Product Attribute to Impact Algorithm (PAIA)

Quantifying a product's energy and carbon footprint is time-consuming and resource intensive, and the results are often uncertain, yet increasingly it is a necessary task as carbon footprint certifications are required by a growing number of countries, corporations, and industry associations. In response to this challenge, MSL is building on existing work in the field to develop a streamlined methodology to calculate the primary drivers behind carbon and energy impact that attempts to minimize the need for data collection and user input while still providing actionable insight. Originally developed for information technology industries and now extending to other product types, the PAIA methodology focuses on quantifying uncertainty in life cycle activity and impact data to triage data collection efforts and understand the product attributes that drive impact.

While cost, quality, and performance remain the primary drivers for decision making within firms, changing market dynamics stemming from volatile energy prices, pressure from consumers and private groups, and rapidly developing eco-labeling efforts are causing many firms to focus on the quantification of environmental performance. However, executing quantitative measurement and identifying primary drivers of impact present particular challenges due to the complex and evolving dynamics of products and supply chains.