When you're ready to start getting more out of your company's data, one of the first big decisions you'll face is who to hire. Should it be an analyst, a data engineer, a data scientist, or even a data manager? While all these roles are vital, there’s a strong case to be made that your first data analytics hire should be an analyst. Here’s why:
1. Direct Business Impact
An analyst can make an immediate impact by tackling complex questions that drive growth and efficiency. As your business evolves, you'll need answers to increasingly complicated questions:
- In Marketing, you might ask: "Which ad channels are delivering the best ROI, and at what times?"
- In Operations, you may need to know: "How can we reduce stockouts while minimizing excess inventory costs?"
- In Sales, you could ask: "What are the characteristics of our most profitable customers, and how can we find more like them?"
And so on.
An analyst excels at interpreting complex data from multiple sources to answer questions like these.
They can clean and combine data, ensuring accuracy, and present actionable insights to stakeholders. By translating data into clear, understandable information, analysts enable informed decision-making that can significantly impact your business across various departments.
2. Versatility and Adaptability
If this is your first data hire, you probably don't have a data warehouse, BI tool, or sophisticated data infrastructure yet. You need someone scrappy and flexible who can work with what you have. Your data likely consists of whatever is native to your existing tools—think Shopify for ecommerce revenue or Facebook for ad performance.
You need an analyst with a broad skill set who can navigate this diverse landscape of data sources and tasks. They should be comfortable writing SQL against your production database, building dashboards, performing ad hoc analyses, and communicating insights across the business. This versatility is crucial in the early stages when you're just starting to build out your data function and your needs are diverse and evolving.
3. Immediate Value with Existing Data
Your company likely already has valuable data, even if it is scattered across various tools and systems. An analyst can pull insights from sales, marketing, customer service, and more to drive immediate value.
Unlike a data engineer who might need time to set up new infrastructure, or a data scientist who might want to build complex models, an analyst can dive in immediately. They can combine data from these disparate sources, clean it up, and start providing actionable insights that inform acquisition, customer retention, and operational efficiency.
This quick time-to-value is crucial when you're just beginning to build out your data capabilities and need to demonstrate the impact of data-driven decision making.
4. Foundation for Data Culture
Hiring an analyst lays the groundwork for a data-driven culture. McKinsey predicts that by 2025, most employees will use data to optimize nearly every aspect of their work. Studies consistently show that data-driven companies outperform their competitors. By bringing on an analyst, you're taking a crucial step towards this future.
Having someone with "data" in their job title transforms data from a side task into a core priority. This cultural shift is essential for long-term success and marks the beginning of your journey towards analytics maturity.
Tip: Need a hand building a data-driven culture? Check out our seven tips on how to do exactly that.
5. Bridging the Gap
Analysts often serve as a bridge between technical data functions and business operations. They understand the language of data as well as the business context, making them ideal for communicating complex insights in a way that’s relevant and understandable for business leaders. This ability to translate technical findings into actionable business strategies is invaluable.
6. Cost-Effective Start
From a budget perspective, hiring an analyst can be a cost-effective way to start building your data capabilities.
According to Indeed, the average salary for a data analyst in the US is $78,258 per year, whereas data scientists earn an average of $123,379 annually. That’s nearly a $45,000 difference, yet analysts still deliver substantial value.
This makes them an ideal first hire for companies looking to get started with data analytics without a significant upfront investment.
7. Foundation for Growth
As your data needs grow, the foundational work done by your analyst can guide future hires.
They'll establish initial data processes and reports, and identify key metrics that matter to your business. This analyst will likely be the one to implement your first data warehouse, set up basic BI tools, and create initial dashboards. Their insights will highlight areas where more specialized roles are needed.
For instance, they might uncover data quality issues that call for a data engineer, or complex predictive problems that require a data scientist. By starting with an analyst, you ensure that future hires and tools address real, identified needs rather than presumed ones.
This sequential growth approach helps you build a data team that's closely aligned with your business objectives and ensures each new hire or tool investment is based on demonstrated value.
Example: What to Expect When Hiring a Data Analyst
Every company and every data analyst is different. But here is a typical scenario to illustrate the potential impact.
Take a fast-growing DTC brand that decided to hire an analyst as their first data hire.
Let’s say the analyst started by cleaning and organizing existing sales data, which revealed patterns in customer behavior and purchasing trends. By creating clear, actionable reports and dashboards, the analyst helped the marketing team optimize their campaigns, resulting in a 20% increase in conversion rates within the first six months.
The initial success demonstrated the value of data-driven decision-making and paved the way for future investments in data infrastructure and additional hires.
Final Thoughts
Analysts provide a cost-effective entry point into the world of data analytics and help bridge the gap between technical data functions and business operations.
It’s important to remember that an analyst is not just a data interpreter but a catalyst for growth, driving your business toward a more informed, data-centric future. Investing in an analyst as your first data hire is a strategic decision that can yield significant returns, both in the short and long term.
Still not sure who to hire? A data agency might also be a good option. Check out our deep-dive comparison Hiring an In-House Data Analyst vs. An Agency: Pros & Cons to make the best decision for your business. Or reach out to our team directly for tailored advice.
