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Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting.

ABSTRACT: The purpose of multi-level contribution margin accounting in cost accounting is to analyze the profitability of products and organizational entities with appropriate allocation of fixed costs and to provide relevant information for short-term, medium- and longer-term decisions. However, the conventional framework of multi-level contribution margin accounting does not usually incorporate a mathematical optimization method that simultaneously integrates variable and fixed costs to determine the best possible product mix within hierarchically structured organizations. This may be surprising in that operations research provides an optimization model in the form of the fixed-charge problem (FCP) that takes into account not only variable costs but also fixed costs of the activities to be planned. This paper links the two approaches by expanding the FCP to a multi-level fixed-charge problem (MLFCP), which maps the hierarchical decomposition of fixed costs in accordance with multi-level contribution margin accounting. In this way, previously hidden optimization potentials can be made visible within the framework of multi-level contribution margin accounting. Applying the linkage to a case study illustrates that the original assessment of profitability gained on the sole basis of a multi-level contribution margin calculation might turn out to be inappropriate or even inverted as soon as mathematical optimization is utilized: products, divisions, and other reference objects for fixed cost allocation, which at first glance seem to be profitable (or unprofitable) might be revealed as actually unprofitable (or profitable), when the multi-level contribution margin calculation is linked to the MLFCP. Furthermore, the proposed concept facilitates assessment of the costs of an increasing variant diversity, which also demonstrates that common rules on how to interpret a multi-level contribution margin calculation may have to be revised in some cases from the viewpoint of optimization. Finally, the impact of changes in the fixed cost structure and other parameters is tested via sensitivity analyses and stochastic optimization.

SUBMITTER: Gutierrez M

PROVIDER: S-EPMC7905367 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:This article describes the data, data flows, and spreadsheet implementations for linking multi-level contribution margin accounting as a subsystem in cost accounting with several versions of a multi-level fixed-charge problem (MLFCP), the latter based on the optimization approach in operations research. This linkage can reveal previously hidden optimization potentials within the framework of multi-level contribution margin accounting, thus providing better information for decision making in companies and other organizations. For the data, plausible fictitious values have been assumed taking into consideration the calculation principles in cost accounting where applicable. They include resource-related data, market-related data, and data from cost accounting needed to analyze the profitability of a company´s products and organizational entities in the presence of hierarchically structured fixed costs. The data are processed and analyzed by means of mathematical optimization techniques and sensitivity analysis. The linkage between multi-level contribution margin accounting and MLFCP is implemented in three spreadsheet files, including versions for deterministic optimization, stochastic optimization, and robust optimization. This paper provides specifications for compatible solver add-ins and for executing sensitivity analysis. The data and spreadsheet implementations described in this article were used in a research article entitled "Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting" [1]. The data sets and the spreadsheet implementations may be reused a) by researchers in management and cost accounting as well as in operations research and quantitative methods for verification and for further development of the linkage concept and of the underlying optimization models; b) by practitioners for gaining insight into the data requirements, methods, and benefits of the proposed linkage, thus supporting continuing education; and c) by instructors in academia who may find the data and spreadsheets valuable for classroom use in advanced courses. The complete spreadsheet implementations in the form of three ready-to-use Excel files (deterministic, stochastic, and robust version) are available for download at Mendeley Data. They may serve as customizable templates for various use cases in research, practice, and education.

Project description:IntroductionComparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses-where outcomes are considered separately, with their joint relationship under uncertainty ignored-lead to incorrect inference regarding preferred strategies.ObjectiveThe objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison.MethodsMultiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL.ResultsConventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home (?1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when ?1=$2,000 and ?2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective.ConclusionComparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions.

Project description:INTRODUCTION:Shared decision making is an interpersonal process whereby healthcare providers collaborate with and support patients in decision-making. Older adults receiving home care need support with decision-making. We will explore what older adults receiving home care and their caregivers need for making better health-related decisions. METHODS AND ANALYSIS:This two-phase sequential exploratory mixed methods study will be conducted in a pan-Canadian healthcare organisation, SE Health. First, we will create a participant advisory group to advise us throughout the research process. In phase 1 (qualitative), we will recruit a convenience sample of 15-30 older adults and caregivers receiving home care to participate in open-ended semi-structured interviews. Phase 1 participants will be invited to share what health-related decisions they face at home and what they need for making better decisions. In phase 2 (quantitative), interdisciplinary health and social care providers will be invited to answer a web-based survey to share their views on the decisional needs of older adults and their caregivers. The survey will include questions informed by findings from qualitative interviews in phase 1, and a workbook for assessing decisional needs based on the Ottawa Decision Support Framework. Finally, qualitative and quantitative results will be triangulated (by methods, investigator, theory and source) to develop a comprehensive understanding of decision-making needs from the perspective of older adults, caregivers and health and social care providers. We will use the quality of mixed methods studies in health services research guidelines and the Checklist for Reporting the Results of Internet E-Surveys checklist. ETHICS AND DISSEMINATION:Ethics approval was obtained from the research ethics boards at Southlake Regional Health Centre and Université Laval. This study will inform the design of decision support interventions. Further dissemination plans include summary briefs for study participants, tailored reports for home care decision makers and policy makers, and peer-reviewed publications. TRIAL REGISTRATION NUMBER:NCT04327830.

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Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting.

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