Six Mistakes in Digital Product Management

Six Mistakes in Digital Product Management

Six Mistakes in Digital Product Management

Here, you can find a list of key mistakes that cause huge delays in time to market, frustration and a terrible waste of money and human potential in Digital Product Management.

We can do much better, and Lean Startup is the key to avoiding these mistakes to deliver awesome customer experiences, as fast as possible with minimum hassle by engaging everyone in the organization.

1) Putting the Cart Before the Horse

This is the most usual mistake traditional companies make. Scaling before having objective evidence that you have built something people want and there exists a reasonable market for your product (Product-Market Fit).

There is a goal, project or idea. They create a business model out of the blue, they fund the whole thing based on estimates and guesses of the future, they put the whole infrastructure, resources and people together upfront and then they start building like crazy.

When working with traditional businesses we ask our clients to approach product development the same way we do for innovation or startups. Management should act as Venture Capitalists using innovation accounting to measure progress until Product-Market Fit and then push for growth.

You don’t need 15 developers if you haven’t yet validated product-market fit, you will find something better to do for them.

You don’t need the budget for the year assigned to projects and products from they one.

You don’t need a scalable architecture from day one. Your infrastructure needs to grow with your customer base, otherwise you will burn cash like crazy.

Some entrepreneurs also make the mistake of jumping into scale phase before achieving product-market fit. This is a huge mistake because scaling sucks cash like hell and if you don’t have product-market fit you are doomed.

2) Build – Build – Build

This is the well-known pattern of waterfall and still today many so-called Agile companies. They basically start building without first understanding what problems they are trying to solve, for whom and if there is a market big enough out there willing to pay for it.

Here the problem is not so much scaling before Product-Market Fit, but a mindset of delivery. A mindset of output over outcome. The measure of success and productivity is delivering working software to production, regardless if that is solving a problem or providing any business benefit at all. Like a feature factory.

You don’t know if there is a problem worth solving and if your solution fixes that problem, but you are already building software. Bear in mind, building software is the most expensive thing you will do, so try to reduce it as much as possible.

Here the agile principle of “working software is the primary measure of progress” doesn’t work, the only measure of progress is validated learning.

3) Measuring the wrong thing

Eric Ries coined the concept of vanity metrics. Those metrics that make you feel good but are useless.

You need to know at every point in time what are the key metrics you are measuring and how your experiments will impact those metrics.

There is also a key mistake most traditional companies make, which is measuring innovation success with the same parameters they measure normal business operation.

What we need here is Innovation Accounting.

4) Building Doesn’t Always Mean Software

Build doesn’t mean a full-fledged product. Building means the minimum thing you can build that will validate a hypothesis and de-risk your business model.

It can be a live product, but it also means Landing Pages, Mockups, User Interviews or a physical product or service simulating an online experience.

5) Innovator Bias

You have a great idea and you immediately think of a solution and start building it without first validating if it solves any problem at all.

This is the typical situation when you have a solution looking for a problem to solve. It is typical of new technologies, that are really cool but cannot become a viable business model.

Here, you are basically skipping Problem-Solution Fit phase, as we will see later.

6) Sunk Costs Fallacy

This is problem is most typical of traditional companies with project mentality and annual budgets. It is a cognitive bias that occurs when you continue with a project because you have already invested a lot of money, time, or effort in it, even when continuing is not the best thing to do. This irrational behavior that causes more economic damage than stopping right away.

You can see this irrational behavior everywhere all the time. The solution to this problem for Digital Product Management is Lean Startup and data.