Features That Matter (and Don’t) in Predictive Maintenance Software

Executive Summary

This comprehensive guide explores the features that truly matter in predictive maintenance software—and the ones that don’t—helping maintenance managers and site leaders in food, dairy, seafood, and FMCG manufacturing cut through vendor noise. Learn which tools deliver fast ROI, reduce downtime, and simplify maintenance, from automated fault detection and wireless sensors to integration-ready platforms like Factory AI. 

Whether you're evaluating condition monitoring systems or seeking the best predictive maintenance software for your plant, this article equips you with the clarity to choose features that boost uptime and eliminate unnecessary complexity.

Introduction

Choosing predictive maintenance (PdM) software can feel overwhelming. With vendors flooding the market—each boasting their own dashboards, AI models, and feature sets—how do you separate the signal from the noise?

If you’re a site reliability engineer or maintenance lead in food, dairy, seafood, or FMCG manufacturing, you’re probably not looking for the flashiest features. You’re looking for the ones that actually make your life easier, prevent unplanned downtime, and deliver ROI in under six months.

And just as importantly, you need to know which features are overhyped, misleading, or downright unnecessary for your plant floor.

This guide is written to help you make smarter decisions, avoid common traps, and ask better questions when evaluating PdM software. We’ll look at:

• Which features actually drive results (and why)
• Which features waste time or budget
• How to think about software in terms of your site’s realities
• What to show your site leader when they ask “Why this one?”
  

We’ll also reference external resources like ReliabilityWeb, Allied Reliability, and our own Factory AI blog here, so you can dive deeper.

Let’s get started with the basics: the features that matter most.

Part 1: The Features That Actually Matter

These are the features that directly reduce downtime, improve decision-making, increase visibility, and keep things moving on the plant floor.

1. Real-Time Condition Monitoring (That Actually Works)

Many PdM solutions claim to offer “real-time monitoring,” but there’s a big difference between periodic checks and truly live, always-on visibility.

Why it matters:

• You can catch fast-developing faults (e.g. motor imbalance, bearing failure) before they cause production stops.
• You don’t rely on monthly manual routes that may miss intermittent issues.
• Operators and maintainers get alerts before they notice symptoms—saving time and product.
  

Factory AI’s Advantage:
Our wireless condition monitoring sensors continuously monitor vibration, temperature, and more—sending data every few minutes. No delay. No gaps. And alerts that actually make sense to your team.

👉 See more about our real-time vibration monitoring approach.

2. No IT Required for Setup

This is one of the most underrated deal-makers (or deal-breakers).

Why it matters:

• Many food and beverage plants have poor Wi-Fi coverage in key areas.
• Getting IT to approve cloud access or network changes can take weeks—or longer.
• If setup depends on plant-wide integration, the project can stall indefinitely.
  

What to Look For:

• 4G or modem-based data transmission
• No reliance on corporate networks
• Pre-encrypted, secure data handling
• Plug-and-play deployment
  

Factory AI’s Advantage:
No IT required. Our sensors transmit data via 4G modem—fully isolated from your production network. That means you can install and go, with zero delays or firewall issues.

3. Actionable, Interpreted Alerts (Not Just Data Dumps)

Raw data is useless without interpretation. Some systems generate endless graphs with no context—leaving your team guessing what to do next.

Why it matters:

• You want your team to take action, not analyse charts.
• Too many false positives = alert fatigue.
• Without clear thresholds or diagnostics, you’re just paying to be confused faster.
  

What to Look For:

• Fault classification built-in (e.g. misalignment, imbalance, bearing wear)
• Alert priority levels (critical, warning, info)
• Plain-language notifications
• Suggestions for what to do next
  

Factory AI’s Advantage:
Our alerts are written for the trades. No jargon. No fluff. Just straight-up insights: “Fan on Line 2 showing signs of looseness. Plan inspection in next 7 days.” That’s how you get ROI.

4. Fast Setup Time (Minutes, Not Days)

You shouldn’t need weeks of training or a systems integrator to get going. If it takes days to install, it’s already too slow for today’s operations.

