Resource Allocation Tutorial - Interpreting the Results

Created by Steve Hoover, Modified on Thu, Feb 13 at 12:14 AM by Steve Hoover

The following results are from the OfficeStar Tutorial data set that loads automatically when you select the Tutorial link in the Enginius Dashboard and run with analysis parameters indicated in Running a Resource Allocation Analysis article. 


Response function calibration

The report will display the response functions calculated for each category in both table and chart form.


In the TV ads example above, you'll notice the model used to calibrate the data was ADBUDG while the Print ads were calibrated using the logistic model for best fit.



The Model fit charts show how the expected Impact (y-axis) is affected by Effort (x-axis) at all levels including the saturation level.

 

Unconstrained optimization

The report will provide a table and chart of the optimization process using unconstrained data compared to the base data. (This chart will be produced even if you have placed constraints on your data.)



Constrained optimization

If you have enabled constraints on your optimized effort, the report will display the optimized efforts that take those constraints into consideration.


Comparison of scenarios

A chart for each category will be produced comparing the current situation to both constrained and unconstrained options. The example for TV ads is shown below.


Sensitivity analysis

If you checked the Run sensitivity analysis option when running the model, Enginius will produce the following chart that summarizes the optimal net marginsat various levels of total effort (global effort).


We have highlighted the potential net margins that could be realized by reallocating current effort optimally (i.e., without a change in current global effort), and the potential net margins that could be realized by changing the total global effort optimally. 


For a discussion and process description, please refer to the discussion of the Delphi method in Chapter 5 and Exhibit 7.9 in Principles of Marketing Engineering and Analytics, 3rd Edition.


Was this article helpful?

That’s Great!

Thank you for your feedback

Sorry! We couldn't be helpful

Thank you for your feedback

Let us know how can we improve this article!

Select at least one of the reasons

Feedback sent

We appreciate your effort and will try to fix the article