Business Continuity is not a product

In many organizations, talking about Business Continuity is, in practice, talking about backups. Sometimes the concept is stretched a bit and things like replication, secondary sites, or disaster recovery are added to the mix. It sounds reasonable, technical, reassuring—especially the more terms are thrown in. The problem is that it’s conceptually wrong.

A backup answers a very specific question: can I recover my data if something goes wrong? Business continuity answers a very different, much more complex one: can the organization keep operating when something goes wrong?

Confusing these two questions is the foundational mistake behind many so-called “continuity strategies” that are, in reality, just solid implementations of tools. Necessary tools, yes—without a doubt. Sufficient? No.

This misunderstanding doesn’t come from bad intentions. It comes from an IT culture that has historically been infrastructure-centric. Success is commonly measured in technical terms: systems up, services responding, data restored. From that perspective, it’s logical to assume that if everything “came back,” the problem is solved. But the business doesn’t live solely inside a virtual machine or a bucket, no matter how critical those are to operations. The business also lives in processes, people, decisions, and timing.

A successful backup does not imply an operational business. You can restore a database and still be unable to bill customers. You can bring up a critical application and have no one who knows what to do with it. You can have intact data that is out of context or simply too late. From IT’s perspective, the incident is closed. From the business’s perspective, the real problem is just beginning.

This conceptual error becomes even more dangerous when it gets institutionalized. When teams or initiatives are labeled “Business Continuity” but their real scope is limited to backup and recovery platforms, a false sense of control emerges. At an organizational level, people believe risk has been mitigated, when in reality it’s only partially addressed—and often poorly understood.

Talking about continuity requires stepping outside the purely technical domain. It requires asking what truly cannot stop, how long an interruption can be tolerated, and what happens if technology recovers but the organization doesn’t. Until those questions are on the table, everything else is just a way to avoid the full conversation. And that’s the real starting point: before discussing tools, we need to admit that backing up systems is not the same as sustaining a business.

What a Backup really is (and why it’s essential)

A backup is, first and foremost, a data protection mechanism. Its purpose is simple, concrete, and absolutely critical: to allow information to be recovered when it is lost, corrupted, or becomes inaccessible. Human error, logical failures, ransomware, bugs, accidental deletions, or physical disasters—backups exist so those events are not final.

From a technical perspective, backups operate on clear, measurable variables:

• RPO (Recovery Point Objective): how much data I’m willing to lose.
• Retention: how long historical versions are kept.
• Integrity and consistency: restored data must actually be usable.
• Restore time: how long it takes to make that data available again.

Note: in the context of backups, we talk about restore time rather than RTO, because RTO by definition measures the maximum tolerable time to recover a business function or service—not just data. Data restoration is only one part of the recovery process; RTO also includes dependent systems, integrations, access, and the actual execution of business processes. Backups influence RTO, but they do not define it on their own.

All of this is familiar territory for any infrastructure team today. And that’s fine, because without backups there is no meaningful discussion about continuity, resilience, or operational maturity. Backups are a necessary condition.

The problem appears when backups are asked to do something they were never designed to solve. A backup does not understand processes, it does not know business priorities, and it cannot distinguish between a critical system and a secondary one unless someone told it so beforehand. It also has no idea whether the data it protects will be useful in the right order, the right context, or at the right moment when restored. Its job ends when the data exists again—not when the business is operational. Backups protect data, not operations.

Restoring a database does not mean the applications that depend on it are ready. Recovering a virtual machine does not guarantee its external integrations will work. Bringing an entire cluster back online does not ensure that access, credentials, workflows, or human dependencies are aligned. The backup does its job, and the problem may still be fully intact.

This is not a critique of backup technology, but a comment on its real scope. Backups do exactly what they promise. The mistake is using them as a closing argument in a discussion that should be much broader.

