30 November, 2020
Artificial intelligence (AI) is redefining the human experience. As businesses digitally transform, they increasingly look to AI to perform cognitive functions that have traditionally required human intelligence such as pattern recognition, learning and problem solving. With AI, businesses are able to streamline processes, increase efficiencies and make faster, data-driven decisions.
Amazon has built its own business on applying AI to improve customer outcomes, optimise selection and revolutionise logistics. AI-enabled innovations like Alexa voice service and Amazon Web Services (AWS) cloud computing technologies are already changing everyday lives and accelerating growth for businesses.
A business’s procurement function is often one of the last to digitally transform. Procurement is rich with data, and that means AI and machine learning (ML) can be especially impactful in helping businesses save money, manage supplier risk and meet customer demand with speed and agility. But some companies, especially those that are smaller or tech averse, believe AI-powered procurement is out of reach. Amazon Business wants to change that. As AWS does for cloud computing, Amazon Business democratises AI-powered procurement for any business or public sector organisation, applying Amazon’s machine-learning technology to a purchasing solution.
As you develop your own technology roadmap, consider the following five ways AI and ML are helping businesses save time and money and learn how Amazon Business is applying AI to help reshape the procurement process.
Analysts are tracking organisations’ use of AI and ML in procurement and are noting the transformative effects. In the past, to evaluate procurement data, companies would need to invest in experts such as business intelligence engineers, data scientists and IT professionals to create complex analytic models from the data. Today, ML technologies can analyse large amounts of data quickly and provide strategic insights that management can use to define and direct strategy.
For example, Amazon Business Spend Visibility is a machine-learning analytics tool available to qualifying Business Prime members. Powered by Amazon QuickSight, Spend Visibility analyses purchasing data to learn and track an organisation’s buying patterns. The tool provides data visualisations managers can use to make budgeting decisions, locate compliance issues and optimise savings. Procurement managers don’t need to be an expert to take complex data and use it to inform strategy.
In their 2020 survey of procurement professionals, WBR Insights found that 76 percent of organisations believe their ability to develop strategic insights based on AI-powered analytics is either “advanced” or “above average.”1
The survey, sponsored by Amazon Business, also found that in addition to developing insights, AI and ML give procurement professionals more time to execute on the opportunities they identify. Collecting, analysing and drawing insights from data becomes less labour intensive. Sixty-two percent of organizations were able to use AI or ML to reallocate time they would have spent on manual processes related to strategic-level planning.1
Procurement professionals are turning over routine and repetitive processes to AI and using ML to optimise spending on both strategically sourced and non-strategic, tail spend supplies.
For strategically-sourced items, organisations employ AI to automate competitive bidding. AI can execute repetitive bids, which helps to increase sourcing speed and secure better pricing.1
For commonly purchased, non-strategic or tail spend supplies, ML can automatically identify preferred products or similar items in Amazon Business’s online store, helping purchasing managers find cost-effective alternatives.
As AI and ML reduce the time required to identify, purchase and reorder supplies, procurement professionals can spend more time on strategic sourcing or other high-value activities.
Many organisations restrict what, where and from whom employees are allowed to buy. Ensuring compliance to company spending policies can be time consuming and is another area where intelligent technologies are simplifying procurement.
AI and ML can assist with supplier evaluation and selection by analysing and flagging potential disruptions in the supply chain and automatically recognizing compliance issues among potential suppliers, minimizing disruptions to operations and saving time.
AI can also assist with guardrails and restrictions around what employees are allowed to buy. Guided Buying allows managers to turn procurement policies into easy-to-follow visual signposts built directly into the shopping experience. The tool steers employees toward the products or suppliers chosen by management and away from restricted suppliers or product categories. Notifications appear on relevant product detail pages and in search results that can include custom messages or show alternative product options when available.
Guided Buying makes it easier for employees to stay compliant and lets management spend less time evaluating purchases and enforcing rules.
AI and ML have long been used in personal shopping to provide a curated buying experience through personalised recommendations, product discoverability and merchandising. Those same capabilities are now transforming business purchasing.
Machine learning gathers data from an individual’s onsite behavior and order history—and on Amazon Business, applies industry-specific parameters and guidelines set by management—to present curated search results and relevant recommendations. And because the system is continually learning, the buyer’s experience improves over time, driving process efficiencies and employee satisfaction.
Unmanaged tail spend can represent as much as 20 percent of total procurement spending and it continues to be especially challenging for large organisations. For tail spend purchases, employees are more likely to go rogue, buying outside of approved channels and creating a blind spot for management.2
As businesses begin to experience the benefits of personalisation at scale, there's a reduction in rogue spending and an increase in control over tail spend. Eighty-two percent of business buyers say they want the same experience when they buy for work as when they’re buying for themselves.3 Traditional procurement systems are less likely to offer a user-friendly experience. When management shifts tail spend purchasing to approved channels that provide an AI-powered, personalised user experience, employees are more likely to purchase from the approved channel where management can control and track spending.
A recent sponsored report from IDC references Amazon Business customers for whom a better user experience is reducing rogue spend and leading to greater visibility and control for management. Multinational food and beverage company Mondelēz reduced lead time from 25 days to 4 days for tail spend items due to better service, easier processes and easier discovery of better-priced products.
According to WBR Insights, eighty-two percent of organizations plan to adopt a cognitive procurement model within the next twelve months or already have one in place.1 As AI and ML play a more significant role in procurement, we can expect to see greater productivity, agility and faster growth.
Though only forty-five percent of organisations have seen a positive ROI from their investments into AI and ML, procurement professionals are optimistic. Sixty-six percent of respondents to the survey by WBR Insights believe ROI and value creation will be the area of their strategy most impacted by cognitive procurement capabilities.1
AI-powered procurement presents an opportunity for procurement leaders to elevate their position and drive strategic value. For organisations of any size, investment in intelligent analytics and automation technology can be as simple as getting starting with Amazon Business.
To learn more, download “Cognitive Procurement and the Implementation of AI and ML.”
1. “Cognitive Procurement and the Implementation of AI and ML.” WBR Insights. 2020.
2. “Overcoming Procurement Challenges in the Age of AI and Digital Transformation.” IDC. 2020.
3. “State of the Connected Customer,” Second Edition. Salesforce.