglect of the

resource deficiencies or redundancies in a business’s operations may lead to operational

inefficiency in a business. Failure to develop operational contingencies may also lead to

operational inefficiencies in a business.

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Operational inefficiency in a business may also be caused by poor scheduling. Without

proper scheduling, activities are not done as they should be done thus decreasing a business’s

efficiency. The activities and processes that are carried out in a business should be clear.

Moreover, the responsibilities of the employees should also be clear to ensure that all the

activities are carried out as it is required. That promotes business efficiency. Poor team quality

control and supervision also promote operational inefficiency. That occurs when the teams in an

organization are not effective. They may be taking too long to complete tasks due to lack of

coordination or other issues, missing the set deadlines, or providing poor quality work. That

affects the operational efficiency of an organization.

Poor data management systems may also result in operational inefficiencies. Today, most

businesses harness big data to identify the trends and insights in a business to improve its

operations. However, if the data management systems that are implemented by a company are

ineffective, it may lead to reduced operational efficiency in an organization.

Justification for Solving the Problem

Operational inefficiency has adverse effects on an organization. It may lead to loss of

customers, poor quality products, increased production costs, reduced employee satisfaction,

reduced revenues, and reduced profitability. That indicates the significance of solving the

problem of operational inefficiency in an organization. Through solving the operational

inefficiency, a business will have improved outcomes such as high-quality products, reduced

production costs, higher customer acquisition and retention, increased revenues, and increased

profitability. Since such positive aspects are desirable, it is essential to solving the issue of

operational inefficiency.

An organization's strategic initiative is a means through which an organization translates its

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goals and visions into practice. That indicates that organizations need to formulate strategic

organizational initiatives to ensure that they are competitive in the market. The organizational

strategic initiative in this case is to improve the operational efficiency of the organization by

harnessing the insights provided from big data analytics. That will enable the organization to

provide high-quality products to its customers thus increasing customer acquisition and retention.

Increased operational efficiency will also streamline the processes in the organization thus

reducing the operational costs. That will affect the profitability of the organization positively.

Use of Statistical Applications to Solve the Problem

Various statistical applications may be used to solve the issue of operational inefficiency in

a business. With the advancement in technology, a lot of organizations have adopted the use of

big data analytics to identify the organization’s trends and essential insights that may be used to

come up with strategic decisions that may improve not only the operational efficiency of a

business but also other aspects such as effective marketing, and promotion of customer

satisfaction. Big data should be analyzed descriptively to ensure that optimal insights are derived

to ensure that an organization achieves operational efficiency. Some of the activities that are

improved through statistical applications in an organization to improve operational efficiency

include improving the processes’ effectiveness and quality of the products produced, improving

inventory management in an organization, and promoting effective controls that improve the

production processes. Examples of statistical techniques that may be used in the analysis of an

organization’s data to promote operational effectiveness include statistical quality control,

sampling inspection, six sigma analysis, and ABC analysis.

Statistical quality control is us of statistical methods in monitoring and maintaining the

quality of the products and services of an organization. It is also used to measure the variation in

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the processes of an organization. The statistical technique uses the data that is collected by an

organization to determine whether the processes and the products and services that are produced

by the organization are of the desired quality. It s also used to monitor the process outputs, which

are the dependent variables in this case (Montgomery, 2020). Statistical quality control has seven

quality control measures and seven supplemental tools. The seven quality tools that are used

include stratification, cause, and effect diagram, scatter diagram, check sheet, Pareto chart,

control chart, and histogram. The seven supplemental tools include data stratification, sample

size determination, defect maps, process, flowcharts, randomization, event logs, and progress

centers.

Six Sigma is a quality management statistical measurement method that is used by

organizations to improve their current processes, products and services, and eliminating the

defects in their processes. The main objective of the six sigma s to streamline quality control in

the business processes to ensure that there is little to no variance throughout the production

process. The six sigma process is expected to be error-free 99.99966% of the time (Chuganiet al.,

2017). That indicates that only 3.4 defective features may be identified in every one million

opportunities. That indicates that it is a very effective statistical technique that may be used by

businesses. Six sigma uses three principles to reduce and eliminate the number of defects

namely; smaller is better, larger is better, and nominal is best. The smaller is better represents the

upper specification limit that targets having zero defects. The larger is better represents the lower

specification limit such as the target being 100%. The nominal is best targets the middle ground

by stressing that the organization should put enough effort into an activity but not too much that

leads to wastage of resources. Six sigma has two methodologies namely the DMAIC and

DMADV. The DMAIC methodology has five stages namely; define, measure, analyze, improve,

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and control. The DMADV also has five stages namely; define, measure, analyze, design, and

verify.

ABC analysis is a measurement method in inventory management. It is used to categorize

techniques. He technique categorizes the inventory into three categories namely; the A items, the

B items, and the C items. They are categorized based on the value that they bring to the business.

Categorizing the inventory in this manner promotes effective inventory management thus

increasing the operational efficiency of the organization (Khan et al., 2017). The A category of

the goods are essential to the business and they may be business-critical. They have high value

and they are mostly sold in large volumes. The B category of inventory is significant but less

significant than the A goods and more significant than the C goods. They are mid-range in their

value and demand. The C goods are marginally essential and they have a low inventory value.

Before using this technique in the categorization of the goods, the big data in a company is

analyzed to identify the goods that have the highest value in a business.

Sampling inspection is an inspection method that is used to determine whether the products

that are being produced and the processes are of high quality. It is a statistical method that is

used to identify the operational efficiency of an organization (Rezaei, 2016). The statistical

technique evaluates a sample of the products that have been produced and the processes to

determine whether the organization has the required operational efficiency. The use of big data

analytics is also harnessed in sampling inspection to identify the effectiveness of an

organization’s products and operations.

In a nutshell, quality control is very significant in an organization. Operational inefficiency

has adverse effects on an organization such as decreased profits, decreased productivity, and at

times low-quality products. With the advancement in technology, organizations are adopting the

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use of big data analytics. With the big data that is collected by organizations, they should

promote the use of statistical applications. Some of the statistical applications that may be used

to improve operational efficiency are statistical quality control, sampling inspection, six sigma

analysis, and ABC analysis. They are harnessed to improve operational efficiency include

improving the processes’ effectiveness and quality of the products produced, improving

inventory management in an organization, and promoting effective controls that improve the

production processes.

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References

Chugani, N., Kumar, V., Garza-Reyes, J. A., Rocha-Lona, L., & Upadhyay, A. (2017).

Investigating the green impact of Lean, Six Sigma and Lean Six Sigma: A systematic

literature review. International Journal of Lean Six Sigma.

Invernizzi, D. C., Locatelli, G., & Brookes, N. J. (2018). The need to improve communication

about scope changes: frustration as an indicator of operational inefficiencies. Production

Planning & Control, 29(9), 729-742.

Khan, S. A. R., Dong, Q. L., & Yu, Z. (2017). Role of ABC Analysis in the process of efficient

order fulfillment: Case study. In Advanced Engineering Forum (Vol. 23, pp. 114-121).

Trans Tech Publications Ltd.

Montgomery, D. C. (2020). Introduction to statistical quality control. John Wiley & Sons.

Rezaei, J. (2016). Economic order quantity and sampling inspection plans for imperfect

items. Computers & Industrial Engineering, 96, 1-7.

Saranga, H., & Nagpal, R. (2016). Drivers of operational efficiency and its impact on market

performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165-

176.