Promotion Compensation Calculation Using Nested Set Data Schema
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Solution Overview
Problem
Existing compensation calculation systems face significant performance issues when processing large volumes of transactions, requiring substantial memory and leading to increased processing time, making it inefficient to determine payouts for sales representatives or customers participating in promotion programs.
Innovation Solution
A promotion-based compensation calculation system utilizing an incentive program model with an accumulation, attainment, and payout module, combined with efficient data structures like nested set models and Star/Snowflake schemas, eliminates the need for intermediate results like quota details, enabling faster processing and performance improvements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a transaction-based compensation calculation system processes hundreds of thousands or millions of transactions on a daily basis, then comprehensive compensation data can be captured, but the system requires significant physical memory and experiences significant increases in payout processing time
Solution Approach 1:
The patent segments the compensation calculation system into distinct modules: accumulation module for gathering transaction data, attainment module for evaluating promotion criteria, and payout module for calculating rewards. This segmentation allows each module to operate independently and efficiently, reducing overall processing time while maintaining the ability to handle large transaction volumes
Solution Approach 2:
The system performs preliminary actions by pre-defining promotion programs, attainment criteria, and payout rules in the incentive program model before processing transactions. This allows the accumulation, attainment, and payout modules to execute predetermined logic without complex real-time decision-making, significantly reducing payout processing time while handling millions of transactions
2Reliability
If intermediate results like quota details are generated for each sales representative, then comprehensive allocation tracking is achieved, but physical memory requirements increase significantly
Solution Approach 1:
The patent extracts and eliminates the intermediate quota details step from the traditional compensation calculation flow. The system directly processes transactions through accumulation to attainment evaluation to payout calculation, removing the memory-intensive intermediate representation while maintaining allocation tracking accuracy through the incentive program model
Solution Approach 2:
The incentive program model serves multiple functions simultaneously: it stores promotion definitions, attainment criteria, allocation rules, and payout structures. This universal model eliminates the need for separate intermediate data structures like quota details, reducing memory requirements while maintaining comprehensive tracking capabilities
Data Source
AI summary
The compensation calculation system provides in one embodiment a promotion based system. A series of user interfaces allow a user to define an incentive program, such as a promotion program, for customers of an entity. In one embodiment, the definition of an incentive program includes the customers who will participate in the program, the products that are the subject of the program, various levels of attainments that must be met to obtain compensation, and the payout generation details. The system efficiently determines accumulations relevant to the attainments and payouts using a combination snowflake data schema and nested set model to facilitate high performance determination of accumulation values. “What-if” analyses can be undertaken in a reasonable amount of time to, for example, determine and/or compare different compensation payouts based on changing variables that affect compensation.