The B(l)oat House Problem: Navigating the Waters of Business Analytics

In the world of data analytics, there's a growing trend towards creating ever-larger repositories of information – data warehouses, data lakes, and the latest, lake houses. It's in this context that we encounter 'The Boat House Problem', a tongue-in-cheek reference that challenges the prevailing notion that more data automatically equates to better insights.

As an engineer who delved into analytics to address a business issue, I quickly realized that existing tools and products weren't cutting it. This led me down the path of building my analytics systems, tailored to my specific needs. But what were these needs?

Understanding the Real Goal in Analytics

If you've read "The Goal: A Process of Ongoing Improvement," you'll know that the purpose of analytics should be to understand your customer base, identify issues, and, ultimately, grow your bottom line. Interestingly, my objective was never about hoarding more data or unifying disparate information. I wanted timely, affordable, understandable, and actionable analysis of my business processes to effect change within my change window and boost revenue.

Dispelling Common Misconceptions in Analytics

There are several misconceptions in the analytics space:

1. Massive Amounts of Data: Yes, data is growing exponentially. Solution providers, who charge by the gigabyte for storage and megabyte for processing, often push this narrative. While partly true, it's not the whole story.
2. All Data is Vital: It's a common belief that every piece of data is crucial for understanding your business. However, actionable outcomes often come from small, related data slices. The challenge lies in identifying these slices and understanding how they interconnect.
3. The Real-Time Trap: Many believe that everything in analytics needs to be real-time. However, effective windows for change are usually limited. Over-focusing on data can lead to missteps due to outlier cases. Understanding causal effects requires more than a single data sample, which takes time to accumulate. Timely analysis is essential – waiting a week for a report delays your response, whereas quick insights into daily or monthly data can lead to the 1% effect: small, consistent changes over time yielding significant results.

The Boat House Analogy

Think of your business like a boat house. It's not about collecting more water (data) but about understanding the currents (customer behaviors, market trends) and navigating them effectively. The boat house doesn't need to be larger; it needs to be smarter, equipped with the right tools to interpret the waters and steer the boat (your business) in the right direction.

Conclusion

In the vast ocean of data, it's easy to get lost, and go broke. The key is not to collect more water but to learn how to navigate it effectively. By focusing on what truly matters – actionable, timely analysis – you can steer your business towards greater success.

To leaving the "Lakehouse" and sailing to fairer shores

Darren Pegg is CTO at DataGPT - A Place to ask questions

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