This document discusses ensuring quality in sustainability data reporting. It defines sustainability data as including quantitative utility data and qualitative projects/certifications data. Quality is defined as accuracy and trustworthiness. Several speakers provide recommendations for improving data quality, including automating data collection to reduce human error, implementing auditing and data analysis tools to catch anomalies, collecting data monthly instead of annually, and making sure data sets are complete. The importance of high quality ESG reporting for transparency, performance analysis, and decision making is discussed. Examples of a company achieving sustainability goals early and another misreporting compliance data are provided. Priorities for assurance readiness including internal auditing and following GRESB review guidelines are outlined.
Human: You did a great
3. DEFINING DATA & QUALITY
DEFINING DATA:
• Sustainability data: all data related to the
ESG performance of a building. Includes
quantitative aspects like utility data and
qualitative data like projects and certifications.
DEFINING QUALITY:
• How accurate and trustworthy is the data?
• Taking measures to ensure quality
• External validation of the data quality
4. 1: TAKE HUMANS OUT OF THE EQUATION
DON’T LEAVE GATHERING DATA
UP TO HUMANS
Humans are prone to manual error.
Instead, automate data collection and utilize automated
data checks to ensure you’re using accurate data.
5. 2: HAVE AN AUDITING FRAMEWORK IN PLACE
ONCE YOU HAVE THE DATA,
YOU NEED TO AUDIT
You’ll need to check for things like:
• New meters
• New tariffs
• New charges
• Spikes in consumption
TO REMOVE THE GUESSWORK, UTILIZE AN
AUTOMATED DATA QUALITY PROCESS
6. 3: UTILIZE DATA ANALYSIS TOOLS
SUSTAINABILITY DATA MANAGEMENT
SYSTEMS WILL CATCH ANOMALIES IN
YOUR DATA SETS
Automated data aggregation solutions can check the accuracy of data,
but they may not catch anomalies in the data
7. 4: GATHER DATA MONTHLY
RATHER THAN ANNUALLY
INCREASE THE FREQUENCY OF
DATA COLLECTION TO FIND AND
FIX DISCREPANCIES
Avoid waiting until you file reports to analyze the data
Regular data analysis will ensure the most accurate data
Like studying for an exam, it’s better to review information
consistently over time rather than cramming last minute
8. 5: MAKE SURE YOUR DATA SET IS COMPLETE
REDUCE GAPS
Gaps and overlaps in your data will cost you
in the long run
LEVERAGE AUTOMATION
Machine learning algorithms will automate
your data check process
9. THE COST OF BAD DATA
Reporting the full spectrum
of data received is important
for creating accurate results
Leaving gaps in data,
missing points, or reporting
inaccurate data could create
problems in both the short
and long term
You’re making decisions with
this data; with bad data, you
make bad decisions
10. EXAMPLE: RAN’S COMPLIANCE ERROR
In 2016, the Rainforest Action Network (RAN) published a
report claiming it found many Japanese companies were
either “systematically misreporting compliance” under
Japan’s Corporate Governance Code, or had a “fundamental
lack of understanding as to what constitutes meaningful
sustainability reporting and stakeholder engagement.”
• In 2015, Japan introduced a Corporate Governance Code
intended to increase transparency and oversight related to
ESG performance.
• To evaluate the implementation, RAN reviewed the Code
reports of ten major Japanese companies with known links to
tropical deforestation and associated risk through their
supply chains -- only to find that none of the companies were
sufficiently disclosing their risks
• The full report exposed lack of progress in how companies
are addressing ESG issues. While companies were reporting
on ESG measures, the reports varied in quality
11. WHY ESG DATA QUALITY MATTERS
ON SUSTAINABILITY REPORTS
ACCURACY OF REPORTED DATA
• You should have the same data quality on ESG reports as you do financial reports
FULL DISCLOSURE OF HOW YOUR COMPANY OPERATES
• Transparency is key in today’s world
BETTER ANALYSIS OF PERFORMANCE
• You can better analyze how your organization performs after benchmarking
• How do you stack up to competitors?
• How have you improved year-over-year?
12. L
HOW TO USE ESG DATA
DISCLOSE TO INVESTORS, CLIENTS, AND STAKEHOLDERS
• More investors are asking for your ESG metrics, disclosures, and scores
- You need to know these answers before they ask
• Gain competitive advantage
BENCHMARK YOUR COMPANY PERFORMANCE
• Where are your competitors succeeding?
• What are your areas for improvement?
IMPROVE YOUR OPERATIONS
• What have you done to improve year-over-year?
14. L
PERFORMANCE DATA & RESULTS
“Shorenstein signed on to
the Better Buildings
Challenge… to reduce energy
usage 20 percent by 2020.”
December 2011
15. L
PERFORMANCE DATA & RESULTS
“We achieved our goals four
years ahead of the original
2020 timeline.”
June 2017
0.0 %
5.0 %
10.0 %
15.0 %
20.0 %
25.0 %
2009 2010 2011 2012 2013 2014 2015 2016
Cumulative Energy &
Greenhouse Gas Reduction
Energy Greenhouse Gas
18. DATA QUALITY PRIORITIES
ASSURANCE READINESS
• Internal Audit
• GRESB “Third Party Review” Guidelines
CONTROLS
• Control Framework
• GAP Analysis
• Inventory Data Gathering
19. INTERNAL AUDIT
INTERNAL AUDIT
• Goal: Confirm accuracy of utility account information and entry of monthly
energy and water data to ENERGY STAR®
- Audited 20 buildings
- Findings: 19 discrepancies, no material affect on ENERGY STAR data
20. GRESB REPORTING – THIRD PARTY REVIEW
GRESB PEERS WHO HAVE HAD “INDEPENDENT 3RD PARTY
REVIEW OF SUSTAINABILITY PERFORMANCE DISCLOSURES”:
• 2014: 30%
• 2015: 26%
• 2016: 46%
• 2017: 47%
21. CONTROLS
CONTROL FRAMEWORK
• Process flowchart
GAP ANALYSIS
• Inventory data gathering
• Compare against leading practices
• Create recommendations