AI-Powered Decision Making: Enterprises Cite Value

In our digital world, competitive differentiation stems from an organization’s ability to enable all employees to make the best possible decisions. Yet the best possible decisions are rarely made, often due to technology limitations, workforce resources, internal processes, and more. How much does investment in better decision making play a role in enterprise success?

The answer may surprise you. 

Decision velocity matters

A supply chain leader at a global consumer packaged goods company shared with me that decision execution was the missing link in his company’s digital transformation initiatives. His team needed the ability to make decisions in real time in response to changing conditions — yet the company’s existing data, technology systems, and workforce presented roadblocks. 

In a recent global survey of Fortune 1000 executives, IDC examined challenges and opportunities around AI-powered decision making, identifying “leaders” (companies successfully operationalizing AI for better decisions) versus “followers.” IDC’s research also revealed the value of decision velocity for enterprises.

Let’s take a closer look.

Decision innovators

In the study, IDC found three key factors uniting those market leaders who are successfully operationalizing AI, analytics, and data to drive value:

• Clear, measurable goals and KPIs
• Pragmatic use of enabling AI, analytics, and data technologies and skills
• Active investment in technology to accelerate decision velocity

As defined by IDC, “decision velocity” is the speed at which a decision-making process can be executed within a set of enterprise controls. 

And this is important. As context, one executive at a global chemicals company explained that beyond having the data and insights from your AI investments, you must be able to quickly determine the action needed in order to make the best decisions. 

An early adopter of AI decision automation, this company applied the technology to a number of use cases, including margin management. With raw material prices increasing and margins shrinking, the executive’s team needed the ability to make well-informed, very careful recommendations about price increases across regions, while ensuring internal consensus.

However, his team lacked the ability to predict situations in real time across multiple dimensions and changing factors, and then actually take action by executing the decision.

AI-powered decision making changed this, preventing margin leakage by generating real-time recommendations about specific price increases based upon raw material pricing predictions. 

The company is now experiencing multi-million dollar margin improvements. Moreover, these positive results have eliminated internal skepticism in using AI to execute decisions and confidence has grown.

While this improvement didn’t happen overnight, it’s a good example of the benefits to be gained from applying AI to an area where decision making is complex and challenging.

Roadblocks to decision velocity

With decision velocity in mind, let’s look at the challenges revealed among “followers.”

What would you do if you knew that a quarter of operational decisions that should be made were not being made because of operational challenges with data, analytics, and AI?

Consider these IDC survey findings:

• Only 20% feel completely comfortable with the number of decisions they need to make daily
• 33% still rely on intuition or past experience to make decisions
• 25% of decisions that should be made are not being made 
• 30% of decisions made in organizations remain undocumented

Respondents also shared that only 55% of executives mostly, or fully, know how lower-level decisions are being made.

Decisioning leaders experience improvements 

Despite these challenges, the IDC survey found that enterprises see the potential in AI-enabled decision making and enterprise “leaders” are improving their decision making processes and experiencing outcomes.

For example, “leaders” cited improvements of 70% or more across these decision velocity characteristics: 

• Decision governance and control: 87%
• Decision speed: 83%
• Decision consistency: 82%
• Decision quality: 81%
• Decision agility: 75% 

This translated to more standardized decision-making procedures and policies, stronger collaboration and empowerment among employees, and decision-making knowledge being captured in software systems and shared throughout the organization.

Enterprises are also generating value. IDC found that decision intelligence drove up to a 20% improvement across key business metrics since last fiscal year.

So how do you get started and how fast do you want to go? 

Achieving decision velocity 

While early adopters have had time to test, scale, and improve their decision transformation initiatives, it’s critically important that others are not left behind.

I’ll summarize a few of IDC’s recommendations here:

• Start by identifying decisions that are good candidates for automation
• Consider these decision intelligence options in your decision-making process:
  • Assist or support your decision making: Your team is “in the loop,” making decisions based on the real-time insights
  • Augment your decision making: Your team is “on the loop,” making decisions after the technology generates the options
  • Automate your decision making: Most of your decisions are being automated within a governance or controls framework, with your team intervening when necessary
• Invest in change management: Any initiatives that change the way existing work is done must consider people and processes to ensure education, adoption, and success.

AI is the future of enterprise technology. Applying AI-enabled technology to business decision making is already proving valuable. Beyond bottom-line outcomes, the ability to achieve decision velocity across your organization translates into better work, greater knowledge retention, enhanced transparency, improved collaboration, and provides the foundation for the self-driving enterprise.

Source: IDC White Paper, commissioned by Aera Technology, What Every Executive Needs to Know About AI-Powered Decision Intelligence, IDC #US51338623, November 2023

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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