Recommendations
Given the difficult nature of
making purchase decisions, a linear programming model has been formulated to
consider demand, space, and capital spending constraints. It is primitive, with a lot more
research required to make the model more meaningful, but it serves its
purpose. While the model’s
objective function is to maximize profits, it seems to be also useful for a
store that may be relocating with new space constraints; finding the optimal
mix of inventory given the new space constraints, while assuming demand holds
constant. Additionally, it seems
useful in looking at how spending constraints affect the optimal mix or even
how changing the layout may be affected.
For example, seeing how the mix changes when available capital for
particular product categories changes or seeing what the optimal mix will be if
the space allocated for the class of products is changed.
Something that complicates this
model is the problem of inventory obsolescence. The demand that is input as a
constraint is a result of previous demand, and the model does not consider the
fact that as items become less popular so does the need for that item. Therefore, historical demand data is not
necessarily ideal and a more appropriate approach for calculating an optimal
mix may be achieved through the use of a continuous order period model, Stochastic
Programming, or simulation.
Stochastic Programming models allow the information to be evaluated
under uncertain conditions and allow for probability assumptions; in this case
demand. Demand is receiving such an
emphasis given the large degree of uncertainty and variability, and because it
is the only uncertain element within our model. It should also be noted that this model
is for single order period decisions, which does not allow the model to
consider excess inventory existing as a result of previous order periods. Further research is required to
transition the present LP model to a Stochastic Programming (SP) model.
In addition to the
aforementioned, it should be noted that the model has not been tested or
proven, as this would require more extensive research. At this point the results are
theoretical and strictly for academic purposes. However, there appears to exist a great
opportunity to conduct further research with the possibility of creating
software that not only considers the proposed LP/SP model, but also integrate
the software with other useful business models (i.e. EOQ, ABC, Yield
Management, and price sensitivity tools) and possibly add an ability for the
software to establish optimal delivery routes given orders as they occur; as a
result of point of sale data as sales occur. In searching the Internet, there does
not seem to be a software package specifically for the furniture industry that
facilitates all of these business necessities. Moving forward:
Business Overview Example pg. 3