Sensitivity to adding or removing concepts

When adjusting your product portfolio, it is important to understand how sensitive your overall portfolio is to adding or removing specific SKUs. The Checking sensitivity to removal of concepts and Checking sensitivity to inclusion of only one concept functions help you quickly determine how the removal / inclusion of specific concepts will lead to a subsequent change in preference share, revenue, and profit for your overall portfolio.

Checking your portfolio’s sensitivity when removing concepts

It is vital to understand the impact removing each concept will have on your overall portfolio. To illustrate this process, let’s look at the example of optimising BrandCo’s portfolio of soft drinks.

BrandCo currently offers four different soft drinks, which compete with another six SKUs from competitors. Currently, BrandCo represents 32.8% of the market.

BrandCo wants to investigate the impact of removing one of their current products while continuing to maximise preference share and revenue. This can easily be done through the Checking sensitivity to removal of concepts function, as follows:

Step 1: Open advanced settings.

Navigate to the simulation tab that you wish to test. In the bottom right corner of the simulator, select the Show advanced settings checkbox.

Step 2: Specify the concepts under Checking sensitivity to removal of concepts

• Scroll down for the Checking sensitivity to removal of concepts tab.
• Click on the tab to open a drop-down menu consisting of existing product concepts.
• Select the concepts you want to test removing from your portfolio.
• Click on the Check button.

Step 3: The output

A new simulation is now generated with added scenarios for each removal of the specified concepts.

For BrandCo’s baseline scenario, their four SKUs comprised 32.8% preference share and revenue index projection of $819.

When removing Banana, we see the lowest decrease in preference share (1.8%) and revenue ($47). We see the largest change, 8.6% and $215 drop in BrandCo’s overall preference share and revenue projections when removing Orange.

Checking your portfolio’s sensitivity when adding individual concepts

Similar to removing concepts, it is also essential to evaluate the impact of adding new concepts to your product portfolio.

BrandCo currently has four SKUs and is preparing to launch an NPD to strengthen its market position further. With three new product concepts in the proposal, it intends to identify the NPD that will maximise its new portfolio’s preference share, revenue, and profit.

This can be easily done with the Checking sensitivity to inclusion of only one concept function as follows:

Step 1: Open the advanced settings.

Navigate to the simulation tab that you wish to test. In the bottom right corner of the simulator, select the Show advanced settings checkbox.

Step 2: Specify the concepts under Checking sensitivity to inclusion of only one concept

• Scroll down for the Checking sensitivity to inclusion of only one concept tab.
• Click on the tab to open a drop-down menu consisting of existing product concepts.
• Select the concepts you want to test adding to your portfolio.
• Click on the Check button.

Step 3: The output

A new scenario will be generated with added scenarios for each addition of the specified concepts.

In this example, BrandCo intends to launch one out of the three NPDs. Hence, BrandCo Lemon is the best concept to add as the overall preference share would be 38%, the highest compared to 36.8% of Kiwi and 36.4% of Apple.

Benchmarking the additional SKU

A question that often comes up is whether the additional NPD performs better or worse than average. It’s possible to benchmark it using simple averages:

If you want to know if the additional SKU performs better or worse than other SKUs for your portfolio, you can compare the growth in the total preference share of your portfolio with expected growth if the the new SKU had preference similar to the average preference on your existing SKUs:

• Y0 is total preference share of your portfolio before adding the SKU
• Y1 is total preference share of your portfolio after adding the SKU
• N0 is total number of SKUs in your portfolio before adding the SKU
• x = (N0 + 1) * Y0 / N0
• Your decision rule is Y1 > x / (x + 1 - Y0)

For example:

• Y0 = 70%
• Y1 = 72%
• N0 = 30
• x = (N0 + 1) * Y0 / N0 = (30 + 1) * 70% / 30 = 0.7233333
• Y1 > x / (x + 1 - Y0) → 72% > 0.7233333 / (0.7233333 + 1 - 0.7) → 72% > 0.7233333 / 1.0233333 → 72% > 70.7% → TRUE. The condition is satisfied, hence the additional SKU performs better than other SKUs in your portfolio.

If you want to know if the additional SKU performs better or worse than the average SKUs on the market, you can compare the growth in the total preference share of your portfolio with expected growth if the the new SKU had preference similar to the average preference on all existing SKUs:

• y1 is the preference share of the new SKU
• N1 is total number of SKUs in the scenario after adding the SKU
• Your decision rule is y1 > 1 / N1

For example:

• y1 = 3%
• N1 = 15
• y1 > 1 / N1 → 3% > 1 / 15 → 3% > 6.66667% → FALSE. The condition is not satisfied, hence the additional SKU performs worse than the average SKUs on the market.