As the C-Suite looks ahead to how to use artificial intelligence and cognitive automation to manage their supply chain challenges, many insights can be gained by examining how their businesses were affected during the COVID-19 crisis.
Businesses experienced extreme drops and increases in supply and demand that placed strain on current technology, and drove many executives to explore greater investments in risk management due to the unpredictable flux.
While the digital transformation was well underway before the world shuttered due to the pandemic, the volatility and need for immediate action in order for enterprises to remain operational pushed that pivot into high gear.
In order to meet the demands of their customers, businesses need to be able to reinvent themselves at a rapid pace, and utilize creativity in the marketplace. Additionally, their supply chains need to be agile, resilient, and much more responsive.
In the past, many businesses have utilized machines to automate physical tasks, which gives the muscle of the supply chain to technology.
Currently, the automation of intelligence-based tasks is being utilized, which gives machines tasks that would typically require the human brain. Actions like creating rules, planning, and forecasting are being conducted by machines, which frees up people to engage in important value-based tasks.
Looking ahead to the future, businesses will adopt automation from the end to end of their supply chain, allowing for vast data storage, fast planning, rational decision making, and real time adaptation to meet the increasing demands of consumers.
With cognitive automation, businesses transition from people doing the work supported by machines, to machines doing the work, guided by people.
Cognitive automation allows businesses to address the change in scale, complexity, and pace of decision making that are now required to be competitive. The challenge of dealing with simultaneous signals, and the need for more frequent, rapid, and real time decisions is easily managed.
Cognitive automation delivers both automation and augmentation of the brain, memory, and decision making process, along with all the complexities, combining the best of humans and the best of machines to help businesses scale.
In the future, supply chains will no longer be a chain, but rather, a circle, with the customer at the center, adapting to their needs in real time.
Cognitive automation allows businesses to do three important tasks when it comes to supply chain management. While the traditional process of finding balance between supply and demand are still valid, cognitive automation supports a different way of viewing the process, allowing businesses to bypass their current lengthy and time-consuming process to quickly take action.
Transitioning the supply chain to cognitive automation is a journey, moving from a siloed approach, which has been largely inaccurate with limited visibility, to a harmonized approach, offering end-to-end visibility and enriched external data in real time.
With full cognitive automation practices in place, supply chain demands are both predictive and prescriptive, with operationalized decisions, and automatic and real-time self-adjustment, replenishment, and fulfillment.
The hardest leap for the enterprise is the moving from the traditional silo approach to the integrative model because it challenges cultural issues and the way the enterprise has been structured.
Once businesses are able to make the paradigm shift, the ability to take advantage of these technologies can come quite rapidly.
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