Continuous discovery - Caitlin Blackwell
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The document discusses the importance of continuous discovery in improving decision-making processes for product managers. It outlines a framework for effective discovery, emphasizing the need to understand customer needs, validate assumptions, and ideate solutions through regular customer interactions. Additionally, it highlights common pitfalls in decision-making and provides practical steps for implementing a successful continuous discovery approach.
Continuous discovery - Caitlin Blackwell
- 1. Continuous Discovery - Worth the effort? Product Anonymous Caitlin Blackwell 27 June 2019
- 2. Caitlin Blackwell Acting Head of Product – Candidate Experience SEEK ANZ
- 3. Agenda 1. What is discovery and why do it? 2. Continuous Discovery Framework 3. Successes and failures
- 4. “McKinsey investigated 1,048 business decisions over 5 years, tracking both the way decisions were made and the subsequent outcomes. These were major decisions such as launching a new product or service, changing the structure of an organisation or an acquisition. They found that the decision making process mattered more than analysis by a factor of 6.” Discovery is about driving better decision making
- 6. Unstructured Variable approaches A developing craft 1. Discovery Deciding what to build Work out the most valuable thing to build Highly structured Agreed approaches Mature 2. Delivery Building it Delivering the most value quickly ? ?
- 7. 1. Discover what the customer solution needs to be If you get discovery wrong then what you deliver could be wasted effort
- 8. We encounter the ‘villains of decision making.’ Why are we wrong? Narrow framing: we unduly limit the options we consider and so we don’t focus on the biggest opportunities & don’t generate enough compelling solutions Lack of clarity on the problem Short term emotion Confirmation bias Overconfidence
- 9. We don’t test our critical assumptions early enough and they fail to be true Why are we wrong? Customers don’t want it (the value isn't there) It’s too hard to use (the usability isn't there); There are business constraints that block the solution from launch (the business viability isn't there) It’s too costly or time consuming to deliver (the feasibility isn't there); It’s not the right thing to do (we uncover ethical issues);
- 10. So how can we be right more often?
- 11. Continuous Discovery 3. Size needs and pick one 2. Speak to customers regularly, map their needs 1. Agree desired business outcome (i.e. your OKR) 4. Ideate and validate assumptions through experiments
- 12. Step 1 3. Size needs and pick one 2. Speak to customers regularly, map their needs 1. Agree desired business outcome (i.e. your OKR) 4. Ideate and validate assumptions through experiments
- 13. 1. Agree Team’s Desired Outcome Objectives Key Results Key ideas/initiatives • Help SME hirers efficiently identify suitable candidates to interview • Increase hirer sat score from x to y • Increase shortlist rate from x to y • Hirer filters • Add more detail to candidate card • Matching tool Objectives • Grow use of product
- 14. Step 2 3. Size needs and pick one 2. Speak to customers regularly, map their needs 1. Agree desired business outcome (i.e. your OKR) 4. Ideate and validate assumptions through experiments
- 15. 2. Speak to customers and map their needs
- 16. 2. Speak to customers and map their needs Desired outcome Opportunity/Need Solution
- 17. “What’s in the spotlight will rarely be everything we need to make a good decision. Sometimes we’ll forget there’s a spotlight at all dwelling so long in the tiny circle of light that we forget there’s a broader landscape beyond it.” Daniel Kahneman
- 18. Step 3 3. Size needs and pick one 2. Speak to customers regularly, map their needs 1. Agree desired business outcome (i.e. your OKR) 4. Ideate and validate assumptions through experiments
- 19. 3. Size Opportunities & pick one
- 20. Step 4 3. Size needs and pick one 2. Speak to customers regularly, map their needs 1. Agree desired business outcome (i.e. your OKR) 4. Ideate and validate assumptions through experiments
- 21. 4. Ideate and validate assumptions through experiments
- 22. 4. Ideate and validate assumptions through experiments
- 23. 4. Ideate and validate assumptions through experiments
- 24. 4. Ideate and validate assumptions through experiments Theresa May
- 25. 4. Ideate and validate assumptions through experiments Important and unknown
- 26. 4. Ideate and validate assumptions through experiments
- 27. 4. Ideate and validate assumptions through experiments
- 28. 4. Ideate and validate assumptions through experiments
- 29. 4. Ideate and validate assumptions through experiments
- 30. 4. Ideate and validate assumptions through experiments Fogg Model
- 31. Use case: I don’t want to commute too far, so I want to ONLY see jobs close to me
- 32. 4. Ideate and validate assumptions through experiments
- 33. 4. Ideate and validate assumptions through experiments
- 34. 4. Ideate and validate assumptions through experiments 34 From this… … to this … and finally this
- 35. Where to start? 1. If you can only do one thing, start by talking to customers and asking them how they use your product. Everything in discovery flows from this. 2. You don’t need to be using OKRs to pick your desired outcome, just find a metric in your product you are looking to shift eg revenue, churn, acquisition
- 36. Where to start? 3. Go broad with ideas – go for quantity first. Blind vote. 4. Some form of assumption mapping is essential if you want to learn before you build
- 37. Where to start? 5. Visual sensemaking tools help you stay aligned, and avoid some of the opinion battles 6. In experimenting aim to learn something on your assumptions, rather than the most definitive answer. Challenge yourself: what can I learn in a week?
- 38. Further reading • An Introduction to Modern Product Discovery - Teresa Torres YouTube • Decisive – Chip and Dan Heath • Inspired – Marty Cagan • Teresa Torres blog producttalk.org, videos and podcast interviews