how to improve analytical and research skills

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4 Ways to Improve Your Analytical Skills

• 07 Jan 2021

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.

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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 Professor Dustin Tingley in the Harvard 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.

Related: Business Analytics: What It Is & Why It’s Important

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.

Related: How to Learn Business Analytics Without A Business Background

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
• 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.

Related: 3 Examples of Business Analytics in Action

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 Harvard Online's Data Science Principles can provide a foundation in the language of data. A more advanced course, like Harvard Online's 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 HBS Online's 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.

Related: Is An Online Business Analytics Course Worth It?

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.”

Are you interested in furthering your data literacy? Download our Beginner’s Guide to Data & Analytics to learn how you can leverage the power of data for professional and organizational success.

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What are analytical skills? Examples and how to level up

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What are analytical skills?

Why are analytical skills important, 9 analytical skills examples, how to improve analytical skills, how to show analytical skills in a job application, the benefits of an analytical mind.

With market forecasts, performance metrics, and KPIs, work throws a lot of information at you. 

If you want to stay ahead of the curve, not only do you have to make sense of the data that comes your way — you need to put it to good use. And that requires analytical skills.

You likely use analytical thinking skills every day without realizing it, like when you solve complex problems or prioritize tasks . But understanding the meaning of analysis skills in a job description, why you should include them in your professional development plan, and what makes them vital to every position can help advance your career.

Analytical skills, or analysis skills, are the ones you use to research and interpret information. Although you might associate them with data analysis, they help you think critically about an issue, make decisions , and solve problems in any context. That means anytime you’re brainstorming for a solution or reviewing a project that didn’t go smoothly, you’re analyzing information to find a conclusion. With so many applications, they’re relevant for nearly every job, making them a must-have on your resume.

Analytical skills help you think objectively about information and come to informed conclusions. Positions that consider these skills the most essential qualification grew by 92% between 1980 and 2018 , which shows just how in-demand they are. And according to Statista, global data creation will grow to more than 180 zettabytes by 2025 — a number with 21 zeros. That data informs every industry, from tech to marketing.

Even if you don’t interact with statistics and data on the job, you still need analytical skills to be successful. They’re incredibly valuable because:

• They’re transferable: You can use analysis skills in a variety of professional contexts and in different areas of your life, like making major decisions as a family or setting better long-term personal goals.
• They build agility: Whether you’re starting a new position or experiencing a workplace shift, analysis helps you understand and adapt quickly to changing conditions. 
• They foster innovation: Analytical skills can help you troubleshoot processes or operational improvements that increase productivity and profitability.
• They make you an attractive candidate: Companies are always looking for future leaders who can build company value. Developing a strong analytical skill set shows potential employers that you’re an intelligent, growth-oriented candidate.

If the thought of evaluating data feels unintuitive, or if math and statistics aren’t your strong suits, don’t stress. Many examples of analytical thinking skills don’t involve numbers. You can build your logic and analysis abilities through a variety of capacities, such as:

1. Brainstorming

Using the information in front of you to generate new ideas is a valuable transferable skill that helps you innovate at work . Developing your brainstorming techniques leads to better collaboration and organizational growth, whether you’re thinking of team bonding activities or troubleshooting a project roadblock. Related skills include benchmarking, diagnosis, and judgment to adequately assess situations and find solutions.

2. Communication

Becoming proficient at analysis is one thing, but you should also know how to communicate your findings to your audience — especially if they don’t have the same context or experience as you. Strong communication skills like public speaking , active listening , and storytelling can help you strategize the best ways to get the message out and collaborate with your team . And thinking critically about how to approach difficult conversations or persuade someone to see your point relies on these skills. 

3. Creativity

You might not associate analysis with your creativity skills, but if you want to find an innovative approach to an age-old problem, you’ll need to combine data with creative thinking . This can help you establish effective metrics, spot trends others miss, and see why the most obvious answer to a problem isn’t always the best. Skills that can help you to think outside the box include strategic planning, collaboration, and integration.

4. Critical thinking

Processing information and determining what’s valuable requires critical thinking skills . They help you avoid the cognitive biases that prevent innovation and growth, allowing you to see things as they really are and understand their relevance. Essential skills to turn yourself into a critical thinker are comparative analysis, business intelligence, and inference.

5. Data analytics

When it comes to large volumes of information, a skilled analytical thinker can sort the beneficial from the irrelevant. Data skills give you the tools to identify trends and patterns and visualize outcomes before they impact an organization or project’s performance. Some of the most common skills you can develop are prescriptive analysis and return on investment (ROI) analysis.

