Procurement and spend analytics have quickly evolved from an emerging trend to one of the most powerful analytical capabilities in leading organizations. In this guide, we're going to offer an easy-to-understand overview of procurement analytics. We'll cover key definitions, benefits, and types of procurement analytics. Finally, we'll provide tips on how to get started.
- What is Procurement Analytics
- What is Spend Analytics
- Types of Procurement Analytics
- The Benefit of Analytics in Procurement
- The Impact of Procurement Spend Analytics
- 6 Procurement Analytics Use Cases to Meet Your Current Needs
- The Procurement Analytic Process: Step-By-Step
Rapidly improving the bottom line is a goal of almost all businesses. However, there's an obstacle in the way: an inability to access, interpret, and use the data that can make it happen. This is especially true for procurement functions, which have been at the forefront of corporate transformation programs, but also have a difficult time getting the analytics they need to see the sustained value and ongoing insights.
Procurement has a unique opportunity to transform itself into a genuine business partner. Procurement functions are already far from the back-office transactional operations of the past. They are now often engaging in complex, cross-functional activities that require strong communication and collaboration skills with other departments. Taking procurement to the next level by using analytics can help them further enhance their ability to help their organizations succeed.
So why use analytics? Well, it helps you make better decisions based on facts rather than guesswork; it allows you to quickly focus on the issues that need attention, and it helps you identify patterns in your spending habits that may be causing you to waste money. Interestingly enough, many companies don't know how much they spend on certain items—and they're surprised by this information once they see it!
In short: analytics is a way for you to make your company more efficient, more effective, and better positioned for growth.
Procurement analytics is a high-potential area that has yet to be fully exploited. IBM's research finds that procurement top performers tend to see real value in the application of procurement analytics. These benefits result from better pricing and negotiations, systematic identification of savings opportunities within a category or department, improved demand management, and favorable long-term contract with suppliers and category management.
At the same time, it's also true that procurement organizations at all levels of performance share gaps in their procurement analytics capabilities.
We know you're probably wondering, "Do I really need to be using procurement analytics?"
The answer is yes.
What Is Procurement Analytics
Procurement analytics is the practice of collecting, analyzing, and reviewing data from various sources to identify trends, anomalies, and opportunities. When this is performed by practitioners, the process is called procurement analysis.
Organizations use it to make data-based decisions, mitigate risk, maximize value and predict future market conditions.
Often, when we see the word "data," our brains are immediately flooded with concepts of boring things like graphs and spreadsheets. But data doesn't have to be intimidating! When used correctly, it can actually be the key to understanding what your company needs to do to improve and thrive.
Data Sources Used for Procurement Analytics
Procurement analytics is a collective term used for all relevant analyses throughout the entire procurement process. Typically, this involves collecting and linking procurement data from different sources. Relevant data sources vary between businesses, but common data sources will often be:
- Data within the ERP (Enterprise Resource Planning) systems
- Invoices, bill of materials, and purchase orders (POs)
- Contract information
- Data from supplier information systems (e.g., supplier portals)
- Supplier assessments (e.g., quality, service, and delivery precision)
- Corporate social responsibility (CSR) and environmental impact
- Market information (e.g., market price/indices)
- External benchmarking indices
Once you have a good idea of what kinds of data sources are available to you, you can start collecting them in one central location. The easiest way to do this is by automating the process—this will save time in the long run and help ensure consistency across all spend data.
Once all spend data sources are collected in one place, they should be analyzed on an ongoing basis so that trends can be identified and acted upon accordingly.
Examples of Procurement Analytics
The purpose of procurement analytics isn't just to gather data; it's to gain insights that drive fact-based, smarter, and more sustainable decisions.
There are many different examples of procurement analytics, such as:
- Spend analytics—the analysis of procurement spend data from internal or external data sources.
- Supplier risk and performance analytics—analysis of risk, performance, and sustainability potential across the supplier base.
- Bid analytics—analysis of bids to determine the best price, value, terms, and least risky options.
- Contracting analytics—analysis of contracts, contract loyalty, and metadata.
- CO2 analytics—granular carbon tracking for industrial decarbonization.
- Savings analytics—analysis of opportunities, initiatives, and realized savings.
- Procurement benchmarking (price/rate/hours)—comparing organizational performance to peers or market benchmarks.
What Is Spend Analytics
Spend analysis, or spend analytics, is a simple concept: it's the practice of reviewing historical data to gain actionable insights.
