Depending on the organization, industry and a number of other variables some particulars of a Product Manager or Product Management Department’s day to day may vary, however, at the heart of it, they all serve the same function within an organization:
Deciding what products to make.
But how do they decide?
The obvious answer is: They pick the most valuable product directions, with the highest ROI. (like, derr…)
There are plenty of product management techniques for determining ROI over the short or long term involving financial modeling, strategic alignment and risk reduction through spreading priority over a variety of different projects, both large and small, in the portfolio.^1
In a startup, however, there exists, by definition, too much uncertainty to reliably predict financial or other performance outcomes. There are different ways to prioritize in this environment as well, but only one that actually seems to make much sense (try to guess which):
- Try to do everything - Jump around from idea to idea.
- Whoever shouts loudest wins - Pretty self explanatory.
- Highest authority employee in the room wins - Worked for Steve Jobs, right? [Answer: not really]
- Tackle low hanging fruit - Estimate effort on your stack first, then tackle the stuff you know you can get done in an a pre-selected amount of time and hope that they will net you big returns.
- Lean Startup Methodology^2 - Use scientific method to test your value hypothesis and adjust as needed.
Regardless of which methodology you use (hint: pick E!) the Product Manager works hand in hand with the executive team to choose a product strategy that’s aligned with the company’s goals and then takes ownership of that strategy to decide what specific products, features, upgrades and fixes align with that strategy and produce desired results (in the form of significant movement towards financial and strategic goals).
Using lean methodology, assumptions, questions and hypothesis which need to be answered in order to reduce uncertainty and validate the product strategy (both that it has value and that it is scaleable) are tested through iterative development cycles, the goal of which is to collect more information. Eric Ries calls this “validated learning”.^2
If leanings from successive experiments (including customer behavior data, information from talking to customers and financial performance) fail to support the product strategy, then a course correction or “Pivot”^2 may be needed. The team takes available data and comes up with a new product strategy, based on a new hypothesis.
At a high level, this should look something like this:
(Click on image to see presentation)
Next up, I’ll drill into a little more detail about how Product Manager’s handle the iterative optimization cycle, what type of skills a good Product Manager needs and also about the need for your product to be remarkable^3.
1. Portfolio Management for New Products (2nd Ed), by Robert G. Cooper, Scott J. Edgett, & Elko J. Kleinschmidt
2. The Lean Startup, by Eric Ries
3. Purple Cow, by Seth Godin