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Resident and property management platform


3 weeks


Data Thinking, Data Use Case Ideation, Pursuit Model and Discovery Workshops, Roadmap and Recommended Solutions

A leading global resident and property management platform for higher education aims to help its customer communities thrive through improving their data and analytics solutions.

Mantel Group were asked to conduct a discovery to identify a Now, Next, Later roadmap for data use cases. Pretzel Lab were brought on to support with user interviews, which were used to identify some of the data use cases from a user perspective.

Key Takeaways

  • Data-use case Roadmap, in which Now use cases address the most common user pain point
  • Data points from customer interviews, survey and SOTA analysis used to identify use cases
  • Personalised data solution strategy recommended

Customer Challenge

The client has developed its products to meet customer requirements. However, the reporting and analytics, and data sharing features are considered suboptimal. The most mentioned customer pain is the lack of historical data for comparative analysis. A previous effort to develop an analytics product failed due to an inability to develop a scalable and well-performing solution that meets customer needs. The client would like a data strategy to bring their platform to the next stage of data centricity which will support their data capabilities and their customer needs.

Our Approach

Mantel Group took on a customer-centric approach paired with pursuit & delivery workshops to unpack data ideation and data use case roadmaps. Over 3 weeks, we interviewed users of the property management platform, who were largely based in the United States. We had a highly engaged group of stakeholders who worked with us to co-ordinate early morning user interviews. This helped us to identify customer pain points and their data & analytics priorities. As well as speaking to users, we also conducted a State of the Art Analysis (SOTA) and sent out a survey to give us additional data points.

From there, we had a pursuit model workshop which focused on gaining alignment on the prioritisation of potential data use cases. The most mentioned customer pain was the lack of historical data for comparative analysis. This helped to form the basis for the data use case roadmap. Following this, a data discovery workshop with the client helped us to unpack feasibility of the identified data use cases.

Using design thinking to create a data strategy 1
Using design thinking to create a data strategy
Using design thinking to create a data strategy
Using design thinking to create a data strategy

Outcomes and Results

We advised the client that there was immense value to be added by addressing immediate customer pains as well as enabling strategic use cases further down the line – in building a fit-for-purpose data lakehouse.

The Now use cases were prioritised based on addressing customer pain points and identifying the foundational building blocks for Next & Later use cases. In addition, use cases that drive the business strategy were highlighted. Combined, this approach aims to deliver fast time-to-value for their customers whilst simultaneously improving their ability to continue adding valuable data & analytics features to their product offering.


"[Mantel Group] precisely delivered the data strategy we were looking for. They worked with us as a partner, identified our customer problems and architected an effective roadmap of specific use cases. They communicated in a clear and knowledgeable way in every step of the process. We were initially cautious of using consultants but [Mantel Group] are truly experts in this field”


If you’d like to learn more about utilising Design thinking in data strategy we recommend this article on ‘What is data thinking?’.