How to Build and Automate a Resilient Testing Program

When the pandemic hit, a lot of organizations found out the hard way that having a business continuity plan (BCP) and having a tested business continuity plan are two very different things. Plans that looked complete on paper fell apart in practice. Not because they were poorly written, but because the assumptions inside them had never been put under real pressure.

And it wasn't just the pandemic. Geopolitical instability, supply chain failures, widespread cyber incidents, and extended infrastructure outages have each forced the same uncomfortable realization: organizations weren't facing unpredictable "black swan" events. In many cases, they were facing foreseeable disruptions at a scale they had simply never validated against.

The plans existed. The testing didn't.

That gap has changed how leadership teams think about business continuity. Increasingly, the question isn’t whether a plan exists and is signed off, it’s whether the organization can actually recover when it needs to. But the tools and processes most teams rely on: manual coordination, spreadsheets, one-off exercises filed away after the fact just don't support continuous validation at the scale that expectation demands.

The result: the gap between how BCM programs look on paper and how they actually perform under pressure remains wide for most organizations.

Why Testing Defines BCM Success

There’s a natural tendency to treat the Business Impact Analyses (BIAs) as the centerpiece of a BCM program. You invest months, sometimes years, gathering data across the organization: processes, dependencies, Recovery Time Objectives (RTOs), Recovery Point Objectives (RPOs), Maximum Tolerable Periods of Disruption (MTPDs). You build that data into continuity plans. You get sign-off.

But the BIA and the plans that come from it are, by definition, based on assumptions. Assumptions about how teams will respond, what resources will be available, how long recovery will actually take, and whether the documented procedures hold up when conditions are imperfect, which they always are during an actual disruption. Testing is where those assumptions meet reality.

The BCI Good Practice Guidelines (GPG Edition 7.0) are unambiguous on this point: "An organization's continuity capability cannot be considered reliable or effective until exercised. No matter how well-designed a BC solution or BC plan appears, realistic exercises should be used to help identify issues and validate assumptions that may require attention."

Leading industry frameworks all align around the same principle:

ISO 22301 (Clause 8.5) requires organizations to test and exercise continuity procedures as part of a formally structured management system, with continuous improvement built into the cycle.

The BCI GPG (Professional Practice 6: Validation) describes testing through a progressive exercise program, moving from discussion-based exercises through simulations to live activities, with lessons learned systematically fed back into the program.

DRII Professional Practice 7 positions scenario-based exercises as the mechanism for assessing operational readiness, emphasizing that scenarios should be realistic, documented, and tied to measurable outcomes.

FFIEC guidance reinforces integrated testing across business and technology recovery capabilities, requiring that continuity and IT disaster recovery testing not exist in separate silos.

Across all of these frameworks, the message is the same: resilience cannot be assumed. It must be validated, documented, and continuously improved.

What Testing Actually Builds

A well-run testing program changes how an organization behaves during disruption. It turns business continuity from a documented process into something operational teams can actually execute under pressure.

It builds muscle memory. Exercises give the people who would actually respond to a disruption the chance to rehearse what they'd do. The right people learn what they're responsible for, how to escalate, who to call, and what order things need to happen in — before any of that matters. Time lost to confusion during an actual incident is time the organization can't get back.

It exposes gaps that documentation misses. You can't find a missing dependency, an outdated contact, or a procedure that doesn't work by reading the plan. You find those things by running through the plan under realistic conditions. The BCI notes that exercises help identify "missing or outdated information, as well as areas for improvement", to highlight that even well-documented plans can contain operational weaknesses that only surface during testing.

It gives regulators what they actually need. A signed-off plan satisfies an audit. A tested plan, with evidence of what was exercised, what gaps were found, and what was done about them, demonstrates a working program. There's a meaningful difference between the two, and increasingly, regulators are expecting it.

The Real Challenges to Effective Testing

Most organizations don't struggle with recognizing the importance of testing. Making it happen consistently across a large, busy organization, with a small BCM team and limited time is where most programs run into trouble.

Getting people to show up. Leadership participation isn't optional for exercises that involve strategic decision-making under pressure. When senior leaders don't participate, two things happen: the exercise loses realism, and the signal sent to the rest of the organization is that business continuity isn't worth their time. Both outcomes are damaging. Testing programs that work tend to have visible executive sponsorship, not just nominal sign-off.

Reaching the frontline. Middle management and frontline teams are the operational backbone of any continuity response. They're also the people with the least discretionary time. Getting meaningful participation from the teams that would actually execute during a disruption requires making the ask as low-friction as possible, which is hard when exercises are scheduled months in advance, require multi-hour time commitments, and don't visibly connect back to how those teams actually work.

