What is Spend Analytics?
Spend Analytics is the discipline of collecting, processing, and analyzing procurement data. Spend analysis uncovers business buying patterns through an in-depth review of procurement data. Organizations use these to manage their suppliers, to track procurement performance, and to decrease cost. Often the terms are interchanged, though the analysis is one (important) step of many in the analytics process.
Why is the Spend Analytics important?
Spend Analytics brings together purchasing-related data and turns it into immediate, budget-saving opportunities. The analysis also generates KPIs to assist decision-making. It provides visibility into an organization’s purchasing trends and offers useful insights. Spend analysts can improve supply management by reducing risk and ensuring compliance of any supplier. And measure and benchmark the flow of the end-to-end procurement process against peers.
Typical procurement improvements:
- Increased visibility on category sourcing patterns
- Gain insights for strategic sourcing
- Better oversight of supply chain processes
- Reduction in supplier risk
- Nurture effective supplier relationships
How can Spend Analytics support Procurement?
It answers core questions to improve the financial efficiency of a company.
- How much money does the company spend?
- Which supplier provides which goods or services?
- Is the organization getting what it expects for the purchase or contract?
Purchasing patterns are easier to see on dashboards, charts, and tables. Often these are static presentations or spreadsheets with errors. Rather than use legacy office applications, analysis tools provide a variety of dynamic visualizations that allow data exploration through filters and drill-downs.
One way to show the data is by the procurement category. Category-specific data allows category managers to use their expertise for cost reduction, supplier consolidation, and contract coverage.
What happens under Spend Analytics?
Spend analytics helps optimize the procurement performance of any organization by integrating information from sourcing data, cleaning it for accuracy, and categorizing to item level. The business, operational managers, and procurement professionals can make better, actionable decisions for their organization using spend analytics software with reliable data and deep classifications. Cost savings are a common goal for this process. Most organizations are increasing the time spent analyzing the process, using the analysis software to understand their spending patterns better, to identify future savings opportunities, and to increase Procure-to-Pay efficiency.
To successfully execute the process, you need to consider the following steps.
- Retrieve procurement data.
- Validate data is complete and accurate.
- Cleanse data and normalize suppliers.
- Place data by category into a deep, standardized taxonomy.
- Enrich data with metrics and benchmarks.
- Analyze data with an analytics solution that provides good visibility and instant insights.
- Identify potential savings opportunities, process efficiencies, and options for contract creation or re-negotiation.
To receive more value, work hard to get accurate, granular data from your records. Using an AI-powered platform, such as Simfoni’s Spend Analytics, data cleansing and categorization time dramatically decrease while data accuracy increases. SaaS procurement analytics can also provide analysis solutions that automatically identify common cost-saving strategies, such as vendor consolidation, volume discounts, and purchase price variance.
Implementation of Spend Analytics
When done manually or with out-dated tools, the data preparation process can take months, which limits the frequency of use. With AI-driven SaaS solutions, the process can take weeks or even days and achieve more accurate richer results. As companies make the switch, Spend Analytics is moving from a once a year check to a quarterly or monthly review. As procurement analysts, business leaders, and management apply the actionable insights, it can become an everyday tool to understand the past and help predict future spending and future saving.