ROI for AGV and AMR - how to calculate return on investment? | MOBOT

ROI for AGV and AMR - how to calculate the return on investment in autonomous vehicles?

A complete guide to the ROI and payback period calculation methodology for AGV/AMR robot implementations - formulas, industry examples and the most common mistakes.

Investing in a fleet of AGV or AMR robots is one of those decisions that are rarely made on impulse. The financial director wants to see hard numbers, the production manager wants to be sure that the process will not stop, and the management board asks one thing: After how many months will this investment pay off?

The answer is: it depends - but it can be calculated precisely if you know what to look for. In this article, we show step by step how to methodically calculate ROI (Return on Investment) for autonomous robots, what costs and savings need to be taken into account, where mistakes are most often made in such calculations, and what the full financial model of such an implementation looks like in practice - with examples for warehouse, production and e-commerce.

Table of contents

1. What exactly is ROI and how does it differ from the payback period?

Before we get to the numbers, it's worth clarifying the concepts, because when talking about automation, several different indicators are often mixed together.

ROI (Return on Investment) is the ratio of net profit from an investment to its cost, expressed as a percentage. It answers the question: "how much have we earned in relation to how much we have invested?" It can be calculated for any period - a month, 12 months, 36 months, the entire fleet life cycle.

Payback period is the time after which the sum of savings generated is equal to the expenditure incurred. This is the question that is most often asked in practice: "after how many months will this investment pay off?"

TCO (Total Cost of Ownership) is the total cost of owning the solution over a given time horizon - it includes not only purchase, but also service, energy, consumable parts, possible fleet expansion, IT support, etc. TCO is the foundation on which ROI is built - without a reliable TCO, every ROI calculation is incomplete.

NPV (Net Present Value) and IRR (Internal Rate of Return) are more advanced indicators that take into account the time value of money (discounting future flows). In practice, AGV/AMR projects with a 3-5 year horizon are rarely necessary, but for larger investments (several dozen or so robots, external financing), the finance department may ask for them.

For most implementation projects in Polish factories and warehouses, two indicators are most important: the payback period (because this is a question asked by the management) and ROI in a 12/24/36/60-month perspective (because it shows profitability over time, and not only the moment of payback).

2. Why ROI for AGV/AMR is calculated differently than for regular equipment

The ROI calculation for an autonomous robot differs from the typical CAPEX calculation for a production machine for several reasons:

Therefore, a solid ROI calculation for AGV/AMR requires building a full cost model on both sides of the equation – current state and post-implementation state – and not just comparing the price of the robot to the “estimated savings on the job.”

3. Step 1: Calculate the full investment cost (CAPEX)

This is the cost side that's easiest to underestimate - companies often only count the list price of a robot, leaving out the rest. The full CAPEX of an AGV/AMR implementation project usually includes:

  • Purchase price of robots - multiplied by the actual number of pieces needed to complete the task (not the "wishful" number, but resulting from the flow analysis).
  • Additional equipment - extensions, grippers, masts, transport equipment dedicated to a specific process.
  • Charging infrastructure - stations/chargers, their number (usually not 1:1 with the number of robots, but resulting from work cycles and charging time).
  • Implementation cost - route programming, integration with WMS/MES/ERP, map configuration, tests, operator training.
  • Optional equipment - sensors, floor markings, automatic gates, integration with elevators or shelves.
  • Delivery and launch cost - logistics, implementation time counted as an opportunity cost (how many weeks/months does the launch take before the fleet starts generating savings).

Good practice: count CAPEX as the total sum of the project, not the unit price of the robot - only the total sum, divided by monthly savings, gives a real payback period.

4. Step 2: Calculate the operating costs of the robot fleet (OPEX)

The robot does not work for free after implementation. To get the full picture, you need the running costs page of the new solution:

  • Energy consumption - kWh cost for companies × robot consumption per working hour × number of working hours per day × working days per month.
  • Service and inspections - most often billed as a recurring rate (e.g. every 60 months) or as a monthly/annual subscription.
  • Consumable parts - batteries, wheels, sensors subject to wear.
  • Project service cost - if the fleet is in the rental model, there is usually a fleet service/management fee.
  • Possible financing installments - leasing or rental if the robot is not purchased for cash.

The sum of these items on a monthly basis is the reference point against which savings are compared - not with the purchase price, but with the sum of the costs of maintaining the new solution.

