The speed of information is key to turning data into strategic assets.
But although this idea is already clear to many leaders, it is still rarely applied in practice.
The reason? A silent enemy: the difficulty in organizing, processing and distributing this information efficiently on a daily basis.
Without a well-defined flow, decisions end up being made based on assumptions and valuable opportunities are lost along the way.
That’s where the data treadmill comes in, but what does it mean in practice?
It is a structured path that information takes within the company – from its origin, through stages of organization and analysis, until it reaches the hands of those who need to act.
It connects people, systems and areas, ensuring fast and reliable access to the right data at the right time!
In this sense, with a well-designed conveyor belt, the company reduces rework, eliminates guesswork and makes decisions with more confidence.
The invisible problem: why are dashboards slow, inconsistent and full of errors?
You’ve already invested time and money creating incredible dashboards, with modern graphics, up-to-date KPIs and a board-friendly interface.
But when it comes to the meeting, the reality is different: incomplete data, delayed information or, worse, indicators that don’t match the company’s official figures.
This is a classic symptom of a poorly implemented data warehouse. According to Gartner, more than 25% of critical corporate data contains errors or inconsistencies that directly impact business decisions.
The problem almost never lies with the BI tool. More often than not, the source is behind the scenes: faulty extract, transform and load (ETL) processes, multiple sources without integration and fragmented technical support.
The turning point: when centralizing the belt changes the game
Recently, we followed a case in which the turning point came precisely because of a move towards centralization.
Previously, the company relied on different suppliers and teams to keep its conveyor belt running. Each program (10 in all) had a different person in charge.
The result: low predictability, slow problem resolution and a constant volume of technical calls.
As they felt they needed support, our team of specialists soon began to take care of the support of almost the entire conveyor belt (9 out of 10 systems), with a response SLA of just 10 minutes, proactive action and a continuous focus on operational improvements.
The impact was immediate:
- Gradual drop in the volume of errors and calls
- Greater stability in data loading and transformation routines
- Better integration between programs
- Dashboards finally fed with reliable and timely data
This approach is in line with the concept of “Data Cost Efficiency”, highlighted by McKinsey, where the focus is on reducing costs with data operations without compromising the quality and agility of deliveries.
Why is the performance of dashboards directly linked to the data treadmill?
Many people only start looking at the treadmill when the dashboard breaks down. But the truth is that the success of the visualization layer depends 100% on the health of the data ingestion and processing layer.
According to a study by Xenoss, good practices in data pipelines include constant monitoring, real-time fault handling and validation routines before the data even reaches BI.
Another key point is data normalization, a process that ensures that different sources speak the same business language. As Moldstud points out, without normalization, the interpretation of indicators can be biased and dangerous for decision-making.
Practical lessons for those who want more reliable and agile dashboards
If your company is facing any of these warning signs:
- Dashboards with broken or inconsistent indicators
- Slow processing of large volumes of data
- Dependence on several suppliers to keep the operation running
- High volume of technical calls related to the data layer
It’s time to take a closer look at your treadmill.
The solution is not just to adopt new tools, but to rethink the support model, prioritizing centralization, aggressive SLAs and a team that understands the complexity of your data environment.
Where Wevy comes in
Here, we offer much more than technical support. Our Data Warehouse Construction and Sustainment service is designed for companies that need a solid, scalable database with absolute operational control.
We focus on
- Intelligent automation of data processes
- Safety in all belt layers
- Agile monitoring and response with aggressive SLAs
- Performance management and end-to-end data governance
If you’re looking for more performance, more predictability and less headaches in your BI operation, talk to our experts and find out how we can help turn your data warehouse into a real intelligence engine for your business.
Find out more at: https://wevy.cloud/dados-ia/
Until next time
