The weakness in Marty Cagan's model is immediately apparent when considering the Four Big Risks.
Traditionally, understanding users' perceptions of both value and utility were the responsibility of market researchers, who provided the information on which product managers made decisions.
As the UX industry developed, it broadened out the usability aspects into a full discipline, but few UX researchers have market research skills.
It can then lead to a black hole in the insights that support decision-making:
* the Product Manager usually has little or no training in how to interview customers (which you rightly say includes the riskiest questions around value);
* the UX researcher usually has little or no training in how to interview customers about purchasing decisions.
As a UX researcher coming from a market research background, I weave those questions into my UX discussion guides in the same way that UX questions used to be woven into my market research guides, and I find the same thing every time:
* perceptions of value are intrinsically tied to usability
* perceptions of usability are instrinically tied to price.
The two are inseparable.
The Product Manager's role is so challenging because we have an entire business function missing!
A strange pattern I'm spotting in "agile" companies is hyperindividualism: everybody has an equal say, regardless of experience, expertise, facts or data.
If seniority is the sole basis on which decisions are made then managers of equal rank are embroiled in endless circular arguments with no clear outcomes.
So, the whole issue of decision-making needs to be taken to a higher level of abstraction:
We must first agree on the concept of "right" and "wrong" - that if the facts invalidate an assumption, the argument is invalid. We must all agree on that rule, and accept the outcome of proof, either way.
In other words, for the Opportunity Solution Tree to have value, they must first agree to abide by what it reveals.
Ironically, when decisions are made on that basis, it creates demand for high-quality data, ultimately improving the user's experience and the perceived value of the product.
