Predicting The Next Supply Chain Disruption

I just lately had the chance to ship the keynote at Demand Driven Technologies’ Global Conference 2021, which targeted on the applied sciences dashing up our provide chains, and sure, we’re certainly coming into a brand new period of enlightenment on this subject. At the time, in late March, a big freighter ship was bottling up the Suez Canal, and I puzzled out loud whether or not provide chains have sufficient intelligence constructed into them to alert and predict the impression on company operations.

Advanced analytics and synthetic intelligence can play a key function right here, in fact, however these are nonetheless the early days for super-intelligent provide chains. The newest survey simply launched by the American Center for Productivity and Quality, for one, finds solely 13% of executives foresee a serious impression from synthetic intelligence or cognitive computing over the approaching 12 months. Another 17% predict a average impression. A survey by Capgemini additionally discovered considerably lukewarm progress in introducing AI into provide chain administration. Only 11% of executives in that survey say that they had applied superior analytics and AI inside their provide chains.

The occasion of occasions over the previous 12 months has been the Covid disaster, which examined provide chains to their max. In the method, the learnings coming from this disaster and the convergence with analytics means a brand new wave of innovation and startups, business leaders and thinkers agree.

“The pandemic is testing supply chains in a manner few have seen in our lifetimes, with businesses struggling to predict demand and keep factory lines moving,” says Sudheesh Nair, CEO of ThoughtSpot. “Businesses need better visibility and the ability to pivot quickly when a crisis arises. AI and data analytics are central to the new model, allowing organizations to spot disruption sooner, accurately gauge its impact, and make intelligent decisions about alternative sources of supply.”

Nair cites geospatial analytics that use satellite tv for pc imagery, cellphone pings, and different information sources “to detect activity on the earth, such as when plants are closing or cargo ships are held up at ports.” Companies can apply AI to this information “to determine if its suppliers will be able to keep up with demand, so it knows quickly if it needs to look for alternatives.”

The Covid disaster additionally sped up the urgency of constructing extra intelligence into provide chains. “We have been surprised by the acceleration of innovation, especially in the supply chain, despite all the ways the pandemic is making it difficult to predict what’s going to happen next,” says Melanie Nuce, senior vp, company improvement at GS1 US. “However, those businesses that are exploring emerging technology today are the ones recognizing that the pandemic exposed major challenges with moving products to the right place at the right time. They can’t waste another minute using antiquated systems that do not allow for flexibility to keep up with the consumer’s shifting behavior.”

Of course, constructing an clever international provide chain requires the trade of knowledge, which must constant and reliable throughout all continents. “Collaboration based on global data standards can engender greater levels of trust in data by acting as a reliable anchor,” Nuce advocates. “This will be a major focus as brands, retailers, restaurants, and other partners prepare for the predicted influx of spending and traveling after Covid restrictions ease. One of the greatest opportunities moving forward is to use emerging technology to better understand, sense, and respond to consumer behavior. With a combination of technologies, such as analytics, AI and machine learning, so much can be achieved to proactively form relationships with consumers, personalize experiences, and expedite how we fulfill orders.”

Businesses “need visibility into their supply chains — and the global factors that influence them — to compete effectively,” says Dr. James Crawford, CEO and founding father of Orbital Insight. “Supply chain visibility remains largely a manual process based on incomplete, unreliable data. Companies piece together information from news services, social media and word of mouth.” Crawford sees the alternatives throughout the making use of of AI to a number of sources of geospatial information. “With answers to critical questions about production, pricing and distribution, businesses can anticipate change sooner and take informed action.”

An organization can make use of AI expertise “to improve the traceability of raw materials along its supply chain,” Crawford provides. “By analyzing delivery patterns, Unilever monitors signs that suppliers are struggling to keep up with demand and checks their financial health to quickly look for alternatives.”

AI “is the most impactful technology in this equation,” agrees Nair. “Applying machine learning to data produces real-time insights, which are critical when reacting to fast-moving events. For example, applying AI to data from social networks and global newswires can help to quickly identify where and how fast a disease is spreading, the severity of local political unrest, or the impact of a climate event such as flooding. These real-time insights buy valuable time in which companies can make critical sourcing decisions to offset supply chain disruption.”

Nair additionally sees functions of AI “to model prices, which has been a particularly tough process during this pandemic, though an intelligent pricing strategy that accounts for real-world conditions is essential even outside of a disruptive event. In a pandemic, a trade war, or another anomalous event, using AI and data to accurately model pricing is even more critical.”

Another aggressive device rising within the post-Covid growth is stronger business collaboration. “I believe this has to do with the increasing emphasis on trust,” says Nuce. “For example, CTOs, CIOs, and other innovation executives are shifting from centralized data models to distributed data. This leads to questions like, ‘who can see my data?’ ‘How accurate is the data I receive?’ ‘What protocols will be in place to authenticate data when more automation is introduced?’”

The Covid disaster “is a widespread shared experience and it’s become very apparent that consumers want to be informed and they want to be in control,” provides Nuce. “Innovators will be focused on leveraging technology and structuring data to facilitate these options.”

Lean stock has been a mantra for many years, however the Covid disaster “has overturned this structure and exposed its weakness against major disruption,” says Nuce. “Even beyond the pandemic, rapid changes in the environment and economy are increasing the frequency and magnitude of supply chain disruptions, necessitating a crucial overhaul to how they are structured. To be able to quickly recover from issues like material and resource scarcity and limited visibility and traceability is key to long-term survival in an increasingly competitive next normal. To ignore the need for greater flexibility would be detrimental to a company’s performance and ability to connect with consumers.”


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