Optional Modules
RevenueVision® has a variety of additional subscription additions that cater to specific university operational demands
GASB-87
Most public institutions are now required to comply with the new GASB-87 Lease Accounting Standards beginning with reporting periods after June 15, 2021. The RevenueVision® GASB-87 features allow customers to have a repository of all leases, terms and conditions and key dates; determine the lease term and calculate deferred outflow/inflow; report on the required financial statement footnote disclosures; and, perform the necessary calculations to determine the net present value of leases and related financial schedules.
Workflow
The RevenueVision® Workflow component allows customers to manage the initiation, routing, and approval of contract documents and solicitations prior to contract award. Through its powerful alerting features, RevenueVision® can alert reviewers when action is needed on specific contracts and items as they move through the pre-award process.
RevenueVision® Connect
RevenueVision® Connect is the web services interface to the system. Using RESTful web services, RevenueVision® Connect allows you to develop integrations for data to be sent automatically to RevenueVision® from your legacy systems on a frequency defined by the institution. Data that can be sent to RevenueVision® via RevenueVision® Connect includes any statistical information defined in a RevenueVision® statistic, contracts, vendors/companies, key dates, etc.
RevenueVision® OpTrans
Most RevenueVision® customers store statistical data in RevenueVision® at the monthly level (e.g. dining sales by month by location) which comes standard with RevenueVision®. For those requiring a higher degree of granularity, RevenueVision® offers detailed statistics and reporting at whatever level of frequency needed by the user. In some cases, with point of sale systems, this data may include detailed transactions at the 30-minute interval. This feature for operational level data includes any necessary database tuning to ensure that performance is maintained with these very large data sets.
