In many cases data collection need to be restricted towards pre-defined outcomes. Drop down values can be defined and linked to KPIs and organisations.
In order to structure a reporting cycle, master data needs to be fixed. Period initialisation does just that, it links the relevant KPIs and Organisations to a specific reporting period, meaning that the scope for data collection and reporting will be set. Opening and closing periods is done by Period Management, allowing data collection for a specific period. Calculations and Central Approval concludes the data collection process.
For an average organization, the number of KPIs and relevant organizations lead to a complex data collection process. Process control allows you to have overviews for the data collection process status from a Central, Organisational and KPI perspective. Via Period Initialisation a task list for data collection process is created. Status management controls the task list via data submission, calculations and central approval status. This way you secure that your sustainability data is correct and complete for any specific reporting cycle.
Data collection entry screens are available for both performance, master and meta data. Sustainability performance data is submitted together with comments to define the sustainability performance context. Indicator’s are used to report on data collection approach and the materiality concept allows to restrict data collection for non material performances. Mass input of data is supported via an excel based loading function.
GreenIntelli software includes the possibility to set up calculations for KPIs. Different algorithms can be defined at KPI Sub level that supports automatic calculations based on lower level data collections. Calculations can be initiated on a single KPI Sub level or as mass calculation for all KPIs.
Data validations are part of the data collection process in terms of consistency. After data has been collected it also needs to be checked for data quality. An approval process needs to be done and afterwards the data can be approved. This can be done on multiple levels from different perspectives. After approval, your data is ready for reporting.
For external assurance, an audit trail is crucial. All performance data changes are tracked in the data base allowing for a complete audit trail. Adding and changing master data can be done dynamically and are subject to audit trails in order to support a full history view of performance and master data.
The data relevancy of a user is dependent on their data responsibility. The data entry template is a useful tool that links the user to all their KPIs and organisations and reports on all data elements that need to be collected. This way the user has a pre-defined list of all their data points in excel format which can be used for mass data uploads.
For external sources data can be loaded by using excel (csv) based loads. Different validations secure that data can only be loaded after checks have been passed. Loading files can be used to facilitate data loaded for total performance and can be used to load additional dimensions data.