Intelligent Investment

The Perfect Recipe

By: Amber Miller, Senior Director, Portfolio Technology & Data Intelligence

June 22, 2026 6 Minute Read

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Better data, not more technology, drives better outcomes.

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I love to cook. Not the open-the-fridge-and-see-what-happens kind of cooking, but the kind where you decide on a dish, read the recipe carefully and respect the process. The kind of cooking where timing and measurements matter, and preparation shows in the result.

Early on, I learned a simple lesson that most experienced cooks eventually accept: If you change ingredients or skip steps, don’t be surprised when the recipe doesn’t work. You might still end up with something edible, but it will not be what was promised. 

Good cooking rewards patience and preparation over clever shortcuts. And while good tools can make cooking easier, they have little bearing on the outcome.

After 20-plus years working in commercial real estate data, I’ve found that managing enterprise data intelligence works much the same way.

Across the real estate industry, companies continue to invest in new platforms and analytics tools, all with their own artificial intelligence. Each promises more insight, efficiency and speed. And each can play an important role.

But technology isn’t the meal; it’s the appliance. And data is the key ingredient.

No matter how advanced the tools, they cannot compensate for poor inputs or unclear instructions. Research consistently shows that poor data quality costs companies an average of nearly $13 million each year and contributes to a meaningful share of failed business initiatives.

With AI, the impact is even more visible. Many projects struggle to deliver on their promise not because of the models themselves but because the underlying data was never ready for the task.

I’ve seen enterprises struggle to optimize portfolios because the foundational data could not support what the technology was designed to do: Reports told different stories. Dashboards produced conflicting results. Leadership teams spent more time questioning the numbers than acting on them.

These are not technology problems. They are preparation problems.

In cooking, ingredient quality sets the ceiling for what is possible—and preparation ensures each element can unlock its full potential. Presentation can only take you so far if the fundamentals are weak.

In real estate, data is the ingredient that feeds every system and decision. Across industries, more than half of all datasets contain meaningful accuracy issues, and data inaccuracy impacts most organizations. Asset attributes, lease terms, space allocations, utilization metrics, energy readings—all of it underpins operational reporting, portfolio strategy and long-term planning.

AI systems learn from the data they are given. When that data is incomplete, inconsistent or poorly understood, the effects cascade quickly. Automation behaves unpredictably. Analytics lose credibility. Teams compensate manually, filling gaps with spreadsheets and reconciliations that slow everything down.

When data quality is prioritized and care is given to cleaning and organizing it properly, the opposite happens. Reporting becomes consistent. Conversations become simpler. Decisions feel more confident. The organization spends less time fixing issues and more time using insights.

Preparation and governance enable scale.

In many companies, it’s not uncommon for highly skilled data professionals to spend 60%-80% of their time cleaning, organizing and reconciling data before analysis can even begin. That effort shapes everything that follows.

It’s easy to view governance as restrictive. Standards, definitions, ownership, validation rules: On the surface, they can feel like obstacles.

Early in my career, much of the work centered on getting the numbers right: making sure the reports reconcile, fixing data issues when they surface, responding to requests as they come in. Over time, expectations changed. Leaders wanted more than accurate reporting. They wanted foresight. They wanted agility. They wanted to understand not just what was happening, but what should happen next.

That shift mirrors the difference between following a single recipe and running a kitchen. Success depends less on individual effort and more on the systems that enable consistent results across people, tools and time.

Governance is what makes this scale possible.

While most organizations have begun investing in governance, only a small fraction have reached true maturity. In fact, just 3% of companies meet basic governance standards today.

Just as a recipe provides structure so cooks can repeat results consistently, data governance provides a shared understanding of what information means and how it should be used. It ensures that as portfolios grow and change, the data supporting them remains aligned.

Without governance, organizations operate in a constant state of correction. With governance, they build systems that hold up under pressure.

AI doesn’t fix weak foundations. It amplifies them.

Artificial intelligence has become a focal point in real estate discussions, from predictive maintenance to portfolio optimization. The potential is real, but it comes with a misunderstanding.

Without data intelligence, there can be no sustainable benefit from AI.

Organizations that see lasting value from AI will be those that invested first in data quality, governance and alignment.

Don’t get me wrong, there’s nothing wrong with delivering quick wins and immediate value. But the longer-term advantages are where the difference compounds. Think lower cost of future change, faster adoption of new technologies and confidence that insights will remain valid as portfolios evolve.

Like a good recipe, the payoff grows over time.

CBRE’s Data Intelligence group grounds itself in a simple belief: strong outcomes depend on strong fundamentals. We help organizations align data, governance and operating models so technology investments deliver consistent and dependable results over time.

This is not about building the most complex kitchen. It is about making sure the ingredients are sound, the instructions are clear, and the process can scale as portfolios grow and shift.

When that foundation is in place, insight comes more easily, decisions are steadier, and results tend to hold up over time.

If the dish is not turning out the way you expected, it may not be the recipe. And it may not be the tools. It just may be time to take a closer look at the ingredients and make sure they’re being properly prepped.

About the Author

Amber Miller is a Senior Director of Portfolio Technology & Data Intelligence at CBRE, where she advises occupiers and investors on building trusted, scalable data foundations that enable better decision-making and responsible adoption of advanced analytics and AI.

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