Why it matters:

• Speed of setup = speed to value.
• Minimal disruption to production = higher team buy-in.
• Reduces perceived risk when pitching a pilot.
  

What to Look For:

• Sensor install time per asset (<30 minutes is ideal)
• Pre-calibrated, pre-configured hardware
• Built-in diagnostics to verify setup quality
  

Factory AI’s Advantage:
We can set up a 20-asset pilot in one afternoon. No cabling. No control system wiring. No extra boxes.

Quote from a Reliability Manager:

“We installed 15 sensors in under 4 hours. It took longer to unwrap the Tim Tams.” (Actual customer quote... probably after a break.)

5. Sensor-Agnostic Compatibility

If the software requires proprietary sensors only, that’s a red flag.

Why it matters:

• You may already have vibration or temperature sensors installed.
• Swapping out existing hardware adds cost, downtime, and resistance.
• Lock-in creates risk—what if the vendor sunsets the hardware?
  

What to Look For:

• Compatibility with third-party sensors
• Support for standard protocols (4–20mA, Modbus, etc.)
• Clear API documentation (if you do want to integrate)
  

Factory AI’s Advantage:
We work with what you’ve got. Use our sensors or your own. Your choice.

6. Built-In ROI Tracking

If you can’t show ROI, the project won’t survive.

Why it matters:

• Site leaders need proof, not promises.
• Without tracked wins, you won’t get budget for expansion.
• ROI metrics build confidence across the plant.
  

What to Look For:

• Automated tracking of alerts vs. downtime avoided
• Estimated cost savings per event
• Dashboard summarising wins
• Customisable reports for site leadership
  

Factory AI’s Advantage:
Our platform tracks everything—from alerts to maintenance actions to estimated cost savings. That means you can walk into your monthly ops meeting with facts, not feelings.

7. Simple, Transparent Pricing

Maintenance teams are often flying blind when it comes to budget planning. You need pricing that’s predictable and fair.

Why it matters:

• Hidden fees (for extra users, integrations, dashboards) erode trust.
• Annual budget cycles require clear forecasts.
• Perpetual licenses with support charges are a pain.
  

What to Look For:

• Flat-rate pricing per asset or site
• No surprise implementation or training costs
• Bundle options (e.g. sensor + software)

Factory AI’s Advantage:
We charge $500 per monitoring point per year (that’s the starting rate, it gets less expensive if you add more assets). Full stop. Includes software, support, and updates. No surprises. Just savings.

Part 2: The Features That Don’t Matter (or Hurt More Than They Help)

Not all features are created equal. In fact, many PdM platforms over-index on flashy capabilities that sound impressive in a demo but fail to deliver any practical value on the floor. Worse, some features can create drag—slowing adoption, draining your team’s time, or adding hidden costs.

Let’s walk through the most common examples.

1. 3D Digital Twins (When You Just Need an Alert)

Digital twins are a hot buzzword. Some vendors let you create a full 3D model of your plant, with moving machinery, sensor data overlays, and colour-coded health indicators.

Sounds great. But…

Why it often doesn’t matter:

• Creating digital twins takes time, effort, and engineering resources.
• Most reliability engineers don’t need a 3D model to know what’s wrong.
• It can distract from the basics: what’s the fault, and when do I fix it?

Unless you’re managing hundreds of interdependent machines in a highly automated facility, a simple dashboard does the job better.

Verdict: Nice to look at. Rarely worth the setup.

2. AI Jargon with No Explanation

You’ll see terms like “proprietary machine learning models,” “edge AI inference,” and “digital signal processing with adaptive baselines.”

They might all be true—but are they useful?

Why it doesn’t matter:

• Most tradespeople and site engineers aren’t evaluating PdM based on neural network architecture.
• If the insights aren’t interpretable, the AI doesn’t help.
• Jargon erodes trust. If a vendor can’t explain what’s happening in plain English, that’s a red flag.

What matters more: A system that detects a fault, classifies it clearly, and suggests a fix.

