Returning to the product manager, I think clarity is something vague at this point and needs to be split. Whenever you have a new product manager or owner, he needs to bring four major critical contributions to their team. The product manager needs to have deep knowledge:
- in the customer segments
- in the data
- of your business and its stakeholders
- of the market and industry
Clarity in the customer segments is not just having complete profiles but having the ability to empathize with these customers. Every decision that goes into the product must bring value to the customer - this is not just a fancy sentence - anything that goes into the sprint from the backlog has to actually be something that solves a known product problem or a new important customer problem.
Regarding the enforcement to the sprint I made above, keep in mind two inconvenient truths that cause failed product efforts:
- at least half of our ideas are just not going to work - customers ultimately won't use it (which is why you need customer validation and customer discovery early in the process)
- it takes several iterations to implement an idea that delivers necessary business value (every agile product ever except car companies with unconnected cars) - you can argue that all cars are basically the same (for now) and any car solves more or less the same customer problem - taking you from A to B (some are self-driving, some have leather seats, some are fast etc).
Data-driven decisions and stakeholder management
I'd make the statement that any product manager that has a successful product or is building one that's going to survive, has to be data-driven. Typical roadmaps nowadays are the root cause of waste and failed efforts in product organizations. The motivation: that it's easy to create processes that govern how you create products and bring innovation. Yes. Some stakeholders think that innovation can be solved with a fixed process.
This type of organization needs to wean off typical roadmaps and focus on business outcomes, providing stakeholders visibility so that they know your team is working on important items and eventually make high-integrity commitments when critical delivery dates are needed. Part of this is managing stakeholder expectations and engaging them early in the product discovery process with (ideally) high-fidelity prototypes. To manage stakeholder expectations, a product manager needs to bring clarity to the table and also understand the stakeholder's context.
Being data-driven also means that you, the product manager, gets to decide what is built. If you get backlash, bringing customer data to the table, needs to be the only source of truth. But be careful, the decisions, have to be compliant with the long term vision of the product and also make business sense.
Market and industry knowledge
The product manager needs to be aware of the organization concerns and also about the market conditions. She should have knowledge of valuable business models and consciously apply a specific model when required.
Your team needs to be aware that the product meets the needs of a specific market. Market knowledge also means being aware of the competition and that is the differentiator to your product. Depending on your customer segments, the product manager can also assume the size of the market based on customer interviews and quantitative numbers extracted from that data. When trying to figure out the market size and condition, the product manager also needs to be in sync with marketing, sales, customer success, finance, legal, BD, security etc, before making market statements.
Again, talking with different people inside the business and ecosystem can get the product manager closer to the market truth, limits and movement.
Product managers need to bring clarity
While the entire team is responsible for product success, only the product manager is responsible for product failure. The argumentation here is very simple: the product manager had all the tools, people, team, data and access to key people. If the product is a failure, the decisions were wrong and the product manager made them. The product did not solve an important problem for the customers in the market he researched.
Possible reasons for bad decisions:
- untested assumptions
- no real empathy for the customer
- company constraints
- confirmation bias
- wrong direction
- wrong timing
- the wrong market
- the wrong problem solved
- low-quality product
- failure to satisfy early adopters
- failure to listen to customers
- scaling too early
Make 10 customers love your product. If you manage that, you'll be successful.