Is a smart building really more profitable? What to calculate before you invest

Who it’s for: Investors, developers, owners and executives.

The profitability of a smart building is not measured by the number of features installed, but by its ability to improve the building’s performance over time and keep its whole-life cost under control.

In brief

• A smart building only pays off if it genuinely improves how the building operates: equipment alone does not produce savings.
• Profitability is calculated on whole-life cost (investment, energy, maintenance, future changes), using assumptions specific to the project.
• No savings percentage or payback period is universal: you need a baseline, compared scenarios and measurement after commissioning.

A building can have high-performance air conditioning, modern lighting, motorised blinds and plenty of connected devices, and still not operate optimally.

Why? Because the performance of each piece of equipment does not guarantee the performance of the whole. Air conditioning can run while the premises are empty. Lights can stay on despite plenty of daylight. Equipment can run at the same time without any coordination, while data that would be useful for operations goes unused.

This is exactly where a smart building makes sense: making the building’s systems work together, according to actual needs.

But one question remains for every investor, developer, owner or executive:

Is building intelligence a profitable investment, and under what conditions?

To answer it seriously, you have to look beyond the purchase price of the equipment and examine whole-life cost, measurable benefits and real performance over time.

The real cost of a building does not stop at construction

When a property project is assessed, attention naturally focuses on the cost of the works, the equipment and the delivery schedule.

Yet once the building is handed over, the spending continues: energy, maintenance, equipment replacement, technical call-outs and day-to-day management. Over several decades, these costs can account for a large share of the total cost of ownership.

The whole-life cost of a building should therefore be considered over a defined period, including in particular:

• The initial investment: equipment, studies, design, cabling, integration, programming, testing and commissioning;
• Operating costs: electricity, heating, cooling, ventilation and other energy use;
• Maintenance: preventive servicing, repairs, diagnostics and component replacement;
• The cost of malfunctions: avoidable call-outs, inappropriate operation and business interruptions when they can be attributed to the installations;
• How the building evolves: adapting to new uses, reconfiguring spaces and adding features.

A solution that is cheaper to buy is therefore not necessarily the most economical in the long run.

Conversely, a sophisticated installation is not automatically profitable. Its value depends on how relevant its design is, the quality of its integration and how well it matches the building’s needs.

The right question is not simply: “How much does automation cost?”

It is rather: “What whole-life cost can we achieve with and without this solution, for a comparable level of service?”

Where is the savings potential of a smart building?

Automation does not produce savings just by being there. It has to correct inappropriate operation, avoid unnecessary consumption or improve the way equipment is run.

Smart lighting control

In an office, a hotel or a retail space, lighting can be adapted to occupancy, daylight and opening hours.

Presence detection, dimming and time scheduling reduce periods of unnecessary operation.

The result, however, depends on actual opening hours, the existing equipment, the settings and the occupants’ needs.

Heating, ventilation and air-conditioning control

Heating, ventilation and air-conditioning (HVAC) systems are another major area.

Coherent control can adapt setpoints to occupancy schedules, outdoor conditions and the needs of each zone. It can also avoid certain operating conflicts, such as heating and cooling the same space at the same time.

Performance here depends on the quality of the equipment, the control logic, the settings and verification of how the system actually runs.

Coordinating blinds and daylight

Coordinated control of blinds, lighting and air conditioning can limit unwanted solar gains, make use of daylight and preserve visual comfort.

Its value depends in particular on the building’s orientation, its glazed areas, the climate and how the building is used.

Supervision and energy monitoring

Supervision gives a better understanding of how the building operates: abnormal consumption, equipment running outside scheduled hours, gaps between setpoints and measured conditions.

This information makes it easier to identify anomalies and put corrective action in place.

Two things must nevertheless be kept apart: measuring consumption does not reduce it automatically. The value appears when the data supports decisions, and then confirms their results.

The key principle: savings come from a real improvement in how the building operates, not from the mere fact of having installed connected equipment.

How do you calculate the return on investment?

Return on investment should be assessed using data specific to the project, not a savings percentage presented as universal.

A first approach is to compare the cost of a conventional solution with that of a solution including relevant automation. You then estimate the additional annual benefits, separating energy savings, maintenance savings and any other genuinely quantifiable benefits.

A simple formula gives a first indicator:

Simple payback period = additional investment ÷ additional net annual benefit

The net annual benefit is the annual savings and gains retained, minus the recurring additional costs of the solution.

