Purchase Retrospective Discounts

Discount Plan Management for Dynamics GP

Vendor incentives come in many forms and need to be appropriate to individual trading circumstances. For some vendors, particularly those who are selling to a customer regularly but in small amounts, it is often more practical to incentivize them over a period of time by providing a retrospective discount plan that will allow the customer to achieve a cumulative discount.

The Purchase Retrospective Discounts module for Dynamics GP – part of the Trinity Distribution Suite – allows for the management and monitoring of these discount plans.

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Key Features

Key features and benefits of the Purchase Retrospective Discounts module for Dynamics GP include the following:

Progress Monitoring

Inquiries and reports allow for easy access to all levels of information, from a detailed view of a single vendor’s latest position through to a summary of the overall potential company liability against accrued purchase retrospective discounts. Inquiries can be drilled down to individual transactions of all sales negotiation activity.

Discount Parameters

Discounts may be given irrespective of volume or value of purchases. It is also possible to build plans with staged targets based on either volume or value. These may relate to individual items or to item groups. The discounts themselves may be ‘value of’ or ‘percentage of.’

Automated Update Routines

Demand for purchase retrospective discounts often originates from the vendor themselves. Larger corporate vendors may dictate the ways in which they wish to see these arrangements structured. The module is designed to be flexible enough to meet a wide range of needs that may differ widely from vendor to vendor.

Accrue for Discount Liability

Potential discount liability can fluctuate dramatically depending on whether or not a company hits specified targets within qualifying periods. Automated purchase retrospective discount management within the core product enables financial controllers to make informed and accurate predictions of potential liability.

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