July 26, 2021
Over the years, some of the most successful business decisions were informed by alternative data and artificial intelligence. Consequently, analytics has needed to expand its objective beyond simple analysis processes and visualization techniques. One stellar example includes the expansion and refinement of procurement analytics.
More specifically, procurement analytics refers to the process of collecting, filtering, and analyzing large amounts of internal and external cost-based data, with the objective of improving business performance and returns. The following sections break down the concept of procurement analytics, its importance in finance, and how businesses can leverage various data sources to improve their bottom line.
The concept of procurement analytics refers to collecting and analyzing data. But what exactly is procurement data? Procurement data, or cost-based data, includes purchase information, accounts payable, credit card expenditures, and any other information that is related to expenses involved in finished products or services. Analyzing procurement data helps the overall business decision-making process by providing meaningful internal financial insights.
According to a survey by Deloitte, analytics is one of the most powerful disruptive forces when it comes to procurement. It is also seen as the one area with the most substantial impact on business. Additionally, analytics is estimated to remain the most disruptive force in this field for the next ten years.
Analytics is a vital component of processing procurement data as it goes beyond simple spend analyses. In practice, businesses harness the power of analytics to improve operations ranging from sourcing to procure-to-pay processes and category management. When analytics is efficiently used in procurement, managers can identify savings opportunities, innovate, address risk opportunities, and prioritize suppliers, among others.
Some examples of how to use analytics in procurement include:
Generally, businesses now have access to heterogeneous data either from their internal processes or external sources. More and more companies use both sources to obtain powerful insights to make more informed business decisions internally and externally.
Internal procurement data refers to information created within the corporation. In some cases, procurement analysts use financial records (i.e., general ledger) or access data from different suppliers or business units using staple software, such as Excel.
External data refers to any type of information that comes from the outside of a corporation. For instance, readily available information, such as job postings data, social media comments, or LinkedIn profiles for your suppliers, qualify as external data.
In the era of big data, external sources of information can turn out to be invaluable for businesses. While internal data is limited to internal capabilities and the quality of information management of a given company, external data has the benefit of being virtually limitless.
For instance, instead of requesting your suppliers to provide more information regarding their risk profiles, which can be subjective, you can now collect and analyze relevant data from LinkedIn, gauge social media sentiment and brand perception. Some examples of how alternative data can enrich procurement analysis are listed below.
Many businesses may be challenged by the “build or buy” question when it comes to procurement. In general, the advantages and drawbacks of building spend intelligence and buying procurement analytics are common to other fields in which you need to decide on establishing your own or outsourcing business processes.
For instance, business spend intelligence requires data scientists who mine, visualize, and report data. When companies buy these reports, they are often out of date, and it is extremely challenging to keep the data fresh. However, this may be a cost-efficient way of having a quick view of procurement spend.
Another option is to opt for procurement analytics as a continuous activity in which your company has access to fresh, accurate datasets. Unlike spend intelligence, a self-made business reporting solution, procurement analytics requires you to enrich spend data. It is based on continuous data collection and interpretation, which leads to the discovery and timely communication of insightful patterns identified in procurement data.
One of the main benefits is that it is a continuous process, ensuring a fresh inflow of information that fuels your business decisions. It can also be customized to include numerous sources of information, including alternative data that refer to social media profiles. This can be costlier than a one-off reporting purchase, but your organization benefits from an in-flow of actionable insights based on fresh data.
There are numerous benefits of utilizing procurement data. It can be leveraged to improve the overall operational efficiency across your entire business. Some of the main advantages are:
There are four main types of procurement analytics processes. These depend on your purposes; for instance, descriptive analytics aims to provide you with a detailed overview of what happened in the past. You may better understand your past procurement performance and use this information to make future decisions and identify challenges or inefficiencies.
Diagnostic analytics is similar to descriptive analytics, but it purports to explain why something happened in the past. For instance, if descriptive analytics identifies a cost inefficiency in the past, diagnostic analytics helps you understand why the cost inefficiency happened. Then, you may be able to address the issue to improve future performance.
Predictive analytics is a process where you can use current data trends and patterns to forecast expected procurement performance. As a result, predictive analytics may help you test different business scenarios.
Finally, prescriptive analytics is based on predictive models that use procurement data. This type is used to facilitate business decision-making via data-driven insights.
Procurement metrics or KPIs (key performance indicators) provide you with quantifiable indicators that help efficiently measure performance. The ten most important procurement metrics and KPIs businesses should keep track of include:
1. Spend vs. budget
2. Spend under management (SUM)
3. The total cost of ownership
4. Cost avoidance
5. Cost savings
6. Exchange rate exposure
7. Average payment terms
8. Number of suppliers
9. Vendor performance
10. Price competitiveness
These KPIs can measure internal performance or be used as a benchmark for future procurement analytics processes. You may also use these to compare your organization with other competitors or industry standards.
It is important to note that while these KPIs have been proven to improve the bottom line, stakeholders and investors might not necessarily engage with these KPIs. If this is the case procurement KPIs might be an obstacle, as financial indicators may have different meanings for stakeholders.
One way to work around this obstacle is to provide stakeholders and investors with KPIs surrounding business performance as well as cost-based KPIs. All of this depends on your company’s objectives, industry, business strategy, and more.
In the era of artificial intelligence and big data, advanced analytics has turned out to be one of the most efficient, cost-effective ways to provide actionable insights for business decisions. When businesses harness internal data and up-to-date, high-quality alternative data, procurement analytics delivers information that can become an invaluable source of competitive advantage.
In all, by employing updated or new business strategies informed by procurement data, companies can improve business performance and create a strong supply chain that delivers continuous cost-efficient value while focusing on corporate social responsibility (CSR) and sustainability.
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