5. Step 3: Calculate the costs of the current state (baseline)

This is the element that is most often taken lightly - and the credibility of the ROI calculation depends on its quality. Baseline is the full cost of completing the same transport task using the current method, before robots were implemented. Items to include:

  • The cost of employing an employee in a given position - not only the gross salary, but the full cost of the employer (ZUS contributions, benefits, overheads), calculated per month and per shift.
  • Number of positions replaced - how many people are currently performing internal transport tasks that are to be taken over by the robot, and in how many shifts per day.
  • Job availability factor - absences, leaves, turnover, unproductive time - the real cost of an "effective working hour" is usually higher than the hourly rate itself.
  • The cost of renting or leasing forklifts, if transport is currently carried out by this means.
  • Energy consumption of current equipment (e.g. electric wheelchairs) - analogous to calculations for robots.
  • Indirect costs - damage to goods and shelves, accidents and their costs (OHS, downtime, compensation), picking errors, overtime costs during seasonal peaks.

Only a comparison of the full baseline with the full cost of the new solution gives a real difference, which is the basis for calculating monthly savings.

6. Step 4: Identify all sources of savings i dodatkowych przychodów

Savings from implementing AGV/AMR rarely come down to "fewer jobs". It is worth dividing them into categories so as not to miss any:

Direct savings (hard, easy to calculate)

  • reduction of employment costs in internal transport positions
  • reduction of forklift rental/leasing costs
  • lower energy consumption (AMR/AGV robots usually consume less energy than internal combustion forklifts or large electric forklifts)
  • reduction of overtime and work in additional shifts

Indirect savings (significant, but need to be estimated)

  • less damage to goods, packaging and infrastructure (robots drive repetitively and predictably)
  • fewer accidents and health and safety incidents related to internal transport
  • lower turnover in difficult, monotonous positions (the cost of recruiting and implementing a new employee is sometimes overlooked, but is real)
  • fewer logistic errors (delivery of wrong material, address errors)

Revenue and quality benefits (more difficult to value, but real)

  • higher process throughput - ability to handle larger volumes without additional employment
  • work 24/7 or in additional time windows without the need to employ a third shift
  • flexibility to scale the fleet up or down depending on seasonality (especially important in the rental model)
  • operational data from the fleet management system - better process visibility, ability to optimize the layout

Recommendation:In the basic ROI calculation, it is worth basing the direct savings on direct savings (they are easy to defend before the management), and presenting indirect savings and qualitative benefits as an additional, conservatively estimated bonus - this builds the credibility of the analysis.

7. Step 5: Build the formula and calculate the ROI and payback period

Having complete data from steps 1-4, the calculation comes down to a few simple formulas.

Net monthly savings:

Monthly Savings = As-is Cost (per month)

                        − OPEX cost of the new solution (monthly)

 

Payback period (in months):

Payback period = total CAPEX / Net monthly savings

 

ROI over a given period (e.g. 12, 24, 36 months):

ROI (%) = [(Monthly savings × number of months) − CAPEX] / CAPEX × 100%

 

It is worth calculating ROI for several time horizons at the same time (e.g. 12, 18, 24, 36, 60 months) - for many implementations the result after 12 months is still negative (because the investment has not yet paid off), and only after exceeding the payback period does the ROI begin to grow dynamically. Showing this in the form of a chart (the "investment balance" line accumulated over time) is much more convincing to the management than a single percentage number.

8. Step-by-step numerical example

The example below is for illustration purposes only - it shows the methodology, not a specific offer. The actual numbers depend on the industry, layout, number of changes and process specifics.

Assumptions

  • The company replaces the work currently carried out in 3 shifts with a total of 6 internal transport positions.
  • The full cost of employing one employee (employer's cost, overhead) is approximately PLN 9,000 per month.
  • Additionally, the company gives up renting 2 forklifts for approximately PLN 2,800 per month each.
  • The new fleet includes 5 AMR robots, the total CAPEX of the project (robots, accessories, chargers, implementation) is PLN 1,200,000.
  • The monthly OPEX of the new fleet (energy, subscription service) is PLN 18,000.