3. Gamified Dashboards and Leaderboards

Some PdM vendors include “gamification” features to drive usage—like badges for logging in, leaderboards for most inspections completed, or colour-coded team stats.

Why it doesn’t matter:

• Your team isn’t here to win trophies—they want fewer callouts.
• These features are often designed for corporate, not trade-level users.
• They can distract from high-impact alerts and work order priorities.

What matters more: Fast, intuitive alert dashboards and mobile-friendly reporting.

4. Weekly Vibration Reports (That No One Reads)

Some systems automatically generate dense PDF reports with waterfall plots, FFT data, and trend lines—emailed weekly.

Why it doesn’t help:

• Most people don’t have time to read 30 pages of data per week.
• Teams quickly ignore them or create a “PdM Reports” folder that no one opens.
• These reports often don’t tell you what to do next.

Better alternative: Live dashboards with critical alert summaries, and optional on-demand reports when needed.

Quote from a Reliability Tech:

“If I need to download a PDF to know what’s wrong, I’m already behind.”

5. Sensor Widgets and Custom Visual Builders

Some platforms include “low-code” or “no-code” tools that let you build custom dashboards, graphs, or widgets.

Why it doesn’t matter for most:

• You’re a reliability engineer, not a UI designer.
• Building dashboards takes time away from fixing problems.
• Most plants benefit from standardised dashboards that show alerts, uptime trends, and ROI.
  

Exception: If you’re rolling PdM out to multiple sites and need flexible reporting, it can be helpful—but only if your team actually uses it.

Factory AI’s Position:
We give you a clean, ready-to-go interface. No coding. No dashboard-building. Just insights.

6. Over-Integration with ERP or SCADA

Many vendors promise “deep integration” with your ERP, MES, SCADA, or even HR system.

Why it might not help (initially):

• Integration projects are slow, expensive, and often unnecessary at the pilot stage.
• You don’t need SAP data to know a fan is vibrating too much.
• SCADA and PdM serve different purposes—forcing them together too early can create confusion, duplicated data, or misaligned teams.
  

Factory AI’s Position:
Yes, we do integrate with SCADA—but only under the right circumstances, and only after the results of predictive maintenance have been proven at your site. We find that integration is most successful after leadership, engineering, and IT are fully onboard. That’s when it adds strategic value, not friction.

We also take a selective approach: SCADA systems often house hundreds of variables and tags. We work with you to identify exactly which data points matter (e.g. RPM, load, temperature), so we don’t create a flood of unnecessary noise. It’s about clarity, not complexity.

Best practice: Start with a standalone PdM deployment to prove the value, then scope a light, high-impact integration only when needed—and with full cross-functional support.

External Read:
ReliabilityWeb: Why Simple Integrations Win in Reliability

7. Unlimited Customisation

The promise of “anything is possible” is tempting—but also dangerous.

Why it often backfires:

• If you customise everything, your system becomes unmaintainable.
• Updates break more often.
• Training becomes harder across teams.
• You lose vendor support because you’ve built a Frankenstein version of their platform.
  

What to look for instead: Smart defaults with sensible flexibility—e.g. alert routing rules, priority levels, and asset grouping.

8. Automated Work Order Creation Without Context

Some PdM platforms brag about automatic CMMS ticket creation. Sounds good—until you realise every minor threshold breach spams your maintenance queue.

Why it can backfire:

• Overloaded CMMS = ignored alerts
• Techs waste time chasing non-issues
• Admins stop trusting the system
  

Better approach: Let critical alerts create work orders, with human-in-the-loop review or confirmation. Context matters.

Factory AI Integration Tip:
We support CMMS triggers with filters—so only relevant, confirmed alerts generate work.

9. High-Frequency Data Sampling with No Clear Purpose

Some PdM platforms promote ultra-high sample rates—up to 51,200 Hz or higher—as a sign of superior performance, implying that more data equals better accuracy.

