How To Gather And Use Data For Business Analysis

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HOW TO GATHER AND USE DATA FOR BUSINESS ANALYSIS

M.L. HUMPHREY

CONTENTS

Introduction

Understand Your Business

Track Every Variable You Want to Analyze In a Usable Way

Separate the Information You Want to Track Into Discrete Units

Enter Once, Use Many Times

Be Consistent Across Data Tables or Data Sources

Use Categorical Variables Instead of Free Text Where Possible

Use Dropdown Menus Where Feasible

Consider Using an Other Option

Keep Your Values Up To Date

Take Care When Making Changes to Your Data

Don't Change Your Raw Data

Document Your Data Clean-Up and Analysis Steps

Save Versions

Test Your Results

Make Assumptions Visible

Know the Limitations of Your Programs

Know the Difference Between a Report and Raw Data

View Your Data From a Business Perspective

Build In Checks and Balances Where You Can

Activity-Based Costing

Conclusion

About the Author

Copyright

INTRODUCTION

There's a lot of buzz these days around big data, data science, and data analysis. And for good reason. Because the more you understand about your business and your customers the more profitable your business can be.

For example, say you have two products, widgets and whatchamacallits, but you don't track the product-level revenue or the product-level expenses. All you know is that last quarter you made $10,000 and you spent $8,000 and that you sold a lot more widgets than whatchamacallits.

You might be tempted given that limited amount of information to think that you should abandon whatchamacallits and sell only widgets. But if you had detailed information about each product you would instead see that you made $6,000 selling whatchamacallits and $4,000 selling widgets and that your expense for selling those whatchamacallits was only $1,000 while your expense for selling widgets was $7,000.

Put those product-level numbers together and you'd see that you made a profit of $5,000 on your whatchamacallit sales and lost $3,000 on your widget sales.

Given those numbers, you'd want to abandon widget sales and focus on whatchamacallits. Or you'd want to fix the issue with why widgets are costing you more than they're making you.

But do you see there why having good information about your business can be so valuable?

Often we make decisions from the gut—I sure sell a lot of widgets, I must be good at that—instead of using factual information that maybe tells a different story. That's why collecting good data and using the data you have to the best effect is so important and crucial to success. That’s why all the buzz.

But data science is a complicated field. There's a lot of that goes into doing it well and not everyone has the type of mind that can process data at those levels. I myself have dabbled in learning R programming and taken a few courses on big data and data science and while I found it interesting and challenging I realized that it wasn't really what I needed as a small business owner. I'm not trying to parse social trends by mining Twitter feeds, for example.

I just want to know what product sells the best so I can make more of it.

So what I'm going to cover for you in this book are some very basic principles around how to collect information, how to store that information, and how to use that information effectively. These principles are a good foundation for even highly complex analysis, but you don't