The Role of Statistical Literacy and Data-Driven Decision Making in Improving MSME Performance: A Systematic Literature Review

Niel Ananto, Cherry Efraim Lumingkewas

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Micro, small, and medium enterprises (MSMEs) generate transaction data daily, yet few use these data as a basis for decisions. This PRISMA 2020 systematic review maps empirical evidence on how statistical literacy and data-driven decision making relate to MSME performance. A Scopus search yielded 323 records (2016–2026); after title and abstract screening, 116 empirical studies were synthesized through descriptive bibliometrics and thematic analysis. Big data analytics capability was examined in 78% of the studies, data-driven decision making in 15%, and record keeping in 15%, whereas owners’ statistical or data literacy was measured in only one study. The focus has shifted: Before 2024, 10 of 25 studies examined record keeping, compared with 7 of 91 since 2024. Most studies (84%) reported positive associations with performance, usually through decision quality, innovation, and sustainability capabilities. Three experiments showed revenue gains of 3.6% and 18.8% from analytics and profit gains for female microentrepreneurs from better bookkeeping. However, 68% of the studies relied on cross-sectional structural equation modeling with perceptual measures. The basic statistical skills of MSME owners, a precondition for data use, remain largely unexamined. We propose a model linking statistical literacy, data use, data-driven decisions, and MSME performance as a research agenda and a basis for statistics training.
Keywords: statistical literacy, data literacy, data-driven decision making, MSME performance, systematic literature review

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DOI: https://doi.org/10.37531/mirai.v12i1.12952

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