But here’s the reality:

• Most mechanical faults (bearing wear, misalignment, imbalance) are detectable with sample rates in the 3,200–6,400 Hz range.
• Ultra-high-frequency sampling is typically only necessary for extremely technical or niche diagnostics.
• More data doesn’t just mean more detail—it means more processing, more storage, and more time spent interpreting results.
  

Factory AI’s Perspective:
Yes, we can support high-frequency sampling where it makes sense. But we’re crystal clear with customers: the use case needs to be specific and justified.

For example, ultra-high frequencies may be appropriate for:

Diagnosing inconsistencies caused by operator behaviour in highly sensitive equipment

• Monitoring high-speed, precision assets where fault patterns occur within milliseconds
• Validating performance of expensive OEM systems under stress

But the trade-offs are real:

• Higher cost per sensor
• Reduced battery life, sometimes significantly
• Greater need for expert interpretation
  

We guide our customers to use higher sample rates only when required—and to focus on actionable insights, not data volume for its own sake.

Better Rule of Thumb: Right-size your data resolution to your asset class and maintenance goals.

External Resource:
DataQ : What You Really Need to Know About Sampling Rates

Summary: Less Noise, More Signal

Here’s the truth: You don’t need every feature under the sun. You need the right features, used the right way, by the right people.

PdM software should:

• Make maintenance simpler
• Reduce fire drills
• Free up time
• Pay for itself
• Help your team act—not analyse
  

And the more “features” get in the way of that, the more you should question their place in your plant.

Part 3: Prioritising Features Based on Your Plant Environment

Not all plants are created equal. A feature that matters in a dairy may be irrelevant in a high-speed bottling facility. Likewise, a seafood site operating in sub-zero conditions has different reliability needs than a baked goods site producing 24/7.

In this section, we’ll show you how to align predictive maintenance software features with the realities of your plant environment—from hygiene and compliance to culture and infrastructure. Whether you’re evaluating for one line or ten sites, this guide will help you prioritise smart.

1. If You're in a High-Hygiene Environment (Dairy, Seafood, Frozen)

Prioritise:

• IP-rated, food-grade compatible sensors
• Wireless, non-intrusive installations
• Easy-to-clean hardware with no external cabling
• HACCP audit-ready documentation
• Minimal equipment footprint (no bulky gateways or wired enclosures)
  

Why It Matters:
High-hygiene zones leave little room for bulky or maintenance-intensive hardware. Any PdM system needs to respect sanitation workflows and cleaning schedules. Sensors must be rugged, sealed, and safe for daily washdowns.

Factory AI Fit:
Factory AI’s sensors are IP67-rated and food-safe. Our wireless, self-contained devices require no drilling, no PLC integration, and no cabling—perfect for dairy, seafood, and frozen processing environments. We’ve helped sites maintain HACCP compliance while expanding coverage across cold rooms and wet zones.

2. If Your Plant Has Legacy or “Dumb” Equipment

Prioritise:

• Sensor-based monitoring (rather than built-in OEM diagnostics)
• Systems that don’t rely on PLCs or native equipment data
• AI that doesn’t assume digital inputs
• Manual override and flexible data tagging
  

Why It Matters:
Older equipment won’t broadcast fault codes or usage stats. You need a PdM system that can pull insights from physical behaviour—like vibration, temperature, or load—rather than requiring digital connectivity.

Factory AI Fit:
Our system was designed with legacy plants in mind. We don’t need your gear to be “smart.” If it turns, we can monitor it. That means motors, pumps, conveyors, fans—regardless of age or OEM.

3. If You Don’t Have Site-Wide Wi-Fi or IT Support

Prioritise:

• 4G or modem-based transmission
• Systems that don’t depend on your corporate network
• Zero local server requirements
• Fully managed data handling (cloud-based, secure)
  
  

Why It Matters:
Getting IT to approve access, open firewalls, or provision VLANs can take months. If your PdM system needs this upfront, it won’t get off the ground.

Factory AI Fit:
We run on a private 4G connection and handle all data transmission through an encrypted modem. No IT bottlenecks, no network configuration, and no latency.

