Behind the Scenes, AI Is Making More Business Decisions Than Ever

Aera Technology is a Business Reporter client.

At some of the world’s largest companies, decision intelligence is filling gaps in knowledge and headcount—and saving millions of dollars in the process.

A pharmaceutical company that manufactures medical devices recently deployed a decision intelligence platform to deliver near-real-time order updates and proactive communications to its customers. 

For those familiar with the customer experience provided by leading online retailers, where delivery dates are readily available, this may not seem like a big deal. But, by analyzing data from numerous supply chain sources, decision intelligence is providing this manufacturer with the same kind of information for complex, build-to-order products. 

Similarly, an integrated steel manufacturer uses decision intelligence to ensure that customer orders are fulfilled on time and in full. By automating routine decisions, based on data analysis, the system automatically responds in real time to make sure the company keeps its customer promises. Again, these decisions are made with data sourced from across the company—not only inventory, but all the way upstream to logistics, manufacturing and inbound supply. 

These are real-world examples from companies that have adopted decision intelligence—the digitalization and automation of decision-making at an enterprise level using artificial intelligence (AI) and machine learning (ML) technologies. Decision intelligence is transforming business processes companywide by enabling decision-making at the speed and scale required to remain competitive today. 

AI and ML fill the gaps in decision-making

From line-of-business managers to the C-suite, the demand for business decisions exceeds the supply of people, actionable data and time required to make them. Decision intelligence helps fill knowledge gaps, revealing decision-making opportunities that increase agility and save money. 

There’s also a gap in predictability. Just-in-time methods and established processes have been unable to efficiently adapt to a flurry of recent crises and challenges: natural disasters, Covid-19, labor shortages, reduced shipping capacity, high demand for materials, the war in Ukraine and rising inflation, among others. 

Even as businesses face knowledge gaps, many experienced workers are retiring or changing jobs and leaving with the valuable skills and insights they gained during their careers. They are often replaced by younger hires who don’t have that institutional knowledge and may not stay in positions for as long as their predecessors did. The Great Resignation follows years of companies asking more of employees in almost every job role—a trend complicated by the pandemic and shifts in how and where people work. 

Employees have more decisions to make than ever—and much less time to make them. The volume, velocity and complexity of decisions in every part of an enterprise have increased to levels that can obscure opportunities for efficiency. 

Finally, there’s the customer experience gap, as businesses frantically try to fulfill demand for goods and services from customers trained to expect rapid service. Workers are frustrated if they don’t have the data or the time they need to work more efficiently. And consumers are frustrated by a lack of action from companies on core issues such as environmental sustainability, diversity, equity and inclusion. 

These gaps push us beyond any metaphor we’ve used in the past—“black swan,” “perfect storm,” take your pick—to an inflection point where businesses must evolve the way they make decisions in order to survive. 

The “killer use case” for enterprise AI and ML

Decision intelligence fills these gaps by doing what data lakes, predictive analytics, robotic process automation and digital control towers can’t do on their own. These solutions can leverage AI and ML and create faster, smarter and more intuitive tools that help analysts, planners, buyers and others find answers. But we’re still expecting people to do the work when there are too many decisions to make and not enough time. 

Digital-native online retailers figured out early in their journeys that to deliver e-commerce at scale, pricing and inventory management decisions had to be automated. The massive shift from brick-and-mortar retail to online ordering and rapid fulfilment was made possible because of systems that were built from the ground up to provide the data and insights needed to deliver that experience. 

Decision intelligence is a game changer because it opens the door to a high level of agility for businesses without a rip-and-replace approach or a time- and resource-intensive transformation process. Unlike those digital natives, many businesses today still rely on a tapestry of siloed legacy systems—some on-premises, others in the cloud—for planning, procurement, distribution and other critical functions, with each system presenting its own challenges. A decision intelligence platform complements existing planning and transaction solutions by ingesting data from them and creating a closed loop. 

That’s why decision intelligence is the “killer app” for the enterprise, leveraging AI and ML technologies to go beyond surface data, analytics and simple process automation. 

At the companies mentioned above, decision intelligence has transformed how workers use technology: Instead of people using machines to make decisions, AI is making decisions with guidance from experienced people. 

Decision-making at the speed of business

Decision intelligence represents a crucial change from the way business decisions have been made for decades. When experienced, knowledgeable employees are no longer struggling to keep up with an ever-increasing list of decisions with ever-shorter windows of opportunity, the nature of their roles is transformed. 

At companies that have leveraged decision intelligence, workers are spending less time on repetitive and transactional activities. They are now increasingly able to focus on value-added areas such as strategy and collaboration—taking proactive steps instead of reactive ones. This transformation will shape their future career choices as employees choose companies that give them the tools to be more creative and effective. 

As organizations shift to the new paradigm of decision intelligence, they’re finding new opportunities to be agile and to innovate. Leaders can move from asking questions such as, “What routine decisions can we automate?” to more transformational ones, such as, “Where could real-time decisions help transform our customer experience?” or, “Where do we have to make 80/20 tradeoffs with our time, resources and focus?” By helping leaders think more strategically, decision intelligence is allowing companies to benefit from opportunities that would have gone unaddressed or unseen without the aid of technology.

Learn more about how decision intelligence is driving business outcomes by reading the latest white papers from Aera Technology.

— Fred Fontes, Head of Growth, Aera Technology

This article originally appeared in Business Reporter.

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Author image: Courtesy of Aera Technology