At Optima Partners, we’ve been reflecting recently on what the emergence of mainstream self-service analytics and AI-driven tools will have on the future of traditional business dashboards and at what point these may become obsolete.
Executive dashboards have been the gold standard for tracking key metrics like revenue, customer growth, and overall business performance for more than two decades, but with the hype increasing around AI and advanced data analytics, are dashboards finally on their way out?
The short answer is probably not. In fact, dashboards are still very much relevant, but we definitely see their role evolving in the near future. Let’s discuss why we believe that dashboards aren’t going anywhere, even with the proliferation of AI and self-service analytics.
One of the main things that excite people about AI is its ability to analyse data at scale, deliver predictions, uncover hidden insights, and make recommendations in real-time. But instead of making dashboards obsolete, AI actually enhances them.
Here’s why; Dashboards are fantastic at providing you with an overview of key performance metrics, but AI can take that one step further. Its strengths are in analysing large data sets, spotting trends, and highlighting anomalies that you might miss by just looking at a dashboard. AI can also forecast what might happen in the future, helping you to predict trends rather than just react to them. Huge for capitalising on emerging market opportunities and staying ahead of your competition.
For example, whilst a dashboard might show you current sales performance, AI can tell you which products are likely to see a spike in demand next month or which customer segments are most at risk. So, AI doesn’t replace dashboards it simply makes them a lot smarter and more effective.
Self-service analytics is all about empowering users to explore and analyse data without needing to rely on IT or data teams. This is great because it allows non-technical employees to dive into data on their own terms, and ask questions like, “Why did sales drop last week?” or “What are the biggest drivers for customer attrition?” through advancements in Natural Language Processing (NLP).
However, even with these powerful tools in the hands of users, dashboards still play a key role in making sure everyone is looking at the same set of data. Dashboards help standardise the critical business metrics and KPIs across departments, ensuring that teams are aligned on what’s important to overall performance and are using consistent data.
Without dashboards, you could have one team looking at one set of numbers, and another using a completely different dataset, which can lead to confusion and inconsistent decision-making.
Whilst self-service analytics powered by AI lets users explore the data freely, dashboards ensure that everyone is on the same page with the most important business metrics. What we’re seeing is that as the lines blur between the two solutions, the colleague experience is becoming vastly improved with a noticeably more seamless analysis workflow emerging for end users.
Traditional dashboards are going through a major makeover so that they no longer have to be static, one-size-fits-all displays. With AI, they can become much more dynamic. Rather than just showing a snapshot of data, AI can help make dashboards interactive and personalised to the user’s needs or contextualised to the specific business problem we’re trying to solve.
AI can also utilise a user’s past behaviour and suggest which metrics they should focus on. Or, if something unusual happens in the data – say, a spike in customer complaints – AI can flag that proactively for the user and suggest potential reasons for the change. It can even recommend actions to take to address the issue. A game-changer for the average non-technical user.
This turns a traditional dashboard into more of a smart assistant not only showing data but also guiding users to the insights that matter most in real-time. In this way, dashboards are evolving from simply being a display tool to becoming more interactive, insightful and user friendly.
Here’s the twist though – self-service tools and dashboards aren’t really in competition with each other, they serve different purposes. So, it’s important for you to factor this into your operating model design in terms of how data experts provide, and how users consume, data within your organisation.
Dashboards are awesome for tracking consistent metrics and ensuring alignment across teams. But self-service analytics gives you the flexibility to go beyond the dashboard and explore the data in ways you may not have thought possible, without being constrained by a backlog of ad-hoc data requests managed by a central data support team.
Our key takeaway is that dashboards aren’t going anywhere. In fact, with the addition of AI and self-service analytics, dashboards are becoming even more powerful.
Dashboards still provide the centralised view of your key business metrics. They’re essential for ensuring consistency, aligning teams, and tracking performance in real time.
And AI and self-service analytics tools are great for digging deeper and asking more complex questions than was ever possible before. Provided this happens within a well governed analytical environment of course.
Instead of replacing dashboards, AI and self-service tools are enhancing them. They work together to create a more dynamic, comprehensive data ecosystem where dashboards provide the starting point and AI adds the intelligence.
In the end, business dashboards are far from obsolete today – they’re evolving into smarter, more dynamic tools that still provide the consistency and structure businesses need.
Together, these technologies are creating a more agile, data-driven environment where businesses can track key metrics and also make smarter, more informed decisions in real time. So, whilst dashboard deployments may start to look quite differently in the future, they’re here to stay – and they’re going to be a lot more powerful with new AI capabilities.
If you’d like to learn more about how to leverage AI technologies within your existing analytics technology stack or are struggling to maximise the opportunities we’ve highlighted in this space, please fill out the form here or reach out directly to me via LinkedIn.
