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10 experiments you can try to improve discovery
2017-08-19

Want to improve your discovery? Here are 10 things you and your organisation can try to make your discovery even more valuable, based on a recent retrospective of discovery.

Experiment 1: Can’t interview? Don’t start.

Data/research suggests that

  • teams can wait for weeks to carry out their first interviews with users when they have to develop a route to users. This means that the first few weeks of discovery may have limited return on investment and the final weeks are over-loaded with interviews and do not have enough time for the team to draw conclusions before discovery ends

So if we try

  • starting discovery when the first interview can take place within 3 days

And measure

  • time taken for first interview
  • time taken to complete discovery
  • % of discoveries requiring extensions
  • confidence in discovery insights

We should see this change

  • better insights from discovery (with ‘better’ defined as team and stakeholder confidence in these insights)

Experiment 2: Subject matter experts are invaluable

Data/research suggests that

  • subject matter experts being a core member of a discovery team increases the value of the discovery (and may reduce the time taken to complete discovery)

So if we try

  • increasing the involvement of subject matter experts with the core discovery team (where this is useful)

And measure

  • % of discovery team ceremonies attended by stakeholders
  • time take to carry out first user interview
  • amount of time spent with users during discovery
  • % of discoveries that require a deadline extension

We should see this change

  • greater confidence in outcomes of discovery (and potentially shorter discoveries).

Experiment 3: Don’t be too digital

Data/research suggests that

  • discoveries carried out by ‘Digital’ teams will tend to skew discoveries towards digital solutions (i.e. in-house software)

So if we try

  • Digital 'plus’ teams (better mix of ‘the business’/policy/analytical services, etc and ‘digital’)

And measure

  • % of discoveries that lead to digital solutions

We should see this change

  • greater balance of digital/non-digital solutions

Experiment 4: Lean Startup over Scrum

Data/research suggests that

  • ‘pure’ Scrum is not a great framework for discovery and alpha because it expects requirements and value to be defined up-front

So if we try

And measure

  • % of discoveries that do not continue to alpha
  • % of discoveries that pivot the problem, or user, or both
  • % of discoveries that recommend pausing until conditions are right for alpha
  • % of discoveries that suggest that ‘digital’ isn’t the best, or only solution space to explore in alpha

We should see this change

  • data-driven decisions in discovery; teams able to share the hypotheses how they’ve tested to draw conclusions as to the value of a problem being solved.

Experiment 5: Share discovery guidance

Data/research suggest that

  • dysfunction can appear during discovery due to a lack of shared understanding of the value of discovery, and the approach to discovery
  • members of discovery teams may not have the same understanding
  • discovery teams and their Service Manager may not have the same understanding as ‘the business’/stakeholders

So if we try

  • sharing discovery guidance

And measure

  • % of discovery team members, Service Managers and stakeholders that can consistently describe the value and approach to discovery
  • stakeholders/’the business’ satisfaction with discovery

We should see this change

  • teams encounter less dysfunction due to uncertainty around the point of discovery and the approach to discovery, and stakeholders’ expectations around discovery being met more consistently.

Experiment 6: Don’t reinvent the wheel

Data/research suggests that

  • some of the core concepts of discovery and alpha (new to government) share more with project management concepts (familiar to government) than we expect

So if we try

  • highlighting similarities between agile development and project management
  • learning from project management
  • sharing guidance on when project management is the best approach, and when working with agility is the best approach

And measure

  • % of ‘work’ that makes an informed choice in the best model (agile or project) based on the conditions in which it’s working

We should see this change

  • the right approach is taken for the right ‘work’ because there is greater shared understanding of how the approaches work and the value of their differences.

Experiment 7: Show me the money

Data/research suggests that

  • discovery teams would like greater accountability

So if we try

  • making discovery teams aware of their budget and the rate at which they are spending it

And measure

  • the average cost of a discovery

We should see this change

  • average cost decreases

Experiment 8: What’s a pre-discovery?

Data/research suggests that

  • pre-discovery has become a common stage of development but has yet to be clearly defined so is used inconsistently

So if we try

  • defining the value of a pre-discovery stage, and deciding if it should exist, and (if ‘yes’) applying it correctly

And measure

  • number of pre-Discoveries that take place in the future versus in the past
  • % discovery teams reporting that a pre-discovery helped their discovery

We should see this change

  • pre-discovery of more use to discovery teams Or
  • pre-discovery of more use to portfolio Or
  • pre-discovery no longer used Or
  • ???

Experiment 9: Clearer briefs

Data/research suggest that

  • discovery teams can spend several days (sometimes over a week) clarifying the brief for a discovery

So if we try

  • a consistent approach to discovery briefs

And measure

  • average time spent by a team defining the brief

We should see this change

  • teams begin discovery sooner

Experiment 10: Run regular discovery retrospectives

Data/research suggests that

  • the questions used to carry out the retrospective that led to these hypotheses worked well

So if we try

  • team/organisational discovery retrospectives using similar questions

And measure

  • responses

We should see this change

  • improvement in discovery.

Notes

  • note 1: I wrote a post about product roadmaps in which I highlighted a format for hypotheses shared by Jock Busuttil and have used that format for this post
  • note 2: it'd be great to hear from anyone who tries any of these hypotheses or has suggestions of their own, say hello on Twitter or share suggestions on Github.