Procurement analytics has been a hot topic among supply chain and procurement professionals for several years. Indeed, in 2019, Deloitte’s annual CPO survey focused heavily on the topic. And, the research revealed that 59 percent of CPOs believed that procurement data analytics would have the biggest impact on their business over the next two years.
Fast forward to now, and each subsequent CPO survey touched on the topic. Unfortunately, challenges abound and progress in procurement analysis is slow. Admittedly, world events play a role. As organizations adapted to circumstance, priorities shifted and digital transformation plans accelerated. So, while the resulting widespread adoption of procurement technology makes data collection more accessible than ever, few organizations are taking full advantage.
Performing procurement analysis has always been a part of the procurement profession. However, the sheer volume of information now available is understandably intimidating.
In this blog, we’re going to offer an easy-to-understand overview of procurement analytics. We’ll cover key definitions, benefits and common challenges. Finally, we’ll provide tips for how to get started.
Procurement analytics is the outcome of collecting, comparing and reviewing procurement data from various sources to identify trends, anomalies and opportunities. When performed by practitioners, the process is called procurement analysis. Organizations use procurement analysis to make data-based decisions, mitigate risk, maximize value and predict future market conditions.
Common types of data analysis used by procurement
While there are countless ways to use procurement data, what type of analysis you use depends on what you’re hoping to accomplish. The four primary types of analysis are: descriptive, diagnostic, predictive and prescriptive. Procurement services company Sievo provides these helpful descriptions.
Descriptive analytics – when procurement data is analyzed to describe what has happened in the past.
Diagnostic analytics – where procurement data is interpreted to understand why something has happened in the past.
Predictive analytics – where trends and patterns in data are used to forecast future procurement performance.
Prescriptive analytics – where predictive models based on procurement data aid decision making.
Data sources used for procurement analytics
Procurement data can come from dozens of sources. Indeed, both internal and external systems can provide helpful information. To start, explore your internal procurement technologies first. Then, explore which external data sources will help you meet your goals.
In some organizations, procurement analytics don’t inspire any excitement because the potential benefits are too abstract. This hesitation is understandable because no two businesses will have the same data sets or needs. It may be helpful to think of analytics as questions you can use data to answer.
Questions procurement analytics answer:
Which categories represent the largest spend?
What is the ROI per category?
How often are goods and services delivered on time?
What are the trends in payment terms?
How many suppliers provide the same goods or services?
Which vendors have raised their prices most often?
With the answers to questions like these, you can make decisions with confidence. The 2021 Deloitte CPO survey puts it like this:
“Analytics is arguably the most straightforward way for CPOs to add value at the proverbial table by providing better decision-making support for stakeholders and better supporting Procurement transformation using analytics-created insights and intelligence.
It can be a powerful tool to help “connect the dots” between strategy, integrated business planning (from forecasting to downstream supplier management), scenario planning (linking into complex sourcing events and extended networks), supplier collaboration/ innovation, and risk management.”
Recent request management research indicates that 70 percent practitioners consider cost reduction one of the most important ways to measure procurement success. Luckily, procurement analysis can uncover new ways to save. For example, effective analysis can reduce maverick spend, optimize category management and support supplier base rationalization.
Procurement analytics benchmark key performance indicators (KPIs). With the right data, you can optimize processes and make incremental improvements that highlight the value of your expertise. It’s also worth noting that professionals with procurement analytics skills are in high demand.
Improve risk management
Gathering procurement and vendor risk information is vital to protecting your organization. Procurement analysis can help predict supply chain changes, pinpoint single-source items and monitor the financial stability of key suppliers. In addition, data-based decision making helps eliminate the risks introduced by human bias.
Support company initiatives
As organizations seek to align their procurement strategy more closely with big-picture goals, procurement analytics offer a way to track progress, monitor results and predict outcomes. For instance, gathering and analyzing vendor diversity data can ensure ROI and help the organization further optimize their diversity spend goals using data.
Procurement functions that benefit from analysis
For many procurement managers, analytics are crucial. Gathering and reviewing data provides insights and directs action. Without these procurement analytics, managing these areas is a high-stakes, trial-and-error guessing game.
The focus of spend management analysis is to examine and optimize how the company spends money. In particular, spend data categorizes direct vs indirect spend, benchmarks spend to budget and identifies buying patterns. Ideally, this analysis leads to more strategic spending.
Spend analysis answers questions like:
What percentage of our spend is with diverse suppliers?
Is our organization’s maverik spend increasing?
Can we reduce indirect spend without damaging productivity?
Which categories represent the largest spend?
Many people think that once executed, a contract requires no further attention. However, contracts play an important role throughout the lifecycle of a vendor relationship. Indeed, contracts are full of important data that should be extracted and analyzed. For example, contracts contain useful information like: agreement type, payment terms, renewal terms, expirations, deliverables, service level agreements, contact information and more.
Contract analysis can answer questions like:
What contract terms work best for our business?
Is there a seasonality to our contract renewals?
Are we taking advantage of volume discounts?
Within procurement analytics, a huge amount of data comes from or deals with suppliers. For instance, what is the first step in selecting a new supplier? An RFP, which gathers dozens of data points to help you make the perfect vendor selection — and that’s just one example. Additional data comes from supplier scorecards, quarterly vendor risk assessments and vendor profiles.
Supplier analytics can help you answer questions like:
How many suppliers provide similar goods and services?
How often do we award a contract to an incumbent vs a new supplier?
