Nearly every business and organization today is extremely dependent on data, but many smaller teams and businesses struggle with where to start.

Modern data analytics combines powerful software tools and statistical techniques to produce insights that can improve results in every field and organizational department. From a data mindset to technical skills, here are our recommendations for how to begin.

Data Mindset

• Focus on Business Problems

• Create Data Literacy

• Build a Data-Driven Culture

Technical Skills

• Collecting Data

• Analyzing Data

• Visualizing Data

Data Mindset

It is important to have a data-driven mindset as it serves as the foundation for improving your key performance metrics. Having a data mindset is a process that helps you to think strategically and critically about your investments, tools, and activities so that you can make decisions rooted in reason and evidence, not just gut feel.

Let’s take a look at 3 actionable steps you can take when developing a data mindset.

Focus on Business Problems

When working with data, before diving into the technical details, it’s important to first think about the business challenges, objectives, and goals that you have in mind for your team.

Think about the business problems you are trying to solve with data. They could be:

• A better understanding your customers’ behaviors

• Determining which parts of your business to prioritize

• Forecasting future demand and sales

• And more…

Asking yourself these types of questions will help you determine what data you’ll need to collect and what analysis to focus on.

Create a Data Literacy Atmosphere

Data literacy is the ability to read, work with, and communicate with data effectively. A recent data literacy survey by Accenture of over 9,000 individuals who hold various roles found that only 21% were confident in their data literacy skills. In addition, over 75% of enterprises have invested in analytics software, yet only 25% of employees in those enterprises feel they are adequately prepared to use the data efficiently.

With this deficit in data literacy skills, it’s likely that each person on your team will come to the table with a different skill level. Some might be able to read statistical tables with ease while others may need some extra time to interpret a graph. Because of this, it’s important for team members to empathize with each other and:

• Create an atmosphere where beginners feel comfortable speaking up when they need help

• Help beginners increase their data literacy skills (with courses like Thinking Like an Analyst) to more effectively communicate with their teammates

With only a quarter of the global workforce reporting that they are confident in their data literacy skills, business leaders must invest in data upskilling to help improve their employees’ use of data and strengthen their data-driven culture.

Pro Tip: Data storytelling is an especially effective way of communicating with data, where a presenter distills insights and weaves them into a story. Humans relate to, and can better remember, stories.

• Data only – Our post got 1000 views yesterday.

• Data storytelling – Our consistent posting on social media has paid off. After two months of weekly posts, we hit our highest view count of 1000 views, which resulted in 5 sales. Let’s keep the momentum going!

Build a Data-Driven Culture

A data-driven culture is one where people make decisions based on data. While intuition is a large part of decision making, you can be more confident in your choices when you back them up with data.

Creating a data-driven culture starts at the top. As the leader of a small team or business, set an example by demonstrating how you’re backing up your own decisions with insights gathered from data analysis.

Also, make sure that your analysis is transparent - it’s very easy to lie with data. Make sure to be honest with yourself when your data isn’t telling you what you want to hear. Data should be used to drive decisions, not the other way around!

Technical Skills

Now that we have highlighted the areas to help you develop a data mindset, let’s dive into the top 3 technical skills your team or business must have.

Collecting Data

Once you’ve identified your business problems, it’s time to start looking into the data.

You likely already have some existing data on hand, such as:

• Spreadsheets keeping track of customers, inventory, pricing, sales, marketing, etc.

• Data within the tools that your organization uses such as:

  • Website data (e.g. Google Analytics)

  • Social media data (TikTok, Facebook, Instagram, LinkedIn, etc.)

  • YouTube Analytics for your channel

  • etc.

After taking inventory of what data you have, you’ll likely notice some gaps. This is where you can begin collecting data on your own.

There are a variety of ways to do this:

• Easy: Manually record data at a specific time each day / week / month (it’s ok to start this way!)

• Medium: Regularly export data (.csv or .txt files) from an analytics tool to later analyze within a spreadsheet

• Difficult: Programmatically collect data using a paid service, API, etc.

The most important parts of data collection are (1) that the data is accurate and (2) that the data you’re collecting is useful. I would recommend spending some time to think about exactly what data would help supplement your analysis, and how to collect it in a consistent way.

Analyzing Data

Data on its own isn’t very useful. Instead, the power comes from analyzing the data you’ve collected.

Once you’re able to identify a few data sources, you can pull the data together into a spreadsheet software like Excel or Google Sheets, and start to find some insights by:

• Looking at summary statistics – What’s the average daily engagement and which days are significantly above or below average?

• Sorting the data – Who are the top customers and what are some characteristics of those customers?

• Grouping the data – What do the summary statistics look like for people within a particular region or demographic group?

By doing these basic exploratory steps, you are almost always able to gather some insights or, at a minimum, obtain a better understanding of the data. Plus, these tools provide a number of additional functions to combine data sets, extract specific pieces of your data, and aggregate data.

Pro Tip: If you’re starting out with data analysis and want to learn just one tool, we recommend your data team learn and understand Excel. It’ll give them a great introduction to light programming and the power of analysis. (We offer 12 courses on Excel. Feel free to take just one to brush up on your skills, or there is a curated Excel path if you are looking to really dive into the tool.)

Visualizing Data

In addition to doing data analysis, visualizing your data can make a huge difference in giving you information about your business.

Data visualizations allow your team to quickly glean insights from data. You can also highlight parts of your visualizations using colors or shapes to draw attention to particular portions.

Some simple, yet powerful visualizations include:

• Line charts – great for looking at performance over time

• Bar charts – great for comparing values

• Scatter plots – great for comparing two numeric fields (i.e. upvotes versus sales)

These charts can be built in common spreadsheet tools like Excel or Google Sheets, in presentation software like PowerPoint or Google Slides, in BI tools like Power BI or Tableau and in plotting libraries within Python.

Pro Tip: You should never make a chart just because you feel like it’s the right thing to do. Instead, think about what message you’re trying to get across and how a chart can help you drive that message home.

Final Thoughts

Small teams and businesses can greatly benefit from data, but it’s important to start with the basics like getting your team into a data mindset. Focusing on just this one step (or change) will help your team look at your business in a different light, guide your team down the path of making better business decisions, and set your team up for future success.