Think “As-a-Service” Models Are Too Expensive?
Let’s Go Through the Facts.
Many decision-makers may hesitate to transition away from traditional, capital-intensive approaches to asset health and maintenance because they fear the recurring costs associated with "As-a-Service" models.
While a traditional approach may still be the right fit for certain operations, bridging the gap between perceived cost and actual value requires a careful comparison of both options. By combining continuous condition monitoring, prescriptive AI insights, and dedicated domain expertise, our outcome-based service models can empower teams to focus on optimizing asset performance, not managing systems
Here is a breakdown of the facts to help weigh the options.
1. The high costs of inaction
One of the arguments people make for sticking with traditional, reactive models is cost avoidance and fear of increasing annual subscriptions. However, the costs of unplanned downtime are a massive financial liability.
When a machine runs to failure, the direct repair expenses are just the tip of the iceberg. The indirect, hidden costs of unplanned downtime—including lost production, safety risks, and environmental impacts—can be up to five times higher than the direct maintenance costs. For many assets, a single unexpected failure can mean a substantial or total loss of production, which can cost operations tens of thousands to millions of dollars per day.
Relying on time-based maintenance to prevent these costs is also highly inefficient, as 90% of machine failures are random rather than time-based. Without continuous monitoring, operators remain unaware of rapid degradation between calendar checks, inviting catastrophic, unexpected failures.
2. The hidden costs of manual data collection
Many organizations rely on manual walkarounds and portable data collection (PDC) programs to monitor asset health, believing it to be a cost-effective strategy. However, this approach provides only a periodic snapshot of asset health rather than the continuous stream of data required to detect rapid-onset degradation. As conditions can change rapidly between calendar checks, relying on PDC alone can create the risk of operational blind spots and unexpected failures that a continuous as-a-service monitoring solution could have detected earlier.
3. As-a-Service offerings can enhance, rather than replace existing investments
Transitioning to an outcome-based as-a-service model does not mean organizations must discard all existing monitoring investments. An effective, scalable, plant-wide asset health strategy relies on a fit-for-purpose approach, meaning different solutions are applied based on a specific asset's type and criticality. While continuous monitoring is ideal for catching rapid-onset degradation on critical or hard-to-reach assets, portable data collection (PDC) programs can still play a role in a comprehensive strategy.
Instead of competing with existing tools, a modern service model complements them. Platforms like Cordant™ Machine Health are designed to break down data silos by integrating inputs from multiple sources. Data collected concurrently from handheld PDC devices, legacy permanent sensors, and modern wireless sensors can all be brought together to provide a holistic, enterprise-wide view of asset health.
4. Outcome-based as-a-service offerings pay for themselves
The financial advantage of as-a-service offerings in asset health is not just about avoiding catastrophic failure; it is about increasing capital efficiency and measurable returns.
By outsourcing management of asset health-related hardware and software, for example, you can ensure scalability and performance while lowering total cost of ownership.
With outcomes-focused partnerships, as-a-service offerings also deliver value aligned to your organizational goals, supporting reliability, availability, and maintenance objectives.
5. Tapping into specialized talent and expertise
One of the hurdles to "doing it yourself" via traditional CapEx routes is having the right talent. Industry leaders often cite a shortage of skilled labor as a top challenge, as the industrial sector faces resource constraints compounded by a retiring workforce and a need for new digital skills.
As-a-service models add value by directly addressing this talent gap. Instead of struggling to hire and retain scarce talent, organizations can use outcome-based service models to tap into a pool of specialized expertise. Solutions like Cordant™ Machine Health bridge the skills gap by routing complex data to an on-demand team of expert vibration analysts and reliability engineers.
By pairing the existing workforce with this embedded intelligence and expert support, organizations empower technicians to shift focus away from routine, time-based inspections on perfectly healthy equipment. Instead, they can leverage prescriptive diagnostics to execute the right maintenance exactly when the data dictates it.
A path to proactive reliability
Evaluating the true cost of an asset health program requires looking beyond the initial price tag to understand the full operational impact. Clinging to traditional, CapEx-heavy models and manual data collection can leave operations vulnerable to unexpected failures and strain already limited resources.
On the other hand, transitioning to a continuous, outcome-based service model, organizations gain a steady stream of prescriptive insights backed by dedicated domain expertise. This approach eliminates the heavy IT and administrative burdens of the past, empowering maintenance teams to stop managing disconnected systems and start executing confident, data-driven decisions that maximize plant-wide reliability, safety, and profitability.
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