Predicting the future has always been the purview of sci-fi and fantasy, but in the real world, it also used to be a lot easier. Extreme disruptions used to be as rare as a black swan — the most notable in recent history being the blockage of the Suez Canal by Ever Given.
Cue the present day: Black Swan events are just about the only dependable factor in planning around complex systems anymore. Relying on traditional tools and approaches in the face of rapid and interlocking changes won’t cut it.
Businesses need a new type of solution that grows and adapts with the times.
In the supply chain world, we’re turning to cognitive automation, which is the digitization, augmentation, and automation of decision making, to more quickly react to an ever-changing environment.
Enterprises need to collect massive amounts of historical and real-time data, analyze it at scale and nimbly advance recommendations for quick turnaround decisions.
By applying both software and domain expertise, we can solve problems that help get everything from food to raw materials to consumer goods where they need to be: into the hands of the people who expect to receive them on time and in full.
Perfect data and processes, of course, don’t exist, no matter how large or small your industry or business footprint. But you don’t need to have everything perfectly mapped out to take advantage of cognitive automation.
The most important factor is a willingness to sidestep the inherent rigidity of traditional supply chain systems and see undiscovered paths within the bigger picture.
No artificial intelligence could have warned us about flooding in Germany, a block in the Suez Canal, or a global pandemic. Still, while you can’t avoid risks, you can minimize their impact by quickly adapting to circumstances as they arise, no matter how large or small.
The solution: a platform that gives global visibility into not only the state of your organization and supply chain, but also external information that could impact your ability to deliver, from market signals and supply risk to weather and logistics, to inform your decisions.
By analyzing a diversity of large, dynamic data sets, machines can recognize an event earlier and react faster. Cognitive automation can triage recommendations, which can then translate from a mathematical model into real-world action.
While AI is increasingly being used to augment analytics and inform recommendations, the ability to operationalize these models is still a challenge. An ideal platform tightly integrates the ability to utilize these models in a business context, linking them to processes and policies and automatically executing the decisions made in the underlying transactional systems.
Having this end-to-end process on a single platform allows for future automation of decision making, which will free up humans for the creative discovery work that suits us best while improving our ability to respond to complexity with better, more complete information.
A cognitive automation platform should work with, and not against, existing platforms and transactional systems to improve decision making without “breaking” what’s already in place and working sufficiently.
When we can quickly assess our options and determine the best path forward, we’re doing more than serving our customers. Since supply chains are dynamic systems, we affect our inputs whenever we enact a decision about them. Redirecting a cargo ship or sourcing inventory from another country isn’t a neutral choice, especially when it comes to inefficiencies and material waste.
Given how much energy and how many resources supply chain management requires, in this case, automated micromanagement can actually have a measurable, positive and self-reinforcing impact, not just on bottom lines but on economies and climate — two enormous factors in globally escalating black swan events.
Cognitive automation, while transformative in nature, does not require a transformation of your underlying technical infrastructure. It does not, or should not, require time-consuming and costly changes to technology infrastructure and processes.
A cognitive automation platform should work with, and not against, existing platforms and transactional systems to improve decision making without “breaking” what’s already in place and working sufficiently.Given the continuous change that is happening today, a company can’t wait years to transform. You should expect agility to be achievable in weeks.
In the end, technology is here to serve human capital, not replace it. By focusing on augmenting and automating decisions, cognitive automation ultimately increases the decision-making capacity of the organization. Even before worrying about black swans, many decisions were left unmade.
A computer can quickly pull together vast swaths of data from sources you didn’t know you needed and entertain innumerable combinations of outcomes. By using a cognitive automation platform, every decision has the potential to be made.
The business of prediction has always been fraught. It’s also an exciting frontier for technologists and for businesses themselves.Whatever the state or size of your problem, cognitive automation, artificial intelligence and advanced analytics can offer actionable solutions for the world we live in now.
That means counting on being surprised and prepared — as well as ensuring a path toward real-time responses to even the wildest black swan.
This article originally appeared on The NewStack and is syndicated here with permission.