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Step-by-Step: Format Organisational Data

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Written by Gemma - Plan A Support
Updated over 3 weeks ago

Organisational Data refers to key information about your company’s structure, including details about your facilities, their locations, and sizes, as well as employee information like the number of employees, their working hours, and how often they work from home.

Collecting this data is the essential first step in your reporting journey.

Step 1. Choose your preferred data entry frequency

It’s important to decide how frequently you will enter data. For example, if your Organisational data remains consistent throughout the year, you can enter it annually. If you have more detailed data, you can choose quarterly or monthly intervals. To ensure successful file uploads, avoid overlapping timeframes and time gaps in your data.

Step 2. Fill out the Organisational data template

There are 6 data points to collect per facility, meaning each facility should have 6 rows of data per time period. Please see a full overview of each below.

Column A: start_date

  • The first date of your data period.

  • The suggested date format is YYYY-MM-DD, but check the Accepted Formats article to see a full list of formats you can use.

  • This field is mandatory.

Column B: end_date

  • The last date of your data period.

  • The suggested date format is YYYY-MM-DD, but check the Accepted Formats article to see a full list of formats you can use.

  • This field is mandatory.

Column C: location

  • The ISO-3166 alpha-2 code of the country where the facility or company is located (e.g., DE).

  • This field is mandatory.

Column D: facility_name

  • In this column you can “create” facilities that you can allocate your emissions to.

  • Be sure to use simple names that you will be able to reproduce for any other emissions category, without any special characters.

  • For each facility that you create, you will add six rows of data, one for each of the data_types in Column F.

  • This field is mandatory.

The following two columns (value and data_type) are linked to each other. The value in column E is described by the label in column F. We suggest to fill in the data_type column first and then input the numeric value in column E, to not confuse different data types.

Column F: data_type

  • There are 6 data types required per facility:

    • employees number (total number of employees in Full Time Equivalents (FTE))

    • employees working from home number (number of employees working from home at least once per week)

    • working days per week

    • working from home days per week (average work from home days per week)

    • working hours per day

    • facility size (in square metres)

  • This field is mandatory.

Column E: value

  • In this column you will enter numbers related to the ‘Data Type’ chosen in column F (e.g., if you selected "work hours per day" in column F, you add the number of hours in column E).

  • Please see a detailed breakdown of what each data point requires below:

    • employees number

      • This is the total number of employees in Full Time Equivalents (FTEs)

      • Only enter whole numbers (no decimals)

    • employees working from home number

      • This is the number of employees working from home at least once per week)

      • Only enter whole numbers (no decimals)

    • working days per week

      • This is the number of working days per week at the given facility

      • Only enter whole numbers up to 7

    • working from home days per week

      • This is the number of days spent working from home days per week across the employees at the given facility

      • Based on a 5-day working week, the formula to calculate this is:

        This means adding multiplying each number of days by the corresponding number of employees who worked that amount of days in order to find the total individual work from home days, and dividing this by the total number of employees who worked from at least once per week.


        Example: You have 130 employees in a given facility, including 125 employees who work from home at least once per week and a 5 day working week. The 5 who work from the office can be excluded as they don't contribute to the total working from home days.

        To organise the data, you would list out how many employees worked each number of days from home. In this example, the 125 employees who work from home at least once per week can be organised as:


        1 day/week = 5 employees
        2 days/week = 10 employees
        3 days/week = 50 employees
        4 days/week = 50 employees
        5 days/week = 10 employees

        You would then do the following equation to work out the average:

        ((1*5)+(2*10)+(3*50)+(4*50)+(5*10))/125= 3.4 working from home days per week.

        For more information, see 'How do I calculate working from home days per week?' in the FAQs below.

    • working hours per day

      • This is the number of working hours per day at the given facility.

    • facility size

      • This is the size of the facility, or the share of a facility owned or operated by your company.

      • Please enter the data in square meters

If any of the values change over time, add a new row for the same data_type and new value. E.g., if number of employees change, you will need to enter a new row with the new time frame and a new number of employees. In the example below the yellow rows show the employee count from January through May 2023 while the green rows are for June through December when 50 new employees were added.

Step 3. Upload Organisational data to Plan A

Upload Organisational data to Plan A here.

Organisational Data FAQ

How do I calculate working from home days per week?

Calculating working from home days per week requires you to calculate an average based on how many employees work from home across a range of possible amounts of days (in most cases, 1-5 days). This calculation, however, can be made with a simple formula.

1. Arrange your data

Look at your survey data, and see which amounts of working from home days were given. For facilities where employees work 5-day weeks, for example, this will usually range from 0-5.

List out the range of days spent working, and the number of employees who worked from home for each number of days. For example:

You have 130 employees in a given facility, including 125 employees who work from home at least once per week and a 5 day working week. The 5 who work from the office can be excluded as they don't contribute to the total working from home days.

