With the first deadline for NGERS emissions reporting looming, and the pending introduction of the CPRS in Australia, it will be important for organisations to ensure data is captured to enable them to meet their responsibilities. Both business efficiency and audit facets need to be considered when choosing a data capture system/method.
16. Clearly this cannot be solved by Excel Image from www.xkcd.com/282 Some Rights Reserved . Image from Flickr user http://www.flickr.com/photos/felipearte Some Rights Reserved .
SLIDE FOUR Diagram SLIDE FIVE Diagram SLIDE SIX 50kt of CO2 emissions is the equivalent of, for example, the operation of 15 data centres with 1000 servers over one year – so, not a small business! As for SME’s, they are less affected from an information systems perspective. Similar concerns exist though for ensuring that the integrity of, for example, price estimation models is accurate (given, for example, electricity cost increases of 18% and gas cost increases of 12%). It is likely that you will need to estimate and select prices based upon a rigorous method, or potentially attract the attention of the ACCC. SME’s that supply liable entities and/or entities that have ‘green’ purchasing policies may especially need to understand the impact of the scheme on their future demand ‘ Very Large’ SME’s and large corporations that are currently outside of the CPRS, but could be caught in potential future expansions of the definition, should consider implementing greenhouse gas emissions reporting information systems to inform future lobbying efforts and by way of advance preparation.
Data entry controls: Data entry requirements are clearly stated, enforced and supported by automated techniques at all levels, including database and file interfaces Data ownership: The responsibilities for data ownership and integrity requirements are clearly stated and accepted throughout the organisation Training in standards: Data accuracy and standards are clearly communicated and incorporated into the training and personnel development processes Data correction: Data entry standards and correction are enforced at the point of entry Output standards: Data input, processing and output integrity standards are formalised and enforced Data quarantine: Data are held in suspense until corrected Integrity Monitoring: Effective detection methods are used to enforce data accuracy and integrity standards Reliable and meaningful data interfaces: Effective translation of data across platforms is implemented without loss of integrity or reliability to meet changing business demands Minimal keying: There is a decreased reliance on manual data input and re-keying processes Data access tools: Efficient and flexible solutions promote effective use of data Archive management: Data are archived and protected and are readily available when needed for recovery Data dictionary: [blah] Information inventory: [blah]