Lessons learned from using the revised INREV reporting guidelines

In 2023 the European Association for Investors in Non-Listed Real Estate Vehicles (INREV) announced the publication of an updated set of reporting guidelines. Among non-ESG guidelines and metrics, the updated Reporting module includes asset-level reporting guidelines and a set of sustainability reporting disclosures, complemented by a set of required and recommended ESG KPIs, which now cover not only the manager’s operational control, but also that of the occupier.

While early adoption has been encouraged, the guidelines will become fully effective for reporting periods ending on 31st December 2024 onwards – so we expect many companies to be preparing to implement them in the run-up to 2025.

Verco has supported a large client with early adoption of the new guidelines, and we would like to share our experience, along with the pitfalls and the difficulties experienced along the way.

What KPIs are required?

As previously, the sustainability requirements include qualitative disclosures. For example, this includes describing the overall ESG strategy, objectives and targets of the vehicle and how these were developed (RG70); disclosing any ESG initiatives undertaken (RG72), disclosing the current level of compliance with applicable ESG legislation (RG75) and more.

RG73 mandates that a set of essential sustainability key performance indicators (KPIs) should be defined for the vehicle, and that as a minimum these should include the list specified by INREV in Table 1 of the guidelines.

How should they be calculated?

There are 28 mandatory indicators. While each indicator is stated, there is no prescribed methodology for calculating it. As in the last version of the INREV guidelines, any widely recognised methodology can be used, including GRESB or CRREM. The methodology needs to be explained, the degree to which estimated data was used needs to be stated, and both absolute and like-for-like data should be considered.

How is this different from before?

While the old INREV guidelines followed roughly the same principle in terms of allowing flexibility in the methodology followed, most companies using them focused their ESG indicator reporting on landlord-controlled utilities and GHG, and many included only actual data in their disclosures.

The revised guidelines take ESG reporting to a whole-building view, by requiring disclosure of energy use both under the manager’s and the occupiers’ operational control, and by explicitly including estimated data in separate indicators (e.g. ENV3, for estimated energy consumption).

Furthermore, the new guidelines are significantly more prescriptive, with indicators included not only for utilities and GHG, but also for data coverage, renewable energy, the extent of green building certifications and energy ratings, and climate risk – both physical and transition.

The first attempt at reporting…

In 2024, Verco was appointed by a client to prepare quantitative disclosures for multiple funds in line with the new INREV guidelines, for the reporting year ending either 31st December 2023, or 31st March 2024, depending on the fund.

Highlighted below are three main challenges which had to be surmounted when reporting:

1) Developing a whole-building view for energy

Verco already held utility consumption data for the client’s assets, where this was available. Most of this data was for buildings and spaces under landlord operational control, with some exceptions, including some cases where tenant-obtained utility consumption figures had been obtained for GRESB reporting. Verco also held information, provided by the client’s property managers, on whether this data covered the common parts or the whole building, and would conduct quarterly variance checks to assess and explain any significant changes in reported consumption.

To comply with the required KPIs, Verco supplemented the actual data with estimated figures to arrive at a whole building view for energy. Where actual utility consumption data was not available for a given space (e.g. common areas, or whole building), Verco would use a standard energy intensity benchmark specific to that property type, and apply this to the recorded floor area to generate estimated electricity and gas figures.

For hypothetical buildings, this would yield the following:

Single-let Building A: actual data available for 10 months for the whole building. Extrapolated to 12 months; no benchmark-based estimation done.
Multi-let building B: actual data available for 12 months for common parts, no data available for the tenant units. Benchmark-based estimation done for the NLA of the building.

This approach, while efficient when dealing with a large portfolio, turned up a few difficulties. There are no global, widely accepted, and recent energy intensity benchmarks that could be applied to a portfolio as diversified as this client’s. The proprietary benchmarks selected by Verco were chosen on the basis of how granular, recent and reliable the underlying data was. They presented the best compromise - but they still had limitations.

These limitations came to light as some fund managers queried the benchmark-estimated consumption, citing reasons why they believed the benchmark-derived figures were either under- or over-estimating their portfolio energy consumption. For instance, the benchmarks did not cover the eventuality of data centres, and were significantly underestimating the energy consumed by the tenants in a few shopping centres, as the benchmark applied was based on typical shopping centre energy consumption. To correct for this, an exception was made: Verco researched and derived a custom benchmark for the assets which had data centres, and applied this modified benchmark to them.

In another case, a residential portfolio had no actual energy consumption data available, but had conducted a set of energy audits a few years prior. As this portfolio consisted of very similar buildings, located in the same region, the information collected during those audits was used by Verco to create a custom benchmark to be applied to this fund’s assets only.

2) Assigning estimated energy to GHG scopes

With the first hurdle surpassed, the estimated energy then needed to be assigned to either Scope 1 and 2, or Scope 3. The client reported on an Operational Control basis, so it was agreed that a building’s management status would be used as a proxy for whether operational control exists over its utilities. The following logic was agreed: benchmark-estimated emissions in a managed building would be assigned to Scope 1 & 2, while in an unmanaged building they would be assigned to Scope 3.

When fund managers reviewed the draft reports, they flagged that in some cases, they believed that the management status did not adequately reflect operational control. Some fund managers received draft reports which had Scope 1 and 2 emissions which they believed were too high, and did not reflect the amount of influence they actually had on the assets’ energy and GHG performance. As previous reporting had focused on actual data, this issue had not arisen before.

Unfortunately, the timescales of report production were quite short, and there was no time to go out to the many property managers with a questionnaire. As a result, a hybrid approach was adopted: for most buildings, the logic described above was followed, but an exception was made for certain property types (e.g. residential, where the operational control always sits with the tenants) and several portfolios where the fund manager could provide an explicit confirmation that the management company - and therefore the landlord - held no operational control over the building’s energy consumption.

3) Interpreting the output

The new set of required metrics, while structured and logical, prove to be somewhat unintuitive when viewed in a table. This is because actual and estimated data are reported separately, in ENV1 (landlord actual), ENV2 (tenant actual), ENV3 (tenant and landlord estimated), and ENV4 (all data together). When looking at a fund, it is difficult to use the numbers in these four metrics to understand what has happened.

For instance, due to the timing of the reporting, which occurred before GRESB-related tenant data collection, there were many funds where tenant data was only available for Year 1 of the report, and not for Year 2. This data would then be extrapolated as estimated figures in Year 2, which would yield a massive % reduction in ENV2 (tenant actual energy), and a corresponding massive % increase in the tenant portion of ENV3. Meanwhile, this would not affect the whole building energy consumption (ENV4), which would remain mostly driven by the actual trends in the landlord energy (ENV1). The same issue is seen with the GHG metrics.

Sharing our learnings

To learn from the process Verco and our client went through, we recommend the following:

Involve your fund and property managers. In this reporting cycle, the fund managers provided invaluable feedback which allowed for adjustment and fine-tuning of the methodology. Involve your stakeholders in confirming the assumptions – this will help you arrive at a view which is accurate and complete.
Start by agreeing and documenting a methodology. There are several significant methodological decisions to be made. Beyond the examples described here, you will also need to decide how to calculate your exposure to energy-inefficient assets for metric ENV28, which is an SFDR-derived metric and has a complex definition of its own.
Do a test run. Try preparing a report early using old data, leaving time for additional data collection if required. When doing the calculations, you may realise that you are missing a key piece of the puzzle, and if you leave enough time, you may be able to collect this.
Think about presentation. With the KPIs not being the most intuitive or easy to interpret, the narrative around them will be essential in communicating performance to your stakeholders.

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