The Dos and Don'ts of Small Business Data Analytics

The dos and don'ts of data analytics for small businesses.

There is so much data available to you as a business owner. Vanessa Pham, expert data analyst and co-founder of food brand Omsom, helps you dissect the first steps to take to decide what data matters most to your business and how to use it to your best advantage.

When owning and operating a small business, learning how to work with data and integrate it into your decision-making can feel daunting. Between setting your team up for success, ensuring day-to-day operations run smoothly, and managing cash flow, there’s already plenty of work and learning to be done. However, investing some time up front to get comfortable with using data analytics in your small business can go a long way—across all aspects of your company. 

In my past life, I was a management consultant who advised Fortune 500 companies on their toughest strategic challenges. And while I learned a lot about data and analytics, I had to adapt and focus my skills once I started my own small business with my sister. Having coached and advised a number of entrepreneurs, I’ve honed in on a few guiding principles when leveraging data analytics for small businesses—here are some of my key dos and don’ts.

DOs:

1. Have a very clear handle on what problem you’re solving or what decision you’re making. 
With the abundance of software and data collection tools available to small businesses, figuring out where to start and what data to look at can be overwhelming. As such, it’s best to work backwards from the problem or decision at hand: What within your business needs to be improved the most? What decisions are most pressing or high-impact for your business? Once you’ve decided that, you can then go straight to the data sources that are most relevant and be very focused in your approach to analyzing data. 

2. Spend a bit of time cleaning up your data, focusing on what could actually muddy your findings. 
Let’s be honest, data can be really messy. There’s user error in inputting data, there are outliers that can mess with calculations, and there are all the nuances of your business that can impact data in ways you might not be able to anticipate. Even with all these complexities, data-driven insights can be worth pursuing—you just need to put in a little bit of elbow grease up front to prepare your data for analysis. 

The first step is to think about your business and identify where your data might need to be cleaned. In other words, where could your data potentially be incorrect, unclear, redundant, or out of date? For example, do you have different types of customers that need to be treated differently when you're analyzing data? If so, you will want to bucket them and build in that nuance based on what you know about your business and your internal processes.

3. Look to surface “the story” with your findings and tell that story to your team and / or other stakeholders. 
Figures, numbers, and data are not meaningful out of context. To make your analytical findings as impactful as possible, tell a story. First, set the stage for your audience: What is the challenge or decision at hand? How did we get here? Second, explain the key takeaways and learnings up front in a succinct way, so that your audience can internalize the most important information. Last, share critical stats, details, charts, and / or graphics that bolster your findings. The first half of the battle is gaining the insight—but the second half, and perhaps most important part, is turning that insight into improvements and optimizations within the business. To enable that change, telling a captivating story to mobilize your team is critical.

DON’Ts:

1. Don’t look at data in a vacuum—be sure to layer on your intuition and direct operating experience. 
Numbers and data certainly have a wealth of potential in terms of what they can teach us—but don’t get pulled into seeing them as the end all, be all. The analysis can only take you so far; to really be turned into tangible learnings, it must then be interpreted, contextualized, and applied. This is where all the knowledge, qualitative information, and operator instinct can coalesce with the analytical findings to lead to critical insights. 

2. Don’t “boil the ocean”—try to focus on the data and actionable insights that have the highest impact on your business. 
Back in my management consulting days, we would do a lot of analysis in service of providing all kinds of insights to our clients—but the most impactful ones could actually help them steer the ship, make critical decisions, and drive tangible improvements to their business. 

For small businesses with limited resources, we often can only afford to focus on insights that can deliver real value and help drive better management decisions. In my experience, the best way to drive towards actionable insight is to focus on learnings that are directly linked to your business’s most dire needs. For example, if a business’s customer referral rate is low, a good place to start would be to survey customers for feedback and analyze online reviews for critical insights.

In my experience, the best way to drive towards actionable insight is to focus on learnings that are directly linked to your business’s most dire needs.

At the end of the day, as a small business owner with limited resources and even less time, you’re in need of tools that make a meaningful impact on your business with minimal lift. When it comes to the process of integrating and analyzing data into your decision making, following the guidelines above will help you take a pragmatic and focused approach so that you can get the most out of your data analysis.
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