4 WAYS TO IMPROVE YOUR ANALYTICAL SKILLS

Data is ubiquitous. It’s collected at every purchase made, flight taken, ad clicked, and social media post liked—which means it’s never been more crucial to understand how to analyze it.

“Never before has so much data about so many different things been collected and stored every second of every day,” says Harvard Business School Professor Jan Hammond in the online course Business Analytics.

The volume of data you encounter can be overwhelming and raise several questions: Can I trust the data’s source? Is it structured in a way that makes sense? What story does it tell, and what actions does it prompt?

Data literacy and analytical skills can enable you to answer these questions and not only make sense of raw data, but use it to drive impactful change at your organization.

Here’s a look at what it means to be data literate and four ways to improve your analytical skills.

WHAT IS DATA LITERACY?

Data literacy is the ability to analyze, interpret, and question data. A dataset is made up of numerous data points that, when viewed together, tell a story.

Before conducting an analysis, it’s important to ensure your data’s quality and structure is in accordance with your organization’s needs.

“In order to transform data into actionable information, you first need to evaluate its quality,” says Harvard Professor Dustin Tingley in the online course Data Science Principles. “But evaluating the quality of your data is just the first step. You’ll also need to structure your data. Without structure, it’s nearly impossible to extract any information.”

When you’re able to look at quality data, structure it, and analyze it, trends emerge. The next step is to reflect on your analysis and take action.

Tingley shares several questions to ask yourself once you’ve analyzed your dataset: “Did all the steps I took make sense? If so, how should I respond to my analysis? If not, what should I go back and improve?”

For example, you may track users who click a button to download an e-book from your website.

After ensuring your data’s quality and structuring it in a way that makes sense, you begin your analysis and find that a user’s age is positively correlated with their likelihood to click. What story does this trend tell? What does it say about your users, product offering, and business strategy?

To answer these questions, you need strong analytical skills, which you can develop in several ways.

HOW TO IMPROVE YOUR ANALYTICAL SKILLS

Analysis is an important skill to have in any industry because it enables you to support decisions with data, learn more about your customers, and predict future trends.

Key analytical skills for business include:

Visualizing data
Determining the relationship between two or more variables
Forming and testing hypotheses
Performing regressions using statistical programs, such as Microsoft Excel
Deriving actionable conclusions from data analysis

If you want to provide meaningful conclusions and data-based recommendations to your team, here are four ways to bolster your analytical skills.

1. Consider Opposing Viewpoints

While engaging with opposing viewpoints can help you expand your perspective, combat bias, and show your fellow employees their opinions are valued, it can also be a useful way to practice analytical skills.

When analyzing data, it’s crucial to consider all possible interpretations and avoid getting stuck in one way of thinking.

For instance, revisit the example of tracking users who click a button on your site to download an e-book. The data shows that the user’s age is positively correlated with their likelihood to click the button; as age increases, downloads increase, too. At first glance, you may interpret this trend to mean that a user chooses to download the e-book because of their age.

This conclusion, however, doesn’t take into consideration the vast number of variables that change with age. For instance, perhaps the real reason your older users are more likely to download the e-book is their higher level of responsibility at work, higher average income, or higher likelihood of being parents.

This example illustrates the need to consider multiple interpretations of data, and specifically shows the difference between correlation (the trending of two or more variables in the same direction) and causation (when a trend in one variable causes a trend to occur in one or more other variables).

“Data science is built on a foundation of critical thinking,” Tingley says in Data Science Principles. “From the first step of determining the quality of a data source to determining the accuracy of an algorithm, critical thinking is at the heart of every decision data scientists—and those who work with them—make.”

To practice this skill, challenge yourself to question your assumptions and ask others for their opinions. The more you actively engage with different viewpoints, the less likely you are to get stuck in a one-track mindset when analyzing data.

2. Play Games or Brain Teasers

If you’re looking to sharpen your skills on a daily basis, there are many simple, enjoyable ways to do so.

Games, puzzles, and stories that require visualizing relationships between variables, examining situations from multiple angles, and drawing conclusions from known data points can help you build the skills necessary to analyze data.

Some fun ways to practice analytical thinking include:

Crossword puzzles
Mystery novels
Logic puzzles
Riddles
Sudoku
Strategic board games or card games

These options can supplement your analytics coursework and on-the-job experience. Some of them also allow you to spend time with friends or family. Try engaging with one each day to hone your analytical mindset.

3. Take an Online Analytics Course

Whether you want to learn the basics, brush up on your skills, or expand your knowledge, taking an analytics course is an effective way to improve. A course can enable you to focus on the content you want to learn, engage with the material presented by a professional in the field, and network and interact with others in the data analytics space.

For a beginner, courses like Data Science Principles can provide a foundation in the language of data. A more advanced course, like Data Science for Business, may be a fit if you’re looking to explore specific facets of analytics, such as forecasting and machine learning. If you’re interested in hands-on applications of analytical formulas, a course like Business Analytics could be right for you. The key is to understand what skills you hope to gain, then find a course that best fits your needs.

If you’re balancing a full-time job with your analytics education, an online format may be a good choice. It offers the flexibility to engage with course content whenever and wherever is most convenient for you.

An online course may also present the opportunity to network and build relationships with other professionals devoted to strengthening their analytical skills. A community of like-minded learners can prove to be an invaluable resource as you learn and advance your career.

4. Engage With Data

Once you have a solid understanding of data science concepts and formulas, the next step is to practice. Like any skill, analytical skills improve the more you use them.

Mock datasets—which you can find online or create yourself—present a low-risk option for putting your skills to the test. Import the data into Microsoft Excel, then explore: make mistakes, try that formula you’re unsure of, and ask big questions of your dataset. By testing out different analyses, you can gain confidence in your knowledge.

Once you’re comfortable, engage with your organization’s data. Because these datasets have inherent meaning to your business's financial health, growth, and strategic direction, analyzing them can produce evidence and insights that support your decisions and drive change at your organization.

INVESTING IN YOUR DATA LITERACY

As data continues to be one of businesses’ most valuable resources, taking the time and effort to build and bolster your analytical skill set is vital.

“Much more data are going to be available; we’re only seeing the beginning now,” Hammond says in a previous article. “If you don’t use the data, you’re going to fall behind. People that have those capabilities—as well as an understanding of business contexts—are going to be the ones that will add the most value and have the greatest impact.”

Do you want to learn how to drive data-driven growth at your organization? Explore how our online analytics courses can help you develop a data mindset.

About the Author

Catherine Cote is a marketing coordinator at Harvard Business School Online. Prior to joining HBS Online, she worked at an early-stage SaaS startup where she found her passion for writing content, and at a digital consulting agency, where she specialized in SEO. Catherine holds a B.A. from Holy Cross, where she studied psychology, education, and Mandarin Chinese. When not at work, you can find her hiking, performing or watching theatre, or hunting for the best burger in Boston.

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