One of the benefits of modern transaction processing is the wealth of information provided in the data behind the processes. As businesses look to lean out and structure operations to be more cost-effective, many are finding that spend analysis is providing a host of benefits.
Spend analysis requires the use of real-time data and analytics but can provide incredible insight to help your business save money.
In this FAQ we will cover what spend analysis is, why it is important, and how you can use data to perform spend analytics.
What Is Spend Analysis?
The process of collecting, grouping, categorizing, and scrubbing information on how your business spends money is referred to as spend analysis.
This type of analysis is performed with the main intent of reducing costs related to procurement or improving efficiency and transparency. Spend analytics is a subset of spend management, which is the practice of managing relationships with suppliers and purchases.
Why Is Spend Analysis Important?
The process of analyzing spending related to procurement is an important action that businesses take to manage inventory cost and supplier relationships.
It is a primary tool used by procurement professionals to attempt to identify ways to save money, manage risks, or position the business to optimize its buying power.
One of the major benefits of implementing spend analysis is the visibility it provides into corporate spending. The wealth of information provided in spend analysis is often used to help improve the performance of the supply chain and those that manage it.
The analysis provides useful information that can be used in the decision-making process or to develop strategies and techniques to reduce inventory or raw material costs.
The process of data aggregation in spend analysis helps paint a broader picture of the overall purchasing environment.
The data that is aggregated defines the purchasing ecosystem that the business operates in and helps to identify which parts of that ecosystem the business can exploit to its advantage.
Finally, the data provides a good historical context by which to measure the success of the plans and strategies deployed by the business to induce cost savings.
How To Perform Spend Analysis
The process of data identification, collection, and the subsequent grouping, categorizing, and analyzing attempts to answer some key questions. These questions guide the data you will collect and where to get it.
Defining The Procurement Ecosystem
The supply chain has many moving parts. Fortunately, spend analysis is solely concerned with procurement. The data collection process is concerned with identifying the following:
- What products or materials are being purchased, in some cases services
- Who the suppliers of products, materials, or services are
- The individuals performing the purchasing
- The frequency of purchases
- The timing of purchases
- The cost of each purchase
- Products or materials received versus what was purchased
- The location of physical deliveries
- Historical purchasing information
Data Collection
The data collection process is typically done with help of Enterprise Resource Planning (ERP) systems. Often accounting general ledgers contain much of the financial and transaction data as well.
Purchase orders should always be referenced as well as any other data that can be acquired from suppliers or other systems that the business has in place.
Understanding Direct And Indirect Procurement Spending
Understanding the difference between direct and indirect procurement spending will help to make the categorizing process easier.
Direct Spending is the cost of procuring materials (or services) that are directly related to making products. These typically include raw material or other pertinent services.
Indirect Spending can be considered all procurement costs that are not directly related to the production of goods and services. This is sometimes referred to as overhead and can sometimes require some form of cost analysis. Some examples of indirect spending include marketing, consultant fees, meals and travel, IT, HR, and utilities.
Spend Taxonomy
In order to make analysis easier, both direct and indirect spending needs to be categorized. Spend taxonomy is a classification system that is used in procurement to collect and group direct and indirect spend in similar groups.
There is a standardized taxonomy provided by the United Nations Standard Products and Services Code (UNSPSC).
Define Spend Analysis KPIs
Once data has been identified, collected, and categorized it can then be dissected and analyzed.
Defining key performance indicators will help to dial your focus onto relevant information within the procurement process. There are some common KPIs used by organizations. Some relevant KPIs include:
- Number of suppliers by category
- Spend by category
- Number of transactions by category
- Average purchase order
- Spend distribution
- Material price changes
- Payment terms and conditions
- Total expense by supplier
Monitor
Once the spend analysis is performed the resulting information will help you to develop strategies and implement changes to improve or manage the relevant KPIs to your business.
This part of the process is perhaps the most important as it provides relevant, real-time insight into your procurement practices.
This type of analysis helps you to be more proactive in your decision-making regarding your supply chain and the cost associated with procurement. It provides full visibility into spending and helps to highlight opportunities to save money.
Skipping this vital step negates the whole process of spend analysis, so time should be spent establishing good monitoring techniques.
Using Datarails to Perform Your Spend Analytics
Every finance department knows how challenging performing spend analytics can be. Regardless of the type of spend analytics you are performing, it requires big data to ensure accuracy, timely execution, and of course, monitoring.
Datarails is an enhanced data management tool that can help your team create and monitor financial forecasts faster and more accurately than ever before.
By replacing spreadsheets with real-time data and integrating fragmented workbooks and data sources into one centralized location, you can work in the comfort of excel with the support of a much more sophisticated data management system behind you.
This takes financial forecasting from time-consuming to rewarding.