|Ekaterina Burova||Peter the Great St. Petersburg Polytechnic University, 29 Politechnicheskaya Ulitsa, St. Petersburg, 195251, Russia|
|Sergei Grishunin||National Research University, Higher School of Economics, 20 Myasnitskaya Ulitsa, Moscow, 101000, Russia|
|Svetlana Suloeva||Peter the Great St. Petersburg Polytechnic University, 29 Politechnicheskaya Ulitsa, St. Petersburg, 195251, Russia|
|Andrei Stepanchuk||Peter the Great St. Petersburg Polytechnic University, 29 Politechnicheskaya Ulitsa, St. Petersburg, 195251, Russia|
This study aims to develop a mechanism for the cost management of innovative products in an industrial enterprise given the inherent risks. Under the conditions of the high volatility of the digital economy, risk assessment in cost management, as well as the development of some mechanisms for staying flexible and adaptable with regard to continual changes, is a priority for the further development of cost management systems for an industrial enterprise. The research results include: (1) a mechanism for assessing and considering the changes in the key cost drivers, which continuously controls the target cost level that has been achieved and can be used for taking into account the risk factors in cost management and for increasing the effectiveness of the business processes of industrial enterprises operating in the digital economy; and (2) a description of the methods recommended for implementing each stage of the mechanism suggested. The mechanism is based on the synthesis of the cost driver concept and the risk-controlling concept. The following tools were used to develop the mechanism: target-costing, kaizen-costing, variance analysis for cost planning, accounting and analysis, an Ishikawa diagram, a fault tree for identifying risk factors for key cost drivers, and simulation modeling using the Monte Carlo method. The mechanism: (1) makes it possible to consider the high uncertainty level of the external environment and the effect of risks in the cost management system; (2) can be used to control the level of target costs reached in real time and introduce prompt corrections regarding the planned costs according to external and internal changes; and (3) is based on using modern, high-precision tools for assessing risks and the effect they produce on the costs and profitability of an industrial enterprise. The advantages above help to increase the dynamics and flexibility of the process of the cost management of innovative products and to maintain such products’ competitiveness.
Cost management; Digital economy; Innovative products; Key cost drivers; Key risk factors
Studies conducted by specialists in national industrial enterprises reveal that its cost management system is one of the top priorities for the digital development of an enterprise (Su and Wu, 2019; Mizikovskii, 2020). Being a subsystem of corporate management, cost management is considered “in the information-tool environment of enterprise management as a powerful driver of transformation processes, which ensures that digital systems and technologies are introduced” (Mizikovskii, 2020).
The digital economy provides vast opportunities for the continuous improvement of the processes, technologies, and competences of management accounting, which helps to considerably increase the efficiency of cost management in an industrial enterprise (Bencsik, 2020; Bhimani, 2020). The tools of the digital economy, such as big data, machine learning, blockchain, and cloud computing, can be used in a cost management system to improve the accuracy of information and decision-making and to respond effectively to changes in the external and internal environment of an enterprise, thus making business processes more efficient (Berawi, 2020). According to the results of the global research study in the field of cost management conducted by Deloitte every other year, in 2019, the top priorities in terms of the strategic goals of industrial enterprises were sales growth, technology implementation, product profitability, digital enablement, and cost reduction1. According to the study, 78% of the respondent industrial companies failed to achieve the cost-cutting values they had planned, 15% reached their target values, and just 7% exceeded them. Cost-cutting value targets are mostly not achieved due to the occurrence of numerous risks in the turbulent surroundings of an industrial enterprise, which prevent such a company from reaching its objectives. Considering risks within cost management systems and developing mechanisms for flexible adaptation to ongoing changes are vital to the further improvement of cost management systems. Today digital transformation is especially important in managing the costs of innovative products (IP) (Mizikovskii, 2020). In order to manufacture competitive products and to guarantee that the value of an industrial enterprise will grow, it is not enough to just determine the “target” costs of IP. There is the need for a mechanism that can be used to achieve the target values of costs given the continuous effects of externalities and internalities on the activities of an enterprise. This study aims to develop a mechanism for managing the costs of IP faced by an industrial enterprise given the risks. In order to reach this goal, the following objectives have to be attained: (1) study the modern concepts that are used to manage the costs of IP and analyze the existing risk management concepts; (2) suggest a stage-by-stage mechanism for accounting for risks in the cost management of IP; and (3) choose and substantiate the methods and tools necessary for the implementation of each stage of the mechanism. The mechanism relies on the interaction between a cost management system and a risk management system and implies using the main principles of cost drivers, risk controlling, variance analysis, target-costing, and kaizen-costing. This mechanism can be used to control the target cost values reached in real time and to take corrective actions in the case of any deviation.
The review of the literature dedicated to managing the costs of IP shows that a large variety of methods are suggested (Wang et al., 2020). Today, methods such as target-costing and kaizen-costing are recommended (Olszewska, 2019) because they embrace the client focus and customization of an enterprise (Daneci-Patrau and Coca, 2017), and at the same time, they make the company strive for a cost level lower than that of its competitors. If target-costing and kaizen-costing methods are used, an enterprise can set correct objectives in terms of cost assessment and find ways to achieve them. However, the above methods are not used to consider the risks that may arise due to the continuous interaction of an enterprise with the external environment, which makes them less efficient. The concept of cost drivers was designed for the profound analysis of costs and the factors that generate them in order to increase the quality and efficiency of cost management. Yet, such analysis does not make it possible to monitor the changing cost drivers that arise from the transformation of the enterprise’s external environment, which makes the concept static. Variance analysis, based on its classical interpretation, is a method of retrospective analysis, which is used by industrial enterprises for evaluating and analyzing the actual deviations in different cost drivers. This work suggests using the main principles of variance analysis to protect an enterprise from and account for the deviations in key cost drivers from the target cost values, related to possible risk occurrence. The academic literature review (Samimi, 2020; Grishunin et al., 2020) illustrates that the modern tools of risk management described above consider the specifics regarding the operation of industrial enterprises in the digital economy, but that there are not enough research studies in the field of risk management and cost management integration.
