Analytics Is Like Cooking — And Most Teams Skip the Recipe
- Michael Lee, MBA
- Aug 8
- 5 min read
Walk into any professional kitchen and you’ll see more than just food being made — you’ll see systems, collaboration, creativity, and precision all working in harmony.
Now walk into a data team’s workspace. You might find dashboards instead of dishes, spreadsheets instead of spices — but the dynamics? Surprisingly similar.
That’s why I love the analogy:
Analytics is like cooking. And just like cooking, it takes more than raw ingredients to get a great result.
Let’s explore the 4 essentials every analytics process needs — and how the kitchen gives us the perfect metaphor to make sense of them.
🍅 1. Data = Ingredients
In the kitchen: You start with raw ingredients — fresh, frozen, or somewhere in between. Some are top-quality; others are about to expire. You need to clean, cut, peel, weigh, and prep before they’re usable.
In analytics: You start with raw data — sales records, customer feedback, employee surveys, website clickstreams. But raw data is not insight. It’s messy, incomplete, and often inconsistent.
Real-World Example:
A retail chain wanted to understand why sales dipped in Q3. They had transactional data, footfall data, and POS logs. But the timestamps were inconsistent across stores, some files were missing entries, and others used different date formats.
Cleaning that data took a week — but it revealed that sales weren’t down overall. They had simply shifted channels. More customers were buying online — something only visible after correcting the store IDs and aligning timestamps.
Lesson: Just like spoiled ingredients can ruin a dish, dirty data can spoil your analysis.
A chef doesn’t grab everything from the pantry. They select what’s needed for the dish they’re making. Likewise, analysts must start with the question, not the dataset.
Key question: Are you gathering data with purpose — or just hoarding it like kitchen clutter?
⚖️ 2. Technology & Tools = Pots, Pans, and Appliances
Even the best ingredients go to waste without the right tools.
In the kitchen: You need tools that match the job — from non-stick pans to high-powered mixers. Some dishes need low heat and patience; others need a blowtorch.
In analytics: Tools like Excel, Power BI, SQL, Python, Google Sheets, or ChatGPT all serve different purposes. You don’t need every tool — just the right one for your task, and the skill to use it well.
Real-World Example:
An operations team was struggling with a massive Excel file used to track manufacturing defects. They were using filters, copy-paste, and manual counting. A consultant introduced Power Query, which transformed their workflow — cleaning, merging, and updating everything with a single click.
The team didn’t need new data. They needed a better pan to cook with.
Lesson: Good tools make your work faster, cleaner, more scalable — but only if you know when and how to use them.
Key question: Do your tools match the complexity of the dish — or are you frying eggs with a hairdryer?
📖 3. Frameworks = Recipes
In the kitchen: Recipes offer order and consistency. Even chefs who improvise build from foundational knowledge. Great cooking is not chaos — it’s creative constraint.
In analytics: Frameworks help structure the thinking. You don’t just jump into analysis — you break down the problem and build your way to insight.
Real-World Example:
A regional bank was losing young customers. Rather than guessing, the analytics team applied a Fishbone Diagram to identify causes: UX issues, product relevance, customer service wait times, digital onboarding delays. Then they used customer feedback data to validate each branch of the diagram.
They didn't start with dashboards. They started with thinking — like following a recipe before turning on the stove.
Alternative approach: Some teams use SWOT analysis to guide what data to gather — internal strengths and weaknesses vs. external threats and trends. This ensures they focus only on relevant signals, not noise.
Real-world moment: Ever been handed a massive Excel sheet and told “find something interesting”? That’s what happens when there’s no recipe.
Key question: Do you follow a clear process — or do your analytics projects feel like potluck every time?
🤝 4. People = People (Surprise!)
Even with the best data, tools, and frameworks — nothing happens without people.
In the kitchen: The coordination between prep, cooking, plating, and serving is critical. Chefs communicate. They adjust. They cover for one another.
In analytics: Misalignment between data teams and business teams is a recipe for disaster.
Real-World Example:
An HR department wanted to understand employee attrition trends. The data team pulled numbers, charts, and pivot tables showing exit rates by department, tenure, and age. But leadership wanted to know something different: why people were leaving — not just how many.
The teams weren’t speaking the same language.
After regrouping, they created an analysis flow that combined exit interview text data with tenure analysis. Now it told a story: most resignations among junior staff weren’t about salary — they were about poor onboarding and lack of recognition.
Human moment: Ever built a gorgeous dashboard only to hear, “Yeah, but that’s not what we were looking for?” That’s what misalignment feels like. Burnt toast.
Key question: Are your people working in sync — or yelling across the kitchen with different recipes?
🥘 So, What Are You Cooking?
In both analytics and cooking, the goal is the same: transformation.
You're not just serving raw data.You're serving understanding. Insight. Action.
You’re feeding decision-makers something they can chew on — and do something with.
When everything comes together — clean data, the right tools, a solid framework, and a high-performing team — the outcome is more than “just a dashboard.”
It’s a meal worth remembering.
🔄 Final Thoughts: You Don’t Need to Be a Master Chef
Not everyone needs to be a five-star data scientist.But just like cooking, anyone can learn the basics:
Clean your data
Use the right tools
Follow a proven process
Collaborate well
And just like great food, great analysis starts with curiosity and care.
So the next time you open a dataset, ask yourself:“What am I cooking today — and who’s it for?”
👨🍳 Want to Know What Kind of 'Chef' You Are?
At FYT Consulting, we design hands-on workshops that help you build the skills, mindset, and confidence to cook up clear, compelling insights — no matter your level.
If you're curious whether your team is running a well-oiled analytics kitchen… or just microwaving spreadsheets — let’s talk.
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