This method is a first filter. It does not replace a full financial analysis, because it takes no account of the time value of money, changes in costs or future expenditure.

A worked example: €20,000 of additional investment

Let us take a purely illustrative example, unrelated to any real client project. A building has the following assumptions:

• Additional investment for the automation solution: €20,000;
• Estimated annual energy savings: €5,000;
• Annual net savings on maintenance and operations, excluding energy: €1,000;
• Additional annual costs for maintaining the solution: €500.

The estimated net annual benefit is then:

€5,000 + €1,000 − €500 = €5,500 per year.

The simple payback period is:

€20,000 ÷ €5,500 = about 3.6 years.

On the basis of these assumptions, the additional investment would be recovered in just under four years.

This result only holds, however, if the expected savings materialise. It must be checked against measured consumption, energy tariffs, installation and maintenance costs, and the service life of the equipment.

And what if the expected savings do not materialise? With €3,000 of energy savings instead of €5,000, all other assumptions unchanged, the net annual benefit drops to €3,500 and the payback period rises to about 5.7 years. A €2,000 difference in a single assumption extends the payback by more than two years: this is why savings must be measured, not just estimated.

This example is neither a performance forecast nor a guarantee of profitability. It simply shows how to reason from explicit assumptions.

Why payback period is not enough

Two solutions can have a similar payback period and yet produce very different economic results over twenty years.

For an investment decision, it is better to complete the calculation with a whole-life cost analysis over the period studied and, where the data allows, a net present value (NPV).

This approach takes future cash flows and their discounting into account. It allows several scenarios to be compared more rigorously, provided the same assumptions are used for duration, costs and level of service. Possible replacements, tariff changes, maintenance costs and the need to adapt the installations must also be planned for.

A fast payback is attractive. Lasting economic value is even more so.

Do comfort, maintenance and flexibility have economic value?

Yes, but that value must be assessed methodically.

The profitability of a smart building is not limited to the energy bill. Some improvements can deliver operational or property benefits, provided they can be linked to relevant indicators.

These benefits are not all demonstrated in the same way:

Only energy can be valued directly and quickly. Maintenance needs several years of hindsight, while comfort and property value need specific indicators, before they can be included in a profitability calculation.

Occupant comfort

Better-controlled temperatures, suitable lighting and coherent management of spaces can improve conditions of use.

In a workplace, indicators such as comfort-related complaints, temperature deviations or occupant satisfaction can be tracked.

It would nevertheless be unwise to attribute a rise in productivity or a fall in absenteeism to automation alone. These outcomes depend on many factors.

Maintenance and operational continuity

Supervision and fault detection can help technical teams identify certain problems more quickly.

The economic value depends in particular on how often breakdowns occur, the cost of call-outs, how critical the equipment is and the ability to fix anomalies before they become more expensive.

For a hotel, a healthcare facility or a heavily occupied commercial building, the consequences of an interruption can be significant. They must still be assessed in their real context.

Scalability of the installations

A building changes over time: spaces are reconfigured, uses evolve and new equipment appears.

A well-designed architecture can make these changes easier and limit some rewiring or heavy works.

This advantage depends on the choice of technologies, interoperability, documentation and the availability of the skills needed to operate the building.

Property value

The quality of the technical installations, energy performance, comfort and ease of operation can all contribute to the appeal of a property asset.

Potential appeal must not, however, be confused with a guaranteed increase in market value.

To quantify any effect on property value, you need comparable market data, taking into account location, the condition of the building, its use and demand.

Why some automation projects fail to deliver

A project can use high-performance technologies and still produce disappointing results. Several mistakes come up again and again:

• Automating without analysing needs. Adding features that do not match actual use increases cost without guaranteeing a proportionate benefit;
• Choosing equipment before defining the architecture. A product-led approach can lead to systems that are hard to connect and maintain;
• Neglecting integration. Heating, air conditioning, lighting and supervision must work together coherently. Interoperability and clearly defined responsibilities are essential;
• Forgetting commissioning. An installation must be tested in representative conditions: schedules, sensors, setpoints and control sequences must all be checked;
• Not measuring results. Without a baseline or monitoring after commissioning, it becomes hard to know whether the expected performance has been achieved;
• Overlooking the future operators. A complex, poorly documented or hard-to-use solution risks being badly operated, even if its original design was sound.

Profitability is therefore prepared from the earliest stages of a project. It depends as much on design choices and how they are implemented as on the equipment itself.

