Before we go into the core topic of this article, it is essential to ensure that we all have the same understanding of the meaning of spend analytics. Spend analysis is the process by which unstructured spend or invoice data, is converted into structured data and meaningful information that can subsequently provide executive management transparency.
This guide will teach you how to use your spend data to transform your business for profitable growth.
Download our free Low Risk Low Value (LVLR® ) framework to get complete spend visibility and achieve over 20% reduction in costs.
Download our Category Management Optimiser Checklist that has helped business leaders monitor and improve the effectiveness of their existing spend categories and subcategories enabling them to add millions to their bottom line.
Download our Transforming Finance With Artificial Intelligence (AI) Guide now and explore how AI can help you improve efficiency, build agility and make optimal strategic business decisions.
As per a report from Research and Markets, “The Spend Analytics Software Market was valued at USD 1.12 billion in 2019 and is expected to reach USD 3.05 billion by 2025, at a CAGR of 18.2% over the forecast period 2020-2025”. Another report from Data Bridge Market Research states that “Global spend analytics market is expected to rise to an estimated value of USD 5.66 billion by 2026, registering a healthy CAGR in the forecast period of 2019-2026”. As a result, it is no surprise that various organisations are coming up with strategies to restrict unwanted spending by adopting spend analytics software to analyse financial / spend / invoice data. The analytics platform also enables monitoring trends by integrating real-time data feeding.
To conclude, it is evident from experience that organizations will have increased demand for a more analytical and automated approach to managing their operational expenses (OPEX). With the ever-evolving technologies, features such as artificial intelligence (AI) and machine learning (ML) can effectively automate data scrubbing and data classification based on pre-defined taxonomy. But the critical point to note is that data analytics is not a one-time or periodic activity; more importantly, it is to review and analyze transactions in near real-time continuously. In this way, automation tools can identify spending behavior patterns and deliver actionable insight to help guide the leadership team to take timely actions.
With Covid-19 acting as a catalyst for digital transformation, embracing data analytics as a tool to mitigate risk will be an essential part of organizations' efforts to strengthen financial positions at a time when market volatility demands it. Spend analytics will no longer be a nice to have but a must-have capability for all organizations.
Discover how Jessica, the CFO of a mid-sized tech firm achieved quick, effective, and guaranteed improvements in her organisation’s financial health with AI.
Unleashing Gen AI for Pharma Leaders to Catalyse Cost Efficiency and Drive Fiscal Excellence.
Discover Emily's journey and learn how her strategic use of automated spend analytics transformed procurement in the pharmaceutical industry, elevating Veritas's financial health and inspiring a new business approach.