6. Forecasting

Predicting future business, market, and cultural trends better positions your organization to take advantage of new opportunities or prepare for downturns. Business forecasting requires a mix of research skills and predictive abilities, like statistical analysis and data visualization, and the ability to present your findings clearly.

7. Logical reasoning

Becoming a logical thinker means learning to observe and analyze situations to draw rational and objective conclusions. With logic, you can evaluate available facts, identify patterns or correlations, and use them to improve decision-making outcomes. If you’re looking to improve in this area, consider developing inductive and deductive reasoning skills.

8. Problem-solving

Problem-solving appears in all facets of your life — not just work. Effectively finding solutions to any issue takes analysis and logic, and you also need to take initiative with clear action plans . To improve your problem-solving skills , invest in developing visualization , collaboration, and goal-setting skills.

9. Research

Knowing how to locate information is just as valuable as understanding what to do with it. With research skills, you’ll recognize and collect data relevant to the problem you’re trying to solve or the initiative you’re trying to start. You can improve these skills by learning about data collection techniques, accuracy evaluation, and metrics.

You don’t need to earn a degree in data science to develop these skills. All it takes is time, practice, and commitment. Everything from work experience to hobbies can help you learn new things and make progress. Try a few of these ideas and stick with the ones you enjoy:

1. Document your skill set

The next time you encounter a problem and need to find solutions, take time to assess your process. Ask yourself:

• What facts are you considering?
• Do you ask for help or research on your own? What are your sources of advice?
• What does your brainstorming process look like?
• How do you make and execute a final decision?
• Do you reflect on the outcomes of your choices to identify lessons and opportunities for improvement?
• Are there any mistakes you find yourself making repeatedly?
• What problems do you constantly solve easily? 

These questions can give insight into your analytical strengths and weaknesses and point you toward opportunities for growth.

2. Take courses

Many online and in-person courses can expand your logical thinking and analysis skills. They don’t necessarily have to involve information sciences. Just choose something that trains your brain and fills in your skills gaps . 

Consider studying philosophy to learn how to develop your arguments or public speaking to better communicate the results of your research. You could also work on your hard skills with tools like Microsoft Excel and learn how to crunch numbers effectively. Whatever you choose, you can explore different online courses or certification programs to upskill. 

3. Analyze everything

Spend time consciously and critically evaluating everything — your surroundings, work processes, and even the way you interact with others. Integrating analysis into your day-to-day helps you practice. The analytical part of your brain is like a muscle, and the more you use it, the stronger it’ll become. 

After reading a book, listening to a podcast, or watching a movie, take some time to analyze what you watched. What were the messages? What did you learn? How was it delivered? Taking this approach to media will help you apply it to other scenarios in your life. 

If you’re giving a presentation at work or helping your team upskill , use the opportunity to flex the analytical side of your brain. For effective teaching, you’ll need to process and analyze the topic thoroughly, which requires skills like logic and communication. You also have to analyze others’ learning styles and adjust your teachings to match them. 

5. Play games

Spend your commute or weekends working on your skills in a way you enjoy. Try doing logic games like Sudoku and crossword puzzles during work breaks to foster critical thinking. And you can also integrate analytical skills into your existing hobbies. According to researcher Rakesh Ghildiyal, even team sports like soccer or hockey will stretch your capacity for analysis and strategic thinking . 

6. Ask questions

According to a study in Tr ends in Cognitive Sciences, being curious improves cognitive function , helping you develop problem-solving skills, retention, and memory. Start speaking up in meetings and questioning the why and how of different decisions around you. You’ll think more critically and even help your team find breakthrough solutions they otherwise wouldn’t.

7.Seek advice

If you’re unsure what analytical skills you need to develop, try asking your manager or colleagues for feedback . Their outside perspective offers insight you might not find within, like patterns in. And if you’re looking for more consistent guidance, talking to a coach can help you spot weaknesses and set goals for the long term.

8. Pursue opportunities

Speak to your manager about participating in special projects that could help you develop and flex your skills. If you’d like to learn about SEO or market research, ask to shadow someone in the ecommerce or marketing departments. If you’re interested in business forecasting, talk to the data analysis team. Taking initiative demonstrates a desire to learn and shows leadership that you’re eager to grow. 