4. If Your Team is Short-Staffed or Reactive

Prioritise:

• Automated fault detection
• Plain-language alerts
• Integration with existing maintenance workflows
• Minimal time to interpret insights
• Mobile-first design for techs in the field
  

Why It Matters:
PdM must reduce workload—not add another dashboard to manage. If your team is already stretched thin, simplicity and clarity become your most valuable features.

Factory AI Fit:
Our platform sends actionable alerts your techs can understand and act on. We reduce the need for manual inspections, prevent surprise failures, and free up time for high-value work. Most customers say Factory AI saves technician hours, not adds them.

5. If Leadership Is Skeptical or Budget-Constrained

Prioritise:

• Fast setup and fast ROI
• Pay-as-you-go pricing
• Pilot program availability
• ROI dashboards for monthly reviews
• Case studies from similar industries
  

Why It Matters:
Without leadership buy-in, your PdM project may never get beyond the trial phase. If your software proves its value in 30 days—and communicates that value clearly—you’ll win that buy-in fast.

Factory AI Fit:
We start with a low-risk pilot, typically covering 10–25 assets. Full installation in one day. ROI data in the first month. Our dashboards track dollars saved, not just faults detected. It’s not just predictive maintenance—it’s a business case builder.

External Read:
Reliability program: How to sell, implement, and sustain one

6. If You Need CMMS Integration—But Not Right Away

Prioritise:

• Systems that work standalone from day one
• Optional integrations (e.g. work order creation, asset linking)
• Compatibility with your existing CMMS (not just SAP or IBM Maximo)
  

Why It Matters:
Many PdM systems force early integration with your CMMS, causing IT delays and training headaches. A better route is proving the PdM works first, then linking it into your existing workflows.

Factory AI Fit:
We work beautifully with or without a CMMS. Want to trigger work orders? We can do that. But we won’t force it. We’ll help you prove value first—then automate the handoff when it makes sense.

Summary: Match Features to Reality

The best predictive maintenance system isn’t the one with the most features—it’s the one that matches your plant’s operating context. Ask yourself:

• Are you in a high-hygiene zone?
• Is your equipment old, manual, or offline?
• Do you have limited Wi-Fi or IT support?
• Is your team already reactive and under-resourced?
• Do you need to win over leadership fast?
  

Your answers will help you focus on what truly matters—and skip what doesn’t.

Part 4: Features That Matter vs. Features That Don’t — A Practical Checklist

There’s no shortage of features in the predictive maintenance (PdM) software landscape. But more features doesn’t always mean better results. In fact, some of the most effective tools are simple, fast, and focused—while flashy add-ons can slow teams down or create confusion.

This section gives you a clear, practical feature checklist—broken into five categories: alerts and insights, hardware and installation, integration, analytics and reporting, and user experience. We’ll call out whether each feature is essential, situational, or usually unnecessary, based on real-world experience in manufacturing environments.

1. Alerts & Insights

Start with what matters most: catching failures before they happen, and giving your team clear instructions on what to do next.

Must-have features:

• Automated fault detection that doesn’t require manual review or vibration expertise.
• Severity-based alerts that prioritise faults into critical, warning, or info.
• Plain-language diagnostics that clearly describe what’s wrong and what action to take.

Nice-to-have features:

• A historical fault tracker to monitor patterns over time.
• A live asset health score or colour-coded condition status, which is useful for visual summaries but doesn’t replace clear alerts.

Skip-it features:

• Raw waveform data dumps or alerts with no explanation. They create noise, not value.

Factory AI delivers all the must-haves by default—real-time alerts, easy-to-understand fault explanations, and prioritisation that makes decision-making easier.

2. Hardware & Installation

Hardware choices impact everything from install time to long-term usability. The right hardware should be fast to deploy, compliant with hygiene standards, and robust enough for tough plant conditions.

Must-have features:

• Wireless sensors that don’t require cabling or complex setup.
• IP67-rated enclosures suitable for washdowns in dairy, seafood, or frozen environments.
• Fast installation (under 30 minutes per asset) with no need for a third-party integrator.

