The RevStream 5X SSP Engine extends the RevStream Transaction Hub to provide a dynamic and scalable platform for performing batch-based evidence studies of historical pricing activity. Originally introduced to allow organizations to arrive at VSOE and BESP fair values to support SOP 97-2 and EITF 08-01 / ASU 2009-13, the SSP Engine is an integral component of the RevStream ERLM Suite to automate Revenue Lifecycle Management.
Studies are performed by batches in RevStream SSP Engine, allowing you to specify the evidence time period, products, services, and offerings to be included in each study. Batches are created from data loaded into the RevStream Transaction Hub for processing by the Revenue Recognition Module. This results in no additional data conversion or integration requirements. Advanced configuration allows for the exclusion of transactions based on a variety of attributes such as zero pricing, customer, and line type.
Fair Values are identified by grouping evidence lines in the batch by product, product category, currency, and defined stratifications. Midpoints may be determined by Mean, Median, Weighted Mean, Weighted Median, or retrieving the last approved Fair Value. Fair Value Ranges may be set by Percentage or Standard Deviations to set low and high values from the midpoint. The ability to use the last approved Fair Value for the midpoint validates previously approved studies compliancy, and SSP's can remain unchanged.
Up to 15 stratifications are accepted by RevStream, and a variety of Stratification Sets may be configured to allow for different stratifications to be used by Product or Product Category. For example, Support may use Region and Customer Tier, while Software may use Sales Channel and Customer Type. RevStream also supports currency and volume pricing tiers, assigning tier pricing levels to transactions as a stratification.
Define and apply Fair Value Test Sets to establish Low and High Ranges based on Percentage or Standard Deviations, and then test the evidence lines for the Fair Value against thresholds such as Population Percentage, Distinct Customers, and Quantity Thresholds to ensure an adequate sample set for testing. Multiple prioritized Test Sets may be run until a passing result is achieved. Outliers may be analyzed and to identify pricing anomalies that skew results, and subsequently excluded from the study.
Modeling batches may be created to perform ‘what-if’ scenarios whereby the user can adjust Fair Value Determination Methods, Test Sets, and Stratification Sets to discover the best fit policy for establishing SSPs.
SSP Engine was engineered for high volume processing to support the ability to process large transactional volumes, for timely results and analysis.
SSP Engine includes reporting for Fair Value Summaries, Analysis Charts, and Audit Reporting to support analytical and control requirements.
Configure Test Results to automatically approve
resulting Fair Values, or flag Fair Values for user review and approval.