The CP Journal

The CP Journal

The Operational Level of Left of Bang

How organizations recognize, assess, decide, and act before an event occurs.

Patrick Van Horne's avatar
Patrick Van Horne
Jun 10, 2026
∙ Paid

This leadership essay is for paying subscribers to The CP Journal.

Many organizations can already access the indicators that could help them get left of bang. The problem is that recognizing an indicator and acting on it are two very different things.

That challenge sits at the center of a question we have been trying to answer for readers and clients for years.

How do we apply the concepts described in Left of Bang to the broader range of threats, hazards, disruptions, and opportunities our organizations face?

The concepts described in the book are relatively straightforward when applied at the individual level. A person develops a baseline, recognizes an anomaly, and decides what action they will take. The process is often compressed into seconds or minutes and is carried out by a single individual.

But organizations are different.

The person who first recognizes a potential issue may not be the person responsible for assessing it. The person conducting the assessment may not have the authority to decide what should be done. And the people responsible for implementing a decision may not have participated in any of the previous steps.

What occurs naturally within an individual must be deliberately designed within an organization.

If organizations are going to consistently get left of bang, information must move from recognition to action. That requires a process that can be understood, delegated, managed, and repeated across different teams, functions, threats, hazards, and situations.

Over the last several years, through client engagements, our own research and application, and observing how organizations succeed or fail to act on pre-event indicators, we have been working to answer that question.

What emerged is the foundation of the Operational Level of our Left of Bang Framework.

What follows is an initial introduction to that approach.

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