Asset Dashboard @TOPdesk
A quick assessment on asset life-cycle management for managers.
Project Overview.
Role: Product designer
ITSM WebApp - B2B
Duration: 6 months
Tools: Figma, Miro, Apache Superset
Problem statement
Asset managers need an in-built dashboard to quickly check their asset database life-cycle and detect anomalies, prevent errors. They want the dashboard to be customizable to their needs and reportable for audits. For low mature users, PowerBI is too complex to use so they seek out for an easy-to-use dashboard tool.
Solution
We collaborated with our reporting team and used Apache Superset, a third-party tool, to create our own Asset Dashboard MVP that is quickly accessable, easy to report and detect anomalies in the AMDB.
High-level problems with collaboration, 3rd-party tool limitations
🧠 Expectation management was set multiple times and project got delayed.
💡 We communicated the deadline when we need to release the dashboard for the the up-coming marketing campaign and we had check-in meetings to see the progress.
🧠 Apache superset has limitations on chart settings and the layout was also hard to customize.
💡 I had several iterations with the other team and my tester to solve UI issues on the spot and not after release.
🧠 The reporting team never worked with a product designer, which lead to misunderstandings.
💡 I had an open conversation with the developers to show them what I do and how far my knowledge goes so that we have a mutual understanding to set expectations for both sides.
The Design Process.
Gathering use cases
Our persona was the Asset Manager, who is responsible for the asset life-cycle management.
We gathered use cases based on fields we are able to use for a chart. We also asked for visuals from customers who use 3rd-party tools for dashboards.
Prioritization
I used Impact Effort Matrix to identify what can be our quick wins together with my PO and Solution Architect. This method helped us to easily categorize our use cases and then decide on what is our MVP.
Based on the quick wins, we decided on the chart types we would use to visualize the data. As we had a lot of technical issues with unaccessible external data, we concluded to use big number charts and then make them a link where it directs the user to a filtered Asset Overview to export or further manipulate data.
The released MVP
Feedback and Dashboard 2.0
We received 160 feedback within a month and categorized them.
Filters and Customization: the dashboard is too basic, users need extensive filtering which includes filters by country, branch, location, customer. Besides filters, custom views, drag-and-drop widgets, and the ability to save and apply filters are highly requested features.
Clickable elements and drill-down capability: Drill-down capabilities are essentials to access more granular data directly from the dashboard.
Additional data and views: Users are looking for more data points and views, such as cost information, personalized fields, graphical views of asset relationships, and more detailed breakdowns by asset type and model.
Export functionalities: Users need robust export options, including exporting to Excel with detailed information and metadata. There is a specific request for exporting data related to the reason for archiving assets.
Dashboard 2.0 will incorporate extensive filtering, drill-down and additional data. We still constrained to the 3rd-party tool, Apache Superset, which has its limitations, but together with the reporting team, we leverage all the possibilities we can.
Impact.
Objectives
Decrease usage of integrated 3rd-party tools.
Increase asset life-cycle management efficiency.
Key results
Customers still use 3rd-party tools because of missing filtering capabilities but for low-mature customers, the dashboard offers a basic control of their AMDB.
AMDB errors have decreased by 20% after 1 year.
Credits.
Strength is within a team, not in individuals.
Development team, Product owner
Reporting team