Scaling with a small team. A BCM team of two or three people managing testing across thousands of employees across multiple business units and geographies cannot run enough exercises manually to maintain real coverage. Every hour spent designing scenarios, coordinating schedules, chasing participants, and formatting after-action reports is an hour not spent analyzing what the results mean or improving the program. The work of running testing can consume all the capacity that should go toward learning from it.

How to Design a Testing Program That Builds Capability

Building an effective testing program starts well before the first exercise. The structure, goals, and expectations you set upfront determine whether testing becomes a meaningful resilience capability or just another scheduled activity.

Build a network of champions. The BCM team can't own all of this alone. Identifying business continuity champions or ambassadors within individual business units, people who understand the program, can facilitate local exercises, and can keep BCM visible in their area, is how you extend reach without extending headcount. This also shifts exercise delivery from something the BCM team does to the business into something the business does with it, under the guidance of BCM teams.

Design for outcomes, not events. Define what success looks like before designing the exercise, not after. Without measurable outcomes, testing becomes a recurring activity rather than a capability-building program. Below are some example metrics you can apply based on the exercise type. Every organization will have a unique operating environment, so make sure that the metrics you set align with the reality of your business.

Focus on recovery, not cause. It's tempting to design exercises around specific, highly detailed scenarios: a particular cyberattack, a specific vendor failing, a defined weather event. That level of specificity can add realism, but it can also create a false sense of preparation. Organizations can't test every possible trigger. Mature programs focus less on predicting what will go wrong and more on validating that critical operations can recover regardless of the cause.

That said, some disruption types do introduce genuinely unique constraints that generic scenario-agnostic testing won't surface. A pandemic scenario, for instance, needs to account for reduced workforce availability across multiple locations and geographies simultaneously.. A cyberattack scenario needs to address communication channels being compromised alongside systems being unavailable. A regional conflict scenario needs to test vendor and geographic dependencies that might not appear in a fire or flood scenario. The goal is to build enough scenario variety into the program to surface those unique constraints without becoming so specific that testing is only preparing for one version of events.

Build in continuous testing, not just scheduled cycles. Annual exercises check a box. They don't reflect the reality of how organizations change. Mergers, acquisitions, technology changes, team restructuring, and business growth all alter the assumptions your plans are built on. A testing schedule needs to accommodate planned cycles and also respond to change; when something significant shifts in the organization, the relevant plans and the exercises that validate them should shift too.

Upleveling with Technology and Automation

Technology doesn't replace BCM expertise. It amplifies what a small team can do with the expertise they already have.

The manual work involved in running a testing program is substantial. Designing scenarios takes time. Coordinating participants takes time. Tracking what happened during an exercise, capturing the findings, assigning follow-up actions, and reporting on the program, all manual, all time-consuming, and all largely disconnected from the next exercise in the cycle.

Automation changes that equation in a few specific ways:

Scenario generation. Realistic exercise scenarios, injects, and discussion questions based on organizational parameters, regulatory frameworks, and the dependency data already in your program can be scaled using AI. What used to take days of preparation can take minutes, which means teams can run more complex exercises more frequently without proportionally more effort.

Participant coordination. Scheduling, reminders, and post-exercise follow-up can be handled systematically rather than manually tracked in someone's inbox.

After-action reporting. Capturing exercise findings in structured, analyzable format, rather than free-text notes that get filed and forgotten makes it possible to identify patterns across exercises over time. Where are the same gaps appearing? Which teams are consistently underprepared? What scenarios keep revealing the same dependencies?

Gap management and evidence collection. Maintaining a clear record of what was tested, when, what was found, and what was done about it creates the audit trail that regulators look for and makes the case internally that the program is producing results, not just activity.

The goal of automation in testing isn't to run exercises faster. It's to run more of them, with better data, so that findings can actually drive improvement rather than sitting in a report nobody reads.

Operational Confidence Is the Standard

Business continuity testing is not primarily about documentation. It's about knowing, with actual evidence, that your organization can respond, adapt, and recover when it needs to.

The BCI describes this as validation: confirming that the solutions designed, the plans produced, and the people responsible for executing them can actually deliver when a disruption occurs. That confirmation can only come from putting the program under realistic pressure, capturing what happens, closing the gaps that surface, and repeating the cycle.

Organizations that build continuous, measurable, and scalable testing into their resilience strategy are doing something meaningfully different from those that run an annual tabletop and file the report. They're accumulating evidence that their capability is real. They're finding gaps while there's still time to close them. They're building the kind of muscle memory that makes the difference when the disruption isn't hypothetical.

That's what a testing program is for. And with the right structure and the right support it's achievable even for small teams managing large programs.

Want to see how automation can help your team design, run, and analyze exercises at scale? Explore Fortiv's Exercises and Simulations capability.