Heuristic rating estimation is a newly proposed method that supports decisions analysis based on the use of pairwise comparisons. It allows the ranking values of some alternatives (herein referred to as concepts) to be initially known, whilst ranks for other concepts have yet to be estimated. To calculate the missing ranks it is assumed that the priority of every single concept can be determined as the weighted arithmetic mean of the priorities of all the other concepts. It has been shown that the problem has an admissible solution if the inconsistency of the pairwise comparisons is not too high. The proposed approach adopts heuristics according to which a weighted geometric mean is used to determine the missing priorities. In this approach, despite increased complexity, a solution always exists and its existence does not depend on the inconsistency or reciprocity of the input matrix. Thus, the presented approach might be appropriate for a larger number of problems than previous methods. Moreover, it turns out that the geometric approach, as proposed in the article, can be optimal. The optimality condition is presented in the form of a corresponding theorem. A formal definition of the proposed geometric heuristics is accompanied by two numerical examples.

The paper deals with problems in the post-implementation phase of management Enterprise Resource Planning (ERP) systems. Proper management of the system maintenance stage is a basis for efficient system development in terms of business needs. Based on the research and analysis of collected materials, it turns out that making a decision to upgrade the system is equally crucial. We present revealed mechanisms determining the post-implementation approach to upgrade or reimplement the ERP system. The main aim is to determine the methodology and difference understanding to achieve success in the post-implementation stage. The paper shows that the systemic approach to the maintenance stage of the ERP system affects its further decisions: upgrade or reimplement. It has a direct impact on future maintenance costs and the scope of new business demands. This research is an outcome of industry–academia collaboration and based on several developed implementation systems, achieved upgrade and reimplementation projects. Based on case study analysis, we show that reimplementation means an evolution of the current ERP processes rather than another attempt to “reimplement” an unsuccessful system implementation. On the other hand, upgrades are not only a tool or system actualization but the easiest way to bolster company sustainability and to have the information system up to date. The issues discussed in the article will be used to develop changes in the implementation methodology of ERP systems.

Corporate budget planning involves forecasting expenses and revenues to support strategic goals, resource allocation, and supply chain coordination. Regular updates to forecasts and collaboration across organizational levels ensure adaptability to changing business conditions. Long-term sales forecasts form the foundation for budgeting, guiding resource allocation and enhancing financial efficiency. The budgeting process in organizations is complex and requires data from various operational areas, which is collected over a representative period. Key inputs include quantitative sales data, direct costs indirect costs, and historical revenues and profitability, which are often sourced from ERP systems. While ERP systems typically provide tools for basic budgeting, they lack advanced capabilities for forecasting and simulation. We proposed a solution, which includes dynamic demand forecasting based on time series methods such as Build-in method in Power BI (which is ETS—exponential smoothing), linear regression, XGBoost, ARIMA and flexible product groupings, which are simulations for cost changes. The case study concerns a manufacturing company in the mass customization industry. The solution is designed to be intuitive and easily implemented in the business.

A defect prevention is a part of manufacturing company practice. Paper proposes a formal approach for solving scheduling problems with unexpected events as extension of general frameworks for Zero-Defect Manufacturing (ZDM) strategy. ZDM aims to improve the process efficiency and the product quality while eliminating defects and minimizing process errors. However, most of ZDM applications focus on using the technological achievements of Industry 4.0 to detect and predict defects, forgetting to optimize the schedule on the production line. We propose formal method to create predictive-reactive schedule for problems with defect detection and repair. Our proposal is based on the formal Algebraic-Logical Meta-Model (ALMM). In particular, it uses the model switching method and combines defect detection, heuristics construction and decision support containing predictions of disturbances in the production process and enabling their prevention. Production defects are detected and repaired, and consequently, production delivers components without defects, and in the shortest possible time. Moreover, the collection and analysis of data related to the occurrence of disturbances in the production process helps the management board in making decisions based on analysis gathered and stored data. Thus, the proposed method includes strategies such as detection, repair, prediction and prevention for defect-free production. We illustrate the proposed method on the example of a flow-shop system with different types of product defect problem.

The paper presents a new approach, based on an algebraic-logical meta-models (ALMM), to solving NP - hard manufacturing problems. There is considered the flow-shop manufacturing problem with time limits, the quality control, removing of manufacturing defects on an additional repair machine and retreatment of task in technological route. Proposed solution consist in switching of original algebraic-logical model to model with modified parameters when quality defects appear. In particular algebraic-logical model of flow-shop manufacturing problem with time limits and modified model with additional repair machine are proposed. Furthermore, the switching function from original model into modified model is given.