Calculations

Current cost (monthly): 6 × PLN 9,000 + 2 × PLN 2,800 = PLN 54,000 + PLN 5,600 = PLN 59,600

Cost of the new solution (monthly): PLN 18,000

Net monthly savings: PLN 59,600 − PLN 18,000 = PLN 41,600

Payback period: PLN 1,200,000 / PLN 41,600 ≈ 28.8 months (approx. 2 years and 5 months)

ROI after 36 months: [(PLN 41,600 × 36) − PLN 1,200,000] / PLN 1,200,000 × 100% ≈ 24.8%

ROI after 60 months: [(PLN 41,600 × 60) − PLN 1,200,000] / PLN 1,200,000 × 100% = 108%

The same calculation scheme - regardless of the scale - allows you to assess the profitability of each AGV/AMR implementation project, as long as the input data (baseline and OPEX) are reliably calculated.

9. ROI in practice: warehouse, production, e-commerce

The ROI calculation methodology is universal, but what actually determines the amount of savings and the length of the payback period varies depending on the industry and the nature of the process. Below are the three most common AGV/AMR application scenarios - without reference to specific implementations or customer data, only as a description of typical ROI characteristics in a given segment.

Warehouse and distribution center

Typical scenario: transporting pallets or containers between the receiving area, the racks and the picking area, handled today by forklifts or hand pallet trucks on short, repetitive routes.

ROI characteristics:a large number of transport cycles during a shift, high work intensity in 2-3 shifts, in many cases clear seasonality of volume. The cost baseline can be one of the highest among all applications - it includes not only the full-time positions of forklift operators, but also the costs of equipment rental, UDT inspections and the increased risk of collisions in narrow aisles. Thanks to the high repeatability of routes, fleet selection is relatively easy to model, which often translates into one of the shorter payback periods in the AGV/AMR application portfolio.

Production - supply of assembly lines and sockets

Typical scenario: delivery of components to nests or production lines in the rhythm of production (so-called milk run), receipt of finished products, inter-operational transport between process stages.

ROI characteristics:The number of transport cycles is sometimes lower than in the warehouse, but the key factor here is the precision and repeatability of deliveries - the lack of material at the production cell generates the cost of line downtime, which is much higher than the cost of transport itself. When calculating ROI for production, in addition to reducing transport jobs, it is worth taking into account - as a quality benefit - the reduced risk of downtime resulting from errors or delays in material delivery. ROI here depends largely on how closely the fleet is synchronized with the production schedule, and not solely on the number of people replaced.

E-commerce and fulfillment

Typical scenario: highly seasonal order volumes (peaks such as Black Friday or the pre-holiday period), pressure on order fulfillment time (order-to-ship), transport of containers between the picking, packing and shipping zones.

ROI characteristics: Seasonality is the main calculation challenge here - the cost baseline in the peak season can be much higher than in the rest of the year, mainly due to more expensive temporary and agency work. This is an environment in which the fleet rental model (RaaS) works particularly well, allowing you to flexibly increase the number of robots during peak times without permanently increasing CAPEX. A reliable ROI calculation for e-commerce should be calculated on an annual basis, taking into account volume fluctuations, and not on the basis of a single, averaged month.

10. Purchase, leasing or rental - how the financing model changes ROI

The method of financing the fleet has a significant impact on the shape of the return on investment curve, even if the total cost in the long term is similar.

Cash purchase - the highest one-time expense (CAPEX), but the lowest monthly cost in OPEX. The investment balance curve starts well "below the line" and grows most rapidly after crossing the return point - this is a financially beneficial option in the long term (3-5+ years) if the company has capital.

Leasing - spreads the cost into installments, lowering the entry threshold. The payback point calculated on a cash basis is sometimes shorter than in the case of a cash purchase, because the first payment is lower (usually several percent of the value), but the cost of financing (interest/lessor's margin) must be added to the total TCO.

Rental / RaaS (Robot as a Service) model - the company pays a monthly fee for the availability of the fleet, which often also includes service and maintenance. This is the lowest barrier to entry and the most predictable monthly cost, but usually the highest overall cost over the long term (5+ years) compared to purchasing. This model is particularly attractive when the company wants to remain flexible (scaling the fleet up/down, testing the process before making a purchase decision) or when it wants to protect financial liquidity and CAPEX.

In practice, a good ROI calculation shows all three scenarios side by side - this allows management to consciously choose a financing model that suits the company's strategy, not just the lowest unit price.

