Scaling a business usually means addressing messy processes, clashing metrics, and teams that aren’t speaking the same language. For Madalina Teodorescu, Head of Marketing at HYDROGRID, these challenges are familiar. With more than 15 years of experience across digital, brand, performance, and demand generation roles, she’s seen how data pipelines either enable growth or break under the pressure of it.
In this episode of The Undiscovered Metric, Madalina shared the red flags to watch for, the mistakes she’s learned from, and why communication is the skill that matters most as companies scale. Watch the full episode below, or read on for key insights.
Where data breaks as you scale
Asked where she most often sees cracks appear in scaling businesses, Madalina points to one unmistakable sign: “The biggest red flag is when different teams report different numbers for the same metric.”
Those mismatches usually come from deeper problems. She explains that teams often base decisions on inconsistent naming conventions, disconnected systems, or too little data to make statistically sound choices. Sometimes they even ignore qualitative insights altogether.
The lesson? Scaling doesn’t work if you don’t have alignment at the foundation. As Madalina puts it, “for an early-stage startup, you need to simplify and measure fewer things, but with more accuracy.”
When processes are too rigid, they eventually crack under the pressure of scale.
The biggest mistake in scaling marketing
Looking back, Madalina is candid about the missteps she’s made herself. “The biggest mistakes I made were trying to scale too quickly or relying on my previous experience from different companies, different setups, different industries to do it just because I had results elsewhere,” she admits.
That shortcut approach rarely works. Every company’s setup, product, and audience is different. Instead, Madalina stresses the importance of industry knowledge and customer understanding. “You need to be on the sales calls. You can’t skip those. You need to actually listen to prospecting calls, join your customer success team,” she says.
Her advice is to nail down the basics first: a simple, shared data foundation, clear definitions, and real conversations with customers.
Skills and culture for larger data environments
As companies grow, data operations inevitably get more complex. More tools, more metrics, more teams involved. According to Madalina, one skill becomes critical above all others: communication.
“Everyone needs to speak the same language,” she explains. That means shared definitions, consistent naming conventions, and a common understanding of why data matters. Without that, scaling only adds noise.
Stakeholder alignment and clarity, she adds, are what keep operations on track. “If you’re clear on your objectives, on what you measure, and why you’re measuring it, then you can scale, even with just a few metrics.”
Clear, consistent communication is the foundation of successful scaling.
How AI changes the scaling game
Of course, scaling today doesn’t look the same as it did even five years ago. The rise of conversational AI and machine learning is making it much faster to turn raw data into insights.
“You can simply ask a platform to build your reports on your tracked metrics,” Madalina says. That reduces the need for deep technical skills and brings marketers closer to instant answers.
But she’s quick to add a caveat: AI only works if the data foundations are in place. “As long as the data connections and the data governance are in place, the speed and accessibility that AI brings help the entire organization get closer to actionable insights,” she explains. In other words, AI accelerates analysis, but it doesn’t replace the need for solid pipelines.
Culture and alignment as the ultimate enabler
Behind every successful scaling effort, Madalina argues, is culture. “I’ve never seen anything working well without a good culture,” she says.
That culture needs to be intentional: clear communication of goals, shared dashboards, and simple metrics that everyone can track together. Cross-functional workshops and knowledge-sharing sessions can help, but only if the organization maintains alignment from top to bottom. Tech alone can’t create value from your data. Fostering a data-driven culture is essential. Without it, teams slip back into silos.
Final takeaway
Scaling up your data operations often feels chaotic. A lot of the time, this comes from the impulse to add endless tools and try to track every possible metric. However, if you align teams around goals and metrics, stay close to customers, and start from a few simple shared metrics, then creating a data-driven culture becomes much more manageable.
While tools and metrics are important, Madalina makes it clear that scaling is ultimately about people. Shared language, cultural alignment, and communication are what hold a data strategy together as companies grow. Get those foundations right, and the technology can finally do its job.
About Madalina Teodorescu
Madalina Teodorescu is Head of Marketing at HYDROGRID, bringing more than 15 years of experience across B2B SaaS, e-commerce, and creative industries. She has built and scaled demand generation, brand, and growth programs for startups and scale-ups, including a four-year tenure at Adverity, where she led global campaigns during the company’s journey from early startup to unicorn. At HYDROGRID, she now leads marketing strategy and operations for a niche but growing sector, helping hydropower operators run their plants more efficiently with smart technology.
About Sam Holly
Sam Holly is the Sales Enablement Manager at Adverity, with more than ten years of experience helping sales teams perform at their best. Before joining Adverity, he held enablement and training roles at Google, Apple, Intralinks, and City Storage Systems, building programs that improved performance across EMEA and APAC.
