Connecting the Dots with Decision Intelligence

CIO Journal - Wall Street Journal

Twenty years ago, business leaders could occasionally take a moment to breathe before deciding on their next course of action. Companies typically formulated five-year business plans and worked steadily toward those goals; major disruption was relatively infrequent.

Today, of course, that’s all changed. Advanced technologies, elevated consumer expectations, and a range of political, economic, environmental, and social factors have transformed the business landscape. Disruption is continual, and decisions must typically be made immediately, if not sooner.

“With the massively increased complexity of this digital world, leaders need agility and scale to keep up with digital-native companies,” says Fred Laluyaux, president and CEO of Aera Technology, which provides a cloud platform designed to enable companies to develop, deploy, and manage decision intelligence at scale across the enterprise. “There’s been a dramatic acceleration of the speed with which decisions need to be made and a corresponding jump in the need for intelligence and accuracy.”

Here, Laluyaux and Sid Patil, a principal with Deloitte Consulting LLP, discuss enterprises’ heightened decision-making needs in this modern era and how decision intelligence can help.

What is decision intelligence, and how does it differ from more traditional approaches to business decision-making?

Laluyaux: Fundamentally, decision intelligence aims to enable the digitization, augmentation, and automation of decision-making for faster execution and better agility. Decisions such as how much raw materials to order, how to allocate inventory, or how to price and promote products, for example, all depend on getting the right data, trusting that it’s accurate, and applying the right logic to execute quickly. Despite millions of dollars in investments in data lakes and other technologies, this is often still a challenge. Many organizations rely on bespoke apps, phone calls, and emails to make their decisions, but that’s just not fast or accurate enough anymore.

With decision intelligence, the software collects the data, applies decision logic digitally, and either executes automatically or presents recommendations to a human operator, much like in a self-driving car. With velocity and scale, decision-making is no longer constrained by people—you can make 10,000 decisions a day if you have to—but humans can be in the loop for the high-value, strategic decisions, which typically account for roughly 20% of those that need to be made. In the meantime, the technology captures all the decisions made and learns from them to get smarter over time.

What’s driving the need for a new decision-making approach today?

Patil: Over the past few years, driven in part by the global pandemic, the number and complexity of decisions enterprises need to make has gone up exponentially. Yet companies often continue to rely on simple dashboards and large spreadsheets to make them. Many decisions now expire before someone even has a chance to gather the right data from across silos and interpret it for action.

Where in the organization can decision intelligence be applied, and what are some of the top benefits?

Laluyaux: First and foremost are the customer service benefits to be gained from heightened agility and the ability to make intelligent decisions in real time. By improving customer service, many companies can improve their top line and achieve cost savings. Another part of the value of decision intelligence is that it not only helps organizations improve the decisions they’ve been making all along in supply chain, finance, and other areas, but it also allows them to start making decisions they haven’t been able to tackle before. For example, what if I could connect my media and promotions planning decisions with my supply chain decisions, so that when I run a promotion, I know ahead of time that when the promotion is live, the product I’m advertising will be physically available in the regions where the ad will be seen? For big consumer packaged goods companies, those have traditionally been separate processes, creating the need for large safety stock inventories and other risk-sensitive measures. Connecting the dots that are not connected today is where the exponential value of decision intelligence lies.

“Many organizations rely on bespoke apps, phone calls, and emails to make their decisions, but that’s just not fast or accurate enough anymore.”


Sustainability concerns add another layer of complexity to many decisions, requiring companies to wrestle with questions such as whether the best decision in terms of traditional business considerations is also best for the environment. Human brains may struggle with that complexity, but decision intelligence can handle it.

Finally, there’s also an impact on employee satisfaction and the future of work. Many workers now live in a world of constant stress and rarely feel they have completed their work, and as a result of the Great Resignation, the number of workers is decreasing in many organizations. By optimizing, orchestrating, and accelerating decision-making and execution, this kind of digital technology can help give people an increased sense of doing their jobs successfully. It can also enable more decisions to be made by fewer people.

How do companies implement decision intelligence, and what’s the best way to get started?

Patil: A good way to begin is by conducting a capability assessment to determine process maturity and areas for potential improvement. From there, companies can focus on prioritizing improvement opportunities, developing an automation road map and business case, and obtaining C-suite buy-in. Many companies will execute a pilot test in the highest-priority automation use case, followed by scaling and repeating that process in other areas.

Laluyaux: It frequently starts at the top with the decisions made by senior leaders in an area with high complexity, where there are big models and spreadsheets involved. Most companies start with a small deployment and scale as it proves successful. But it’s important to remember that this is not a matter of a particular new technology replacing an old one or providing an alternative to business intelligence or planning—lots of technologies can be involved, including machine learning and more. What matters is that the way the company makes its decisions will evolve over time, optimizing for shifting priorities and orchestrating for maximum impact to take the company into the future.

CIO Journal content by Deloitte. The Wall Street Journal news department was not involved in producing this sponsor content.

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