Business Intelligence in HR as a Lever for Digital Transformation in the Food Industry

Abstract

Purpose

In particular, it is worth mentoring new and more efficient solutions that can meet the increasingly specific needs of each company, especially in food management. A business intelligence (BI) solution can help your food company better understand and manage business processes more effectively. Management information is essential for all levels of an organisation to make quick and correct decisions. However, what exactly is BI, and what can it mean for a food company?

Design/Methodology/Approach

The PRISMA stands for (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and content analysis strategy used the SLR (systematic literature review) methodology to examine 151 papers published in peer-reviewed academic journals and industry reports between 2016 and 2023.

Findings

The findings show that artificial intelligence and digitalisation are linked to the UN 2030 Agenda. BI management ranks first (66%), followed by crop and land mapping systems (40%), agricultural machinery monitoring tools (39%) and decision support systems (31%). The road to digital transformation remains extended, with the main impediments being more compatibility between enterprise systems and a shortage of expertise.

Limitations/Impacts of the Research

The section relating to methodological perspective adopts the PRISMA methodology for systematic review. Interoperability is easily managed by assigning qualified teams to projects. The added value of a consulting firm with extensive project management experience in the food industry is closely related to the results achieved.

Originality/Value

BI: What exactly is it, and why a data-driven culture is essential in the food and beverage industry?

Citation

Meena, G. and Santhanalakshmi, K. (2024), "Business Intelligence in HR as a Lever for Digital Transformation in the Food Industry", Taneja, S., Kumar, P., Sood, K., Özen, E. and Grima, S. (Ed.) Finance Analytics in Business (Emerald Studies in Finance, Insurance, and Risk Management), Emerald Publishing Limited, Leeds, pp. 77-91. https://doi.org/10.1108/978-1-83753-572-920241004