Data strategy from reactive to prescriptive maintenance for a social housing organization
While working at Bit as a research lead, we developed a data strategy to move from reactive to predictive, and ultimately prescriptive maintenance for a social housing organization in the Netherlands.
The team
I was the research lead on the project. I was responsible for leading a multi-disciplinary team of 6, designing and conducting the research, synthesizing insights, aligning and co-creating with the client, and presenting the final results.
About Bit
Bit is a research and prototyping studio run by 50 young tech talents, on a mission to fast-forward the impact of emerging tech.
The brief
Working as a design researcher at Bit, we worked together with a social housing organization in the Netherlands to explore how data and emerging tech might support their maintenance process and staff.
The approach
Informed by qualitative interviews with residents, staff, planners, management, and other stakeholders, we identified 5 major pain points. Some could be solved with APIs and out-of-the-box functions, some temporarily eased, yet all of them could benefit long-term by better data management.
The deliverable
We developed a data strategy to move from reactive to predictive, and ultimately prescriptive maintenance. We offered 3 concepts to start with, each offering a different approach to collect the quality and quantity of data required. The most important insights from the research were presented in a visual deck.
The impact
The concepts are aligned with the residents’ needs and have the potential for a 5-10% cost reduction. Our recommendations are influential for the organization’s data strategy, and one of the concepts is currently in development.