Understanding what a backup is—and, more importantly, what it is not—is essential to avoid building false expectations. Because when the day comes and an incident happens, discovering that “everything was restored” but “nothing works” is usually an expensive surprise—and a completely avoidable one. Backups are indispensable, but on their own they do not sustain a business.

What Business Continuity is (and why it’s not just a technical problem)

Business continuity is not a one-off solution or a set of isolated procedures. When properly understood, it is a management system. In fact, more mature frameworks such as ISO 22301   don’t talk about tools at all, but about a Business Continuity Management System (BCMS): a set of policies, processes, roles, and decisions aimed at ensuring the organization can continue operating in the face of disruptions.

This already draws a clear line between continuity and any purely technical perspective. Continuity is not something you “implement” once; it is managed over time. It evolves with the business, with its risks, its context, and its dependencies. And like any management system, it requires something that can be uncomfortable: ongoing conversation between areas that don’t speak the same language.

At the center of that system sits the Business Impact Analysis (BIA), the mechanism that translates the business into something actionable. The BIA forces the business to answer necessary questions:

• Which processes are critical?
• How long can they be interrupted?
• What is the real impact of that interruption?
• What dependencies exist beyond technology?

The problem is that this translation is rarely straightforward. For those of us working in technology, the business often appears as a diffuse, constantly changing entity—asking for “high availability” without knowing what it actually means, or calling everything “critical.” From that position, designing continuity becomes a frustrating exercise: context is missing, priorities are unclear, and assumptions abound.

But the problem isn’t only on the business side. As mentioned earlier, in IT we often fall into the opposite trap: assuming that if the system is up, the process is solved. It’s more comfortable to talk about backups, clusters, and replication than to sit down and understand how work really flows, where decisions are made, or what can degrade without breaking everything.

A well-designed continuity management system acknowledges this tension and works with it. It doesn’t expect the business to speak in technical terms, nor IT to guess priorities. It establishes formal mechanisms to translate impact into requirements, and requirements into solutions. It doesn’t eliminate friction, but it does make it productive.

From this perspective, continuity stops being an IT-only responsibility and becomes an organizational responsibility, where technology, processes, and people align—with effort, negotiation, and constant revision—around a central question: what needs to keep working for the business to survive a disruption?

The answer is rarely clear, complete, or final. But without that exercise, any technical architecture—no matter how sophisticated—ends up sustaining infrastructure, not operations.

The gap between restoring systems and restoring operations

Restoring systems is a technical event. Restoring operations is an organizational process. Between the two there is a gap that cannot be bridged with more infrastructure or better tools, but with prior understanding of the context in which those systems exist.

A system can be “up” and still be useless. The examples are common:

• a database restored, but without temporal consistency with other systems
• an application running, but with external integrations not working
• a full environment brought back online, but without users, access, or valid credentials
• a Kubernetes cluster recovered, but without secrets, pipelines, DNS, or deployment workflows

From the administration consoles these scenarios may look fine, but from the business side “nothing works.”

This is where many recovery strategies fail. Infrastructure restorations are tested, health checks are validated, and it is documented that the RTO was “met.” But none of that is useful if it isn’t validated whether the complete process—end to end—can actually run under degraded conditions: whether someone can really invoice, ship, support a customer, or make a critical decision.

The problem is not only technical; it’s one of alignment. Technology tends to recover in layers: infrastructure first, then platforms, then applications. The business, on the other hand, operates through flows: events, decisions, sequences. When these two models don’t meet, recovery is only partial.

On top of that, there’s a human factor that is almost never considered in technical plans: stress, improvisation, and lack of information. In a real disruption, people don’t behave like they do in diagrams. They look for shortcuts, make mistakes, and misprioritize. That’s why a continuity approach cannot depend on everyone “doing the right thing,” but on critical decisions already being made, roles being clear, and alternative paths defined in advance. When that doesn’t happen, what remains isn’t continuity—it’s hope.

