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Designing Dashboards for Big Data

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Anirudh Ganti    By Anirudh Ganti
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By Anirudh Ganti

In manufacturing, User Experience (UX) and User Interface (UI) design are not for the faint of heart.

With the fourth industrial revolution in full swing, manufacturers are generating and collecting more data than ever before. For example, a transmission assembly line at a Tier- 1 American supplier performs approximately 100 tests for every transmission it produces, with more than 30 signals being monitored during each test. This equates to over 500,000 data points per transmission.

Data from testing a single transmission unit.

 

How do you make such vast amounts of information accessible to humans?

The product and design team at Acerta had to answer this question when we were tasked with building an intuitive dashboard for automotive manufacturing engineers and end-of-line engineering managers to identify potential defects on the line.

 

Making Big Data User-Friendly

We started by talking to our customers in the automotive industry, with the aim of building user personas for each one. What we learned was that there is significant variation in the types and quantities of data different personas wanted to see. It makes sense: the operations manager cares about very different KPIs than the plant manager.

LinePulse Dashboard

A pitfall we tried to avoid was the urge to overload the user dashboard with tons of widgets and visualization. While we could have easily used these to showcase the prowess of our machine-learning models, a conscious decision was made to limit the number of displayed contributors to end-of-line failures. 

By highlighting the top three contributing signals per operation, we gave the engineers the option to immediately investigate or choose to view more signals via an additional click on the dashboard. It’s imperative to understand that while users appreciate the powerful insights that come with data analytics, the majority of them do not want to see what’s more than necessary.

 

Simplicity and Clarity in UX Design

It’s easy to get caught up with designing a visually beautiful dashboard, but you don’t want to go overboard with the ornate flare, especially in auto manufacturing If it ain’t baroque and you fix it, your dashboard can actually end up confusing your users. At the end of the day, simplicity and clarity provide better guidelines for a UX than beauty. 

In the LinePulse dashboard, all the complex operations along an assembly line are represented in a simple line graph. This allows a manufacturing engineer to identify the health of a particular operation and investigate the culprit(s) that contribute to the end-of-line failures.

For all the companies trying to jump on the Industry 4.0 bandwagon, many lack the capability to perform data analysis. This could be due to a lack of budget for hiring or a lack of qualified data analysts to hire. Therefore, it is important to design for the layperson as well as the expert: make the most important data immediately available to the user. However, this varies for each persona so a great dashboard is one where the information adapts to the type of user.

Data analytics is a complex subject but it pays to keep the UX for your data analytics tool as clear and simple as possible. If there is one takeaway, it’s this: present only the data that the user needs to see, when they need to see it. Spend time upfront to fully understand your users before you start designing. This will help your dashboard present the data in a consumable format and, more importantly, enable users to gather actionable insights.

Checkout LinePulse on our Solutions page for more information.

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