“Procurement teams do not have the time or resources to aggregate data that is spread across multiple systems and/or spreadsheets, nor are they able to 'catch up' as new data is constantly created and ingested...This is a problem, as bad data leads to bad decisions: organizations that wait too long to implement good data management practices affect downstream business decisions which leads to loss of revenue.”

Make The Case Report - Spend Matters 



Make The Case Report

In today's data-driven business landscape, effective data management is crucial for organizations of all sizes and industries. However, managing data can be a complex and time-consuming task, especially when it involves disparate systems and vast amounts of information. The consequences of poor data management are far-reaching, affecting everything from risk tracking and supplier performance to business goals and the adoption of emerging technologies.

This report explores the challenges that organizations face in data management and how partnering with a data analytics specialist like Rosslyn can transform data from a source of frustration into a valuable asset, enabling informed decision-making, and paving the way for progress.

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Spend Matters Make the Case

Press Release: Rosslyn named '50 Providers to Know'

For the third consecutive year, Rosslyn has made it on Spend Matters' 50 To Know list. The list recognizes the best-in-class companies that lead the charge on new technologies and services within the procurement industry.

Case Study: Procurement transformation in times of uncertainty

Air France-KLM faced various challenges during the volatile year of 2020 and the COVID19 pandemic. Read the case study to uncover which critical decisions the business had to make to withstand those challenges.

 Insights: 2022 summary of procurement technology analyst findings

More and more businesses are buying into procurement technology to gain visibility of their data, as data influences decisions, dictates processes, and promotes better decision-making.