Multi-feature product inventory management and allocation system and method

A method, comprising:

• determining, for a dealer of interest, a target inventory mix rate for an item having multiple features by using dealer-level historical sales mix rates and market-level historical sales mix rates for the features;
• determining a projected inventory mix rate for the features based at least in part on projected dealer sales for the features;
• and
• performing, in a computing device having a processor and a memory, a mathematical programming optimization that includes an objective function and constraints to obtain a recommended feature allocation of the item including the features, based at least in part on at least one weighting factor associated with the dealer of interest, by minimizing a difference between a projected inventory mix rate for the features and the target inventory mix rate for the features.

A system, comprising:

• a data store that includes, for a dealer of interest, a target inventory mix rate for an item having multiple features by using dealer-level historical sales mix rates and market-level historical sales mix rates for the features;
• and
• a computing device including a processor and a memory that is configured to:
• determine a projected inventory mix rate for the features based at least in part on projected dealer sales for the features;
• and
• perform a mathematical programming optimization that includes an objective function and constraints to obtain a recommended feature allocation of the item including the features, based at least in part on at least one weighting factor associated with the dealer of interest, by minimizing a difference between a projected inventory mix rate for the features and the target inventory mix rate for the features.

A computer-readable medium having computer-executable instructions tangibly embodied thereon, the instructions comprising instructions for:

• determining, for a dealer of interest, a target inventory mix rate for an item having multiple features by using dealer-level historical sales mix rates and market-level historical sales mix rates for the features;
• determining a projected inventory mix rate for the features based at least in part on projected dealer sales for the features;
• and
• performing, in a computing device having a processor and a memory, a mathematical programming optimization that includes an objective function and constraints to obtain a recommended feature allocation of the item including the features, based at least in part on at least one weighting factor associated with the dealer of interest, by minimizing a difference between a projected inventory mix rate for the features and the target inventory mix rate for the features;