Energy Consumption Data from Business Responsibility Report (BRR) and XBRL

Introduction:

Each BR Report is available in human readable form contained in a PDF file. It is also available in machine readable XBR Language contained in a XML file. Both these versions are available NSE website and also on the websites of respective participating organisations.

In this post I will mention the benefits of using the latter. As an example; I will use only energy consumption data of 3 leading Indian IT companies.

What is BRR?

In 2012, the Securities and Exchange Board of India (SEBI) mandated the top 100 listed companies by market capitalisation to file Business Responsibility Reports (SEBI-BRRs/ BRR) through the Listing Agreement. 

These disclosures were intended to enable businesses to engage more meaningfully with their stakeholders, and encourage them to go beyond regulatory financial compliance and report on their social and environmental impacts. 

The requirement for filing BRRs was extended to the top 500 listed companies by market capitalisation from the financial year 2015-16. In March 2019, the updated NVGs were released as the ‘National Guidelines for Responsible Business Conduct’ (NGRBCs).

In December 2019, SEBI extended the BRR requirement to the top 1000 listed companies by market capitalisation, from the financial year 2019-20.

BRR was changed to Business Responsibility and Sustainability Report (BRSR) with the introduction of BRSR in May 2021. Reporting is mandatory for the top 1,000 listed companies (by market capitalisation) from FY2022–23, while disclosure is voluntary for FY2021–22. Click SEBI website for more information.

What is XBRL?

XBRL (eXtensible Business Reporting Language) is a language for electronic communication of business and financial data which is revolutionising business reporting around the world. It offers major benefits to all those who have to create, transmit, use or analyse such information. XBRL has been developed by XBRL International, a not-for-profit consortium of over 600 companies and agencies which is promoting its worldwide use. Please click XBRI org for additional information.

Key benefits of XBRL and XML file format:

Automate the data capture process:

The benefit of using the machine readable XBRL  is as follows. You can automate the process of capturing the data from XBRL  from one or many XML files. And then bringing in data in to a report you want to prepare. Once you have the data you can manipulate the data. This must be the reason the report is made machine readable by regulators. Regulators can capture data from hundreds of such reports to prepare their report. 

Get the precise specific data points:

With XBRL  you can capture only the specific data points you want for further study. My example below will show how specific data points related to energy consumption were captured. 

You can manually read, copy and capture the data as well. But if you want to capture data from many files, then the process becomes tedious and prone to error. It is also difficult to estimate time to complete the manual task. 

An example:

By writing a script (a few lines of code in Python) you will be able to get the precise information you wants. You can bring that information in a report by automating this task.  

Here I have scrapped energy usage data of three leading Indian IT companies for year 2021-22. This post is for educational purpose only. 

Section - I) covers essential and leadership indicators from the BRR report. 

Section - II) covers ratios from the BRR report and prepared by me. 

These ratios can be compared across the companies. 

Section - I)

“PRINCIPLE 6: Businesses should respect and make efforts to protect and restore the environment”

"Essential Indicators"

“Total Electricity Consumption (A):” 

This is scrapped  data as it is.

	Company	Elec Consumption GJ
0	Mindtree	11572.00
1	HCL	713135.77
2	Infy	615063.00

“Total Fuel Consumption (B):” 

This is scrapped  data as it is.

	Company	Fuel Consumption GJ
0	Mindtree	1496.0
1	HCL	35445.3
2	Infy	35413.0

“Energy consumption through other sources (C):” 

This is scrapped  data as it is. Only after reading the human readable PDF file; it became clear that consumption numbers are from renewable sources of energy. 

	Company	Other Consumption GJ
0	Mindtree	40474.00
1	HCL	160563.78
2	Infy	0.00

“Total Energy Consumption A+B+C:” 

This is scrapped  data as it is.

	Company	TotalEnergy Consumption GJ
0	Mindtree	53542.00
1	HCL	909144.85
2	Infy	650476.00

“Energy Intensity:” 

Here I got data, but I had to work on it. 

a) Mindtree returned “0.” So using its total energy consumed and its turnover data points from the XBRL XML file; I calculated the ratio. I checked this ratio from its human readable PDF file. 

But the two did not match. I have gone ahead with my calculation.  

b) Infosys data point had Rs Cr in the denominator.  So I used it as it is and changed the other two to have the same denominator. 

C) HCL reported the number in Rupees million. So it was changed to Rs Crore. 

	Company	EnergyIntensityGJ / RsCr
0	Mindtree	6.719806
1	HCL	10.600000
2	Infy	5.350000

“Leadership Indicators:-“

“Provide break-up of the total energy consumed (in Joules or multiples) from renewable and non-renewable sources, in the following :”

“From Renewable sources:”

“Renewable Sources of Electricity (A):” 

This is scrapped  data as it is.

	Company	ElectricityRenewableGJ
0	Mindtree	40474.00
1	HCL	160563.78
2	Infy	266119.00

“Renewable Sources of Fuel (B):” This is scrapped  data as it is.

	Company	FuelRenewableGJ
0	Mindtree	0
1	HCL	0
2	Infy	0

“Renewable Other Sources (C):” This is scrapped  data as it is.

	Company	OtherRenewableGJ
0	Mindtree	0.0
1	HCL	0.0
2	Infy	0.0

“Renewable Consumption - Total (A+B+C)” 

This is scrapped  data as it is.

	Company	TotalEnergyRenewableGJ
0	Mindtree	40474.00
1	HCL	160563.78
2	Infy	266119.00

“From non Renewable sources:”

“Non Renewable Sources of Electricity (A):” This is scrapped  data as it is.

	Company	TotalElecNonRenewableGJ
0	Mindtree	11572.00
1	HCL	713135.77
2	Infy	348944.00

“Non Renewable Sources of Fuel (B):” This is scrapped  data as it is.

	Company	TotalFuelNonRenewableGJ
0	Mindtree	1496.0
1	HCL	35445.3
2	Infy	35413.0

“Non Renewable Other Sources (C):” This is scrapped  data as it is.

	Company	TotalOtherNonRenewableGJ
0	Mindtree	0.0
1	HCL	0.0
2	Infy	0.0

“Non Renewable Consumption - Total” 

This is scrapped  data as it is.

	Company	TotalNonRenewableGJ
0	Mindtree	13068.00
1	HCL	748581.07
2	Infy	384357.00

Section - II)

Ratios:

“Energy Intensity:” 

This ratio was provided in the XML file but I had to rework it as explained above to make it uniform. On the face of it, the lower the ratio the better it is.

	Company	EnergyIntensityGJ / RsCr
0	Mindtree	6.719806
1	HCL	10.600000
2	Infy	5.350000

Percentage of renewable sources of energy in the total consumption:

This ratio was prepared by me to show percentage of energy consumed that was derived from renewable sources of energy. On the face of it, the higher the percentage the better it is. 

	Company	TotalEnergyRenewableGJ	TotalEnergy Consumption GJ	pcRenewable
0	Mindtree	40474.00	53542.00	75.592992
1	HCL	160563.78	909144.85	17.660968
2	Infy	266119.00	650476.00	40.911425

My comments on the ratios:

While these ratios can be compared across the companies to do some analysis; I am not doing it. The reason is I want to dedicate this post only to show value of machine readable XBRL formats. 

Going back to rations; to do the meaningful analysis of these rations, you will have to read the sustainability report of each company carefully and accordingly do the analysis. 

Conclusion:

You can get the specific relevant data (or the whole) from the machine readable XBRL contained in the XML file or files, automate the whole process of getting the data for your custom reports, just by writing a small script. The above example showed it.