Factory benchmarking — are useful indicators used?

Common factory figures have often been used as performance indicators by generations of technologists and managers. This paper seeks to examine their suitability for this purpose. Metrics were evaluated against criteria describing a perfect indicator, defined as one that was adequately related to actual business outcomes, reflected success in managing controllable factors, considered the impacts of uncontrollable factors, and was expressed in commercially relevant terms. Relevance was considered at the levels of overall business, facility, and individual technologist. The results challenge some longstanding perceptions about the relevance of commonly used factory figures. Expression in terms of pol/sucrose losses ignored the impacts of factors beyond the control of the business. While reflecting the influence of individual decisions, assessing against losses alone did not discriminate between the different organisational functions influencing outcomes. Losses were better seen as expressions of lost opportunity for the business, making them more aligned with being accounting rather than technically orientated measures. Their use in forecasting and budgeting without consideration of prevailing conditions was questioned. Recovery was the least meaningful metric. It ignored the impacts of common variables, did not reliably reflect commercial outcomes, and lacked relevance as either a technical or commercial indicator. Being calculated from two variables determined through consideration of operating conditions, Pool Sugar Index (PSI) had alignments with characteristics of a technical measure. Some other common metrics that normalised for variables outside business control had some relevance as technical indicators. While common metrics could be influenced at various organisational levels, the impacts of individuals or groups on outcomes cannot be discriminated based on the metrics alone. It seems that generations of technologists have intuitively understood that common metrics do not adequately describe performance and lack context. This may have resulted in a lack of consistency in how people view metrics, with impacts on milling sector culture and cognitive biases that influence decision making. Effective performance assessment should include various metrics and consider operational realities and the context within which a business outcome is being assessed. Key words Performance indicators, benchmarking, factory losses, recovery, Pool Sugar Index