What is a high-leverage transformation opportunity?
TLDR
Identifying whether an opportunity is high-leverage or not, can help you achieve significant business returns in the long run. The key variables that can help you decide are
strategic relevance to your business context
the number of teams the opportunity will help
potential to have a slice of improvement that can be feasibly implemented in time to see an impact (key to win hearts and minds)
the future potential of the improvement
risk of the impact of improvements on teams, stakeholders and customers
Context matters, so what is the context? When a team or leader struggles with customer outcomes or delivery speed, they want to transform. Or to find continuous improvement opportunities to be more cost-efficient. The problem is that they find there are several options to improve. So which ones to go after and how to deal with them?
What are we assuming in our context? Let’s assume you have a list of improvement opportunities already. There are at least 50 people in your teams (engineers + designers + data + product + transformation or delivery, etc.) OR your teams drive or impact at least $5m of ARR OR at least $5m of annual budget. Legacy organisations easily satisfy these criteria. There are several instances of this context in these organisations. Even new organisations that are growing also do.
To judge whether an opportunity is high-leverage, the following variables can help
Strategic relevance to your business context that will have an impact in a 6-12 month time window. The connection between the improvement and it’s strategic relevance may not be straightforward. John Cutler’s Product flywheel can help with this conversation and eventual decision. The factor that might influence it could be internal e.g., architecture or external e.g., new market opportunity.
Example: Let’s say a business is struggling with customer retention and would like to improve that. A key insight driving this poor retention is a recent outage. This requires changes in architecture - observability as well as resiliency improvements. This architectural improvement has suddenly become strategically relevant.
The number of teams that this improvement could positively impact. The teams could have different services and goals.
Example: Most teams are struggling with automated testing in their continuous delivery processes. This is a fairly standard practice in technology teams and hence this is a high-leverage improvement.
Potential to have a slice of improvement that can be feasibly implemented and released to the customer to see the impact of that improvement.
Example: Teams want to try using data across customer research, sales feedback and customer support to decide what problem to focus on. They try to do this in a cycle of 3 months and can release a new feature based on this habit. They can compare if this new habit has helped them with their outcomes compared to before.
Future potential of improvement with a multiplier impact on the future of the team’s capabilities or customer outcomes.
Example: a platform team that is experimenting with an improvement by providing a new automated service could benefit multiple other teams in the organisation and their capability to deliver for their customers.
Risk of the impact of improvements on teams, stakeholders and customers. It is hard to implement any change when the momentum is too big for whatever reason.
Example: A new automated service from a platform team is going to impact 10 different teams in the organisation. However, the team is rolling this out to 2 teams first to test if it works OR
Example: A product leader is testing a new approach to using new data for developing a product strategy. It is going to impact most teams involved in the product strategy i.e., sales, the product teams, and the business unit leader. This can be a big change. In this case, the product leader would benefit from rolling this improvement gradually - by sharing insights first with all involved, and understanding if these resonate with stakeholders’ goals and are significant enough to impact product strategy at all.
