Sign up for our newsletter and get the latest big data news and analysis.

Procurement Turns to AI to Navigate Supply Chain Upheaval

In this special guest feature, Ophelia Otto, scoutbee Industry Relations Lead, discusses AI technology can bring a business operation like procurement from the stone age to the modern age by allowing teams to rely on automation rather than placing all bets on little black books and outdated spreadsheets. Ophelia works primarily on the development of technology, end-to-end procurement processes, and master data management implementation. Ophelia has more than 18 years of prior experience at a variety of companies including Microsoft and Chain IQ Group developing global business intelligence frameworks.

The COVID-19 pandemic may have halted many business processes, but the pace at which companies are now implementing digital transformation has accelerated: Microsoft’s CEO discussed two years of digitization in two months back in April, and not to be outdone, Accenture’s CEO noted their organization saw three years of transformation in three months. And while digital transformation has been one of the en vogue terms of 2020, its importance is not new. 

When thinking about digitization, it is crucial to ask: what change will bring the most value with minimal interruptions and future-proof my organization to ensure future success? When China closed its borders in the early days of the pandemic, it became clear that global supply chains and procurement operations were incredibly vulnerable to disruption and ripe for change. However, fewer than 50% of large, global companies are using artificial intelligence (AI) and machine learning (ML) to support procurement efforts. 

Analog procurement in a digital world

The primary reason sourcing has had trouble integrating AI and ML is that procurement leaders have traditionally relied on longstanding relationships with a few vetted suppliers and their personal network. Moreover, getting the full picture of even a single supplier’s operations often requires mapping a complex web of global supplier sub-tiers—an expensive, time-consuming endeavor. This is not to discount the importance of strong supplier relationships, but during a crisis, the lack of transparency and flexibility often built into these relationships can be even more costly, as recent events have demonstrated. Now, procurement and supply chain leaders need to rethink their approach to data, AI, and ML, in order to build a more resilient, diversified supplier network. 

Supplier Discovery

AI’s first major impact on supply chains will be broadening the pool of potential suppliers, meaning there could be thousands relevant for a sourcing demand. Procurement relies on “little black books” of contacts largely because it simply is not tenable for one person (or even a large team of people) to vet the entire market of potential suppliers, especially not in the face of seemingly simple human barriers like language. In a crisis, most procurement teams want to default to rapid but risk-aware sourcing, meeting with more suppliers than they usually would. Manually—without ML—this process is so onerous that it is not done unless there is a crisis. Specially, supervised ML can screen millions of suppliers in 24 to 48 hours, leaving organizations well-prepared for what crises lay ahead. 

Risk Mitigation

If an organization waits until a crisis to create agile processes, it is already too late. The COVID-19 pandemic was the latest—and most severe—global event to disrupt supply networks, but it will certainly not be the last. Logistics teams are actively working against any number of trade barriers from disease, to geopolitical moves like trade wars and tariffs, to natural disasters, and research suggests the number of disruptions will keep going up, averaging a 36% yearly increase. By integrating AI based global search technologies into procurement, enterprises have a multitude of suppliers to choose from and can quickly and easily pivot to well-vetted secondary or tertiary suppliers when the geopolitical norms change, rather than struggling to find those sources amidst a crisis. The AI does the heavy lifting—understanding the parameters and requirements for a given supply chain, building a long list of suppliers to meet those needs, and whittling that list down to the best choices, leaving the final vetting and decision making to those who do it best: people. 

Cost Optimization

Introducing AI into procurement efforts is not cheap, but the cost of not doing so is even greater. In the face of the pandemic, supply chains lost days or weeks to production delays which can add up significantly in lost revenue. Tools like AI and ML not only augment people to focus on what they do best, but also make operations better by doing the work people can’t—meaning organizations work with more efficiency during normal times and react more nimbly during times of crisis. 

Vital processes need vital technology

For a process so vital to major enterprises’ revenue and growth (even Apple, which owes its status as the world’s most valuable company to its unrivaled supply chain, has not been spared by the pandemic), AI and ML often are not available for supply chain teams. This technology can bring a business operation like procurement from the stone age to the modern age by allowing teams to rely on automation rather than placing all bets on little black books and outdated spreadsheets. 

Sign up for the free insideBIGDATA newsletter.

Comments

  1. I enjoyed your article.

    Joseph A. Yacura
    M.B.A., M.S., M.Q.M.
    Founder International Association for Data Quality, Governance and Analytics
    http://www.IADQGA.com

Leave a Comment

*

Resource Links: