In today's fast-paced business environment, the ability to make quick, informed decisions is a critical differentiator. As artificial intelligence reshapes how organizations operate, leaders are rethinking traditional decision-making structures. Jennifer Renaud, CEO of Kradle LLC and a board director with over 30 years of experience in digital innovation and strategy, shares insights on how companies can build cultures that prioritize speed without sacrificing alignment. This article explores the shift from hierarchical models to decision proximity—a framework that places authority closer to where insights originate.
The Problem with Traditional Hierarchies
Traditional hierarchies were designed for an era of stability and control. Markets moved slowly, information traveled through limited channels, and decisions could afford to be deliberate. However, today's landscape is different. Customer expectations shift rapidly, competitive advantages erode quickly, and organizations must respond almost instantly. According to Renaud, many companies still assume that more approval layers lead to better decisions. In reality, excessive approvals create delays, and when decision authority sits too high, teams wait for alignment while market signals lose relevance.
Organizations rarely fail because of a single bad decision. More often, they struggle because they make too few decisions to keep up with change. Leaders are recognizing that decision quality improves when authority rests with those closest to the customer, product, or operations. These individuals best understand emerging tradeoffs and can act with context that executives may lack.
Decision Proximity: A New Framework
Renaud introduces the concept of decision proximity—the distance between where decision authority sits and where the necessary information resides. When decisions move too far from the source of insight, context weakens and response times slow. Leaders may gain consistency but often lose accuracy and speed. By shortening the distance between signal and response, high-growth companies can act faster and smarter.
One of the most powerful tools in this framework is categorizing decisions as reversible or irreversible, a practice famously used by Amazon. Teams are encouraged to move quickly on reversible decisions—those that can be adjusted later—rather than waiting for perfect consensus. This approach reduces fear of failure and accelerates learning. Not every decision needs executive involvement, and the best judgment often comes from those closest to the issue.
Moving Faster Without Losing Alignment
Speed and alignment are not mutually exclusive. Renaud emphasizes that high-growth companies intentionally design their decision-making processes to balance both. They empower teams to act within clear guardrails, using decision proximity as a guide. Alignment comes not from top-down approval but from shared principles and a culture that encourages responsible risk-taking.
For example, instead of requiring sign-offs from multiple departments for a pricing change, a company might give the product team autonomy to adjust prices within a predefined range. This preserves speed while ensuring consistency with overall strategy. As Renaud notes, the people closest to the customer understand the tradeoffs most clearly, and their judgment is often superior when backed by real-time data.
AI's Impact on Decision-Making
Artificial intelligence is dramatically increasing the volume of signals organizations can act on. It is not just automating tasks—it is continuously generating insights across pricing, forecasting, supply chains, and customer behavior. This abundance of data challenges traditional decision hierarchies. Without a culture that embraces rapid, informed choices, companies risk drowning in signals without responding effectively.
Renaud points out that AI demands a shift from control to adaptability. Leaders must trust their teams to interpret AI-generated insights and make decisions quickly. This requires investing in training and creating feedback loops that refine both human judgment and AI models. The goal is to create a symbiotic relationship where AI enhances decision-making rather than bottlenecking it through approval chains.
Building a Decision Culture
High-growth companies deliberately cultivate a culture where speed and quality coexist. This involves rethinking performance metrics, rewarding timely decisions even when they are imperfect, and fostering psychological safety. Leaders play a crucial role by modeling behavior—demonstrating that they trust teams to make calls within their domain.
To build a true decision culture, organizations must:
- Clearly define which decisions are reversible and which require caution.
- Push authority to the point of insight using the decision proximity principle.
- Use AI to surface insights but empower humans to act on them.
- Create mechanisms for rapid feedback and course correction.
By doing so, companies can transform decision-making from a bottleneck into a competitive advantage. As Renaud concludes, the most successful organizations are those that recognize that in a fast-changing world, the ability to decide and adapt is more important than getting every decision perfect the first time.