Statistical Methods: Enhancing Unilever's Business Operations

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APPLICATION OF BUSINESS STATISTICAL METHODS
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Unilever is a British company engaged in the production and selling of consumer goods.
Statistical methods refer to the mathematical models, techniques, formulas, and tools adopted for
the purpose of conducting statistical analysis of research data. Statistical methods are applied in
organizations for different purposes such as quality control, evaluation of training, management
decision-making, and market research and so on. However, the organizations use these methods
mainly for depicting the significant and relevant information from the pool of research data along
with the analysis of the relevancy and accuracy of the data.
Quality control: Unilever may get benefits from statistical methods and tools in the enhancement
and controlling the quality. Mainly, the statistical quality control tools comprise of acceptance
sampling, descriptive statistics, and statistical process control. Acceptance sampling is applied
with an aim of assessing the acceptance or rejection of the whole batch of goods on the basis of
random inspection of goods (Hussin, and Saidin, 2014). Descriptive statistics involves the
determination of the quality characteristics and their inter-relationships. Statistical process
control refers to the process of inspecting the robustness of the process whether it is functioning
and operating in proper manner.
Market Research: The application of statistical methods in market research can be beneficial for
Unilever. There are certain methods of statistics that are used for market research are comprised
of factor analysis, multiple regressions, and cluster analysis and so on. Factor Analysis involves
the development of the most robust dimensions from the pool of inter-correlated variables.
Multiple regressions are utilized with an aim of predicting the variable value on the basis of
changes take place to different variables (Sarstedt, et. al., 2017). Cluster Analysis is applied
when the purpose is to categorize the data objects into the homogenous groups. The other
significant statistical methods can be defined as conjoint analysis and discriminant analysis.
Unilever may be enabled to conduct effective market research in relation to market or finance or
any other purpose.
Decision-Making: Statistical methods may also useful for Unilever in the field of business
decision-making. The statistical methods are used for the purpose of collecting data and making
predictions for the future from the pool of data. For Unilever, the statistical methods are the
foundation of the decision-making as this process cannot be initiated without the availability of
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relevant and adequate data (Onukwuli, et. al., 2014). With the help of these methods, the
variables can be inter-related and Unilever may ensure the improved quality of products and
services as well as the employees.
Employee Training and Retention: Use of statistical methods in the employee training,
engagement, and retention cannot be ignored by Unilever. Mainly the descriptive statistics,
statistical modeling, and inferential statistics can be used by Unilever for providing solutions to
the HR challenges. Descriptive statistics such as ratios, mean, median and mode provide
assistance to monitor the performance of the employees. The statistical modeling comprises
talent analytics, workload analytics, and people analytics. Workload Analytics are used for
assessing the shape and size of the workforce available in the company (Bhattacharyya, 2018).
People analytics involve the analysis of how the workforce influences the business. Talent
analytics refers to the identification and development of talented people for maintaining the
talent in the organization.
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References
 Bhattacharyya, D. K., 2018. Statistical Tools and Analysis in Human Resources
Management. Advances in Human Resources Management and Organizational
Development (AHRMOD).
 Hussin, M. H. N., and Saidin, W. A. N. W., 2014. An Application of Statistical Quality
Control On Process Improvement: Case Study. Australian Journal of Basic and Applied
Sciences. 8(22).
 Onukwuli, A., Onwuka, E. M., and Nwagbala, C., 2014. Application of quantitative
techniques in small business management in sub-saharan African state. Journal of
international academic research for multidisciplinary. 2(5).
 Sarstedt, M., Bengart, P., Shaltoni, A. M., and Lehmann, S., 2017. The use of sampling
methods in advertising research: a gap between theory and practice. INTERNATIONAL
JOURNAL OF ADVERTISING.
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