11. Factors that most influence the calculation result

Not every internal transportation automation project has the same return potential. Several variables have a particularly large impact on the result:

  • Number of shifts and work intensity. The more shifts currently handled manually (especially more expensive night and weekend work), the higher the cost baseline and the shorter the payback period.
  • Transport distances and route frequency. Longer routes and a greater number of transport cycles per hour require a larger fleet, but also generate greater savings in man-hours.
  • Cost of labor in the region and industry. Rising employment costs (minimum wage, deficit of manual workers) systematically shorten the payback period from automation year to year.
  • Fleet utilization rate. A robot standing idle for half a shift does not generate a return - a good analysis of flows and the correct selection of the number of robots to the actual demand is crucial.
  • Integration complexity. Implementation requiring deep integration with WMS/MES/ERP, construction of infrastructure (gates, elevators, separate zones) extends the implementation time and increases CAPEX, which extends the payback period - but usually also increases the quality and scalability of the solution.
  • Seasonality of demand. With high seasonality, it is worth considering a rental model with the option of scaling the fleet, instead of purchasing a maximum fleet "just in case".

12. The most common mistakes when calculating ROI for AGV/AMR

Implementation experience shows several recurring errors that distort the calculation result - usually in favor of an overly optimistic picture:

  • Comparing the robot price with the gross salary - instead of the full cost of the employer and the full baseline.
  • Ignoring the OPEX costs of the new solution - treating the robot as a "one-off" investment, without taking into account energy, service and consumable parts in subsequent years.
  • Too optimistic assumption of the number of positions replaced - without analysis of the actual transport workload during a shift.
  • Skipping the implementation time - a fleet that will actually start operating only 2-3 months after signing the contract "loses" this time in the calculation of the payback period counted from day zero.
  • No consideration of seasonality and production variability - calculation based on the peak season gives a falsely short payback period.
  • Calculating ROI only in one time horizon - without showing the trend (12/24/36/60 months), which makes it difficult to assess whether the investment is "accelerating" or "flattening out" over time.
  • Omitting indirect benefits completely - on the other hand, some companies do not take into account the reduction of damage, accidents or turnover at all, which lowers the real profitability of the project.

13. How to build your own ROI model (and a ready-made tool that makes it easier)

The above methodology - full baseline, full OPEX of the new solution, breaking down savings into categories and calculating the payback period and ROI in several time horizons - is universal and can be reproduced in a spreadsheet for any project.

In practice, the most time is spent not on the pattern itself, but on reliable collection of input data: the number of shifts, employment costs, transport distances, energy prices and technical parameters of robots selected for a specific process.

To speed up this analysis, we provide an ROI calculator for AGV and AMR (mobot.pl/roi), which allows you to quickly estimate the approximate payback period based on several basic parameters of your process. This is a good starting point for an initial assessment of profitability - a full, precise calculation (taking into account the specific layout, number of robots, financing model and individual conditions) is always created at the stage of a detailed offer, prepared after a site visit or analysis of the factory layout.

14. Summary

A reliable ROI calculation for AGV/AMR robots is not just one number, but a full financial model combining two sides: the real cost of the current situation (full cost of employment, equipment rental, energy and indirect costs) and the full cost of the new solution (implementation CAPEX plus monthly OPEX of the fleet). Only the difference between these two sides, spread over time, gives a reliable payback period and an ROI indicator that will defend itself against questions from the management board and the finance department.

Key rules to remember:

  • count the full cost of the investment, not just the list price of the robots
  • count the full baseline of the current state, not just gross salary
  • separate savings into direct, indirect and qualitative – and treat them with the appropriate level of certainty
  • show the result in several time horizons (12/24/36/60 months), not just one number
  • compare financing scenarios (purchase, leasing, rental) - the choice of model affects the shape of the return curve as much as the technology itself

It's best to check this with your own numbers. Start with a few minutes with our online ROI calculator (mobot.pl/roi) - it's a quick and safe way to get an idea of ​​the order of magnitude before you commit more time to the topic.

And if you are interested in the initial result (or you simply prefer to talk to a person right away, rather than using a form) - arrange a conversation with a specialist in the launch of MOBOT® projects, we will be happy to sit down together to discuss your case. You don't need to have a ready-made layout or all the numbers counted - just tell us what internal transport looks like in your factory or warehouse today, and we will help you with the rest step by step. At this stage, it is just a regular conversation between partners about your challenges, not a commercial offer. It will result in a detailed ROI analysis tailored to you, based on the real layout and specificity of the process in your factory or warehouse - we will be happy to help you calculate how much you can gain from automation.

 

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