With over 20 years of experience in the data and data operations arena, I’ve seen, created, and decommissioned my fair share of dashboards.
I know what you’re thinking: Didn’t ThoughtSpot say dashboards are dead?
And to that effect, you’d be correct. The static, inanimate, out-of-sync dashboard is antiquated and lifeless. That’s why we offer a Liveboard. It’s interactive, real time, and created for sharing, embedding, and data storytelling.
But regardless of what you call them, these data snapshots still play an important role in the modern business landscape.
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A BI dashboard is an information management and data visualization tool that tracks, analyzes, and visualizes KPIs and critical data points of an organization's performance. It is designed to help business users quickly analyze and understand complex data in a visually intuitive way.
For instance, consider your smartwatch—the data you see about your activity is a form of a dashboard, fit with KPIs and data visualizations.
A BI dashboard is a great way to convey an accurate representation of the business to an audience who doesn’t always have the time or know-how to sort through a data sheet and perform their own analysis. Traditionally, it has been the job of a data team or analyst to compile these dashboards for the business leader or business user to consume.
A BI dashboard may pull in data from disparate sources to create meaningful insights. For example, consider how a marketer might utilize Google Analytics to review their website performance. However, when you need to see how this data correlates with data from other sources, having a centralized data repository and business intelligence solution helps you unlock otherwise disparate data insights.
A dashboard is typically fitted with a series of KPIs and data visualizations. Instead of seeing personal activity data on your smartwatch, the data you see in your BI dashboard is pulled from various business sources and modeled to provide information relative to your company and/or role.
BI dashboards can also include filters, parameters, and drill-down features that allow you to find additional insights sitting below the surface-level data visualization. You might also find text boxes or widgets that provide contextual information about the data.
These features are all fairly standard for BI dashboards. Modern solutions like ThoughtSpot’s Liveboards also feature components that increase functionality for all types of users. Here’s a few examples:
Unlimited drill paths and data visualization filters to help users explore their data
Verified Liveboards for data governance, quality and trust across your organization
SpotIQ to provide AI-assisted insights from data visualizations or KPIs
Mobile monitor for real-time alerts on KPIs thresholds that matter to your business
Connectors to operationalize dashboard data through sharing and collaboration
But the true value of these tools is not how beautiful they are, how long it took you to build them, or how well-modeled the underlying data is. BI dashboards only have impact if they’re being utilized to make data-driven decisions.
Liveboards are designed to increase user engagement and adoption by meeting users where they are. Their level of data fluency, time restraints, and ability to view data in the applications that they’re already working on—all of this enhances data usability, exponentially increasing the value of your data (and your data team) to your business.
Creating a useful dashboard isn’t the same for every company or every team. That said, there are a few general steps you can follow to help ensure your dashboard provides business value.
1. Understand the needs of your stakeholders
Start off with an intake. Here are some questions you might want to consider asking:
Who will be using this dashboard?
What insights are the most important to these users?
What does their current vs ideal workflow look like?
What data sources are they currently using?
Will they actually have time to log into the dashboard, or should you set up a KPI monitoring system?
If they are using the dashboard, what paths will they need to be able to drill down into?
What information should your users be able to access? And perhaps more importantly, what data should they not access?
2. Clearly define and agree on your objectives
Once you’ve completed your discovery, you can draft the project objectives. This should be a collaborative process between you and your stakeholders. It isn’t complete until the objectives are clearly defined and agreed to by both the data team and the end consumers.
3. Build your data pipeline
Now is the time to start building a pipeline for your data—funneling the information from disparate sources, mapping each data point back to your business data, and ensuring the necessary information is governed and accessible to relevant stakeholders.
Here’s more on how to build a data pipeline.
4. Collaborate and iterate on layout and design
With your objectives in mind, you can start mocking up the dashboard layout. This is more important when using a static dashboard like PowerBI or Tableau.