For this reason, the distance between restored systems and functional operations is not closed by adding more copies, more automation, or more technology. It’s closed by understanding which parts of the process are truly essential, what can fail without breaking everything, and which decisions must be predefined before an incident occurs. Until that difference is acknowledged, IT will keep celebrating successful recoveries while the business deals with a very different reality: the technology is back, but the operation still isn’t.

How Backups, DR, and Business Continuity actually fit together

To move the conversation forward, we need to untangle concepts that are often mixed, overlapped, or outright confused. Backups, Disaster Recovery (DR), and Business Continuity do not compete with or replace each other; they serve different purposes and operate at different levels.

Backups operate at the data layer. Their role is to preserve information and enable recovery in the event of loss, corruption, or attack. They are the last resort when something has gone wrong. They protect the what.

Disaster Recovery (DR) operates at the technical layer. Its goal is to restore systems, platforms, and services within predefined times and conditions. It focuses on infrastructure, applications, and technical dependencies. It protects the how.

Business Continuity (BC), on the other hand, operates at the organizational layer. It defines which processes must keep running, in what order, with what acceptable degradation, and under which decision criteria. It protects the why.

The most common mistake is to invert this hierarchy—designing continuity based on what backups or DR happen to allow. When that happens, decisions are constrained by technical limitations instead of real business needs. The result is a “possible” continuity, not a “necessary” one.

A mature approach works in the opposite direction. Continuity defines priorities, tolerances, and impact. DR translates those definitions into technical architectures and procedures. Backups cover the scenarios where fast recovery is not viable or not a priority. Each layer plays its role without trying to absorb the others.

This also explains why an organization can have a technically flawless DR setup and still lack continuity. If there is no clarity around which processes must be restored first, which dependencies are critical, or what can wait, recovery becomes arbitrary.

Understanding this relationship avoids sterile debates. It’s not about choosing between backups or DR, nor about deciding whether continuity “belongs to IT or to the business.” It’s about accepting that continuity uses technology, but is not defined by technology.

When the concepts are properly aligned, the conversation changes. The focus is no longer on how many copies exist, how many sites are in place, or how granular the backups are—but on whether those decisions actually sustain operations when it matters most. And that is a question no tool can answer on its own.

The mistake of vendor-driven continuity

In many organizations, continuity strategy doesn’t come from an impact analysis or from a deep conversation with the business. It comes from a vendor’s catalog. What should be a management discipline ends up turning into a feature implementation, driven by licenses, roadmaps, and commercial agreements.

A new capability appears in a platform—advanced replication, container support, automated failover—and it is immediately folded into the continuity narrative. Not because the business asked for it, but because now “it can be done.” The question shifts from what do we need to sustain? to what else can we protect?

This approach creates a dangerous illusion: technical maturity as a synonym for organizational resilience. The assumption is that the more sophisticated the solution, the better prepared the business must be. But sophistication without judgment only increases complexity, cost, and dependency. It doesn’t necessarily reduce risk.

A clear symptom of this drift shows up when conversations about continuity and resilience automatically translate into product terms: which version we’re on, which feature is enabled, which extra module we need to buy. The discussion stops revolving around what needs to keep working and starts focusing on which technology we’ll use to solve it.

At that point, business continuity stops being a cross-cutting capability, spanning processes, people, and decisions, and degrades into a technical characteristic. Something you “have” because it’s contracted, installed, or checked in a console. As if resilience were just another license.

This becomes especially problematic in modern environments like cloud-native platforms or Kubernetes. I’ve seen protection strategies designed simply because the platform now allows it—not necessarily because, or when, the process actually requires it. RTOs and RPOs get defined based on what the tool supports, not on what the business can tolerate. The result is a continuity setup that is technically elegant but strategically empty.

What I’m getting at is this: the problem isn’t the tool—tools are necessary—but the mental model we adopt. When we measure continuity in terms of versions, vendors, or amounts of infrastructure, we’re measuring means, not outcomes. The business doesn’t need backups with deduplication X or DR with automatic failover; it needs to keep operating within an acceptable damage threshold. Everything else is implementation detail.

