The ADP is our primary product offering, making it the sole solution for managing customer data. From the ADP customers can order new data and import their existing data, as well as create inspections and reports. This results in a variety of data types that they need to manage – including point clouds, 3D models, orthos, photo collections and more. Large quantities and a wide variety of data types are challenging to manage at scale. Simplifying the data management experience could result in critical speed & efficiency gains.
User Goal
Users want to manage large quantities of various data types.
Business Goal
We want our users to feel comfortable importing all of their data into our system because usage is a trackable event that can be easily monetized.
How might we make user data easier to understand and manage?
Customers have expressed dissatisfaction with existing data management solutions. Sheer volume and a variety of data types are challenging to manage at scale. Even in our current solution the data is divided across various silos – orders, imported data, utility layers, and archived data (timeline) – and each of these silos presents the data in a unique way.
All data, whether it be from orders, the archive, or it's imported, are simply layers that can be added to the map. The term "data or data products" is vague and can be easily misinterpreted (assets could be considered data).
If we redesign how data is presented across the various sources (ordered, imported, etc.) and remove the silos that contain them then our users will be able to better understand all of the data they have. We hope this will result in more flexibility around data management and empower our users to import more data.
Solution 01
Let's first change how we refer to user data. "Layers" is more tangible and has real-world associations that better describe its purpose. Rule of thumb – if it can be added to the Workspace then it is a Layer.
Level of Effort
Low
Possible Dependencies
n/a
Wireframes
n/a