Beyond Silo Targets for Interdependent KPI Goal Setting

Performance measurement frameworks deployed across supply chain organizations — most notably the Supply Chain Operations Reference (SCOR) model (Supply Chain Council, 2022), and the Balanced Scorecard (Kaplan & Norton, 1992) - share a structural blind spot: they define and track Key Performance Indicators (KPIs) as if they were independent of the others. Decades of operations research establish, however, that supply chain performance variables are bound together by well published mathematical constraints. The relationship between inventory, throughput, and cycle time (Little, 1961), the convex sensitivity of cycle time to capacity utilization (Kingman, 1961), and the nonlinear cost of achieving high fill rates through safety stock (Eppen & Martin, 1988) are not situational nuances — they are inescapable system properties. When annual KPI targets are formulated without accounting for these dependencies, organizations routinely construct goal portfolios that cannot be simultaneously achieved, setting the stage for incentive misalignment, finger pointing and blame, and a very short cycle of shifting priorities that erodes both performance and morale. Despite the breadth of research on supply chain trade-offs and on goal conflict in organizational psychology, there is a notable absence of structured guidance on how to translate trade-off awareness into operational KPI goal setting. Existing methodologies (Management by Objectives, OKR, and SMART goals) offer valuable principles for clarity and accountability but provide no mechanism for evaluating whether a set of targets for interdependent metrics is jointly feasible. The SCOR model, similarly, offers a comprehensive taxonomy of 149 performance indicators and a five-stage maturity model requiring increasing cross-functional integration, yet supplies no framework for multi-objective trade-off analysis when formulating those targets. This research is directed at closing that gap. Several research questions organize the inquiry: what does the academic literature reveal about goal setting for interdependent supply chain KPIs and how do practitioners do it? To what extent are the interdependencies among the KPIs explicitly reflected in the goal-setting process? What approaches and frameworks would improve the goal setting process? The study proceeds combining a systematic literature review spanning operations research, goal-setting psychology, and performance management with a survey of 60 supply chain professionals across manufacturing, distribution, and retail sectors. The structured questionnaire is organized into six sections addressing demographic context, goal-setting practices for each of the three KPI domains, KPI governance and prioritization, and barriers to trade-off integration. The survey is complemented by semi-structured interviews with six to eight VP- or Director-level supply chain leaders. A joint quantitative and qualitative analysis is employed to characterize current practices and identify organizational archetypes; qualitative analysis follows Braun and Clarke's (2006) thematic approach to surface behavioral mechanisms not captured by survey responses. The expected empirical findings are anchored in a specific hypothesized gap: while approximately 75% of surveyed organizations are anticipated to pursue simultaneous improvements across all three KPI domains, fewer than 20% are expected to conduct explicit trade-off modeling. This disconnect is predicted to manifest behaviorally as a self-reinforcing dysfunction triad (Locke & Latham, 2002)— constant priority shifting, cross-functional blame, and silo formation — whose prevalence should correlate strongly and negatively with trade-off modeling maturity. The cluster analysis is expected to reveal three organizational archetypes: Silo-Driven organizations, characterized by low trade-off awareness, high dysfunctional behavior, and below-target performance; Aspirational organizations, aware of the problem but lacking tools; and finally Interdependency Aware organizations, whose practices will inform the artifact design. The theoretical contribution of this research lies in bridging three streams that have developed largely in isolation: operations research models of supply chain trade-offs, goal-setting theory and goal conflict evidence from organizational psychology, and strategic supply chain management frameworks. The practical contribution addresses a recognized but underserved managerial need: structured, analytically grounded guidance for setting coherent KPI targets that acknowledge interdependence rather than papering over it. For maritime and logistics supply chains specifically — where the interplay between transit time, inventory positioning, cost, and service reliability is especially consequential — the research offers a practical tool for navigating a trade-off frontier that shifts with every change in routing, sourcing geography, or service commitment. The ability to formulate performance targets that are simultaneously achievable, strategically coherent, and organizationally fair is a foundational requirement for effective supply chain management. This research proposes that meeting that requirement demands moving beyond aspirational benchmarking toward a goal-setting process grounded in the mathematical structure of the supply chain itself.