In today’s procurement technology landscape, there’s a solution designed specifically to each of these topics. Your team may use one tool for spend management, another for contract management and have yet another solution for strategic sourcing. In this best-of-breed approach, it’s important to consider how data from each system can be used together to be even more powerful.
The 3 steps in procurement analytics
Unfortunately, procurement analysis doesn’t happen with the flip of a switch. Certainly, like most things, it requires preparation, consideration and consistency to be effective. As you plan your approach to procurement analytics, remember these three steps: gather, organize, analyze.
The first step in analytics is to gather your data. First, put together a list of data sources. Use the examples above to get started. Then, determine how you’re going to collect the information. To be most effective, all of your data should come together into one central database. Next, start exporting. Ideally, you have a procurement analytics platform ready to go. But, even if you don’t, you can still practice manually using a spreadsheet (more on this later).
Now, you’ve got your data in one place, but it looks like chaos. Don’t be discouraged, this is totally normal. The next step is to clean, organize and enrich your data.
If you’re ready to go all in on procurement analytics, you may consider hiring a procurement consultant to help clean and categorize your data. But, if you’re just getting started, fix what you can and take note of which systems or users produce dirty data. Take the opportunity to establish data standards with your procurement team to make future analysis faster.
Once your data has been cleaned and organized, it’s time to dig in. Determine your goals and ask questions. Then, see how the data can give you answers. 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.
Facing common procurement data challenges
While the potential of procurement analysis is promising, admittedly, there are barriers to progress. Historically, organizations viewed data as a byproduct of technology rather than a core benefit. Consequently, it’s unsurprising that few businesses have the necessary organizational foundation to make the most of their information. However, as executives turn their focus to optimizing operations, investments in procurement analysis are sure to follow. Before businesses can begin to benefit, they’ll need to overcome a few common barriers.
The first (and many argue the biggest) challenge, is that far too many procurement processes are still done mostly manually. Manual processes result in lost data. For example, requesting information from vendors using email, spreadsheets and Word documents make gathering the resulting data difficult.
Every RFX, security assessment, vendor risk assessment and vendor performance evaluation is full of data. But, when performed without the benefit of a request management system, the data is likely inconsistent, incomplete and unclear.
Overcoming this obstacle isn’t easy, but it’s worth it. Investing in technology that centralizes processes and data is crucial. It’s also important to consider how individual procurement technologies integrate with one another.
Finally, many technologies come with out-of-the-box reporting and analysis capabilities. So, if your organization is slow to invest in new technology, explore how you can use existing systems for analysis. Then, you can use the results to share insights or identify gaps in functionality that will help you build a business case for new tools.
Even if you have a highly-customized, fully-equipped procurement technology stack, data quality may still be a challenge. And, unfortunately, analysis based on bad data leads to risky decisions.
There are numerous reasons why your data may be unreliable. Unfortunately, one common denominator is human error. Luckily, improving the quality of your data is manageable. With user engagement, education and process training you can inspire incremental changes. In addition, making data review a regular priority rapidly improves dependability. Procurement data specialist company, The Classification Guru, puts it this way:
“The secret to keeping your procurement, supplier, and spending data clean is just like good housekeeping—it needs to be checked and maintained on a regular basis. In the same way you give your carpets a regular once-over with the vacuum, regularly maintaining your data makes life easier in the long run. Remember, the more data you have, the more frequently you should check it.”
Lack of vision and investment
Time and money — it’s what most of these challenges come down to. While procurement managers may champion better data analysis, they need buy-in from executives. Alternatively, CPOs may make procurement analytics a priority, but teams often lack the training and resources to effectively implement change.
The inability to move beyond the moment and see the future can hold people back from understanding and getting excited for the possibility of data. But, the promise of leveraging big data in procurement will eventually take hold. So, it’s important to do everything you can now to ensure you’re prepared when your organization decides it’s time to invest.
Quick tips to help you get started
Embrace technology now
As mentioned above, technology is a huge factor in procurement analytics. So, don’t wait to explore new technologies. Make a business case focused not only on the problem that solutions solve, but also on the potential for the data it can collect. Remember to consider internal reporting and integrations before every purchase.
Leverage the data you already have
Explore your existing data and technology. Apply the three steps of procurement analysis to the data sets you already have: gather, organize, analyze. The time spent investigating your data will almost certainly yield insights.
Additionally, when you have a question that your existing data can’t answer, make a note. What data do you need to find that answer? How could you take action? What are the potential benefits to your business? Keep a list of these questions and reference them when discussions of analytics arise.
Level up your analysis
There are so many incredible resources available for anyone curious about procurement analytics. So, go explore. Make time each month (even just an hour) to research the latest in procurement-specific topics like AI and machine learning, new external data sources and services, and analysis training.
The 2021 Deloitte CPO survey also noted that there’s a need for procurement practitioners with analytics experience.
“In terms of skills, the biggest skill gaps are those related to using digital tools such as analytics to leverage data to influence and collaborate with stakeholders.”
When it comes to procurement analytics, if you wait for a perfect system or time, you’ll never get started. At the end of the day, some analytics practices are better than none. A recent study from NC State University survived executives and explains the importance of starting now saying:
The executives we interviewed described significant challenges in constructing reliable and trustworthy analytics for stakeholders, due to a lack of systems. But it was also rare to find organizations that have achieved a high level of spend data integrity across all of their business units. The message is clear: procurement must seek to build analytical insight in the absence of perfect data, and be able to leverage “whatever data is available”.