Back to Intuition: Proposal for a Performance Indicators Framework to Facilitate Eco-factories Management and Benchmarking

Abstract

In the current competitive and regulated landscape, manufacturing enterprises struggle to improve their performances, encompassing environmental as well as economic objectives, towards sustainable manufacturing and the future Eco-factories. Experts and scholars have developed more and more indicators, usually referred to as Key Performance Indicators (KPIs), as a mean for steering and controlling the complex factory systems, characterized by dynamic interdependencies among different subsystems and external variables. The present study proposes a synthetic framework to bring back hundreds of environmental and economic KPIs to a few sound intuitive categories, in order to reduce duplications, recuperate meaningfulness and consciousness, facilitate inter and intra-organizational benchmarking. The approach, based on input-output modelling of physical flows (products, materials, energy, emissions, etc.) in manufacturing systems, can be used at different hierarchical levels in the plant and in different factory life-cycle phases (design, operations and re-design). The application of the framework is demonstrated on an extensive review of performance indicators gathered in industrial cases and in the literature

Testing and Verification of a New Corporate Sustainability Assessment Method for Manufacturing: A Multiple Case Research Study

“…The approaches to the development of tools include fuzzy methods, AHP, system dynamics modeling, indices, and principles-based assessments.Although extensive research has been done, the scientific community is still inconclusive about many of the shortcomings and limitations of CSA. Some of the potential shortcomings are: (1) CSA often fails to address system performance [41]; (2) CSA tends to mix sustainability performance of the company and sustainability-oriented practices [44]; (3) CSA includes an uncomprehensive and unsystematic list of indicators [46]; (4) an observed inability of many CSAs to provide a practical approach for the companies to identify improvements and possible sustainability-oriented practices [48,82]; (5) the inability of some CSA to capture the complexity of sustainable manufacturing (SM) due to a widely used reductionist approach to CSA [83]; (6) the use of a set of unrelated indicators [84]; and, (7) companies measure what is measurable, rather than what is necessary concerning the given subject or phenomenon [47]. These observed shortcomings affect the ability of CSA to provide a holistic view on the sustainability performance of a company and identify the associated improvement potential.…”

Development of Manufacturing Sustainability Assessment Using Systems Thinking

“…Another reason why different companies try to achieve different sustainability performance is specific benchmarking values. For instance, the benchmarking value of an indicator can be based on past performance of the company, a particular standard, the amount of reduction required in a specific period [35], a defined target, or similar manufacturing systems [47].…”

“…First, it is difficult "to identify current measurable indicators that point to sustainability" since sustainability is associated with the future while indicators measure the present [48]. Second, "sustainability indicators in fact are calculating by gauging, comparing, correlating these quantities during a specified period of time, blind to the dynamics of the manufacturing processes in that period of time" [47]. Moreover, it is not an easy task to compare and correlate different indicators.…”

“…Additional sources of complexity are different assessment levels (product, process, company, etc. ), different sustainability dimensions (social, economic, and environmental), different perspectives, and different time references [47].…”

“…The authors point out that a visualization of cause-effect relationships between qualitative and quantitative indicators can facilitate the development process in the company. Fantini et al [47] presented a framework for key performance indicators built on only a few main indicators that allow capturing the whole eco-factory performance. This work contributes to a possible performance management system that can enable a systematic assessment of manufacturing behavior from different viewpoints.…”