The methodology is straightforward: you collect, cleanse, classify (or categorize), and analyze the spend in your organization. This can help you reduce costs, increase efficiency, improve supplier relationships, and much more. Spend analytics is a basic principle in strategic procurement and should be the foundation for every professional procurement function. It's an important tool for identifying savings opportunities, managing risk, developing procurement strategies, and implementing category management. Spend analytics also provides more transparency across the entire business.
As procurement becomes more mature and a strategic business function, spend analysis will play a key role in aligning all the various stakeholders in the organization.
Why Just Spend Analytics Is No Longer Enough and Why We Need Procurement Analytics
Like any good business, you need to be making smart decisions every day.
You probably have a whole team of people who are focused on spending time and energy on things that help your organization succeed: finding new suppliers, negotiating better deals with existing suppliers, and working to make sure everything gets delivered on time and without mistakes.
But what if there was a way to take all that time and energy you spend worrying about those details and put it toward something bigger? What if you could focus on the big picture instead of micromanaging every single order?
That's where Procurement Analytics comes in. Procurement Analytics is a tool that helps organizations track their spending habits and make better decisions based on what they learn. It provides real-time data about costs, timing, and quality so you can see how your business is performing across all departments—from sourcing through delivery. In short: it's data-driven decision making at its finest!
Types of Procurement Analytics
The thing about analytics is that there are different stages of maturity when it comes to how much data you have and how good at using it you are. Each stage gets more advanced than the last, so let's take a look at where most procurement departments fall on this spectrum:
- Descriptive Analytics: This first step involves collecting information from various sources (including ERP systems) to gain insight into past performance and identify trends across periods. This type of analysis may include things like annual sales figures or inventory levels over time.
- Diagnostic Analytics: Diagnostic analytics is done to understand the reasons behind current performances or, in simpler terms, to run correlations and identify why it happened. A perfect example of this type of analysis is having dashboards that provide drill-down functionality for deeper insights.
- Predictive Analytics: Predictive analytics is based on correlations or patterns to predict the situation to know when something will happen so that you can avoid it or lower its impact. An example of such analyses is adding rule-based calculations to datasets to reveal cause-effect relationships.
- Prescriptive Analytics: Prescriptive analytics is the process of using data and AI to predict future events and make decisions about what to do when those events occur. These types of analytics use prescriptive models to suggest decisions, actions, and implications so that you know what to do when something happens.
The Benefit of Analytics in Procurement
By applying analytics to myriad data points you already have, you'll be able to make better business decisions and do so more quickly. In turn, you'll increase cost savings while enhancing efficiency—something all companies are keen to do.
With analytics, you could, for example, use new insights to create:
- Improved foundation for decision-making and implementation of measures to save costs and time
- The most effective category plans
- Fair market pricing evaluations to maximize savings
- Better contract terms to improve compliance
- A streamlined supply base with fewer suppliers and a simplified supplier management process, thus ensuring reduced costs and standardized quality
- Supplier risk assessment to reduce your vulnerability to supply chain failure
- Analysis of consumption patterns to reduce overall spend
- Analysis of your preferred supplier compliance, contract coverage, and buying channel distribution to identify saving leakages
The Impact of Procurement Spend Analytics
In today's digital age, procurement is more than just buying stuff and getting it delivered on time—it's about driving cost savings, improving performance of the value chain, and making fact-based decisions based on data rather than gut instinct. And with tools like spend analysis, supplier risk and performance analytics, benchmarking, and savings analytics at your disposal, procurement can get all the visibility they need to make it happen.
With advanced analytics at their fingertips, procurement teams can use it to distinguish patterns in complex data sets and determine the significant drivers of price without human intervention. Given the exponential and measurable value advanced analytics delivers in procurement, organizations increasingly count on it.
The procurement analytics market is expected to grow from $1.6 billion in 2018-19 to $5 billion by 2025.
6 Procurement Analytics Use Cases to Meet Your Current Needs
Advanced analytics helps organizations gain a competitive advantage in procurement by providing better visibility to procurement teams across all functions. It typically reports on procurement KPIs such as lead time, procurement cost, ROI, spend leakage. In contrast, predictive and prescriptive analytics are deployed to predict procurement value chain events such as price forecasting and prescribe the best procurement strategy.