To organise the data, you would list out how many employees worked each number of days from home. In this example, the 125 employees who work from home at least once per week can be organised as:


1 day/week = 5 employees
2 days/week = 10 employees
3 days/week = 50 employees
4 days/week = 50 employees
5 days/week = 10 employees

2. Input your data into the formula

Based on a 5-day working week, the formula to calculate this is:

This means:

  • Multiplying each number of days by the corresponding number of employees who worked that amount of days

  • Adding these values together to find the total individual work from home days

  • And dividing this by the total number of employees who worked from at least once per week.

Following the above example, the calculation would be:

((1*5)+(2*10)+(3*50)+(4*50)+(5*10))/125= 3.4 working from home days per week.

How do I account for remote workers?

You can account for remote employees in your Organisational data in two ways, depending on their work setup:

1. Fully remote employees (no assigned office)

If an employee works remotely and is not attached to a specific office, we recommend creating a dedicated ‘remote facility’ for the relevant country. For example, at Plan A, we would set up a facility called ‘Netherlands - Remote Employees’. This ensures that country-specific emission factors are applied correctly. It also prevents remote employee data from skewing office-based emissions.

2. Fully remote employees attached to an office

If an employee is fully remote but linked to a physical office (i.e. they have an assigned office but do not commute there to work), they should be included in the facility’s Organisational data.

  • These employees should be counted under ‘employees working from home’.

  • Their remote working contribution should be based on a 5-day working week, adding ‘5’ to the average number of working from home days per week.

How to enter facility size for remote facilities?

If you have business locations with employees working fully remotely and plan to allocate emissions to these “facilities” you will need to enter 0 for the facility size. This will also allow you to be able to account for their “Working from Home” emissions. In the example below you can see how a remote facility in Paris with 20 employees was added.

How to enter facility size for co-working facilities?

For the facility size data_type you are expected to provide the size of your company’s space in square metres, which might seem complicated if you have employees working in a co-working or shared office. Depending on your membership subscription (i.e. private/open work space) and the specific services provided, your co-working space provider will be able to provide the size of space allocated to your company. If they do not have an existing value, one of the potential solutions is to divide the total co-working space by the ratio of the number of your employees, to the total number of people working in the space. The number should include the entire space your office uses, including shared rooms, hallways, and working stations.

Do I need to account for space that I sublet to other organisations?

If you sublet space to another organisation, you don't need to include this space in your carbon footprint, and should therefore not include this in your organisational data. If you sublet part of your rented space (e.g. desk space or rooms for other organisations within your rented space), simply deduct this from the total space.

This logic extends to activities taking place in the rented space, meaning there is no need to account for electricity, heating, or water (etc.) consumed in sublet spaces. If these are included in a total bill alongside your organisation's utilities, we recommend splitting the usage according to the ratio of space in control by the different organisations.

How to reflect a move to a new office or facility?

If you're just moving from one office to another within the same country, this doesn't impact your service agreement. If you are, please contact Support or your Customer Success Manager.

When the physical location of an existing facility, the easiest thing to do on the Plan A Sustainability Platform is keep the same facility, but just update a few things to the following to this:

Update your company settings (only applicable if this is your HQ or billing address):

Reflect your new facility size information in your Organisational data template

Reflect changes Fugitive emissions templates (where necessary):

How should I account for contractors and freelancers when counting my number of employees?

It is important here to distinguish between long-term and short-term contractors and freelancers.

  • Long-term contractors and freelancers, providing they work in a similar pattern to regular employees, should be included in your employees number.

  • Short-term contractors and freelancers, who carry out occasional or temporary work, should be accounted for in Scope 3 Category 1 as a 'purchased service'. In this case, the payment for their services can be used to calculate emissions using the 'spend-based' calculation method. See here for a list of relevant Plan A Categories.

How to account for changes in employee numbers?

If your employee number counts change throughout the year, you have two options of how to enter the data.

  • First option, you can use an average number for the entire year by summing all the monthly employees numbers and divide per number of months. This way you will only have one line of data for the employee number value.

  • Second option, you can enter the exact time frames for when the employee counts changed. This option may require more work, but will result in more accurate emissions and allow for more granular emissions analysis.

As with any category you can choose any timeframe, just be sure to avoid double counting or missing any time periods. Keep in mind, that when the employee number changes, the 'employees working from home number' and 'working from home days per week' values likely will also change and should be adjusted accordingly.

In the example below, you can see that the Berlin office entered the employee number on an annual basis, but the Hamburg office entered it on a quarterly pattern, based on when the employee number changed. In this example you can also notice that the Hamburg office has a “no work from home policy.”

How do data points from Organisational data impact National averages and Work From Home calculations?

National Averages

National average calculations are triggered when both:

  • employees number is greater than 0

  • working days per week is greater than 0

National average emissions change accordingly when:

  • employees number changes

  • working days per week changes

  • working hours per day changes

Work From Home

Work from Home calculations are triggered, when all of the following are true:

  • employees number is greater than 0

  • working days per week is greater than 0

  • working from home days per week is greater an 0

  • employees working from home number is greater than 0

Work from Home emissions change accordingly when:

  • working from home days per week changes

  • employees working from home number changes

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