{ "background": "Manufacturing systems in West Africa face persistent challenges in achieving cost-effectiveness, with a recognised need for robust analytical frameworks to support operational decision-making. Existing evaluations often lack the integration of systematic forecasting techniques tailored to local industrial contexts. ", "purpose and objectives": "This study aims to develop and validate a time-series forecasting model to measure and predict cost-effectiveness in manufacturing plants. The objective is to provide a methodological tool for evaluating system performance and informing capital allocation. ", "methodology": "A longitudinal dataset of operational and financial metrics from multiple plants was analysed. The core methodological innovation is a seasonal autoregressive integrated moving average (SARIMA) model, specified as \ (B) \ (Bˢ) \ᵈ\D yt = \ (B) \ (Bˢ) \, where yt is the cost-effectiveness ratio. Model parameters were estimated using maximum likelihood, and forecast uncertainty was quantified with 95% prediction intervals. ", "findings": "The SARIMA (1, 1, 1) (0, 1, 1) ₇ model provided the best fit, with a mean absolute percentage error (MAPE) of 4. 7% on the test set. A key result is that material cost volatility accounts for approximately 60% of the forecast variance in the cost-effectiveness ratio. Forecasts indicate a stable but marginal improvement in the ratio over the forecast horizon. ", "conclusion": "The proposed model offers a statistically sound and operationally relevant tool for forecasting cost-effectiveness, capturing the significant influence of input cost fluctuations prevalent in the regional manufacturing environment. ", "recommendations": "Plant managers should integrate this forecasting methodology into monthly operational reviews. Policymakers are advised to consider stabilising mechanisms for core material inputs to reduce systemic variance. ", "key words": "cost-effectiveness, time-series analysis, SARIMA, manufacturing systems, operational forecasting, West Africa", "contribution statement": "This paper presents a novel application of SARIMA modelling for cost-effectiveness forecasting in an under
Ndiaye et al. (Mon,) studied this question.