Procurement is one of the key protagonists in the success story of an organization, and over the decades, it has become globalized, specialized, and leaner. With the world turning into a global village, competition and opportunities intensify. As such, procurement teams can leverage analytics to gain an edge over the competition and the first-mover advantage.
1. Identify, Prioritize, and Realize the Best Savings Opportunities
With the rise of digital procurement solutions and Artificial Intelligence (AI), the need for an integrated approach to procurement is becoming increasingly apparent. This is particularly true in the case of cost reduction activities, which are often conducted in silos and without a holistic view of spend across the business.
For procurement organizations, the path to cost optimization can be attained by various means, whether by getting insights into commodity trends and payment terms opportunities to negotiating more favorable pricing rates with suppliers, or reducing contract leakage. The key to understanding where to reduce expenditures lies principally within an entity's spend analysis solution; it becomes nearly impossible to identify cost reduction opportunities without a comprehensive view of spend across the business.
a. Opportunity Assessment With Spend Analysis
Every company spends money every day on multiple things they need. But how much do you really know about that spend?
That's where opportunity analysis comes in. Opportunity analysis is a process that introduces a wider perspective by grouping spend, analyzing it by category or supplier, and looking for synergies, value-for-money, increased leverage, and other opportunities to improve procurement outcomes. One of the key benefits of opportunity assessment is the power of negotiation it brings when dealing with different suppliers.
A recent survey by the Chartered Institute of Procurement & Supply (CIPS) found that more than half of UK companies are using AI and machine learning to analyze their spend.
To unearth savings opportunities and identify savings potential, forecast spending needs, uncover spending anomalies, negotiate better deals, and control tail spend.
The possibilities for AI-powered procurement are endless: It could help you optimize your supply chain by applying predictive algorithms on historical data to analyze spending patterns over time and predict future trends; it could help you identify suppliers who offer value-for-money products or services; and it could help you find synergies between different areas of your business (like procurement or finance).
b. Reduced Maverick Spend With Contract Coverage Analysis
One of the most important things that companies can do to improve efficiency and reduce costs is to make sure their purchasing agreements and contracts are aligned with their needs.
But how do you know if they're aligned?
There are two ways to do it:
- analyze contract utilization across different categories and business units, or
- analyze agreement utilization trends.
By analyzing contract utilization across different categories and business units, companies can see how well their contracts match their needs.
Contract agreement utilization analysis can help identify opportunities to realign agreements and contracts with purchase needs. Insights into agreement utilization trends can be used to increase spend under management. This can help procurement identify opportunities to realign agreements and contracts as per the organizational purchasing needs.
c. Payment Term Optimization
Payment terms optimization is one of the most important areas where advanced analytics can be applied. The purpose of this type of analysis is to recommend the most appropriate payment terms which can be negotiated with suppliers to achieve a state of win-win. This can be done by analyzing all possible variables that impact the negotiation, taking into account all the stakeholders involved in this process and their different needs.
A good example of this is when you want to negotiate with a supplier for a new delivery schedule. You may want to consider offering faster payment terms, but only if the supplier agrees to give you more discounts or credit terms.
In order to find out which payment terms are optimal for your company and its suppliers, you will need to analyze data from previous negotiations and evaluate how different variables affect each other.
For example: how does it change if you offer more discounts or credit terms? How does it change if you shorten your payment period? Which one has more influence on your total costs?
d. Spend Benchmarking
Spend benchmarking is a great way to make sure your prices are competitive and fair. A lot of companies don't do it, but it can really help you stay on top of industry trends and make sure your suppliers are getting paid fairly.
Here's how it works: You look at how much other companies are paying for similar products and services and then see if you can work out a deal with your supplier that's better than the average. If not, then maybe there's something wrong with your pricing strategy!
You can use external benchmarking data for this analysis—but only if it's reliable. If not, then don't bother because it won't be accurate enough for you to use as an indicator for whether or not something is overpriced or underpriced.
