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Become a Product Visionary with Alternative Futures Analysis

The Product Coalition

Alternative futures analysis is a structured analytic technique that helps teams predict how the future might unfold. With this knowledge in hand, teams can more effectively identify and exploit opportunities and adopt risk strategies. As you assemble your team, take special care to select a diverse group of subject matter experts.

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First, Do No Harm by Mariah Hay

Mind the Product

And while the medical profession pioneered the concept of professional ethics, other industries have also developed ethical codes. Engineering has developed a strict code of ethics that they are expected to adhere to in practice. This opened up questions for the team: What would the employee be comfortable with us sharing?

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37 Roadmap Tips to Align Stakeholders

ProductPlan

Some will delight and engage the executive team by taking a high-level approach and focusing on goals and strategy. Others dive into the specifics and make engineering teams happy since they’re so detailed. Don’t tell engineers how to do their job… at least not in a roadmap. Don’t out map your team’s capabilities.

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14 Corporate Forces Affecting New Products & Ventures

The Product Coalition

Corporate forces deserve just as much attention and diligence as you would take to developing a Value Proposition or a Business Model. The tool had to be analysed by legal; he had to say what he was going to put on the web, and procurement had to get involved due to data privacy needs. like existing businesses?

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How to Keep on top of Trends that Matter to Product Managers

Department of Product

The types of trends that matter to product teams So if we agree that staying on top of trends matters, the question then is, what types of trends should we bother staying on top of? Regular show and tells – aside from your standard product demos, encourage your engineers to show and tell the new tech they’re using in your product.

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What Does a Data Scientist Do?

PMLesson's Ace the PM Interview

Many times data scientists are charged with communicating their findings with several other teams, many of whom may be as technical as they. For example, imagine our Amazon data scientist has collected their data, built a model, and has developed some predictions and forecasts using it.