Short Form Video: Business Outcomes vs. Product Outcomes
Learn more about product discovery.
From the Product Talk Archives
"Qual research generates insights. Quant research predicts if those insights apply to a larger audience."
Why You Are Probably Interviewing the Wrong People (And How to Fix It)
Worthy Read
What Do We Do About the Biases in AI?
As companies are looking to amp up their use of artificial intelligence (AI), we must make ourselves aware of the risks of this technology, especially when it comes to bias. Take, for example, the recent case where Amazon's hiring AI technology was actively discriminating against female candidates. This article examines a few of the most common ways bias can influence AI algorithms and a few concrete steps we can take to mitigate this.
A Key Concept from My Book
Continuous discovery is about more than just tactics. It requires that we adopt new mindsets. We need to be:
✅ Outcome-oriented: We need to shift from valuing outputs to valuing the impact those outputs have for our customers and our business
✅ Customer-centric: We need to remember that the purpose of a business is to create and serve a customer.
✅ Collaborative: We need to embrace a model where we make team decisions leveraging all the expertise and knowledge that we each bring to those decisions.
✅ Visual: We need to step beyond the comfort of spoken and written language and tap into our immense power as spatial thinkers.
✅ Experimental: We need to learn to think like scientists, identifying assumptions and gathering evidence.
✅ Continuous: We need to move away from a project mindset and realize digital products are never done.
Learn more in my book.
Take a Course
Do your experiments take weeks to collect enough data before you can evaluate the results?
The key to faster testing cycles is to uncover hidden assumptions and test those.
Come learn how: Identifying Hidden Assumptions