Data Landscape Blueprint
YEAR
2021
CLIENT
Pet Insurance Company in New Zealand
CATEGORIES
[Analytics Blueprint]
[Business Intelligence]
TOOLS
[Figma]
[Figjam]
01/ PURPOSE, AUDIENCE & CONTEXT
This Pet Insurance Company relied on legacy systems and spreadsheets for their internal reporting, and their lack of visibility of data and procedures were causing them lots of headache.
This exercise aimed to map and organise their data strategy, gathering requirements across the business, and helping them prioritise the time and effort of their internal reporting team to best tackle the challenges ahead of them. This blueprint also helped them clean up older unused reports, review assumptions, and redefine metrics that were truly aligned with their business purpose and strategy.
02/ PROCESS
A series of interviews was conducted with all main stakeholders of the data team across the company. All service and operations areas were covered: sales, finance, human resources, strategy, leadership among others.
The workshops were aimed to cover three subjects:
The current state of the reporting landscape: what reports had been produced, were currently in use, or could be retired.
The wishlist from stakeholders: the things that the audience would like to have, but didn't at the time, why they mattered and what outcomes they would help them achieve.
The gap between current and ideal state: what could help them go from where they were to where they wanted to be?
After all information was gathered directly from the people involved, I organise the data, find patterns and identify the oportunites they have to optimise their current state, tidy up their old stack and make space for the new requirements, in a more systematic and sustainable way.
03/ OUTCOME
The result was a series of recommendations, in the form of a Blueprint, with three components:
One written report with all findings from the interviews, the analysis and the final recommendations
One interactive tool containing all jobs to be done, expected outcomes, and supporting evidence for each requirement, so that the development team can test and measure success as they tidy up their analytics landscape and start delivering projects to close their gaps
The full notes from all workshops, so they can go back to the source whenever needed in the future, to keep evolving their analytics practice.
In the end, the success of the analytics blueprint is to help a business see what their current analytics landscape looks like: the reports nobody reads, the dashboards hogging resources without real use case and the opportunities to make time and space in their team's schedules to fulfill clear stakeholder needs, mapped towards outcomes. The Blueprint has helped the team to go from feature developers to outcome drivers. It gave them a methodology to help them become better business partners, rather than a service desk.
Data Landscape Blueprint
YEAR
2021
CLIENT
Pet Insurance Company in New Zealand
CATEGORIES
[Analytics Blueprint]
[Business Intelligence]
TOOLS
[Figma]
[Figjam]
01/ PURPOSE, AUDIENCE & CONTEXT
This Pet Insurance Company relied on legacy systems and spreadsheets for their internal reporting, and their lack of visibility of data and procedures were causing them lots of headache.
This exercise aimed to map and organise their data strategy, gathering requirements across the business, and helping them prioritise the time and effort of their internal reporting team to best tackle the challenges ahead of them. This blueprint also helped them clean up older unused reports, review assumptions, and redefine metrics that were truly aligned with their business purpose and strategy.
02/ PROCESS
A series of interviews was conducted with all main stakeholders of the data team across the company. All service and operations areas were covered: sales, finance, human resources, strategy, leadership among others.
The workshops were aimed to cover three subjects:
The current state of the reporting landscape: what reports had been produced, were currently in use, or could be retired.
The wishlist from stakeholders: the things that the audience would like to have, but didn't at the time, why they mattered and what outcomes they would help them achieve.
The gap between current and ideal state: what could help them go from where they were to where they wanted to be?
After all information was gathered directly from the people involved, I organise the data, find patterns and identify the oportunites they have to optimise their current state, tidy up their old stack and make space for the new requirements, in a more systematic and sustainable way.
03/ OUTCOME
The result was a series of recommendations, in the form of a Blueprint, with three components:
One written report with all findings from the interviews, the analysis and the final recommendations
One interactive tool containing all jobs to be done, expected outcomes, and supporting evidence for each requirement, so that the development team can test and measure success as they tidy up their analytics landscape and start delivering projects to close their gaps
The full notes from all workshops, so they can go back to the source whenever needed in the future, to keep evolving their analytics practice.
In the end, the success of the analytics blueprint is to help a business see what their current analytics landscape looks like: the reports nobody reads, the dashboards hogging resources without real use case and the opportunities to make time and space in their team's schedules to fulfill clear stakeholder needs, mapped towards outcomes. The Blueprint has helped the team to go from feature developers to outcome drivers. It gave them a methodology to help them become better business partners, rather than a service desk.