Sensitivity analysis within a chosen manufacturing company

Authors

  • Marek Vochozka Institute of Technology and Business in Ceske Budejovice

Keywords:

sensitivity analysis, risk, small and medium enterprises, financial management, enterprises development

Abstract

Purpose of the article The aim of sensitivity analysis is to determine the effect of the selected financial criteria for firms to possible changes in the values of risk factors that influence the criterion in the selected company. Therefore, it represents an important tool for risk assessment and a decision-making aid for financial management.

Methodology/methods The methods used in this case study are the economic analysis, econometric, statistical and mathematical methods (single-factor analysis, multi-factor analysis, uncertainty index, sensitivity coefficient). Contribution of the paper is essentially a practical demonstration of the real data (from the company, which operates as a subcontractor of components for the automotive industry), their interpretation and subsequent discussion.

Scientific aim The aim of this contribution is to judge the sensitivity, rate of uncertainty, and to evaluate the expected development of chosen risky factors which influence reaching the planned economic result (before taxation) in a chosen manufacturing enterprise in 2017.

Findings Our sensitivity analysis has proven that key risk factors of fulfilling the target economic result in a chosen manufacturing enterprise include reaching at least the planned sales volume for 2017, growth of sale price at least in 2.955% as compared to 2016 and purchase material price which should decrease in 3% as compared to 2016.

Conclusions The contribution assessed the sensitivity, the degree of uncertainty and assessed also the expected of selected risk factors influencing the achievement of the planned profit.

References

Brealey, R. A., Myers, S. C., Allen F. (2014). Teorie a praxe firemních financí. 2nd ed. Brno: Bizbooks.

Derun, I. (2016). Risk identification in the company’s accounting system. Economic Annals-ХХI, 159(5-6), 97-100. Doi: 10.21003/ea.V159-21

Dorcak, P., Markovic, P., Pollak, F. (2017). Multifactor analysis of online reputation as a tool for enhancing competitiveness of subjects from automotive industry. Ekonomický časopis, 65(2), 173-186. ISSN 0013-3035.

Fotr, J., Hnilica, J. (2014). Aplikovaná analýza rizika ve finančním managementu a investičním rozhodování. 2nd updated and expanded ed. Praha: Grada.

Kleijnen, J. P.C. (2005). An overview of the design and analysis of simulation experiments for sensitivity analysis. European Journal of Operational Research, 164(2), 287-300. ISSN 0377-2217. Doi: 10.1016/j.ejor.2004.02.005

Micu, A, Micu, A. E., Cristane, N., Lukacs, E. (2014). The influence of marketing intelligence on performances of Romanian retailers. In Proceedings of the 8th international management conference: management challenges for sustainable development. Bucharest, Romania, 337-349. ISSN 2286-1440.

Pang, S. Y. (2009). Hong Kong property market analysis. In Proceedings of 2009 international conference on construction & real estate management, vols. 1 and 2, Beijing, China, 1026-1031. ISBN 978-7-112-11454-2.

Ptáčková, B. (2014). Sensitivity analysis of a company evaluated by economic value added. In Řízení a modelování finančních rizik, Ostrava, 663-668. ISBN 978-80-248-3631-7.

Rabta, B. (2017). Sensitivity analysis in inventory models by means of ergodicity coefficients. International Journal of Production Economics, 188, 63-71. ISSN 0925-5273. Doi: 10.1016/j.ijpe.2017.03.014

Reilly, T. (2000). Sensitivity analysis for dependent variables. Decision Sciences, 31(3), 551-572. ISSN 0011-7315. Doi: 10.1111/j.1540-5915.2000.tb00934.x

Šimák, L. et al. (2005). Krízové plánovanie. Žilina: University of Žilina. ISBN 80-8070-391-4.

Steinöcker, R (1998). Strategický controlling. Prague: BABTEXT. ISBN 80-900-1782-5.

Tian, Z., Kouvelis, P., Munson, Ch. L. (2014). Understanding and managing product line complexity: Applying sensitivity analysis to a large-scale MILP model to price and schedule new customer orders. IIE Transactions. 47(4), 307-328. Doi: 10.1080/0740817X.2014.916461

Triantaphyllou, E., Sánchez, A. (1997). Sensitivity analysis approach for some deterministic multi-criteria decision-making methods. Decision Sciences, 28(1), 151-194. ISSN 0011-7315. Doi: 10.1111/j.1540-5915.1997.tb01306.x

Webster, C. (1995). Marketing culture and marketing effectiveness in service firms. The Journal of Service Marketing, 9(2), 6-21. ISSN 0887-6045.

Yamwong, W., Kaotien, J., Achalakul, T. (2009). The sampling-based sensitivity analysis model for yield improvement in HDD manufacturing. In 2009 International Conference on Complex, Intelligent and Software In-tensive Systems. Fukuoka, Japan, 1211-1216. ISBN 978-1-4244-3569-2.

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Published

2017-09-21

Issue

Section

Finance in Digital Transformation