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Corporate Responsibility Exchange

Corporate Responsibility Exchange. Paul Rennison – London Stock Exchange. PROBLEM TO SOLVE. Started with research into the problem of “questionnaire fatigue” for companies Companies on average receiving 7 questionnaires relating to CG,CSR etc pa

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Corporate Responsibility Exchange

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  1. Corporate ResponsibilityExchange Paul Rennison – London Stock Exchange

  2. PROBLEM TO SOLVE • Started with research into the problem of “questionnaire fatigue” for companies • Companies on average receiving 7 questionnaires relating to CG,CSR etc pa • Average of 7 man days per month spent responding this stakeholder group • Realised there are information asymmetries that impact on the needs of institutions as well • Briefly: some of the research findings

  3. Proportion of Repetition in Questionnaires • Questionnaires are found by the majority to be highly repetitive – over three-quarters • of respondents believe over 50% of the average questionnaire is a repetition of information • previously given

  4. APPROACH • Developed a normalised set of questions which map across to the key codes, guidelines and questionnaires currently in use: CC, NAPF, ABI,, BITC, EIRiS, SAM, GRI, CDP • The core normalised question set needs to be supplemented by “balancing” questions from the agencies • Not seeking to set the CR agenda, just helping companies to report against it • Consultative and consensual: Steering Group comprising key stakeholders among companies, institutions and research agencies

  5. THE QUESTION SETS • Schema will deliver a supra-questionnaire that captures 70 – 80 % of data requested by all • Schema also allows for non-core questions to be asked according to the code or agency involved • Schema also allows specific proprietary questions to be targeted to companies or sectors • We have a process and architecture that allows flexibility to co-opt new questions for emerging issues (e.g. obesity, OFR) and will be included via a ratification process

  6. CRE Data Architecture

  7. CRE SCHEMA • Defines both quantitative and qualitative non-financial data e.g. “CO2 emissions (tonnes)” vs. “Human Rights policy and declaration” • Allows definitions of alternative taxonomies for categorising the same CSR data e.g. “Strategy, management and operations” or “Social, environmental, economic” • Defines common data types found within the CSR domain e.g. “Gas Emissions”, “Energy Consumption”, “Policy Document” • Time period and applicability data for apportioning and defining the relevance of data e.g. “carbon emissions in Europe”, “child labour excluding sub-Saharan Africa”.

  8. CRE SCHEMA • Allows definition of questionnaire sets, which provide a mechanism for manual but efficient capture of the data this data does typically exist in a structured form in enterprise systems so must be recaptured • Standardised definitions of third-party requirements and ratings and their interrelationships and redundancies e.g. “this data fulfils the requirements of both Global Reporting Initiative EN12 and Carbon Disclosure Project Q4” • Reporting definitions and vocabularies Supports the definition of reports (exceptions and aggregations) that can be used during research and comparative analysis

  9. Migration to a XBRL based standard • CRE schema was designed initially as the enabler for a proprietary software application • However this underlying platform and data schema are open to all • It takes concepts and tenets of XBRL to ease future migration • The London Stock Exchange are engaged with the XBRL Consortia to evolve the CRE schema into an open set of XBRL taxonomies and extensions • Software tools will be made available to the corporate responsibility community to allow definition of new CSR data requirements and questionnaires

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