When should smart building be built into a project?

As early as possible, while architectural and technical choices can still be coordinated.

In new construction, this foresight makes it possible to define needs, the interfaces between technical packages, the infrastructure required and the performance targets. It also makes coordination easier between architects, design offices, engineers, installers and integrators.

In an existing building, the process usually starts with an audit: installations in place, consumption, uses, technical constraints and opportunities for improvement.

In both cases, a rigorous approach follows a similar logic:

1. Establish a baseline. Understand consumption, schedules, uses and malfunctions;
2. Set objectives. Specify the expected results for energy, comfort, maintenance and operations;
3. Compare several scenarios. Assess investment, recurring costs, constraints and estimated benefits;
4. Design a coherent architecture. Define the systems, interfaces, protocols and options for future change;
5. Test and commission. Check the functions and the interactions between equipment;
6. Measure and optimise. Compare results with objectives, correct deviations and adjust the settings.

This approach shifts the logic from buying equipment to delivering building performance. It is also at the heart of our work in digital strategy and design and integration.

Is a smart building more profitable in the long term?

It can be, but not in every configuration, and not at any price.

Profitability depends in particular on the building’s profile, its occupancy hours, its technical systems, its initial consumption, its existing level of automation and the quality of its operation.

A building whose consumption is already well controlled will not necessarily have the same savings potential as one whose installations run without coordination. Likewise, a solution suited to a large commercial building may be out of proportion for a small building with limited needs.

There is therefore no savings percentage or payback period that applies to every project.

European and international references point the same way:

• The Smart Readiness Indicator (SRI), the European indicator of a building’s smart readiness, comes from the Energy Performance of Buildings Directive. It assesses a building’s ability to use smart technologies according to three key functionalities: optimising energy efficiency and in-use performance, adapting its operation to the needs of occupants, and adapting to signals from the electricity grid;
• The ISO 52120-1 standard, which covers the contribution of building automation, controls and building management to the energy performance of buildings, provides a simplified factor-based method for a first estimate, followed by detailed methods to assess the actual effect on a given building.

In other words, even the standard separates the first estimate from the building-specific assessment. The right approach is to set objectives, establish a baseline, compare scenarios and verify results after commissioning.

Frequently asked questions

What payback period can you expect from a smart building?

There is no universal payback period. It depends on the additional investment, the savings actually achieved and the recurring costs of the solution. The simple payback period gives a first order of magnitude, to be completed by a whole-life cost analysis over the period studied.

Can an existing building be made smarter profitably?

Yes, provided you start with a diagnosis: installations in place, consumption, uses and malfunctions. It is this diagnosis that reveals where the improvement potential lies, and therefore whether the investment makes sense.

How can you check that promised savings are real?

By establishing a baseline before the works, then monitoring consumption after commissioning, under comparable weather, occupancy and schedules. Without this measurement, a saving remains an estimate.

Conclusion: invest in performance, not complexity

A smart building is not necessarily the one with the most equipment, the most features or the most spectacular interface.

It is a building whose systems meet real needs, work together, can be operated efficiently and evolve with its uses.

Its profitability is built through coherent decisions: appropriate design, controlled integration, rigorous commissioning and monitoring that measures the performance achieved. This is also the spirit of the BACS decree in France: measure, understand, then control.

For an investor or an owner, the question is therefore not whether a smart building is always profitable. It is to determine which solutions create measurable value for a given building, over what period and at what cost.

It is this analysis that turns a technology expense into an informed investment decision.

At ExaBuilding, this approach puts the coherence of systems, the anticipation of needs and the overall performance of the building at the heart of every project.

Planning a construction, renovation or automation project? Talk to an expert

Methodological note: the financial example in this article is hypothetical. Savings, costs and payback periods must be established from the data of the project concerned, and results vary with the characteristics of the building and its operating conditions.

Sources

Institutional and standards references

• European Commission, “Smart readiness indicator”: indicator introduced by the 2018 revision of the Energy Performance of Buildings Directive (EPBD), framework set out in Commission Delegated Regulation (EU) 2020/2155: https://energy.ec.europa.eu/topics/energy-efficiency/energy-efficient-buildings/smart-readiness-indicator_en
• ISO, “ISO 52120-1:2021, Energy performance of buildings: contribution of building automation, controls and building management, Part 1: general framework and procedures”: https://www.iso.org/standard/65883.html