# REDUCE--A Tool Supporting Inconsistencies Reduction in the Decision-Making Process
## 1 Introduction
Methods to detect and mitigate inconsistencies include consistency indices and optimization techniques [30; 31; 32]. Additionally, scaling pairwise comparison methods for large datasets remains a research focus, with efforts directed towards developing efficient algorithms and computational frameworks [33; 34; 35]. When such methods and algorithms are proposed, one of the key challenges is the problem of large set matrices generation with assumed consistency ratio (\(CR\)) in order to test proposed solutions according to several measures. Inconsistency is a pervasive problem in PCs because human experts are rarely completely consistent in expressing their judgments, especially when the number of objects being compared is relatively high. A low level of inconsistency is usually tolerated, but if the inconsistency exceeds a certain threshold, for example, \(CR=0.10\), pairwise comparisons must be revised. However, in many situations, it may not be possible for an expert to revise the PC. In such cases, appropriate software comes into play. To the best authors' knowledge, there was no known free (non-commercial) online tool for reducing inconsistency in pairwise comparisons; here, the proposed solution is an expansion of system that was initially developed in [36]. Therefore, the purpose of this paper is to present and demonstrate the use of REDUCE, a free online tool designed to reduce inconsistency within the PC. The novelties of REDUCE lie primarily in its accessible, free online format and its specific focus on inconsistency reduction within pairwise comparisons, a feature not typically emphasized in other decision-support tools. Additionally, while other approaches may employ different methodologies, REDUCE was developed to meet the practical needs of small and medium-sized enterprises, which often lack access to costly or complex decision-support software. For these reasons, our primary aim in this paper is to highlight REDUCE's contributions as a streamlined, user-friendly, and cost-effective tool for enhancing decision-making processes. The main motivation for proposed paper is to prepare a user-friendly, simple-to-use tool that can support different users when they use AHP-based approaches for decision making and meet with different problems related to the following: inconsistency of experts' assessment, limited amount of resources (especially money), no desire to use sophisticated tools that usually require extended knowledge about the methodology, and limited knowledge about all theoretical details. Moreover, the proposed solution should be available online, with requirements according to WCAG standards, it should be safe for end-users, and its interface should be limited only to the necessary details. The paper is divided into two parts. The first, major one (Section 2) is devoted to presentation of the REDUCE application: its main features, used technologies, server and administration solutions, performance, and security tests. The second part is related to descriptions of further development (Section 3) and conclusions (Section 4).