Organizations are turning to digital procurement solutions to access previously unavailable or unstructured data and get better visibility and control of their spending. But while these solutions have improved efficiency in making smart business buying decisions, many organizations are leaving some benefits on the table, particularly when it comes to using data.
Significant gaps still exist in the rich data many are collecting — for example, just 54% of organizations collect total spend data, according to research conducted by Harvard Business Review Analytic Services (HRB-AS). Many respondents to that survey want more from the digitization of their procurement processes and technologies than they’re getting now, including increased operational efficiency (72%), reduced costs (58%) and improved data collection and analysis (42%).
Top performing procurement teams — those making significant progress in migrating from tactical work to more agile, scalable and digitally enabled procurement operations — are gaining the most value from advanced analytics and visualization of their data, according to Deloitte’s 2023 Global Chief Procurement Officer Survey. These organizations demonstrate that the path to greater use of data on strategic sourcing, transactions and suppliers in procurement requires next-level analytics capabilities that enable predictive and proactive decision-making.
There are lots of things procurement organizations can do to close that gap and start generating actionable insights on their spend.
Digital transformation has accelerated across most organizations. In fact, it’s the second-most-cited procurement strategy by chief procurement officers studied by Deloitte.
However, many need to maximize the benefits of the new data. According to Gartner, “Current investment in procurement technologies skews heavily toward foundational technologies that ease core work,” but are less focused on investments in advanced next-generation technologies such as analytics.
Taking digitization to the next level means becoming more predictive and proactive with the data those platforms generate. Procurement organizations need the ability to:
Successful organizations are starting to supercharge their procurement by applying more profound analytics techniques across various procurement disciplines. Emerging procurement best practices such as spend visibility, guided buying and data visualization are helping them unlock the ability to:
You can’t manage what you can’t measure — or even see. Procurement analytics dashboards are essential to get a real-time overview of the who, what, why, where and when of spending.
This overview not only gives procurement organizations perspective, it also helps them better understand and manage spend. For example, seeing the total spend by a supplier informs negotiations with them. Sharing views with teams makes it possible to collaborate on reductions or find opportunities to save. Applying data visualization tools to this data promotes a deeper understanding of spend patterns in a way that’s more accessible to users.
When Pacifica Companies’ Pacifica Senior Living division began leveraging Spend Visibility across its 96 care communities through Business Prime (a paid feature), purchasing staff were able to make smart budgeting decisions, identify areas to improve compliance with purchasing policies and spot additional savings opportunities.
Machine learning is a perfect fit for tasks including identifying cost-effective alternative products, automating competitive bidding processes and streamlining and automating reconciliation.
According to Boston Consulting Group, “Using AI to automate decisions reduces redundant roles and frees up managers’ time for value-adding tasks.”
Another area where AI can help procurement is in improving the search experience and product discoverability for administrators and buyers. Features such as the AI-powered product recommendations found with Amazon Business can help organizations find the same or comparable items at lower prices or with discount availability.
Rogue and tail-end spend can wreak havoc on any budget. Guided buying and spend controls don’t just put parameters on those purchases, however. They can also ensure that spend supports enterprise goals, such as buying local or sustainably sourced goods.
Managing the purchases of a large, disparate workforce can be a complex task. But a card-based buying system meant to ease the burden was causing compliance, management and reconciliation hassles for the Seminole County Public School district and its 7,000+ teachers. Since utilizing Amazon Business’ Budget Management tool, teachers can now draw down on their pre-allocated supplies budget using a familiar, seamless shopping portal, bringing both convenience and control to the district.
Just 24% of respondents to the HBR-AS survey use the majority of the data they collect on suppliers in a way that aids decision-making. They recognize its importance; 54% of respondents consider the ability to change suppliers as one of their greatest challenges quickly. However, 31% rate their organization’s current ability to promptly switch suppliers in response to a disruption as poor or very poor.
Applying analytics to supplier data helps procurement organizations make more strategic decisions about supplier selection. For example, they can flag supplier compliance issues to minimize disruptions and save time. Machine learning can also significantly improve supplier evaluation and selection.
Pacifica Senior Living used supplier analysis to replace about 95% of the many disparate vendors it used across the organization with a centralized roster of suppliers. This not only enables the organization to leverage its buying power, but also helps the company scale up as it acquires new properties and operates its purchasing program far more efficiently.
The procurement analytics best practices discussed here can be accessed by layering third-party SaaS analytics on top of current procurement solutions to access deeper, more actionable analytics. Many of these emerging technologies work to enhance the value of legacy systems, involve minimal investment, have low requirements for integration and have payback periods measured in weeks rather than months.
Adopting digitization solutions has already begun producing essential procurement data for many organizations. But too much of the data they now collect needs to be better utilized. Layering next-level analytics applications on top of current solutions facilitates more proactive, actionable procurement decisions that enable the procurement function to deliver smart business buying solutions to organizations.
Originally published on Supply Chain Dive.
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