*By Alexandre Carvalho
In Brazil, financial cooperatives have a complex and autonomous structure, with centers spread across the country and millions of customers. These institutions are closely linked to the agribusiness sector and have a differentiated proposal, in which their members have access to dividends and special credit lines.
Therefore, they play a crucial role in the Brazilian socioeconomic scenario, with an important social impact, contributing significantly to financial inclusion, job creation and stimulation of the local economy. The use of analytics can enhance these efforts, helping to direct credit to where it can have the greatest impact and truly make a difference.
Regarding the current stage of maturity of cooperatives in analytics, adoption is still timid, although these organizations are moving to modernize their operations. In this process, cooperatives often encounter architectural and technology issues, especially when it comes to scaling to work with large databases. The quality of available data and speed of implementation are also among the obstacles that need to be overcome.
In this journey of evolving analytics adoption, cooperatives are faced with significant barriers, but overcoming them can lead to improvements in risk management, fraud and money laundering prevention, operational efficiency and social impact. To achieve this goal, cooperatives need strong technological support, as well as a qualified team to drive digital transformation. Here, strategic partnerships with technology companies can open up new opportunities.
Developing personalized approaches
Despite the challenges, cooperatives have an important opportunity to improve their use of data analysis, on fronts such as service personalization. This observation is consistent with one of the lessons listed in the book “Analytical Competition – Winning Through the New Science”, the classic by Thomas H. Davenport and Jeanne G. Harris, which argues that a company's competitive advantage can be obtained through the use of analytics of data.
Davenport makes the point that companies that use advanced data analytics to guide their strategic decisions are becoming leaders in their respective industries. This is possible through the ability to, for example, better understand an organization's customers, as well as optimize its operations, identify future trends and make evidence-based decisions.
Due to their member-based nature and proximity to the community, co-ops are in a unique position to understand the specific needs of their members and adapt their services accordingly. If we apply Davenport's lessons to cooperatives, companies in the sector can use data analysis to better understand their members, create tailored offers, and improve member satisfaction.
Still based on the author's insights, cooperatives can also use advanced data analysis to identify areas of inefficiency or opportunities for improvement. This can allow cooperatives to continually improve their operations and services. By providing members with data-driven insights into their performance, co-ops can also significantly improve engagement and trust.
Additionally, it is also necessary to create a culture that values data-based decision making, as well as the skills necessary for analyzing and interpreting data. In a scenario of constant change, the union of these elements will be crucial to improving the competitiveness and resilience of cooperatives in the future.
*Alexandre Carvalho is a senior account executive at SAS.
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
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