Automated Procurement in 60 Seconds
Is the solution to disruptions, rising costs and talent shortages at hand? Gary Wollenhaupt walks us through Automated Procurement technology and its vast potential.
Given the challenges of today’s supply chain, procurement organisations search for ways to get better results and drive company performance. Technology-enabled procurement offers a path to overcome rising costs, material and labour shortages.
The numbers can be bleak. Semiconductor issues have caused $210 billion in losses for the auto industry alone. Supply chain disruptions cost companies $184 million per year. Global talent shortages will lead to $8.5 trillion in lost revenues by 2030. Organisations have no hope of breaking the pattern of crippling disruptions if they continue conducting business the same way.
Realising the promise of automation in procurement could deliver significant improvements and lead to surprising innovations.
However, procurement pros may fear the goal of automation is to downsize their department, but that’s rarely the case. The objective is to transform the procurement organisation in order to drive business performance. By automating repetitive tasks, the procurement staff can focus on high-impact decisions instead of managing purchase order changes.
Taking a Lesson
Procurement technology is becoming increasingly automated. A new autonomous commerce revolution leverages AI and machine learning to an enterprise commerce network that works as you’d expect a large freighting enterprise to work, but for B2B buyers.
The Enterprise Commerce Network is a self-governing B2B commerce experience between buyers, suppliers, things (IoT) and partners. More than half a billion dollars’ worth of goods flow frictionlessly through the network every year! The system leverages AI and machine learning to provide enterprise buyers and suppliers smart-match recommendations that align buyer needs with supplier capabilities. The system autonomously executes many repetitive, behind-the-scenes tasks required to facilitate enterprise commerce.
The intelligent procurement solution uses AI and machine learning to deliver product recommendations, which brings together enterprise buyers looking to reduce supplier risk and suppliers looking to grow their revenues. The consumer-style buying experience moves decision-making closer to the business process owner for much of the discretionary spend.
RPA is on the Way
Other innovations, such as source-to-pay transformation enabled by AI and RPA, help supply management organisations build efficiency while freeing up staff for strategic work. Online reverse auctions can fully automate the procurement process for some commodities.
Robotic Process Automation, or RPA, has been one of the fastest-growing automation trends, growing to an estimated $7.1 billion market by 2025. Businesses of all sizes are adopting RPA because it’s one technology that seems to live up to the hype. Research shows that AI-enabled supply chains are up to 60% more effective, with lower overall costs and risks.
RPA is less sophisticated than full-on artificial intelligence. The Institute for Supply Chain Management defines RPA as “A form of business process automation technology based on metaphorical software robots (bots) or artificial intelligence (AI) programs primarily, but not exclusively, targeting repetitive or data-intensive tasks.
Types of Process Automation
The Institute for Supply Chain Management breaks down process automation into three types:
- Enriched Process. The underlying process remains the same but benefits from access to data analytics.
- Augmented Process. Guides and informs human decision-making but still requires human intervention.
- Autonomous Process. Replaces human intervention for all or part of a current process.
Companies consider adopting RPA to improve processes and workflow, raise productivity, and direct workers away from mundane tasks like data entry to more strategic efforts.
In purchasing departments using manual methods, buyers may have to comb through thousands of lines of a spreadsheet purchase order to update quantities or other parameters and send the supplier new information by phone, fax or email.
Using RPA tools, companies can make PO updates directly, reducing the need for manual handling and ensuring orders are up to date. More sophisticated systems employ artificial intelligence and machine learning to drive prescriptive analytics.
Smart contracts could update terms or payment information across all affected contracts, consistently and simultaneously. Using blockchain, smart contracts could provide a high level of confidence in the integrity of the information and other parties involved in transactions.
Over time, artificial intelligence or predictive analytics will provide information about order quantities and timing based on signals it has learned. It could give an early warning if weather or consumption patterns change or even execute orders on its own.
Artificial intelligence is the power behind many online reverse auctions, in which buyers post a request and suppliers bid to win the contract. With the automated process, buyers don’t have to pursue multiple quotes. The process helps determine the best market price. The auction can include other parameters such as quality and delivery requirements, so it’s not focused solely on price. Some auction tools use RPA to initiate auctions and invite suppliers to participate without a buyer’s input for a fully automated negotiation process.
The idea is based on the Nobel Prize-winning work on auction theory, which Google has used to auction advertising space. It’s a transparent, market-driven negotiation suitable for many procurement categories.
Where to Begin the Automation Journey
To get started, experts recommend focusing on transactions with manual steps in the procurement process. AI tools can ingest and process invoices for accounts payable and emails with more information to process payments automatically. Once trained properly with customer data, the AI tools have shown to be up to 99% accurate.
For many companies, the most challenging obstacles are developing and implementing data management systems to support automation. Simply implementing an ERP is not adequate if the data is not organised properly to support the analytics. Most current solutions require a taxonomy or structuring data so that the software can understand it.
Further in the future, automated systems will be able to tap into unstructured data, using it for insights regardless of the format, such as weather reports or social media posts.
The pandemic experience alerted many companies to unknown risks in their supply chains. They lacked visibility into sub-tier suppliers and transportation details. Automation can aid in mapping the supply base to support risk segmentation and supply chain traceability.
Tracking discretionary spending is more effective, and what-if scenarios to support spend assessments based on business case variables.
More work needs to be done on fundamentals before companies can embrace automation. Organisations that have grown through mergers and acquisitions may be using multiple systems that don’t work together very well, with different data formats. They have bolted on systems rather than settling on a comprehensive solution. Spend assessments are necessary before the AI can execute the plan. Contracts must be digitised before they can be managed via blockchain. Automation can deliver a comprehensive view of risk variables, but much of the inputs are located in disparate systems, such as regulatory and compliance, finance, cyber security and business continuity.
With advancing technology, there will be fewer human touchpoints in the purchasing process, but the touchpoints that remain will focus on high-value transactions and relationships.
As ongoing disruptions raise the stakes, procurement professionals can lead the way to ensure their organisation doesn’t fall behind the curve.