One inherent risk of this technology-centric model is that it displaces the conversation. While everyone is talking about features, no one is asking about processes. While new capabilities are being celebrated, no one is validating whether the business could actually operate with them in a real scenario. The tool moves to the center of the narrative, and the business becomes a secondary actor.

Vendor-driven continuity isn’t bad because it uses market tools. It’s bad because it outsources thinking. It confuses possibility with necessity and ends up building solutions that respond better to a commercial roadmap than to a real disruption. When continuity is designed from a vendor’s catalog, there’s a real risk that the business itself gets pushed out of the picture. And sooner or later, that bill comes due.

One final clarification: this isn’t about being against vendors or products—quite the opposite. Without them, modern continuity would be outright unviable. The problem arises when organizational strategy is fully delegated to a tool or a provider, as if adopting a platform automatically meant adopting judgment. Products solve technical problems; they don’t define business priorities, they don’t understand operational context, and they don’t make decisions under pressure. Expecting them to do so is confusing technological support with strategic responsibility.

How to start on the right foot

Not every organization starts from an ideal model. Most begin—and many stay—with backups. And that’s not a problem. The issue isn’t starting there; it’s believing that you’ve already arrived. Starting well doesn’t require a perfect continuity program, but something much simpler: asking the right questions before buying more technology.

The first step is not technical. It’s about identifying processes. Not systems, not applications, not servers—processes. Which activities create value? Which ones cannot stop without causing serious damage? Which can degrade or be done manually for a while? These answers are rarely found in IT, but in many cases IT needs to force them to surface.

The second step is understanding impact—not in the abstract, but in terms of real consequences. What happens if this process stops for two hours? For a day? For a week? What is lost first: revenue, customers, compliance, reputation? This exercise often dismantles many technical assumptions and reveals that not everything needs the same recovery speed.

Only then does the technology question appear. And at that point, the focus shifts. It’s no longer about “which tool do we have,” but about which capability we need to build. Maybe well-tested backups are enough. Maybe DR is justified for some processes and not for others. Maybe the answer isn’t technological at all.

A key point along this path is accepting imperfection. Continuity is not designed for ideal scenarios, but for plausible ones. Not everything can be protected equally, not everything can be recovered at the same time, and not everything is worth what it costs. Making choices is part of the design.

Finally, starting well means testing with the business, not just with IT. Restoring systems in a controlled environment isn’t enough. You need to validate whether processes can actually run, whether people know what to do, and whether decisions are clear when time is working against you.

Mature continuity doesn’t appear overnight. It’s built by iterating, correcting, and learning. But that journey only begins when you stop asking “what else can we back up?” and start asking “what do we need to keep working?”

Business Continuity rarely fails because of a lack of tools

Business continuity rarely fails because of a lack of tools; it fails because of a lack of clarity about what is actually being sustained. Backups, DR, and automation are necessary pieces, but when they become the center of the conversation, they stop serving their purpose and start obscuring the real problem.

If a continuity strategy can be explained by showing a console, then it isn’t a continuity strategy. At best, it’s a collection of technical capabilities that work well—until the context changes.

In the Sandman comics, the character Lucifer Morningstar puts it with striking clarity:

“Tools are the subtlest of traps. We become reliant upon them and in their absence, we are vulnerable, weak, defenseless.”

Tools don’t fail on their own. We fail when we use them as a substitute for thinking, when we delegate to them decisions that should be organizational, and when we confuse technical possibility with business necessity. The more sophisticated tools become, the easier it is to fall into the trap of believing we’re already prepared.

Moving the conversation from backups to continuity does not mean giving up on technology. It means restoring it to its proper role: enabling, not defining. Continuity isn’t about how many systems can come back online; it’s about whether the organization can keep operating coherently when not everything comes back the way we expected. Protection is about allowing the business to exist under uncertainty. And no tool is enough for that if the hard decisions haven’t been made first.