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5 Signs Your Analytics Dashboard is Wasting Time and the Better Analytics Platform for Retail Tech

4 min read

Feb 5, 2026 10:30:50 AM

Platform for Retail Tech

In Singapore’s fast-moving retail and technology sectors, data is essential but data alone isn’t enough. What really counts is how quickly insights lead to better decisions. Many teams invest heavily in dashboards but still struggle to extract value, spending more time sifting through screens than acting on insights.

If your team is frustrated with slow decisions, unclear insights or overwhelming dashboards, your analytics platform might be costing you precious time. Below are five signs your dashboard is wasting time, plus what to look for in a better analytics platform for retail tech teams.

1. Dashboards Are Rarely Used Outside a Small Expert Group

A common theme in BI adoption research is that access doesn’t equal usage.

Even though:

85 % of large organisations report using dashboards for analysis, and
78 % say dashboards are essential for decision-making,
many users still aren’t actively engaging with them.

For example:

Only around 29 % of employees actively use analytics and BI tools on average, even though the broader user base has grown.

This suggests a gap between availability and actual insight consumption. Dashboards sit idle and time invested in building them doesn’t translate to better decisions.

What to expect from a better analytics platform:
High adoption across teams, with insights that are intuitive and used in daily decision-making, not just archived reports.

2. You Spend More Time Building Than Analysing

Traditional BI dashboards often require heavy manual setup and ongoing maintenance. Teams spend time:

Preparing data
Formatting visuals
Updating dashboards when business questions change

According to industry research:

BI adoption surged to 67 % by 2025, but self-service analytics grew 25 % annually because teams want easy, no-code insight exploration.

This means analysts spend the majority of their effort on dashboard construction, not interpretation.

pexels-karola-g-5717794 Photo: Karolina Grabowska www.kaboompics.com: https://www.pexels.com/photo/a-man-sitting-at-the-table-5717794/

What to expect from a better analytics platform:
Automated data integration and AI-assisted insight generation that reduces manual effort and accelerates insight delivery.

3. Your Dashboards Show Data, Not Actionable Insight

Dashboards often provide metrics but not meaning.

Even leading BI thought leaders highlight that static dashboards tend to offer high-level summaries that lack decision guidance.

Meanwhile, advanced analytics trends show dashboard tools increasingly incorporate AI to:

Automate insight summarisation
Enable predictive analytics
Surface trends without manual interpretation

According to Gitnux’s 2025 dashboard report:

90 % of modern BI platforms will feature natural language generation (NLG) by 2025.

This indicates a shift away from raw dashboards to smartly interpreted analytics.

What to expect from a better analytics platform:
Insights that explain why something changed and what to do next, not just charts and numbers.

4. There Are Too Many Dashboards With No Clear Focus

Photo: weCare Media: https://www.pexels.com/photo/close-up-photo-of-black-digital-tablet-on-brown-surface-10020092/

Another frequent problem is dashboard overload.

Many retail teams end up with dozens of dashboards, each trying to cover every metric under the sun. This can lead to:

Confusing or conflicting KPIs
Teams unsure which dashboard to consult
Maintenance bottlenecks across departments

Industry data shows:

The average organisation uses multiple dashboard tools to try to cover all needs.

While this may provide visibility, it also fragments insight and slows decision-making.

What to expect from a better analytics platform:
Role-based views and focused insights that cut through noise and help teams make decisions quickly.

5. Dashboards Don’t Update in Real Time or Feel Contextual

In retail and tech, real-time visibility matters. Delays mean missed opportunities whether it’s adjusting promotions, responding to supply chain issues or adapting to shifting consumer patterns.

Relevant BI research shows:

64 % of enterprise BI users employ real-time analytics in decision-making.

Yet not all dashboards refresh frequently or adjust to evolving contexts without manual intervention.

What to expect from a better analytics platform:
Near real-time updates, actionable alerts and context-aware insights that tell you what changed and why it matters right now.

What Makes a Better Analytics Platform for Retail Tech?

The retail analytics market is growing rapidly, with demand for real-time insights, automation, and predictive analytics rising every year.

Modern retail and tech teams need more than static BI dashboards they need insight-driven analytics platforms that:

Automate data analysis
Support natural language queries
Deliver answers, not just charts
Scale across multiple data sources

Photo: AlphaTradeZone: https://www.pexels.com/photo/a-person-pointing-at-the-laptop-5784808/

A better analytics platform for retail tech should reduce reliance on technical experts, empower non-technical business users and help teams act quickly on insights.

Tictag Insight is designed with these principles in mind automating analytics and turning business questions into actionable answers without heavy dashboard creation or maintenance.

Key Takeaways

If your current analytics dashboard:

Is under-used or ignored by business teams
Requires heavy manual maintenance
Produces data without context
Overwhelms users with multiple dashboards
Lags in real-time insight delivery

…it may be time to reassess your analytics strategy.

Choosing a better analytics platform for retail tech can help your organisation save time, improve data adoption and unlock competitive advantage.

👉 To explore an alternative built for actionable insights, see Tictag Insight at tictag.io/tictag-insight.

Next week, we asked 100 retail executives about the same challenge and the results were surprising. Are dashboards enough, or do leaders need a different approach?