Product Manager Staffing Levels – More Survey Results

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One of our readers is working on determining product manager staffing levels for her company. While every company is different, it always helps to understand where our peers are. We do some in-depth analysis of the 2006 Pragmatic Marketing product management and marketing survey to see how other companies set their staffing levels.

How Many Product Managers?

The first thing we want to identify is how many product managers the survey respondents employ. To make this meaningful, we need to review the product manager staffing levels in light of the revenue levels of the companies. Companies often split the strategic product management activities between product managers and product marketing managers. We’ll look at both. To keep things in perspective, in this and every dataset, we’ll identify the number of respondents in each category.

how many product managers
There are a couple interesting blips in the data.

  • Companies over and under $50 million in revenue have roughly the same absolute product management staffing levels, even though they represent a 4X range of revenue.
  • There’s either a huge jump in staffing over the $500 million revenue level, or a large drop-off at the over $1 billion level.

This data only shows absolute staffing levels, and not the staffing levels relative to the number of products being managed.

How Many Products per Company?

We’re combining the product manager and product marketing manager staffing levels for the rest of the analysis.

The survey asked each respondent how many products they managed. We used the averages (by company size) to approximate a generalization of products per product manager. Here’s what we found when we combine the number of products managed with the absolute staffing levels for PM/PMM.

how many products per company

The huge jump in number of products across the $500 million revenue line might be explained by the higher staffing levels. Or it might be representative of consolidation and higher revenue levels per product for the companies with more than $1 billion in revenue.

Relative Staffing Levels

We started this analysis to help a reader do some strategic planning. Part of that planning is looking at relative staffing levels. These relative levels will also help us counter or validate the statistics above.

Product Management vs. Sales

Many product management activities are in support of marketing and sales departments. To stay strategic, we have to remember to leverage the PM/PMM efforts across multiple customers, and not squander them on individual sales calls.

product management vs sales

The companies with over $1 billion in revenue have by far the largest sales and marketing teams, as well as the lowest ratio of PM/PMM to sales and marketing staffs. This may be representative of additional support within the sales and marketing teams, or it might be a red flag that product managers are being stretched too thin.

Product Management vs. Implementation

Inbound product management involves heavy interaction with the implementation team. We define implementation team as the combination of design, development, and quality assurance. For our interpretation of Pragmatic’s data, we combined dev-lead, development, architect, and user interface specialists with quality assurance to calculate our implementation team sizes.

product management vs implementation

With the exception of the smallest companies, there’s a pretty consistent ratio. This also tends to support the premise that companies in the $500 million to $1 billion revenue range have more products than their larger and smaller peers.

It would also be really beneficial to see the break out of development and quality staffing levels within the implementation team.

Development vs. Quality Assurance

Here’s the data for development and quality assurance teams.

development vs quality assurance

Again, relatively consistent ratios, except for the $500 million – $1 billion revenue companies.

Summary

There’s actually more consistency in staffing levels than we expected to find. Unfortunately, the processes that teams use, profit models and other factors make it really hard to draw concrete conclusions from the survey data. But the consistency of relative staffing models does help us set expectations or sanity check our staffing decisions.

Check out our previous articles looking at gender-bias in the data, and product manager salary data.

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