طراحی سیستم های پشتیبانی تصمیم گیری برای مدیریت مبتنی بر ارزش: بررسی و معماری

Value-based Management (VBM) concepts are prevalent in theory and practice since shareholder value creation is commonly considered the paramount business goal. However, VBM mainly applies data-driven concepts to support decision-making, disregarding model-driven approaches. This paper develops a comprehensive approach to designing model-driven DSS for VBM. First, we derive a conceptual architecture for Integrated Business Planning (IBP) as the foundation for a model-driven approach to VBM. Second, we present a unified modeling approach for value-based performance and risk optimization that implements Value Added (xVA) performance metrics and applies robust optimization methods to mitigate risk impact.

Creating shareholder value is commonly considered the paramount business goal [120], and requires an integrated approach to performance [21] and risk management [98]. Value-based Management (VBM) provides a corresponding framework using value driver trees and risk-adjusted performance metrics as major concepts for performance and risk management [58]. Value driver trees drill down a top-level metric into operational levers for performance management [95] and risk implications are considered via risk-adjusted cost of capital [120]. However, there are two major drawbacks to this common approach from an OR perspective. First, value driver trees are explanatory frameworks and do not provide support on balancing conflicting value drivers. Second, the influence of uncertainty is covered indirectly via risk-adjusted parameters instead of managing risk impact based on scenario information. From a decision support perspective (see [90]), VBM mainly resorts to data-driven concepts, disregarding model-driven approaches. Decision support models for VBM are receiving increasing attention in OR-related publications (e.g., [44], [45], [63] and [92]). These articles implement conceptual approaches [25], [64] and [115] and build upon previous decision support models for integrated supply chain and financial management (e.g., [41], [65], [81] and [109]). They use prevalent value-based performance metrics to do this, such as discounted Free Cash Flow (FCF) and Economic Value Added (EVA), and apply robust optimization methods to deal with risk impact. A few conceptual papers discuss approaches to corporate planning and optimization advocating a comprehensive decision-oriented approach that integrates operations, financial, and risk considerations within the supply chain context [40], [91] and [114]. However, a unified modeling approach for model-driven decision support in VBM has not yet been presented. A comprehensive architecture for Integrated Business Planning (IBP) bridging the gap between Supply Chain Management (SCM) and Financial Management (FM) [103] constitutes the foundation for model-driven decision support in VBM. Conceptual architectures have been developed separately for SCM [34] and FM [4] summarizing a large body of literature on decision-oriented approaches in both domains [73] and [111]. Long-term capital budgeting/structuring and short-term working capital management constitute the two planning levels of FM [4]. SCM distinguishes three planning levels [34]: long-term strategic network planning, mid-term sales and operations planning, and short-term order fulfillment planning. Although modeling frameworks in SCM underline the relevance of financial aspects and risk implications [15] and [75], unified frameworks and approaches to IBP are mainly discussed outside the academic literature [10] and [103]. A diverse body of literature deals with Enterprise Resource Planning (ERP) [77] and [104], including discussions on future trends and research perspectives [55] and [72]. The scope of ERP expands beyond classical data and process integration to provide enhanced modeling and analytical capabilities for complex business problems [76] and [105]. Corresponding DSS for advanced business planning have emerged as stand-alone systems ‘bolt on’ ERP covering different functional aspects and methodological approaches [76] and [97]. Advanced Planning and Scheduling (APS) systems in SCM focus on material flows and pursue a model-driven approach using optimization methods [90] and [111]. In contrast, Business Planning and Simulation (BPS) systems in FM mainly cover financial flows and apply data-driven concepts [32] and [97]. Although the OR discipline could contribute substantially to the conceptual and methodological advancement of ERP [55], a comprehensive conceptual architecture for model-driven IBP has not yet been developed. In summary, a large body of literature deals with concepts and decision support models in VBM and IBP. However, two main gaps in the literature can be determined. First, a comprehensive conceptual architecture for model-driven IBP deserves further research since corresponding approaches are confined to their respective domains. Second, various decision-oriented approaches to VBM exist, but a unified modeling approach has not yet been presented. This paper therefore develops a comprehensive approach to designing model-driven DSS for VBM. The remainder of the paper is structured as follows: a conceptual architecture for IBP following the hierarchical planning paradigm is derived in Section 2 from a literature survey. Section 3 develops a corresponding unified modeling approach for value-based performance and risk management using Value Added (xVA) performance concepts and robust optimization methods. We conclude the paper in Section 4 summarizing major research perspectives.

This paper presents a comprehensive approach to designing model-driven DSS in Value-based Management (VBM). A conceptual architecture for integrated business planning is derived from a literature survey providing the foundation for a model-driven approach to VBM. In contrast to common explanatory frameworks and data-driven concepts such as value driver trees and risk-adjusted parameters, we develop a model-driven approach for integrated performance and risk optimization. Opportunities for further research are identified as part of the literature survey. The Integrated Business Planning (IBP) matrix is derived from a literature survey as a comprehensive conceptual architecture for model-driven DSS in corporate planning. The IBP matrix follows the hierarchical planning paradigm distinguishing three different planning levels and provides an integrated perspective on profit, cash flow, and risk considerations. The IBP matrix defines major domains covering related subdomains and decision-relevant aspects that can serve as a blueprint to configure and coordinate corresponding modular DSS for value-based corporate planning. Summarizing various decision-oriented approaches in the literature, we outline the benefits of a value-based approach compared to a common approach that optimizes the physical and financial dimension of business sequentially. A unified modeling approach for integrated value-based performance and risk optimization is developed using Value Added (xVA) concepts for performance management and robust optimization methods for risk management. A risk-based adaptation of the xVA concept is used to develop a decision-oriented approach to risk management explicitly taking into account the risk(-averse) preference of the decision-maker. Multiple aspects of robust planning and different criteria for robust decisions are examined to outline their benefits in a two-stage stochastic programming approach. The literature survey identifies several perspectives for further research at the different levels of the IBP matrix. At the long-term level of strategic performance and risk management, decision-oriented aspects of further business domains such as supplier, customer, and employee lifecycle management should be integrated into decision models for strategic supply chain design. Since an integrated approach to value-based performance and risk management has not yet been implemented at the long-term level, a corresponding approach using the Market Value Added (MVA) concept should be investigated using a case-oriented application. Coordination with mid-term corporate management should also be further examined to analyze the benefits of using coherent xVA concepts at both levels. Although sales and operations management and project portfolio management cover two different perspectives on business (run vs. change) at the mid-term level, they are closely interlinked since change initiatives influence run parameters and both domains partially compete for the same resources. Consequently, integrated approaches to sales, operations, and project portfolio management should be investigated. Alternatively, a hierarchical coordination approach via long-term strategic business development could be considered. Furthermore, integrated/distributed decision-making concepts should be analogously developed for the level of short-term corporate management taking value-based considerations into account.