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  Tip #5: Understanding Product Development Index
Series Four
Series Three
Tip #1: Dissecting and Enabling Quadrant Analysis
Tip #2: GMROI
Tip #3: Delisting Products at Shelf
Tip #4: Understanding Merchandising Efficiency
Tip #5: Understanding Product Development Index
Tip #6: Optimizing In-Store Promotional Event Mix
Tip #7: National Promotions…"What's Our ROI?"
Tip #8: Creating Virtual Data Sources to Grow Your Bottom Line
Tip #9: Using Store Level Insights to Get in Touch with Consumers
Tip #10: Turning Innovative Analysis into Best Practices
Tip #11: Combine Wal-Mart and Syndicated data for a complete view of the market
Tip #12: A One-Size Fits All Approach to Consumer Centric Marketing
Tip #13: A One-Size Fits All Approach to Consumer Centric Marketing - Part II
Tip #14: Clarifying Business Objectives with "Source of Volum"
Series Two

The Basics:
What it means and why you need to know.
Product Development Index (PDI) is a method to benchmark sales per capita in a given geography against sales per capita in a larger area, such as the total United States. The goal of this measure is to quickly identify geographic areas that are opportunities to develop the product in question.

For instance, if sales per capita of rice in Georgia are much lower than sales per capita of rice across the entire country, it stands to reason that there is an opportunity to grow that category in Georgia.

Product Development indices are generally interpreted by this rule of thumb:

Product Development Index

In Action:
How is a Product Development Index Calculated?

Chart A:
Product Development Index Calculation

PDI is typically calculated as a ratio (or index) of the sales per capita in a given geography to the sales per capita in a larger geography (Total US in the equation above). In order to perform this analysis, you do need access to demographic data as well as sales data. A good, free source of US demographic data is: www.census.gov

What does a PDI analysis look like?

Chart B:

PDI AnalysisIn this example, PDI is graphically displayed at the county level for product X. You can quickly identify opportunities (in red) by simply looking at this map. This information by itself, though, is seldom useful. A good PDI opportunity analysis generally has this quick-reference information,vfew along with some additional detail that can help validate that opportunity.

Chart C:

XP3 ChartFor example, the slide above identifies opportunities at a retail specific level across six chains. In addition to visually mapping opportunities, this analysis quantifies the importance of each retail trading area in terms of both population and ACV. Furthermore, it provides the viewer with year-on-year growth numbers. With this more encompassing view, the user can quickly identify the target areas for growth and determine if the opportunity is significant enough to warrant further investigation.

Considerations for Effectively using PDI In practice, people tend to use the total population of an area to perform PDI. This is probably due to the difficulty of aligning syndicated data with demographic data. Using a tool like XP3 and data like that provided by the US Census, there is no reason not to go into a little more depth. For instance, why not create ethnicity- and education-specific development indices?

The results of complex measures such as PDI cannot easily be aggregated by an end-user. Consider building these measures in an OLAP system at a granular level to afford end-users the ability to roll items together on the fly.

   

 

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