Why real-time enterprises outperform in an age of constant disruption. Explore situational awareness, edge AI and distributed architectures.
In recent years, we’ve seen a rise in the frequency and intensity of so-called “black swan” events - rare, unpredictable disruptions with far-reaching consequences. Think global pandemics, climate crises, or geopolitical conflicts, which shake global industries and markets.
Enterprises today face disruption at every level - from global “black swan” events to smaller, operational shocks we call “black cygnets” - localised events that may not make headlines, but can have significant business impact if organisations lack real-time visibility and decision-making capability. This article explores why real-time situational awareness, AI at the edge, and distributed architectures are becoming critical capabilities for enterprises operating in an unpredictable, AI-driven world.
It’s created a challenging environment for enterprises, but it’s not just the global disruptions that can leave them blindsided. Smaller-scale, more localised events - such as last-minute supplier failures, critical machine breakdowns, or transport disruptions - can also have major operational impact. These are the “black cygnets” that test an organisation’s ability to respond in real time.
Adding AI and GenAI into the mix as they upend business models, introduces another layer of complexity to an already challenging enterprise landscape.
How can enterprises thrive in an environment where the sands are constantly shifting?
In today’s fast-moving world, strategy and planning are crucial but it’s impossible to plan your way through it all. Enterprises must be agile to make rapid, tactical in-the-moment decisions as situations evolve. There’s never been greater pressure to respond in real time.
Drawing inspiration from military strategy, it’s all about the OODA loop: Observe, Orient, Decide, Act. Whether in combat or business, those who create a faster and tighter OODA loop will be the winners.
As enterprises generate more and more data at greater speed, the only way to stay ahead is with a tight, nimble OODA loop that can adapt to any situation to drive the next best action, enabled by automation and AI.
Imagine a retail manager responding to a sudden surge in demand, or a field engineer making decisions based on instant insights from remote sensors to stop a critical wind turbine from breaking down: this is true situational awareness for real-time decisions.
The most successful enterprises are sensing and responding to critical events in real time, unlocking new levels of speed, efficiency, and growth.
According to a recent survey by the MIT Center for Information Systems Research (CISR) of 250+ global enterprises, those excelling in real time are seeing impressive results with 62% higher revenue growth and 97% higher profit margins compared to those in the bottom quartile.
They also experience 22% better operational efficiency, 20% more innovation, and 17% stronger risk management. While these figures might not be as staggering as the headline results, for the enterprise they reflect more than just resilience, they suggest a new level of agility.
Real-time businesses automate processes and empower employees to make instant, informed decisions based on trusted and up-to-date data. But real-time responsiveness isn’t just about handling disruption in the moment: it’s also about unlocking new possibilities for growth, innovation, and resilience.
From black swans to cygnets, real-time businesses aren’t just surviving; they’re thriving by turning challenges into opportunities.
The MIT findings make for compelling reading, but if real-time performance is so powerful why isn’t every enterprise operating as a real-time business?
The key challenge is that enterprises are inherently distributed in terms of people, assets, and data while operating in an increasingly connected world.
Critical operational data is no longer just in the cloud; it’s out in the field (sometimes quite literally) e.g. across wind turbine farms, retail stores, supply chains and manufacturing plants.
And in our digital world there’s a staggering amount of data. IDC, a global market intelligence firm, predicts we’ll generate over 200 zettabytes globally in 2025, soaring to 500 zettabytes by 2029. To put that in perspective: 200 zettabytes = 200 followed by 21 zeroes - a number so vast it defies easy comprehension!
The scale of data should be an opportunity to gain smarter insights, but in reality, it brings many challenges. As data flows in from many distributed sources, sending it all back to be processed in the cloud can’t meet the latency and storage demands of real-time operations. Privacy and compliance considerations of moving data across borders or entities brings a further dimension to the challenge of harnessing all your data for true situational awareness.
That’s why real-time responsiveness demands a different approach - one that moves data processing and intelligence closer to the action.
To operate in real time, enterprises need new approaches, architectures and technologies to take the next leap in real-time business performance.
But when your data is spread across thousands of devices, sensors and other distributed assets a question arises: if my data is everywhere, shouldn’t my AI be everywhere too? If enterprise data is distributed across cloud, edge and operational environments, then AI must also be deployed across cloud and edge architectures to enable real-time responsiveness.
The answer is adding distributed and edge computing as a complement to cloud. For real-time responsiveness this is how enterprises can deploy their AI right next to where the data is generated, and the action is happening.
Imagine a manufacturing plant with critical robots on the assembly line: detecting a machine failure before it happens to avoid costly unplanned downtime requires analysing sensor data instantly.
It’s clear that to be truly real-time, enterprises must also take AI to the edge. But if the winners are real-time businesses, why isn’t every enterprise tapping into this potential?
The path to real time brings many considerations including:
To move forward, enterprises need expertise to navigate these challenges to successfully go from idea to practical execution.
Winning enterprises are increasingly defined by their ability to sense, decide and act in real time - turning situational awareness into measurable business advantage. This requires more than cloud adoption, it demands distributed architectures, AI at the edge, and a continuous OODA loop that enables fast, accountable decision-making in the face of constant disruption.
This area of innovation is moving fast. You can’t plan it all out as a traditional transformation programme - but you can move stepwise with purpose.
The key is to start small, learn fast, and iterate. Apply the OODA loop not just to operations, but to transformation itself: observe your environment, orient around business goals, decide on your next step, and act quickly.
At New Icon, we help enterprises to leverage AI everywhere to get on the real time journey and go from idea to execution - fast.
Whether you're tackling operational inefficiencies, looking to unlock new revenue streams, or navigating your transformation journey, we work with you to build your future – at whatever stage you’re at.
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