Resumen

DELFINO BARILLA, Cinzia  y  LASTARRIA REYNOSO, Lucia. How can Big Data contribute to improve the financial performance of companies?. Rev. mex. econ. finanz [online]. 2020, vol.15, n.spe, pp.589-598.  Epub 05-Mar-2021. ISSN 2448-6795.  https://doi.org/10.21919/remef.v15i0.548.

Objective: We propose a comprehensive methodology that combines a set of Big Data Analytics tools (BDA) with prospective analysis, risk analysis and strategic analysis with the aim to improve the firm’s financial performance measured through Key Performance Indicators (KPIs). Methodology: The methodology consists of five (5) stages: financial modeling, prospective analysis, risk analysis that includes BDA, strategic analysis and monitoring Results: This methodology allows directing the BDA towards the characterization of the critical variables that create value for the company, designing contingent strategies and evaluating their impact on the selected financial indicators (KPI) all this in a multidimensional way Recommendations: We require constant monitoring to generate different forms of innovation and flexibility in the company and improve its financial performance. Limitations: The success of the methodology depends on the company’s ability to improve, adapt, adjust, or innovate to gain, sustain, or reconfigure a competitive advantage. This skill is called process oriented dynamic capabilities (PODC) Originality: The proposed methodology is comprehensive since it allows the inclusion of various areas of the company in order to improve its financial performance represented by the KPIs. Furthermore, the analysis can be performed for specific areas and business units. Conclusions: The proposed methodology promotes innovation and flexibility that will improve the financial performance of the company as long as there is a good fit among Big Data activities, the organizational structure, the commitment of senior management and support for the development of PODC.

Palabras llave : Information Technology Management; Big Data Analytics.

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