There is no shortage of data in category management. And while that can be a good thing, it also creates a very common problem: teams get quick to calculate a number, quick to label it, and sometimes a little too quick to decide what it means.
I see this often with index measures like Category Development Index (CDI) and Fair Share Index (FSI).
Both can be very useful. Both can help point you in the right direction. But neither one should be treated like the answer on its own.
Because in category management, one number is rarely the insight.
One of the easiest traps to fall into is to assume:
That kind of shortcut feels efficient, but it can also create very weak thinking.
With index measures, context matters:
Without that context, an index can be mathematically correct and strategically misleading at the same time.
Category Development Index (CDI) compares a brand’s or segment’s share at a retailer to that brand’s or segment’s share in the market.
CDI (for a brand or segment) = Retailer share ÷ Market share × 100
At first glance, it is tempting to say:
But that is too simplistic. The more useful question is this:
Does this level of development make sense based on the retailer’s strategy and shopper focus?
A retailer may be intentionally stronger in some brands, segments, or price tiers than the broader market. Another retailer may intentionally be lighter in an area because it does not fit the role they want the category to play. Think of private label / store brands - most retailers are striving for very high CDI's on these important brands.
That is why CDI is most useful as a benchmark and discussion starter. It helps identify where development is stronger or weaker than the market — but the real interpretation has to come back to strategy.
Fair Share Index (FSI) compares a brand’s or segment’s share of a tactic with its dollar share. The phrase share of a tactic simply means the brand’s or segment’s portion of whatever support or resource you are measuring. For example:
Once you calculate that tactic share, you compare it to the brand’s or segment’s dollar share.
FSI (for a brand or segment) = Tactic share ÷ Dollar share
This is what makes FSI such a useful benchmark. It gives teams a reference point for how much support a brand or segment is receiving relative to the sales it is generating. But this is also where people can get themselves into trouble.
A common reaction is to see an FSI below 100 and immediately conclude that a brand is not getting its “fair share.” On the surface, that may sound reasonable — but in category management, it is usually not that simple.
FSI is a great benchmark, but it is not the answer on its own.
Its real value comes when you interpret it in the context of category strategy, shopper priorities, and what the retailer is trying to accomplish. That means asking questions like:
That is when FSI starts to become much more meaningful.
So yes, FSI can absolutely help flag where support appears heavy or light. But the number should start the conversation — not end it.
Both CDI and FSI are useful because they help you compare performance or support against a benchmark. That matters. But the real value is not in calculating the number. The value is in asking better questions because of the number.
Instead of asking: Is this above or below 100?
Ask:
That is the kind of thinking that turns a benchmark into insight.
CDI and FSI are not “bad” measures. They are actually very useful. But they work best when teams stop treating them like automatic answers and start using them as tools to guide stronger strategic thinking.
⇒ A number can point you somewhere.
⇒ It can flag a question.
⇒ It can highlight a possible opportunity.
And really, that is true of any set of data or numbers. In this blog, I am using index examples — but the same principle applies more broadly. Data on its own does not create insight. The insight comes from interpreting the numbers in the context of strategy, shopper understanding, and the realities of the business.
That is when data becomes much more powerful — not just as a measurement tool, but as a way to support better decisions.