By Akhilesh Tripathi, global head, Digitate
Procurement professionals in the manufacturing industry provide a crucial service: they purchase the goods their organizations need at the right price and the right time. Manufacturing could come to a standstill without the needed raw materials, so procurement pros are worth their weight in gold for that reason alone. Yet they also provide for the goods and services needs of the entire business, as well.
As manufacturers set up procurement policies, they must consider their procurement team’s years of detailed experience. Otherwise, blind enforcement of generic policies may result in people finding ways to go under the radar. Purchasers sitting within their silos make isolated purchasing decisions based on their experience alone rather than the collective experience of the enterprise. In addition, there are always some who try to game the system.
Procurement needs oversight and management, but caution is advised. Though tighter controls may yield more efficiency, they’re not necessarily the solution because they invariably restrict business agility. To accelerate procurement without compromising efficiency, manufacturers need to empower people to make quick purchasing decisions without losing control over how the money is spent.
AI in Procurement
One of the things that makes procurement so hard is the quality of intelligence available on purchase transactions. It is dated by the time it is received, leaving little or no time for any kind of interception or guidance. Part of this intelligence is derived through traditional analytics, which employ a slice-and-dice approach to analyze data. They help understand the spend distribution over a period of time and identify opportunities for optimization.
Such analytics are helpful, but only to a point; they can’t see deeply enough to discover the patterns of buying behavior that may need to be probed, encouraged or stopped. Intelligence is also derived from subject matter experts or consultants who analyze the spend distribution and provide advice based on industry benchmarks and best practices. However, they fail to drill down to a transaction level and provide specific recommendations.
Because there are now massive volumes of procurement data being generated, it’s virtually impossible to analyze it all to truly understand what’s happening. Purchase transactions have patterns hidden deep within them, some of them good and some bad. These patterns reveal the nuances of buying behavior, and they constantly evolve. The problem is that you don’t know what they are upfront. Hence, you cannot define any rules to detect their occurrence. That is why traditional slice-and-dice approaches fail – and why AI is so helpful.
Procurement needs greater visibility into its data, and AI provides it. AI can auto-discover patterns in purchase transactions that look odd using algorithms and then highlight them to humans. It can observe and learn which of those patterns are accepted by humans as worth monitoring through feedback loops. It can then use this knowledge to detect and predict anomalies in live transactions, allowing humans to intercept and take timely action. That’s when the procurement function starts to become cognitive.
Exceptions to the Rule
Exceptions abound in procurement. Some adversely impact spending because of avoidable price variance, some impact the cost of operations because of avoidable delays and some are non-compliant with procurement policies. Exceptions can be positive as well, such as transaction sets that are always compliant and never result in price variance or delays.
Getting to the heart of an exception requires finding an outcome that defines the exception and then identify a set of influencing factors that could produce it. The outcome could be price variance, which is the difference between the price quoted in an invoice and a standard price at which the item might be bought. There could be any number of influencing factors behind such an exception: business unit, plant, buyer, supplier, item, time of the year and more.
When the procurement process includes AI, in addition to other influencing factors, helps you define such an outcome. This can also help predict likely exceptions ahead of time. Sophisticated algorithms then take over to crunch a purchase transaction data set and discover patterns that require inspection and are presented to humans with transactional evidence. Such a virtual procurement expert would be able to compute and present a financial impact of every identified pattern. Then human procurement experts can validate these patterns.
By creating a human-AI team in the procurement department, you could learn what drives other types of exceptions, such as transaction fallouts, mavericks, anomalies or the unavailability of a purchase order against an invoice.
How AI Benefits Procurement
Procurement professionals need to move quickly to enable business growth, and AI empowers them to operate at such speed and with greater efficiency. When a layer of intelligence is always at work, organizations can continuously monitor and guide people to make the right decisions based on the organization’s collective experience. Exploiting hidden opportunities to optimize spend by identifying and eliminating maverick transactions produces an efficiency boost. Similarly, working with AI helps to eliminate different types of exceptions that would otherwise cause a drag in the process and increase the cost of operations.
Compliance is a key issue that benefits from AI, as well. Rather than making people comply with a generic set of policies, the application of AI allows procurement teams to become more sensitive to real business needs. It enables them to continuously engage with people on the ground and help them make the best choices within their constraints while staying compliant. For those trying to game the system, AI acts as a deterrent and reduces instances of non-compliance.
AI as a Growth Agent
Manufacturers rely on their procurement teams to keeps the wheels of business running. They have amassed detailed knowledge about many goods and suppliers, but the benefit of that knowledge can be diminished by slow processes. AI can speed up those processes by taking on repetitive tasks and freeing the staff to focus on the procurement data that AI provides. In this way, teams can make better decisions that enable business growth and greater agility.
About the author
Akhilesh Tripathi is the global head of Digitate, a software venture of Tata Consultancy Services. He has been a driving force since the venture’s inception and is critical to global revenue generation and service delivery. Previously, as the head of TCS Canada, Akhilesh drove the Canadian entity to be among the top 10 IT services company in its market. His 23-year career with TCS also includes his role as the head of enterprise solutions and technology practices for TCS North America. In that role, he led the management of strategic alliances with software vendors, and participated on the advisory councils of several strategic vendor partners.