Nice-to-have features:

• Optional high-frequency sampling for specialised machinery or fast-failure diagnostics.
• Edge processing (local analytics on the sensor) if latency is a concern or cloud access is limited.

Skip-it features:

• Proprietary hardware that can’t be reused across platforms.
• Non-weatherproof sensors in hygiene-sensitive areas.

Factory AI sensors install quickly, work in wet or cold environments, and don’t require a PLC or SCADA connection to operate.

3. Integration

PdM tools should work well out of the box, and grow into your ecosystem as needed. Integration matters—but only at the right stage.

Must-have features:

• The ability to deploy with no network dependencies. A 4G modem or similar method avoids delays from IT and lets you pilot quickly.
• Optional CMMS integration to link condition data with work orders or asset records—once value is proven.

Nice-to-have features:

• SCADA integration, but only if there’s a clear case for it (e.g. linking operating conditions to asset faults). Factory AI supports this, but only after performance is proven and leadership + IT are aligned.
• API access if you plan to combine PdM data with custom dashboards or enterprise analytics.

Skip-it features:

• Early-stage, deep integrations that slow down your pilot. Don’t start by wiring into your ERP or SCADA—start with proving value.

Factory AI allows for SCADA and CMMS integration—but only when it’s strategic, scoped, and adds clear value.

4. Analytics & Reporting

Your PdM system should help you report wins clearly. But too much complexity here can work against you.

Must-have features:

• A built-in ROI dashboard that calculates downtime prevented, faults caught, and cost savings. This is critical for building your business case.
• On-demand reporting tools you can use to generate summaries for site leadership, audits, or monthly reviews.

Nice-to-have features:

• Auto-generated weekly summaries sent via email, if your team actively reviews them.
• Downloadable CSVs or PDFs for traceability or exporting data to other systems.

Skip-it features:

• Custom visual builders or dashboard creation tools that require training. They often go unused and slow down adoption.

Factory AI includes a simple but powerful ROI dashboard, pre-built reports, and export options—without the need to build anything from scratch.

5. User Experience

The best PdM platform is the one your team will actually use. That means it needs to be accessible, intuitive, and quick to learn.

Must-have features:

• Mobile-friendly design that works on tablets or smartphones.
• Clean, simple interface that lets users find faults fast.
• Training that takes under an hour.

Nice-to-have features:

• Role-based access control to define who can see what, especially helpful at larger sites.
• A shared team dashboard for shift handovers or cross-functional coordination.

Skip-it features:

• Gamification, badges, or leaderboards. Trades don’t care about trophies—they care about fewer callouts.

Factory AI is built for frontline teams. It’s easy to learn, fast to use, and available wherever your team is—on the plant floor, in maintenance bays, or at home on-call.

Our Thoughts: Focus on What Moves the Needle

When comparing predictive maintenance platforms, don’t get distracted by buzzwords or software bloat. Focus on the features that make your maintenance smarter, faster, and easier.

If you’re not sure where to start, ask yourself these questions:

• Will this help me prevent downtime?
• Will it make my team faster or clearer in their decisions?
• Will it reduce my costs within 30–60 days?

If the answer is yes—it matters. If not, it’s a distraction.

Part 5: Aligning Your Team Around the Right Features — A Roadmap for Internal Consensus

Choosing predictive maintenance software is rarely a solo decision. While reliability engineers often lead the evaluation, successful adoption requires input (and alignment) from site leadership, IT, maintenance planners, and the frontline team on the tools.

In this section, we walk through how to bring everyone on the journey—so you choose the right features, avoid unnecessary ones, and increase the odds of long-term success.

1. Start With a Cross-Functional Goals Workshop

Bring together 3–6 people from key roles—maintenance, engineering, production, site leadership, and (if needed) IT. In 30–45 minutes, clarify:

• What is our biggest reliability challenge today?
• Where are we seeing the most unplanned downtime?
• Which assets are critical to production?
• What’s holding us back from solving these issues?
  

