Five elements are key to making digital procurement a reality
With digital procurement, a company can dramatically improve procurement’s speed, agility, and efficiency. Digital procurement gives decision makers better visibility, reduces risk, and boosts compliance—ultimately increasing spend under management and driving more value for the business. But adopting digital procurement is a tall order. It requires what we call a “compound system of knowledge,” which encompasses five key elements that most procurement organizations struggle to fully implement or operate.
The main fuel for a digital procurement organization is data—and lots of it. Data underpins everything a company could do to predict the needs of people, know which goods or services are available to best meet those needs, determine which suppliers are the right ones, and identify the right price to pay.
But in most companies, procurement can’t harness the explosion of data available about suppliers, pricing, the market, and other key factors to make more informed business decisions. Traditionally, they only gather transaction information and, maybe, line-item data. They’re missing the contextual information surrounding purchasing decisions—especially the process data related to the steps they take to, for example, review and approve a requisition, set up a contract, or go through an RFP. They’re also not tapping into the vast range of important external and third-party data.
To build a true digital procurement organization, companies should consider an intentional strategy to capture far more data—internal and external—than they do today:
Everything the organization touches—not only in its sourcing process, but in any process generating data that’s relevant to procurement and sourcing. This includes invoice and payment data to understand compliance with price and process, as well as process information, such as who approved a price variance and for how much.
Data outside the organization, such as deep and broad category and market intelligence, which is arguably even more important. Such data are critical to developing the greatest insight into the TCO or pricing levers the company can consider when negotiating an individual contract. And it’s vital to understanding which is the right item to buy and from whom. But due to the sheer volume of relevant data available, this is an area where most procurement organizations are particularly deficient. It’s also a gap that’s really hard for any one company to close on its own.
The data procurement needs fall into two broad categories. The first is data that can be leveraged to create information that in and of itself has intrinsic value—for instance, a supplier profile, market overview, or descriptive analytics about the average price of a good or a service in a geographic market. The second is data that can be used to discover correlations between the characteristics of sourcing decisions and profit outcomes, and to build analytics-based predictive models and ultimately artificial intelligence. This is why a company should collect everything it can—the “x” that drives “y” in a model is not always intuitive or obvious.
If data is the fuel for digital procurement, technology is its engine. And by technology, we don’t mean ERP-type systems (in the cloud or otherwise) designed to support a process. Rather, we’re talking about technologies that harness and make sense of data—especially AI, natural language processing, analytics, and bots. By combining relevant data and these highly-advanced technologies, a company can automate and enhance a wide range of activities and processes—and, in some cases, go beyond simple automation to providing advanced intelligent support.
Think about plotting, on a two-dimensional matrix, every action and task that's executed in the end-to-end procurement process: Judgment complexity is on one axis and the degree to which the input to that task or that action is structured versus unstructured is on the other (Figure).
Automation versus intelligent support
Any activity or process that involves a high degree of both structured information (such as a supplier name, category, commodity code, discrete item description, or SKU number) and rules-based processing (“if X, then do Y”) can and should be automated to accelerate execution and improve efficiency. This is the domain of bots.
Here’s a simple example: Using Robotic Process Automation (RPA)—a.k.a. bots—a company can automatically, with no human intervention, convert a requisition to a purchase order when all required fields are complete and accurate. Some existing procurement tools already support basic automation, such as automatically validating and assigning category and general ledger codes.
On the other hand, when an activity or process is subject to a high degree of judgment and involves a lot of unstructured information, automation takes the form of predictive models and artificial intelligence that intelligent agents rely on to help humans make better, more informed decisions.
For instance, when determining which suppliers to use in a sourcing event or spot buy, an intelligent agent will apply a complex model based on the sourcing and buying history of the items being sourced, supplier ratings and performance, and recent supplier pricing to recommend—and eventually choose—the suppliers that should be involved.
The technology needed to use data in such innovative ways exists today. And as it matures, it will move to the heart of virtually all procurement-related decisions.
Intuitive user experiences
To fully benefit from digitalization of procurement, a company should provide an attractive, intuitive user experience that encourages stakeholders to use the online procurement tools. The more people who use these digital capabilities, the more effective they are in buying and the more data the organization can collect on specific transactions.
Without a compelling user experience, people will find a way around using the digital tools—whether by not buying something they really need because it’s just too difficult or time consuming, or figuring out another way to get it.
In digital procurement, the ideal experience is akin to that delivered by Amazon.com, Inc or HomeAdvisor, Inc: There’s a single dashboard or portal that serves as the starting point for every interaction, and that presents insights and information succinctly so the right decision or action is obvious to users. All the “messy stuff” happens in the background, far beyond the user’s notice. By using intelligent algorithms, the system can provide recommendations to users instead of forcing them to manually search a database. That’s much like how Amazon’s product recommendations minimize the need for customers to sort through Amazon’s offerings for other things they might want.
Skills and talent
There’s more to creating and operating a digital procurement organization than simply collecting more data and applying digital tools. Generating true value requires another key element: A cross-functional team of people with distinctly different skills:
Data scientists and AI experts who understand how to build and apply models to manipulate the data and tease out different correlations.
Category/business experts who can advise whether those correlations are significant or simply coincidences.
IT professionals who understand the technology tools and software applications, and how to integrate them to create a solution to a problem that actually adds value (not to mention how to incorporate them into the company’s existing IT infrastructure).
Design professionals who are adept at developing compelling experiences that make stakeholders want to use the tools provided rather than find ways to avoid them.
The fact is, procurement is encouraged to consider deep skills across all four of these areas and should combine them in ways that amplify outcomes. Investing in any one of them is not enough, nor is investing in all without a cohesive vision for how they work together to enable the digitalization journey. And this is an area in which most procurement organizations really struggle. Simply adding enough category and business specialists is hard enough. When you couple that with the huge challenge of finding and hiring qualified data scientists and technologists, it's easy to see that closing the talent gap is one of the biggest obstacles a procurement organization will face in becoming truly digital.
New policies and procedures and operating model
Digital procurement gives all stakeholders—company employees and suppliers—a new way to collaborate and interact, as well as access to more robust data and insights. But to fully benefit from these new capabilities, a company should review its policies and procedures and ensure everyone understands their roles and responsibilities in the new procurement process and how they can make the most informed decisions. It’s also likely a new or dramatically different procurement operating model will be needed to reflect the new ways of working.
The final post in the four-part will reinforce why your journey starts now.