| Issue |
SHS Web Conf.
Volume 230, 2026
SYMBICON 2026 – 5th Annual International Conference on Sustainability, Innovation, and Technology
|
|
|---|---|---|
| Article Number | 02003 | |
| Number of page(s) | 13 | |
| Section | Sustainable Innovation and Entrepreneurship | |
| DOI | https://doi.org/10.1051/shsconf/202623002003 | |
| Published online | 10 April 2026 | |
Impact of Data Analysis on Financial Performance in Small and Medium Manufacturing Companies
MIT Art, Design & Technology University, Pune, India
Abstract
The upward-trending digital environment notwithstanding, small- and medium-sized enterprises (SMEs) operating in the manufacturing field are increasingly considering the strategic importance of data analytics to boosting their financial performance. The review provides a conceptual reconsideration of the interconnection between data-analytic adoption and the financial performance of firms. It questions the ability of predictive analytics, business intelligence, and live data processing to enable a greater quality in decision-making, increased cost-effectiveness, improved financial planning, and increased profitability. Based on the recent research conducted in the period between 2014 and 2024, the paper outlines the key financial metrics that are affected by the analytics, especially the return on investment (ROI), profit margins, and operational productivity. According to the empirically proven benefits, however, SMEs still face implementation limitations like the lack of technical infrastructure, poor human resources, challenging data integration, and cybersecurity threats. As a result, some promising future routes are noted in the review, such as the introduction of low-cost analytics or a focus on developing digital skills and the development of policy frameworks that would encompass the needs of SMEs. It concludes that data analytics, when strategically aligned with business goals, offers a powerful pathway for SMEs to achieve financial resilience, competitiveness, and sustainable growth in an increasingly data-driven economy.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