Then frame the question: What would a successful predictive maintenance system help us do that we can’t do today?

You’re not just building a feature list—you’re creating a shared success criteria that will help you evaluate options with clarity.

2. Prioritise Features by Outcome, Not Buzzwords

Next, take the table from Part 4 and tailor it to your plant. Highlight which features are:

• Must-haves: Mission-critical to solving your pain
• Nice-to-haves: Would be helpful but not essential
• Avoid-for-now: Distracting, expensive, or hard to maintain
  

This approach keeps the group focused on business value rather than “cool” features.

📌 Pro tip: Factory AI can help facilitate this exercise with our buyer's guide template.

3. Ask the Frontline Team What Would Actually Help

Too many PdM projects are selected for the trades, not with them. This leads to frustration, resistance, and shelfware.

Instead, ask:

• “What would help you spot breakdowns before they happen?”
• “Where do you spend the most time troubleshooting?”
• “Do you get alerts early enough to act?”
• “Are there machines you worry about every week?”
  

Then show them mockups or demos of PdM tools. Let them give feedback on:

• How clear are the alerts?
• Would they trust the insights?
• Would this save them time or add extra work?
  

Factory AI was designed with plant-floor teams in mind, so we take this step seriously. Our customers often say adoption happens because the techs actually want to use it.

4. Validate With IT and Leadership Last—Not First

This may seem counterintuitive, but it works.

Rather than letting IT gatekeep before anything is scoped, build your shortlist with your plant team, then bring in IT and site leadership with clear answers to:

• How secure is the system?
• Will it need network access?
• What data is collected and where is it stored?
• How do we control access?
  

For Factory AI:

• No IT involvement needed to start
• Modem-based, encrypted, cloud-secure
• Data is only vibration and temperature unless otherwise specified
• Minimal integration overhead
  

Leadership wants to know: does it work, what’s the ROI, and how soon do we see results?

Use our ROI of Predictive Maintenance blog post to prep your case.

5. Run a Pilot With Defined Success Criteria

Once you have alignment, it’s time to try it live. Keep the scope small and the expectations clear.

A good pilot should include:

• 25-50 assets across 1–2 production lines
• Clear criteria: uptime improvement, early detections, labour savings
• Target: ROI in <60 days
• Team roles: who’s reviewing alerts, who’s owning responses
• Weekly check-ins: what’s working, what needs adjusting
  

Factory AI pilots are designed to help you validate features in context—not just in theory.

We track:

• Number of faults caught
• Breakdown costs avoided
• PMs skipped
• Labour hours saved
• Time from alert to response
  

This gives you a ready-to-share success story that helps you justify expansion.

6. Create a Post-Pilot Feature Scorecard

After 4–6 weeks, reconvene your group and ask:

• Which features delivered value?
• Which weren’t used?
• What did we learn about our processes?
• What surprised us?
  

Then rank each major feature category from 1–5 based on impact.

7. Share the Win — and the Plan

Finally, share results with broader leadership:

• "We detected $32,000 in preventable failure risks."
• "We cut 22 hours of unnecessary inspections."
• "Frontline techs are actively using the tool."
• "We propose expanding to Line 2 next month."

Tie it to business outcomes. Use simple visuals. And keep the momentum going.

Final Thought: Start With What Matters

PdM software shouldn’t be an IT project or a data science exercise. It should be a maintenance tool that solves your day-to-day challenges.

By involving the right people, asking the right questions, and testing features in real conditions, you’ll build confidence in your choice—and get better results faster.

Final Call: Book a Demo and Bring Everyone Along

Aligning your team doesn’t have to be hard—but it does take a system that makes results obvious and the rollout easy.

Factory AI was built for exactly this:

• Designed for the crew on the tools
• Simple for site leaders to approve
• Friendly for IT to review
• Proven to pay for itself in under 6 months

If you want help starting the conversation—or you’re ready to bring PdM to your site the smart way—let’s talk.

👉 Book a demo now and see how the right features (and only the right ones) can help your team win.