ThoughtSpot is different. Our search-based, interactive data visualization experience allows you to easily pin, iterate on, and share your Liveboard design in real-time—I often do this during a team meeting or collaborative session.
Either way, it’s important to include your stakeholders in the design process.
5. Prioritize performance and accuracy
In a Harvard Business Review survey, 66% of respondents said improving data quality and trust is the most important step to increasing data value. That’s because analytics adoption and use for decision making correlates with data trustworthiness.
The users’ ability to access that dashboard and speed to insight is also an important factor. If you want your team to actually utilize the dashboard, you’ll want to minimize the effort and time it takes to find the right data. That means prioritizing load speed and minimizing workflow interruptions.
6. Tell a data story to your audience
Think about your audience and how this data applies to their role. Try to put the data into a format that fits into that workflow. For example, maybe they have a KPI that needs to be monitored very closely. If that’s the case, put said KPI at the top left-hand corner so it will be the first thing they see.
This is also an opportunity to provide contextual components to your data. For example, ThoughtSpot’s note tiles allow you to provide important directions for how to read or use a specific visualization.
7. Show how to get the most value from the data and dashboard
You have to remember that your audience isn’t necessarily a data savant. Sure, most users have some level of data literacy, but it will vary in degrees depending on your audience.
When you launch a new dashboard for your team, this is your opportunity to show them the power of the dashboard you’ve built, and underline the value of using data in their day-to-day processes. If they see it in action, they are more likely to buy in and incorporate the new workstream into their current workflow.
8. Monitor and iterate based on post-launch usage
Even if you follow all of these steps down to the letter, there will undoubtedly be changes to workflows, data that didn’t turn out to be useful, or new data sources that get introduced. That’s why it’s important for data teams to monitor dashboard usage and set regular check points with teams to understand areas for improvement.
As mentioned before, every team will have different dashboard requirements. However, here are a few examples and ideas to get you started:
Marketing dashboard covers a lot of different arenas, and everyone has different data sources they monitor—from website analytics and SEO to social media and paid advertising.
More reading: Mode + ThoughtSpot were recognized as Leaders in Snowflake’s 2023 Modern Marketing Data Stack awards
Your sales leaders need a sales dashboard to get up-to-date, SKU-level insights so they can get the high-level overview or drill down to the most granular level.
More reading: See how Fabuwood decommission 50 manual reports with interactive Liveboards
Your HR team can use analytics and measure HR KPIs to mitigate risks like employee turnover and forecast opportunities for your team and your business.
More reading: Discover 5 powerful ways to use people analytics in HR
Some might argue that finance professionals are one of the most data-driven teams in a company. The insights they draw from the financial dashboard can cause your business to sink or swim.
More reading: Here are the top 3 data visualizations for finance professionals
Similarly, your interactions with customers can have a direct impact on your bottom line. It’s important to monitor rep availability and handle time with a customer service dashboard. Additionally, use a customer experience dashboard to track overall customer satisfaction and experience metrics.
More reading: See how managers at Wellthy use Liveboards to support their 200+ member care team
System availability, security, access control, data quality—the list goes on. Having visibility into data trends can improve your IT responsiveness, adding value to your business.
More reading: Here’s how Snowflake hit 99% of IT commit goals with ThoughtSpot for ServiceNow Analytics
There are a number of BI dashboard tools on the market, and it’s likely your business already has one in its arsenal of data solutions. So how can you know which one provides you with the most value in the long run? Here’s a few topics to keep in mind:
Look for a BI solution that offers modern features and connectors—this increases user engagement and data-driven decision making.
Ensure your solution helps all users find granular, actionable insights—reducing your data team’s backlog while maximizing the value of your data.
See if your BI provider is still investing in new features and iteration—are there community resources and do they have a track record of customer-centric innovation?
Don’t leave your data sitting in some siloed, lifeless dashboard. Start your free trial today, and experience the differences between a dashboard and a Liveboard for yourself.
