Your data project can transform your company, but first, you have to get them to listen!

A few months ago, at the company where I used to work, I found myself in a situation that might sound familiar. I had a data project that, in theory, could mark a before and after: optimize processes, reduce costs, improve decision-making. I had put everything in order, every number matched, the technology was ready to deploy... but there was an obstacle I hadn't anticipated. Those in charge of giving the green light seemed not to understand the project's importance, or simply weren't interested enough to put their signature on it.

The rejection wasn't direct, but it was constant. I presented projections, benefits, success stories... and I got the same answers: \"It's not a priority right now\", \"The budget is tight\", \"Maybe later\". It was frustrating. Seeing how an idea that could change the company's direction was left in limbo because no one dared to make a decision.

If you've been through something similar, you know how powerless it can feel. But after several failed attempts, adjustments, and learnings, I found a way to turn the situation around. And I want to share it with you.

Step 1: Win over a member of the management team

My first mistake was trying it alone. I thought solid data and a clear presentation were enough. But the truth is that without an ally within the organization, any initiative is very likely to remain on paper.

I observed the managers and realized something key: not everyone was equally interested in data, but some had urgent problems that my project could solve. I identified a manager who was under pressure due to wrong inventory decisions and went straight to him. I didn't talk about \"Big Data\", I showed him a scenario:

\"If your team could predict demand with 40% more accuracy, you could avoid these losses.\"

That was my entry point. He became my champion, and when someone in his position advocates for a project, the conversation changes.

Step 2: Present the project as a story, not a report

Before, I made presentations full of graphs and numbers. I thought that demonstrated solidity. What I didn't see was that managers didn't make decisions based on data tables, but on risks and opportunities.

The second time, I changed my strategy. I started like this:

\"Imagine you are responsible for a company losing half a million dollars a year because you can't anticipate demand. Your teams continue to rely on spreadsheets and intuition. You know there's a solution, but no one has taken action. Now imagine that in six months, that loss is reduced by half.\"

The managers stopped seeing my presentation as an expense and started seeing it as an investment with real impact.

Step 3: Define tangible success metrics

For those who approve budgets, phrases like \"greater efficiency\" or \"better insights\" mean nothing. They want concrete figures. So I set clear objectives:

  • Reduce analysis time by 30%.

  • Increase prediction accuracy by 25%.

  • Save $100,000 per year in operating costs.

  • Recover the investment in 12 months.

As soon as I put those numbers on the table, the discussion went from \"maybe later\" to \"When can we implement it?\".

Step 4: Find the right partner

Trying to do everything myself was another mistake. I wasted energy on details that weren't essential for approval. When I finally relied on a technology partner with implementation experience, the process became smoother, and my arguments, much more convincing.

At FluentData, we have accompanied many companies in this process. In a 30-minute session, we can analyze together the opportunities and strategies to take your initiative to the next level.

Step 5: Prepare the ground for implementation

Getting the project approved is not the end of the road. If internal teams are not aligned or if processes are not ready for the new technology, the project will fail before it takes off.

To avoid this, I involved the operations, sales, and finance teams from the beginning. I wanted the transition to be as natural as possible. When the time came to implement, there was no resistance, because everyone already knew the project.

Step 6: Don't build a house of cards

I used to think a data project was a final goal. Now I see it as a continuous process.

🔨 The data lake is the foundation.

🎨 Analytical models and machine learning are the walls and decoration.

🏡 A well-built house allows leveraging data, but it also needs constant maintenance and improvements.

Although I no longer work at that company, my project was not only approved but is underway and generating results. But the most important thing I learned is that approval doesn't depend on technology, but on how you manage to connect with the decision-makers.

You can achieve it too!

If you are in a similar situation, I know how frustrating it can be. But I also know that with the right strategy, you can succeed.

Tell me your case. Tell me what obstacle is holding back your project and let's work together on the best solution.

💬 Have you experienced something similar? Tell us in the comments.

📅 If you need support, schedule a session with us and let's see together how to take your project to the next level.