LILA vs Hiring a Data Analyst: The Real Comparison

A data analyst costs $60-100k/year. LILA costs $75/month. But is that comparison even fair? Here's when each makes sense.

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The Price Tag Comparison

The AI vs data analyst debate starts with numbers:

Junior Data Analyst: $60,000-80,000/year + benefits Senior Data Analyst: $90,000-130,000/year + benefits LILA Professional Plan: $900/year

On pure cost, this isn’t close. But that’s not the whole story.

What a Data Analyst Does

Let’s be honest about the full scope:

Report creation and maintenance. Building dashboards, updating reports, ensuring data accuracy.

Ad-hoc analysis. Answering business questions that arise throughout the week.

Data cleaning and preparation. Handling inconsistencies, missing data, format issues.

Strategic insights. Connecting patterns across data sources, identifying trends.

Stakeholder communication. Translating data findings into business recommendations.

Tool management. Maintaining BI platforms, managing data pipelines.

This is skilled, valuable work. Much of it can’t be automated.

What LILA Does

Ad-hoc queries. Instant answers to data questions from anyone on the team.

Self-service reporting. Users get their own answers without analyst involvement.

Basic visualization. Charts generated from query results.

That’s it. LILA doesn’t replace an analyst. It replaces a specific part of an analyst’s job: the routine queries that create bottlenecks.

The Real Question

The question isn’t “LILA or analyst?” It’s “Which parts of data work need a human?”

Needs a human:

  • Understanding business strategy
  • Choosing what to measure
  • Building data infrastructure
  • Complex statistical analysis
  • Communicating insights to executives

Doesn’t need a human:

  • “How much revenue last month?”
  • “List customers who haven’t ordered in 90 days”
  • “Show me sales by region”
  • Basic queries anyone should be able to run

When LILA Makes Sense

You can’t afford a data analyst. For businesses under $5M revenue, a full-time analyst rarely makes financial sense. LILA costs less than 2% of analyst salary.

Your analyst is overloaded. If your analyst spends 30% of time on routine queries, LILA frees them for strategic work.

Speed matters. Analysts have backlogs. LILA has no queue. If questions need answers in seconds, not days, self-service wins.

You need broad access. One analyst can’t serve 50 people promptly. Self-service scales.

When to Hire an Analyst

Data infrastructure needs work. If your data is scattered, inconsistent, or undocumented, you need human expertise first.

Strategic decisions depend on analysis. Major pricing, product, or market decisions require human judgment, not just data retrieval.

Complex analysis is routine. Cohort analysis, attribution modeling, predictive analytics require specialized skills.

Compliance and governance matter. Regulated industries need human oversight of data access and usage.

The Hybrid Approach

The AI vs data analyst question usually resolves to “use both”:

Analyst handles:

LILA handles:

  • Day-to-day questions from team members
  • Ad-hoc queries during meetings
  • Support team data lookups
  • Basic self-service reporting

Analyst becomes more valuable because they focus on high-value work. Team moves faster because they don’t wait for analyst availability.

The Math for Small Teams

Scenario: 10-person company

Without LILA:

  • No analyst (can’t afford one)
  • Developer handles data requests (inefficient)
  • Many questions go unanswered
  • Decisions made on intuition

With LILA ($75/month):

  • Basic data questions answered instantly
  • Developer stays focused on product
  • More decisions informed by data
  • Total cost: $900/year

Scenario: 50-person company with one analyst

Without LILA:

  • Analyst backlog is 2-3 weeks
  • Urgent requests disrupt strategic projects
  • Teams frustrated by wait times

With LILA ($150/month):

  • Routine queries handled by self-service
  • Analyst backlog drops significantly
  • Strategic projects get proper attention
  • Total cost: $1,800/year

What LILA Will Never Do

Be clear about limitations:

  • Build your data warehouse
  • Create executive presentations
  • Identify causation (only correlation)
  • Replace judgment with algorithms
  • Understand your business strategy

LILA is a tool. A powerful one, but still a tool. The human contribution to data work isn’t going away.

The Bottom Line

Hire an analyst if:

  • Data infrastructure needs building
  • Strategic analysis drives major decisions
  • Complex, ongoing analysis is required
  • You can afford $80-120k/year all-in

Use LILA if:

  • Budget is constrained
  • Team needs immediate answers
  • Questions are routine but frequent
  • Current analyst is overloaded

Use both if:

  • You have an analyst and want to maximize their impact
  • Team-wide data access matters
  • Speed and depth both required

The goal is data-informed decisions. The method depends on your resources.

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