2. Enhance Supplier Management and Reduce Risks
Here are some ways to make use of advanced analytics for supplier relationship management:
a. Reducing Supplier Risks
Combining machine learning models with third-party data analytics helps you identify risks associated with your suppliers that can help you avoid disruptions in your organization’s supply chains. Supplier risk management is one of applications of procurement analytics that can be used to understand which suppliers are better and thus, ensure an uninterrupted supply chain.
b. Supplier Negotiation Process
Closing a major contract can take months of negotiations and meetings, but having the right data with actionable intelligence can significantly decrease negotiation time for you. By making data-driven decisions on price limits and contract terms, you'll arrive at the negotiating table with a stronger sense of what you need to communicate to your supplier — and when to walk away.
c. Supplier Normalization
Supplier normalization is the process of standardizing supplier names. It takes place at the beginning of spend analysis, and it's essential to ensure that your spending is reported in a way that makes sense to you. By normalizing supplier names, you ensure that you are reporting true costs with a given supplier—and this means you are achieving maximum volume savings potential and managing the number of suppliers you work with.
Supplier normalization is also called supplier re-mapping or supplier mapping. The purpose of this process is to make sure that when we pull data from our ERP system, all supplier names match up correctly so we can compare apples to apples on our reports.
Supplier normalization is done by matching up supplier names as they appear in different systems. If a company has multiple locations, but only one address in their ERP system (like ours), then we'll have to find another place where they list an address so we can get both locations mapped.
If you're going to be doing any sort of analytics on your spend data, it's important to have a normalized supplier list in place. You can't compare apples to oranges, and normalizing suppliers helps you cross that hurdle. The benefits of supplier normalization include:
- Maximizing volume savings potential by matching purchases with the most efficient supplier
- Reducing costs by eliminating waste associated with duplicate purchasesBetter Category Management
3. Better Category Management
Category management is one of the most important responsibilities for procurement professionals. One of the key asks for category managers is to identify where to spend money and where to save—analytics can help with this.
Category analytics can help you understand what products and services are being purchased, how often they're being purchased, etc.
But what if you could go even further? What if you could analyze which products and services are being purchased by whom? Or which products and services are being purchased by particular departments within your company?
Category analytics drills through your data and helps you get these answers so that you can make smarter decisions about where you should be spending your money and where you can reduce costs without sacrificing quality or service.
4. Enhance Strategic Sourcing
We know you've got a lot on your plate. We also know that sourcing managers are responsible for conducting e-sourcing surveys and identifying what suppliers are worth targeting based on their performance, cost structures, etc.
This is where advanced analytics can be useful. The ability to quickly analyze large amounts of data has been a game-changer for businesses, allowing them to make better decisions faster than ever before.
One example would be using an advanced statistical technique known as regression analysis (or "regression"). Regression is based on the idea that there is a relationship between variables—in this case, between supplier performance and cost structures. It enables sourcing managers to predict potential cost savings by using historical data as well as other factors such as market conditions or changes in regulations.
5. Proactive Contract Management
Procurement teams can save time by keeping an eye on contract expiration dates with help from analytics. Tracking expiring contracts across global operations is a daunting task for many companies, not only because of the volume of work involved but also due to the complexity of the task and the high risk of mistakes.
Using analytics, you get the information you need to manage contract expirations. It can help you visualize contract expiration from multiple dimensions and get alerts delivered before expiration—making it easy for you to sense which contracts need attention.
In addition, by tracking which contracts have been renewed or extended, you can better understand your company’s needs and preferences over time and take advantage of opportunities when renewals are likely or expected.
6. C02 Emission Reporting Analysis
Carbon dioxide is a major contributor to climate change, and procurement can help companies reduce their carbon emissions. But for many organizations’ procurement departments are still stuck in manual processes and report emissions only annually. This is about to change, thanks to CO2 analytics technology that automatically performs calculations in accordance with the GHG protocol, freeing up organizations to report their progress and make a real impact on climate change.
The technology enables companies to measure and manage their carbon footprint throughout the supply chain, allowing them to set science-based targets (SBTs) and track their progress against these targets over time. By making use of CO2 analytics technology, organizations can identify which suppliers are most efficient at reducing their carbon emissions per unit of product produced or delivered.
With this knowledge at hand, you can then take steps toward becoming more sustainable by working with suppliers who have lower emission values than average—while continuing to work with those who are above average as well. Ultimately, this will help your organization meet SBT goals while also reducing costs through enhanced efficiency.
The Procurement Analytic Process: Step-By-Step
To generate savings faster than the competition, procurement teams should figure out an appropriate way to find, manage and maintain data. The challenge, however, is that data is not always easy to collect because it is usually spread throughout the organization.
