Business Analytics

Your data strategy is probably garbage.

Harsh? Maybe. But after transforming data operations at Samsung and countless other companies, I've seen the same pattern: Businesses sitting on goldmines of data they're completely misusing.

You've got dashboards. You've got reports. You've got expensive BI tools. But you're still not turning data into money.

Let's fix that.

The Truth About Your Data Problem

Most businesses think they're playing chess with their data. Reality? They're playing 52-card pickup. You have multiple data sources telling different stories, teams that don't trust their own numbers, and expensive tools that are just glorified Excel sheets.

The Analytics Hierarchy of Needs

Before you chase the next shiny AI tool, let's get real about where you stand.

Level 1: Data Foundation

This is where 90% of businesses fail. You can't build a skyscraper on sand.

When I worked with a $50M company claiming to have a "machine learning problem," their real issue was having three different versions of customer lifetime value. After consolidating their data and implementing basic quality checks, we found $2M in misattributed revenue. That's not an AI problem - that's a foundation problem.

Level 2: Analysis Framework

Once your data is clean, you need a framework to turn it into decisions. Here's mine:

The STORM Method:

1. Situation Analysis: What's actually happening?
2. Trend Recognition: What patterns matter?
3. Opportunity Mapping: Where's the money?
4. Response Design: What actions drive results?
5. Measurement: Did it work?

Level 3: Strategic Implementation

This is where theory meets money. At a struggling retail chain, we transformed their business by actually using their data:

• Restructured inventory based on location-specific demand
• Adjusted staffing to match actual peak hours
• Implemented targeted marketing to high-value segments

Result? Revenue up 32% in 6 months.

The AI Reality Check

Everyone's talking about AI. Here's the truth about when it makes sense:

Use AI When:

• You have clean, structured data
• You need real-time decisions
• Patterns are too complex for human analysis

Don't Use AI When:

• Your data is a mess (fix that first)
• You need explainable decisions
• Basic analysis would solve the problem

Your 48-Hour Action Plan

1. Audit Your Data Foundation

• Where does your data live?
• How many versions of the truth exist?
• Who owns data quality?

1. Map Your Data Flow

• Document data sources
• Track who uses what data
• Identify decision points

1. Find Quick Wins

• List decisions made without data
• Spot redundant reports
• Identify unused data sources

The Bottom Line

Stop treating your data like a record-keeping exercise. Start treating it like the strategic weapon it is.

The businesses that win aren't the ones with the most data - they're the ones that turn data into decisions fastest.

Ready to turn your data chaos into your competitive advantage? Let's talk.