From Excel to Dashboard: Steps Not to Die Trying
Excel is the most successful tool in the history of business computing. It is flexible, powerful, and everyone knows how to use it (more or less). But Excel has a dark side: the "final_version_v3_revised.xlsx", hidden formula errors, and, above all, the huge amount of human hours lost every week updating manual reports. The natural step is to move towards a Business Intelligence (BI) system like Power BI or Looker Studio, but this transition is often a graveyard of failed projects.
Why do they fail? Because we try to replicate Excel in the Dashboard. And they are different animals.
Step 1: Admit you have a data problem, not a visualization one
Most companies that want "a nice dashboard" find that their data is a mess. Duplicate client names, dates in different formats, empty fields... In Excel, the human corrects this on the fly ("Ah, yes, this 'Ggl' means 'Google'"). The machine does not forgive. Before drawing charts, you need an ETL (Extract, Transform, Load) process that cleans the data automatically. If you don't invest 80% of the time in data cleaning, your dashboard will be beautiful, but it will lie.
Step 2: Define the question, not the chart
A classic mistake is to fill the screen with gauges and pie charts because "it looks good". A useful dashboard must answer concrete business questions. "Are we making money today?", "Which salesperson needs help?". If a chart doesn't lead to an action (calling someone, changing a price, congratulating a team), it shouldn't be on the dashboard. Less is more. A red/green traffic light is often more useful than a 50-row table.
Step 3: Automation is the key to life
If to update your new dashboard you have to download a CSV, open it, change a column, and upload it, you have failed. The goal of BI is to eliminate friction. Data must flow alone from your ERP or CRM to the screen. Tools like Fivetran, Airbyte, or even simple Python scripts can move data while you sleep. When you arrive at the office at 9:00, the dashboard should be waiting for you with yesterday's photo closed, not the other way around.
Cultural resistance: "But I want to see the rows"
The hardest change is mental. Excel users love rows and columns; they like to "touch" the data. A dashboard aggregates and summarizes. You have to train the team to learn to trust the aggregate and use interactive filters to "drill down" to the detail only when necessary. It is a data literacy process that requires patience and support.
Conclusion: A one-way trip
Moving from Excel to Dashboard is scary, but once you have it, there is no turning back. The feeling of control and the speed of decision-making you gain more than make up for the pain of initial data cleaning. Start with a single report, the most painful one to do manually, and automate it. The success of this small project will sell the idea to the entire company.