Additionally, before calling the data ready for analysis, it requires thorough preparation, consideration, and consistency to be effective. As you devise your approach to procurement analytics, remember the following steps:
1. Identify and Collect Data
Procurement should work with internal and external parties to identify all data related to spending by the organization. Once these sources are identified, procurement should survey each area to ensure that it has access to all data necessary for effective analysis of how money is spent. Gathering spend data comprises the following sub-steps:
- Create a map of the systems that contain spend data. These systems might include your enterprise resource planning (ERP) system, e-procurement software, accounts payable software, and any point-of-sale terminals.
- Run a performance assessment to examine the completeness of the spend data and identify any missing information that might be required to create a detailed spend record.
- Assess the number, type, and usefulness of classification schemes used across your organization. Consider whether it makes sense to consolidate or replace underused schemes and whether you could map these schemes to an industry-standard scheme in order to analyze organizational spending.
- Examine how your organization manages and analyzes this data. Decide how you will access this data, what sort of reports you want to create, and how often you want to view the data.
2. Cleanse, Classify, and Categorize the Data
After collecting the procurement data, go through it and clean it up. Sort and group it, then categorize it. This will help you make sense of the data, allowing you to perform effective analyses.
- You should organize your data internally by creating your own taxonomy or by adopting an industry-standard classification scheme.
- A good way to start categorizing spend is by grouping spend at the category or supplier level. This can include breaking down purchases into smaller groups, identifying how many suppliers you're using for specific categories of goods and services, as well as how much you're spending on categories and suppliers.
- By using item- and line-level detail, you can view spending by each supplier and commodity on an organizational, departmental, project, and buyer basis.
3. Fill Gaps in the Data by Enriching It
If you want to give your company an edge, it's time to think about enriching your spend data.
There are plenty of ways to do this, but the main idea is that you're adding more information to the data you already have. For example, if you have an understanding of how much money your suppliers cost over time, you can add in some additional information about their performance and risk level. You can also add information about the terms of their contracts with you or any other related information.
This kind of enrichment will help you make better decisions about where your company spends its money, which is important for staying competitive and getting ahead in business.
4. Create Repeatable Data Management Processes
If you want to be at procurement excellence, you should try to make sure that your data extraction, classification, enrichment, and analysis activities are streamlined and repeatable.
To make this happen, you'll want to automate data cleansing and classification solutions by leveraging solutions that can deliver a turnkey procurement analytics service.
The second component is to incorporate your internal sourcing and commodity expertise into the automated system by utilizing software engine rules and self-learning capabilities.
Finally, you should look for ways to generate automated monthly reports of the most current spend data so that your organization's most current spend position is considered in new procurements.
5. Analyze the Data
So you've got your data all organized and cleaned up. That was a big step! Now it's time to dive in and see what you can find.
You know what your goals are, so let's start there. Ask yourself: what do I want to learn from this data? What questions do I have? How can I use this information to make better decisions for my company?
Once you've got some questions in mind, start looking at the data from different angles. Make sure to look at long-term trends as well as short-term ones.
Then look at long-term trends, compare data points and see how multiple factors may correlate. Use these findings to draw conclusions and take action. In addition, consider using visualizations to better understand trends and share results with your organization.
The analysis of spend data is one of the most important tools for supporting management decisions for the organization. Regular analysis of collected spend data provides better oversight of supplier relationships and helps to determine whether the current procurement structure, processes, and roles are adequate to support a more strategic approach to acquiring goods and services.
The power of advanced analytics in procurement is so great that it can help you not only to survive in the competitive market but also outperform your competitors.
Procurement analytics helps prepare a better strategy, provides better control, minimizes costs and risks, improves savings and ROI, evaluates alternatives faster, and offers intelligent insights into the market.
But the question companies ask often is: What analytics can we apply to procurement to improve the process and make our industry more efficient?
Of course, there are various methods of analytics that we can use. The key is writing the algorithms properly with a humble tack on data analysis. We think when procurement analytics is applied in a holistic manner and is not limited to certain areas but rather spread across multiple departments or incorporated into daily operations, the synergy created by merging historical data with real-time information can solve complex business problems like risk management, supply chain optimization, and demand forecasting.
Hence, procurement analytics is an innovation that is going to transform, revolutionize and completely change the way we think of procurement. The possibilities that these technological advancements will unleash and the sacrifices they will bring forth are going to be mind-boggling. Savvy organizations are already harnessing their potential to maximize productivity, efficiency, and profitability. Don't be left behind.