The environmental impact of considering uncertainty in supply chain planning

Companies increasingly wish to adopt concepts such as “Probabilistic Planning” for better protection against supply chain uncertainty. Adopting such more complex planning approaches might create diverging environmental sustainability effects – either benefit or harm. Therefore, we investigate a sequential decision-making setting for master production scheduling where a profit-maximizing firm switches from a simplified, status quo planning approach (deterministic) to an explicit consideration of uncertainty (stochastic). We first outline a process to evaluate the two planning policies in a stochastic base model simulator regarding their economic performance. This is to ensure a fair comparison and to incorporate established planning paradigms such as replanning based on updated information (rolling horizon). We then propose a process to evaluate the economic optimizations’ impact on global warming. For this, a standardized measurement (greenhouse gas emissions in CO2 equivalents) is attributed to the planning decisions in scope. Companies might not necessarily include environmental targets directly (i.e. in the objective or constraints) into their decision making but might stick to economic objectives – e.g. max profit or min cost. Thus, this framework can be used to analyze worst case outcomes for the environment of adopting more complex planning procedures. We aim to show that whether a stochastic planning approach can improve (i.e. reduce) or worsen (i.e. increase) the environmental impact in comparison to a simplified planning approach depends on (i) problem structure (e.g. available decision options and their relative environmental implications), (ii) the availability and quality of data on uncertainty (i.e. is there a significant advantage to plan stochastically) and (iii) the magnitude of the underlying uncertainty. This work opens up a new field for future research as it could help in guiding thoughtful adoption of supply chain planning processes towards a more sustainable future.     «

Companies increasingly wish to adopt concepts such as “Probabilistic Planning” for better protection against supply chain uncertainty. Adopting such more complex planning approaches might create diverging environmental sustainability effects – either benefit or harm. Therefore, we investigate a sequential decision-making setting for master production scheduling where a profit-maximizing firm switches from a simplified, status quo planning approach (deterministic) to an explicit consideration of...     »