I’m Laura. I’ve been working in tech since 2001, in product since 2009 and as a product coach and freelance consultant since 2016. I moved into consulting for two reasons: firstly because as I moved into more senior roles I found I was doing less and less hands-on product development, which is my second favourite part of product management, and secondly because I discovered my favourite part of product management: coaching and mentoring others. I love helping people not by giving them the answers to their questions, but by using my years of experience to give them pointers towards where their own solutions might lie. I get a kick from releasing a life-enhancing product or a feature to the users who need it, but I get an even bigger one when someone I’m working with makes a discovery that moves their product or project forward, unblocks them on a tricky problem, or helps them to decide on their next career step. Having worked across multiple industries over two decades, I have come across versions of most problems. Sometimes I’ve found brilliant solutions, sometimes I’ve found mediocre solutions, and sometimes I’ve failed – but I have always learned something new. Now I’m really enjoying passing on those lessons – and still learning every day at the same time.
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My three favourite product discovery mistakes
I got it wrong so that you don't have to: none of us likes to make mistakes at work, but twenty years into a career in digital product development, it's inevitable that I've made a few: some disastrous, some rescued just in time, some which accidentally improved things - but what they all have in common is that I got better at my job because of them. Here I talk about three of the more interesting ones - what happened, what I learned, what I do differently now and what you can do to avoid making the same mistakes.
- How to assess how much evidence you need before you make a decision based on a hypothesis - The difference between proving a hypothesis (which we can almost never do) and de-risking it (which we can almost always do) - How to start with a problem, not a solution