This paper suggests a mechanism for managing the costs of IP of an industrial enterprise, which: (1) considers the high level of volatility of the external environment common to the digital economy and the effects exerted by risks on cost management; (2) can be used for controlling the level of target costs and introducing corrections made to the costs in due time according to the changing external and internal conditions so that the target profitability can be ensured; and (3) is based on using up-to-date and high-precision tools and methods for assessing risks and their effects on the costs and profitability of the IP. The above advantages aim to increase the responsiveness and flexibility of the entire process of the cost management of IP, which ensures the competitiveness of such products.
Further research should first be about developing
tools for introducing this mechanism into the corporate system of enterprise
management. Second, it should be about creating tools and methods to be used
with the mechanism that target a subsequent increase in the efficiency of the
cost management system and, in particular: (1) the selection of the KCD of IP;
and (2) the improvement of tools for analyzing risk factors related to KCD.
The research is partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership ‘Priority 2030’ program (Agreement 075-15-2021-1333 dated 30.09.2021).
Banker, R.D., Byzalov, D., Fang, S., Liang, Y., 2018. Cost Management Research. Journal of Management Accounting Research, Volume 30(3), pp. 187–209
Bencsik, A., 2020. Challenges of Management in the Digital Economy. International Journal of Technology, Volume 11(6), pp. 1275–1285
Berawi, M.A., 2020. Managing Nature 5.0: The Role of Digital Technologies in the Circular Economy. International Journal of Technology, Volume 11(4), pp. 652–655
Bhimani, A., 2020. Digital Data and Management Accounting: Why We Need to Rethink Research Methods. Journal of Management Control, Volume 31(1–2), pp. 9–23
Cook, M., Mo, J., 2018. Investigating into the Risks of Forming Alliance. In: Transdisciplinary Engineering Methods for Social Innovation of Industry 4.0, pp. 1135–1144
Daneci-Patrau, D., Coca, C.E., 2017. Methodological Considerations on the Process of Determining the Target Cost. Economics, Management & Financial Markets, Volume 12(2), pp. 122–130
Donelan, J.G., Kaplan, E.A., 1998. Value Chain Analysis: A Strategic Approach to Cost Management. Journal of Cost Management, Volume 12(2), pp. 7–15
Grishunin, S., Suloeva, S., Nekrasova, T., Burova, E., 2020. Development of Risk Controlling Mechanism and Tools for Agile Projects in Telecommunications. In: Internet of Things, Smart Spaces, and Next Generation Networks and Systems: NEW2AN 2020, ruSMART 2020. Lecture Notes in Computer Science, Volume 12526.2020. Springer, Cham
Lionel, B.C., Khaled, El Emam, Bomarius, F., 1998. COBRA: A Hybrid Method for Software Cost Estimation, Benchmarking, and Risk Assessment. In: Proceedings of the 20th International Conference on Software Engineering
Matsuoka, K., 2018. Variance Analysis in Fixed Revenue Accounting. Fixed Revenue Accounting: A New Management Accounting Framework, Volume 15, pp. 69–84
Minakov, V.F., Lobanov, O.S., Dyatlov, S.A., 2020. Three-Dimensional Trends Superposition in Digital Innovation Life Cycle Model. International Journal of Technology. Volume 11(6), pp. 1201–1121
Mizikovskii, I.E., 2020. Management Accounting of Expenses for Storage of Material Resources in the Conditions of Digital Transformation of the Industrial Enterprise. Accounting. Analysis. Auditing, Volume 7(3), pp. 56–63
Olszewska, K., 2019. Cost Management with Budgeting and Kaizen Costing. World Scientific News, Volume 133, pp. 171–190
Porter, M., 2005. Competitive Advantage: How to Achieve a High Result and Ensure Its Sustainability. Alpina Business Book, p. 246
Samimi, A., 2020. Risk Management in Information Technology. Progress in Chemical and Biochemical Research, pp. 130–134
Shank, J.K., Govindarajan, V., 1993. Strategic Cost Management: The New Tool for Competitive Advantage. Free Press, New York
Su, X., Wu, S., 2019. Innovation of Enterprise Cost Management Under Internet Plus Era. In: 2019 International Conference on Social Science and Education: ICSSAE 2019, pp. 6–11
Wang, C., Wang, F., He, S., 2020. Conceptualization on the Cost Management Model of Enterprise Supply Chain Under the Background of Big Data. In: Proceedings of the 2020 (3rd) International Conference on Computers in Management and Business (ICCMB 2020). Association for Computing Machinery, New York, NY, USA, pp. 19–24
Yin, Y., Lam, J.S.L., Tan, L.H.I., 2013. Integrated Cost and Risk Management Model for Improving Supply Chain Resilience. International Journal of Logistics Management, Volume 14, pp. 114–126