Public bodies are responsible for ensuring that they submit complete and robust data each year, and that the data submitted meets SEAI’s data quality criteria, as evaluated via the data verification assessment (DVA) framework. Estimates based on sound professional judgement are acceptable in specific limited circumstances.
As much as is practical, the data submitted must also be verifiable. You should be able to provide documented evidence in support of submitted data. This could range from bills to internal records.
You must also document any calculations used to determine values that you report through the M&R system. This must include, where relevant, the rationale for any calculations, key assumptions, key inputs and the basis for calculations. You must retain appropriate records of such calculations.
You are likely to be asked to provide the relevant calculations as evidence during a DVA.
SEAI's general approach for classifying the quality of data submissions and the findings of DVAs, and for publishing savings results, is set out below. The vast majority of organisations submit complete reports every year to SEAI.
In general, if your organisation submits a complete report that is either not selected for DVA or is selected and passes the assessment, then your organisation is listed (published) by SEAI along with its performance results.
If your report is selected for DVA and a data error is identified, the implications are dependent on the scale of the error.
Occasionally, SEAI identifies results that are deemed to lie beyond the expected range of credible values, e.g. extreme deteriorations in energy performance. It is not always possible to clarify or rectify such apparent anomalies during the DVA process. In these circumstances, SEAI may list the organisation as having submitted a complete report, but may not publish the anomalous result(s).
If your organisation does not submit any data, it will be listed (published) by SEAI accordingly.
If your organisation does not submit sufficient data to enable the M&R system to calculate performance results for the reporting year, no scorecard can be produced. Your organisation will be listed (published) by SEAI as not having submitted a report.
If your organisation is selected for DVA but the DVA is deemed to be incomplete, your organisation’s scorecard will be calculated in the normal way. However, your organisation’s listing in SEAI’s publications will be annotated with a note highlighting that SEAI identified a data quality issue with your submission.
DVA is SEAI’s mechanism for maintaining data quality. A DVA is an assessment of specific aspect(s) of an organisation’s submission via M&R. Your organisation’s data is evaluated against data acceptability criteria. The outcome from a DVA is a formal classification of the organisation’s data submission.
DVAs are undertaken immediately after the reporting deadline. Their purpose is to:
Selection for DVA is dependent on several factors including:
A DVA can be undertaken at a number of levels. At the lowest level, this can involve a request to a public body to provide substantiation for a specific piece of data submitted. More comprehensive assessments can include a comprehensive site review by a qualified SEAI assessor of the submission with the person(s) responsible for its compilation.
While a DVA can focus on any aspect of your submission, some data items are more likely to be focused on, including:
In general, data reported for the most recent reporting year, for the energy efficiency baseline and for the GHG baseline are more likely to be the focus of DVAs.
Different assessment criteria may be applied in each DVA:
The following are the current thresholds beyond which submissions are deemed to have failed DVAs.
Parameter | Threshold of acceptable data | |
---|---|---|
1 | Final energy consumption reported for the reporting year, for the energy efficiency baseline period or for the GHG baseline period. | <±5% error |
2 | Fossil fuel consumption reported for the reporting year or for the GHG baseline period. | <±5% error |
3 | Electricity consumption reported for the reporting year or for the GHG baseline period. | <±5% error |
4 | Organisation-level EnPI calculated for the reporting year, for the energy efficiency baseline period. | <±5% error |
5 | Reported energy consumption for any one energy type that is ≥5% of final energy consumption for the reporting year, for the energy efficiency baseline period or for the GHG baseline period. | <±5% error |
6 | Subtotal of reported energy consumption that is based on professional judgement alone (i.e. there is insufficient documented evidence in substantiation of the data) for the reporting year or for the baseline period | <±5% of reported final energy consumption |
Note that these thresholds apply to all years, including the energy efficiency and GHG baseline periods.
The outcome from the DVA process is a report that contains a DVA finding and recommendations for improving data quality. The DVA finding has implications for how SEAI lists your organisation and your data in its publications.
This section outlines the extent to which estimating values for energy consumption is an acceptable alternative to actual consumption data.
An element of professional judgement is required in collating all energy data for submission, including that extracted from robust, well-documented sources. Data derived from estimates based on professional judgement alone (where there is insufficient documented evidence) is acceptable. However, the quantity of reported consumption that is based on professional judgement must be <±5% of the reported total final energy consumption.
You should only choose one of the pre-2009 energy efficiency baseline periods if you have robust consumption and activity metric data for the baseline period.
The methodologies outlined in this sub-section are only acceptable for reporting energy consumption up to 2014. You are required to keep documented records of the calculations, and are likely to be asked to provide the relevant calculations as evidence during a data verification assessment.
In general, energy consumption data derived from financial records is unlikely to be acceptable. If your public body lacks sufficient records of historical energy consumption for consumption for years up to and including 2014, then the following are acceptable methodologies to estimate the relevant energy consumption. These approaches will only be deemed acceptable if you can demonstrate that more robust data was not readily available.
If monthly spend data is available, you should:
Where this methodology is used to estimate energy consumption for your organisation’s baseline, you must discount (reduce) the annual value calculated for the energy efficiency baseline year(s) by 3%. This ensures that no energy efficiency gains are made by deriving energy consumption from financial records. The discount factor should only be applied for baseline year(s). You should self-report the annual energy consumption for each year in the normal manner.
If monthly spend data is not available, you should break down the annual spend for each month using best professional judgement. This should reflect actual, logical or likely usage patterns over the year. If you cannot allocate the annual spend on a monthly basis, you should divide it equally across the twelve months. You should then proceed as outlined above for monthly spend. Where yearly invoiced amounts are used to estimate energy consumption for your organisation’s energy efficiency baseline, you must discount (reduce) the self-reported consumption by 4%.
The methodologies outlined in this sub-section are only acceptable for reporting energy consumption up to 2014. You are required to keep documented records of the calculations, and are likely to be asked to provide the relevant calculations as evidence during a data verification assessment.
If you lack sufficient data for historical diesel consumption used by contractors in mobile plant and machinery, you can estimate consumption in one of two ways. You should use the first option wherever possible.
Where sufficient information is available, you should:
Where run hour data is not available, you can use the following methodology to estimate the diesel consumption. You should: