Die or thrive - what's next for dashboards
BI needs to evolve to create actionable insights and business impact
Published on Fri 27 Jan, 23
Dashboards have been around for over 20 years as the go-to product for business intelligence. Back then, businesses didn’t collect much data and dashboards enabled both reporting (i.e., metrics monitoring) and actionable insights (i.e., diagnostic analytics).
However, a lot has changed in the meantime. Businesses collect more data than ever. In fact, 90% of the world’s data has been collected over the last 2 years. Businesses have millions of data points across products, marketing, etc. Moreover, the needs and expectations have significantly increased. Business stakeholders need to be agile, hence expect quick and comprehensive answers in order to make decisions before it’s too late.
This new complexity and expectations make dashboards fall short for many use cases, especially around data exploration and diagnostic analytics. Many teams navigate around multiple dashboards as if they are navigating in a foggy forest hoping to have a light to help them uncover a path.
“Dashboards started out as reporting tools for measuring the health of the business. They’re great for this purpose. The problem arises when you extend this simple purpose into data exploration.”
Some vendors claim that dashboards are dead, which I consider to be exaggerated. Dashboards are here to stay. They are very valuable in business monitoring, understanding how key business metrics are evolving, and to catch high-level trends. (e.g., marketing spending across regions). They enable people to observe what is happening in the business over time.
The problem raises as dashboards are trying to be repurposed. Every time business stakeholders ask data analysts for a new dashboard on a key business metric, what they actually say is “We need to understand what’s driving this key business metric and what can we do to improve it.” Adding more charts looking at the business metric from different angles is likely useless. All these dashboards won’t answer the most fundamental question: “Now what?”.
Oftentimes data people believe that a comprehensive, well-designed dashboard is a very capable data product that gives business stakeholders endless possibilities to answer any questions they might have.
The reality? Frequently, it’s far from it. Oftentimes business stakeholders and data analysts run into an insights dead end. To reach the “so what”, teams first need to understand what triggered the change in the metric. And the process of diagnosing a key business metric change can be very tedious. And outcome looks something like this:
The outcome of dashboard-based analysis (image by Anderson for eQuest)
The new reality in the amount of data and business speed is making these shortcomings more evident and these 3 requirements critical:
Relying on reports and dashboards that only present what happened with key metrics and having to drill down to why these changes happened manually doesn’t meet the expectations anymore. Nowadays organizations set carefully designed metrics, expect to be able to monitor these on a daily basis and make fast decisions based on the latest numbers.
Continuing with traditional approaches results in 4 main negative consequences, leading to significant lost business value:
Dashboards rarely provide actionable insights. Teams should focus on complementing reporting dashboards with analytical products that enable comprehensive diagnostic analytics at the speed of business.
(image by Kausa — dashboards for reporting and high-level trends; augmented analytics for diagnostic analytics)
New requirements push for solutions based on 5 pillars:
(image by Kausa - new requirements of Dashboards)
Dashboards need to be complemented whenever speed and/or comprehensiveness of the analysis is paramount. A couple of real use cases that have been rising:
Automated insights messages on key business metrics drivers
Many business teams take daily/weekly decisions to optimize the KPIs they own. For instance, performance marketing managers adjust their campaigns and bids on a daily/weekly basis to optimize ROAS (Return on ad spend). With dashboards-based workflows, these teams either spend hours slicing and dicing on dashboards or cut corners and miss out on insights. Augmented analytics can automatically test all the hypotheses, rank the drivers and deliver automatic messages on key business metrics. They can be delivered over Slack, Teams, or Email, making analytics more accessible.
(image by Kausa - delivering data-driven insights over Slack messages)
Comprehensive exploration into drivers of key business metrics
While business teams enjoy easy-to-consume insights, data teams need a smarter way to explore data. The need for diving deeper into the analysis and contextualizing it will never disappear, but it is critical for tools to bring focus to the analysis. So that teams know exactly where to start and focus on segments/subsegments which are prioritized after automated analysis. In the example below, augmented analytics can show that one specific marketing campaign (across hundreds) in Germany is driving a significant increase in AOV for younger customers. Finding these insights in a manual way is like looking for a needle in a haystack. Through augmentation, it takes just a couple of clicks (read more in this article).
(Image by Kausa - Priotization of drivers by impact)
As businesses collect more data and change faster than ever, BI expectations and needs have evolved. Data teams need to deliver effective self-service to scale impact and outcomes. Actionability requires insightful information delivered in a proactive and easy-to-consume manner. Thus BI needs to become augmented, proactive, insightful, integrated, and conversational. This is the only way to improve speed to insight, make analytics more accessible and multiply the outcome of analytics teams.
João Sousa is the Director of Growth at Kausa. Stay tuned for more posts on how tomore posts on how to nail diagnostic analytics and increase the value of data.
Using machine learning, Kausa can analyze all your data, diagnose why metrics are changing, and provide actionable insights to improve business performance. With Kausa teams can save countless hours on data analysis and get ahead of competition by finding opportunities to unlock hidden value.
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