Continued pressures from supply chain disruptions, COVID-19 outbreaks and rising inflation are forcing business leaders to re-think their operations to cut costs. Business negotiations are an untapped source of value that can help Fortune 500 companies optimize their business processes while driving bottom-line value.
Artificial Intelligence (AI)
The global COVID-19 pandemic put supply chain management and procurement in a very bright and positive spotlight for keeping life moving as normal as possible during all the shutdowns, disruption and general uncertainty.
It also highlighted that business and supply chain disruption are ongoing facts of life – such as ongoing extreme weather events globally and a megaship blocking the Suez Canal for weeks, to name just two. And the impacts created a snowball effect on other industries:
Global businesses have now spent nearly two years navigating the various challenges of the pandemic. Although some of the fallout was predictable, the dramatic impact we have witnessed on the global employment market was more unexpected. Companies that were already adjusting to new ways of working now find themselves in the middle of arguably the worst employment crisis in modern history—a phenomenon known as the Great Resignation.
What Does a Data Driven Supply Chain Look Like?
The key to improving any system is information. A data-driven supply chain is built around this concept, leveraging big data and analytics to improve processes at every level of the supply chain. A wide range of technologies contribute to this, from interconnected IoT sensors to warehouse robots and everything in between.
The public’s imagination has been heavily shaped by science fiction, with the term AI evoking images of robots like WALL-E, C3PO from Star Wars and David from Stephen Spielberg’s movie A.I. Scientists and technologists refer to this kind of humanlike AI as “general artificial intelligence.” General AI attempts to mimic the kind of abstract thought and typical problem-solving skills seen in humans.
Supply chain disruptions continue to drive up prices and lead to a growing shortage of goods across the U.S. and abroad.
Over the last few years, we’ve seen artificial intelligence (AI) being used for a host of procurement applications, from spend analysis to supplier risk monitoring. Now, the same technology is increasingly being applied to commodity forecasting.
In the right situation, this can provide invaluable insights. AI makes it possible to look at larger, more complicated data sets over a longer period of time, helping to improve the accuracy of predictions and supercharge decision-making, near real-time.
The COVID-19 pandemic has jolted digital transformation into overdrive, with technology adoption enabling businesses across industries to accommodate remote work and operations. But now more than 18 months into the crisis, businesses that source globally remain ensnared by rampant order delays, factory lockdowns, persistent transit challenges, rising costs and debilitating mass shortages.
While everyone around the globe has become aware of the focus on diversity and inclusion, not everyone has embraced or welcomed it. Some are deliberate and vocal about expressing dislike of these necessities at work, school and in our communities. Others are quietly against it but raging inside, rallying against diversity and inclusion, both consciously and subconsciously.
Keith Hausmann, Chief Revenue Officer, Globality, explains how the AI revolution is transforming the way companies source complex categories – typically services, delivering faster, better decisions; more autonomy for stakeholders; and greater opportunities for procurement professionals to drive innovation.
Think about utility poles, Mohan Tatikonda is saying. He’s a professor of operations management at the Indiana University Kelley School of Business, and for over 30 years his research has focused on how firms can most effectively design, develop, introduce and improve products, services and organizational processes.
And though “think about utility poles” sounds like a strange request, he’s getting ready to talk about the future of work and how people and machines can benefit each other.
Just like in spend data classification, the definition of tail spend is subjective. Some organisations classify tail spend at the bottom 20% of spend, while others might set a financial level such as £100,000 or £1 million.
According to CIPS, tail spend “can often be referred to as rogue spend or maverick spend, is usually small value purchases that are conducted by the organisations outside of a contract and often outside of the awareness of the procurement team.”
Manufacturing growth has skyrocketed over the last few decades, but the industry continues to lag in growing its most important asset: its people. A spike in retirements, paired with a drop in analytical leaders entering the field, is creating demand for procurement and supply chain talent that far outpaces supply.
Email management is a bigger challenge every year. In 2019, business email accounted for more than 128.8 billion emails sent and received per day, according to the Radicati Group. Adding to the challenge, many emails never make it to the right business account because they are sent to bulk accounts like email@example.com or firstname.lastname@example.org.