Your ‘bad’ dashboard isn’t the problem

Dashboards are incredibly powerful tools for monitoring business performance and driving accountability. Studies show that companies who effectively use dashboards significantly outperform their peers on ten key business metrics.

Yet, business intelligence (BI) reporting goes largely ignored by all but 30% of users.  

Given the clear value of implementing a robust analytics practice, why is adoption and utilization of dashboards so low in so many organizations? Why do two-thirds of business leaders still say they’re not confident making data-driven decisions, even when they have dashboards that are readily available?

In many cases, the issue isn’t the dashboard itself, but rather the failure to consider how a dashboard will be implemented and used on an ongoing basis.

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Dashboard Design as a UX Problem

User experience (UX) designers know that great products deliver experiences that extend far beyond the user interface. Great UX creates empathy with users and considers how they will use a product and its auxiliary components, such as external communications, human interactions, and more.

For example, a user booking an Airbnb reservation might start in the app, but their full journey involves email and SMS reminders, an app notification with check-in instructions, and perhaps a phone call with the host. Airbnb knows traveling can be hectic, so they allow users to engage on whichever channel suits their needs at the moment. 

Dashboard UX design is no different. Often, when we see a lack of adoption and utilization in analytics, there’s a common underlying problem: the data wasn’t delivered in a way that suited the user’s needs.

In our experience with analytics UX design at Gitwit, we’ve rallied around three key methods for optimizing data delivery. We’ve found these factors significantly increase dashboard adoption and utilization, leading to greater accountability for teams and improved business outcomes.

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1 — Automated Delivery and Notifications

Nearly all dashboard tools include a mechanism for automated delivery, whether via email, Slack, or another channel. We recommend identifying an appropriate cadence for reviewing your metrics, and scheduling notifications to align your decision makers’ schedules. 

For example, you might deliver a profitability report on the first Tuesday of each month to help inform a recurring finance meeting scheduled on the same day. Leveraging the right distribution channel can also help boost adoption.

Email
The average professional checks their email 15 times per day, or every 37 minutes. This means that delivering your dashboard via email is likely to result in a user seeing and interacting with your data within less than an hour of delivery.

Another added benefit of email is that it doesn’t introduce any additional software or tools for your users to incorporate into their workflow or remember to access. When possible, we recommend delivering a snapshot of the dashboard, rather than just a link to a BI tool, so users can see the data firsthand without leaving their inbox. This active method of sharing data encourages users to be more engaged with the information and is less easily ignored or forgotten.

Better yet, a personalized email digest of the pertinent information for a particular user is far more effective than a bloated dashboard built for exploring mass amounts of data. 

For example, when we built our workplace feedback tool Inch, we designed custom recap emails showing product usage metrics, delivered on Fridays each week. The frequent reminders helped increase product adoption, as did the mild peer pressure from our mascot, Inch-e.

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Slack and Teams
For organizations that are more active on messaging applications than email, integrations with Slack and Microsoft Teams offer many of the same benefits of email report delivery.

We like messaging integrations because they can offer much more than just dropping a report screenshot in a Slack channel. The best implementations leverage tools that provide greater interactivity or even customizable alerts to enable management-by-exception. Some of our favorite tools include:

• Rupert, a platform that provides notifications when metrics meet predefined thresholds, with customizable action buttons in Slack.
• Tableau for Slack, a robust tool for facilitating dashboard collaboration, creating alerts, and even running analysis and predictions directly in Slack’s chat using slash commands.

For use cases requiring more customization, we’ve created our own applications and Slackbots using Slack’s excellent API or no-code tools like Zapier. We love these custom implementations as a way to facilitate two-way interaction with data coming from multiple sources. 

For example, we developed a Slackbot last year that finds new meeting attendees in our Google Calendar accounts and allows us to add them to our Mailchimp newsletter directly from Slack.

2 — Interactive Reporting

While dashboards can be great for monitoring set performance metrics over time, they can be limiting for those seeking a more exploratory, interrogative relationship with their data. Further, users without strong data literacy may struggle to turn raw data from dashboards into actionable insights.

Dozens of great tools have emerged in this space recently, leveraging AI or natural language generation (NLG) to help provide interpretation of complex datasets and trends. A few products that have caught our attention recently include:

• ThoughtSpot, an interactive search and conversation data exploration tool that connects to your BI data warehouse to generate insights.
• Tableau Data Stories, a feature of Tableau that automatically writes up-to-date narratives to guide users through a dashboard. Tableau’s AI offerings including conversational analysis are also rapidly developing.

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3 — Dashboard Utilization as a Management Practice

Of course, technology is no substitute for good old fashioned management. Adopting a disciplined process to review dashboards and having clear accountability for who is responsible for maintenance and updates can also drive more action from your data. 

This might be as simple as a scorecard that your sales team fills out once a week before reviewing together in a weekly standing meeting. Or, it might be a combination of reports that your data analyst is responsible for compiling and editing for review. Whatever the case, the simple act of disciplined review and refinement will get your team more comfortable and familiar with trends and norms and be more effective at spotting issues within the data that are worth solving.

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Dashboards are indeed valuable assets that demand considerable investment of effort, time, and money. However, their worth becomes trivial if they’re developed without UX scrutiny. 

If your organization is like most, and has faced challenges in building a data-driven culture, we’d love to chat. Our door is always open to sketch out a problem on our whiteboard and to ideate solutions. Drop me a line anytime at spencer@gitwit.com.