Free Interactive Tool
Elevator IoT
ROI Calculator
Estimate what connecting your elevators returns: annual saving, payback period in months and net benefit. The expected reduction from predictive maintenance is a slider you control rather than a figure we assert, and every formula is printed on the page.
The Calculator
Set the Assumptions
Yourself, All of Them
Every default below is a round placeholder, not a benchmark. Replace them with your own figures. The result updates as you type or drag, and nothing you enter leaves your browser.
Inputs
Lifts you would connect. Default 100 is a placeholder.
Unplanned events per unit from your ticket history. Default 3 is a placeholder.
Callout charge plus technician hours plus any penalty exposure. The downtime cost calculator produces this figure for you. Default 440 is a placeholder.
How many unplanned events you expect to prevent through early detection. We publish no benchmark here on purpose. Default 20 is a placeholder. Test the case at both a low and a high value.
Interface device, enclosure, installation and commissioning per unit. Default 300 is a placeholder.
Recurring per unit per year: hosting, connectivity, support, firmware maintenance, licence. Divide a flat annual quote by the number of elevators. Default 60 is a placeholder.
Estimated return
Gross annual saving
USD 26,400
60 breakdowns avoided out of 300 per year at 20% reduction.
Net annual benefit
USD 20,400
After USD 6,000 annual platform cost
Payback period
17.6 months
On USD 30,000 one-time hardware cost
Net position after 3 years
USD 31,200
Net position after 5 years
USD 72,000
Annual breakdown cost, before and after
Bars show breakdown cost only. Platform cost and hardware cost are handled separately in the figures above.
This model counts avoided emergency breakdowns as the only benefit. Faster response, evidenced SLA performance, fewer disputes, less month-end reconciliation and revenue from a connected service offer are all real and all excluded, which makes the result deliberately conservative.
Want the hardware and platform figures replaced with a real scope for your controller types? That is what a discovery call produces.
Book a Discovery Call →Show Your Working
How This Is
Calculated
Seven lines of arithmetic, no hidden multipliers and no assumed benchmark anywhere in the chain. Every value that could flatter the result is an input you set.
Current breakdowns per year
number of elevators x breakdowns per lift per year
With your inputs: 100 x 3 = 300
Current annual breakdown cost
current breakdowns x fully loaded cost per breakdown
With your inputs: 300 x 440 = USD 132,000
Breakdowns avoided
current breakdowns x expected reduction
With your inputs: 300 x 20% = 60
Gross annual saving
breakdowns avoided x fully loaded cost per breakdown
With your inputs: 60 x 440 = USD 26,400
Annual platform cost
number of elevators x annual platform and support cost per lift
With your inputs: 100 x 60 = USD 6,000
Net annual benefit
gross annual saving - annual platform cost
With your inputs: USD 26,400 - USD 6,000 = USD 20,400
Payback period in months
(number of elevators x hardware cost per lift) / (net annual benefit / 12)
With your inputs: USD 30,000 / (USD 20,400 / 12) = 17.6 months
Net position after N years
(net annual benefit x N) - total hardware cost
With your inputs: (USD 20,400 x 3) - USD 30,000 = USD 31,200
Assumptions we are making
- Avoided emergency breakdowns are the only benefit counted. Everything else is excluded, which makes the output conservative.
- The reduction percentage applies uniformly across every elevator. In reality a minority of units usually generate a majority of the callouts, so a targeted first phase can outperform this model.
- Benefit begins immediately and accrues evenly through the year. A phased rollout ramps instead, so real payback is typically slower at the start and then catches up.
- Hardware is a single one-time cost with no replacement or refresh within the period shown.
- The platform and support cost is flat per lift per year and does not change with the number of elevators or contract term.
- No inflation, financing cost, discounting or tax treatment is applied. If your finance team requires a discounted cash flow, use the annual figures here as the input to it.
- Breakdown cost per event stays constant. If your labour rates are rising, the saving shown is understated.
Using the Result
Test the Case Before
You Present It
The whole model is one chain. Each link is an input you set above.
Early detection prevents a share of unplanned events.
Each avoided event saves its fully loaded cost.
Saving less the recurring platform cost per lift.
One-time hardware cost divided by monthly net benefit.
The most useful thing this calculator does is show you which assumption the case rests on. Drop the reduction percentage to a pessimistic value and look at the net annual benefit. If the case still stands, you have a strong proposal and a good answer for the first sceptical question in the room. If it collapses, you know exactly where the fragility is, and you can go and gather evidence on that single variable instead of defending a spreadsheet.
Then vary the number of elevators. Recurring platform cost scales with units while hardware cost is one-time, so the shape of the case changes with scale in a way that is easy to miss. A small pilot often looks poor on paper because the fixed learning cost is spread across few units, while the same economics across all your elevators look completely different.
Finally, consider running the model on your worst subset rather than all your elevators. If one controller family or one region generates a disproportionate share of your callouts, connecting those units first produces a better return than an even rollout, and the numbers here will show that clearly if you enter the subset figures instead of the average across all your elevators.
What this model cannot do is tell you what proportion of your breakdowns are genuinely detectable in advance. That depends on your controllers and your fault mix, and it is the first thing a controller survey establishes. Bring your fault history to a call and we will tell you what is visible in the signal your panels already produce.
Four levers decide whether the case holds. Test each one before you present it.
- Reduction percentage: set it low and high to see how sensitive the case is
- Number of elevators: recurring cost scales with units while hardware is one-time
- Cost per breakdown: take it straight from the downtime cost calculator
- Worst subset first: a targeted phase can beat an even rollout
Frequently Asked Questions
About the
Model
Because we would be making it up. The proportion of your breakdowns that are preceded by a detectable signal depends on your controller families, your fault mix, the age of your elevators and how quickly your team acts on an alert. A vendor publishing a single confident percentage is quoting a marketing figure, not measuring your elevators. Set the slider low and high, and judge the case by how sensitive it is to that one number.
Keep Reading
Related Pages
Replace the Placeholders
With Real Numbers.
The two inputs you cannot get from your own records are hardware cost per lift and the recurring platform cost, because both depend on your controller families and what your first phase covers. A discovery call turns those into scoped figures you can put in front of a board.