Shining a spotlight on your analytical skills can help you at any stage of your job search. But since they take many forms, it’s best to be specific and show potential employers exactly why and how they make you a better candidate. Here are a few ways you can showcase them to the fullest:

1. In your cover letter

Your cover letter crafts a narrative around your skills and work experience. Use it to tell a story about how you put your analytical skills to use to solve a problem or improve workflow. Make sure to include concrete details to explain your thought process and solution — just keep it concise. Relate it back to the job description to show the hiring manager or recruiter you have the qualifications necessary to succeed.

2. On your resume

Depending on the type of resume you’re writing, there are many opportunities to convey your analytical skills to a potential employer. You could include them in sections like: 

• Professional summary: If you decide to include a summary, describe yourself as an analytical person or a problem-solver, whichever relates best to the job posting. 
• Work experience: Describe all the ways your skill for analysis has helped you perform or go above and beyond your responsibilities. Be sure to include specific details about challenges and outcomes related to the role you’re applying for to show how you use those skills. 
• Skills section: If your resume has a skill-specific section, itemize the analytical abilities you’ve developed over your career. These can include hard analytical skills like predictive modeling as well as interpersonal skills like communication.

3. During a job interview

As part of your interview preparation , list your professional accomplishments and the skills that helped along the way, such as problem-solving, data literacy, or strategic thinking. Then, pull them together into confident answers to common interview questions using the STAR method to give the interviewer a holistic picture of your skill set.

Developing analytical skills isn’t only helpful in the workplace. It’s essential to life. You’ll use them daily whenever you read the news, make a major purchase, or interact with others. Learning to critically evaluate information can benefit your relationships and help you feel more confident in your decisions, whether you’re weighing your personal budget or making a big career change .

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Elizabeth Perry, ACC

Elizabeth Perry is a Coach Community Manager at BetterUp. She uses strategic engagement strategies to cultivate a learning community across a global network of Coaches through in-person and virtual experiences, technology-enabled platforms, and strategic coaching industry partnerships. With over 3 years of coaching experience and a certification in transformative leadership and life coaching from Sofia University, Elizabeth leverages transpersonal psychology expertise to help coaches and clients gain awareness of their behavioral and thought patterns, discover their purpose and passions, and elevate their potential. She is a lifelong student of psychology, personal growth, and human potential as well as an ICF-certified ACC transpersonal life and leadership Coach.

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What Is Analytical Thinking and How Can You Improve It?

Learn why analytical thinking is important and how it differs from critical and creative thinking. Explore some good-paying jobs for analytical thinkers, and find out how you can improve your analytical thinking skills.

When processing a lot of information or facing challenging problems, it often helps to take an analytical approach. Analytical thinking helps you determine the validity of information, carefully consider problems, and arrive at the best solutions.

What is analytical thinking? 

Analytical thinking involves using a systemic approach to make decisions or solve problems. By breaking down information into parts, analytical thinkers can better understand it and come to a sensible conclusion. 

For instance, once analytical thinkers identify a problem, they typically gather more information, develop possible solutions, test them, and analyze which works best. Solving complex problems often requires analytical reasoning, which may involve:

Determining causation (if and how one event causes another)

Examining similarities, differences, and relationships

Predicting the next event by following a sequence

Recognizing patterns or trends

Using conditional and converse (if-then) statements 

Why is analytical thinking important?

In daily life, analytical thinking allows you to sift through a steady barrage of information from the news, social media, and accounts from friends and family to get to the truth. Analytical thinking also offers professional value. Employers look for candidates with good analytical skills to help solve problems and make sound decisions in the workplace. 

How is analytical thinking different from creative and critical thinking?

To better understand analytical thinking, it helps to learn how it's different from other types of thinking. For instance, when solving a problem, analytical thinkers take a methodical approach, breaking up information and analyzing each part until they form a conclusion. 

Creative thinkers take a less organized approach to problem-solving. They examine a problem from many angles and welcome new information to devise a creative solution.  

Critical thinkers are open-minded and have superior evaluative skills. To develop a logical solution to a problem, they study evidence, ask questions, assess other points of view, and explore any relative assumptions or biases. 

4 good-paying careers for analytical thinkers 

If you can think analytically, it can benefit you in a variety of careers. Explore four good-paying careers for analytical thinkers. 

1. Business analyst

Median annual US salary (BLS): $95,290 [ 1 ]

Job outlook: 10 percent job growth [ 1 ]

Job requirements: A business analyst often holds a bachelor's or master's degree in business administration .

Beneficial skills to have: Analytical skills, communication , problem-solving, and time management

Tasks and responsibilities: As a business analyst, you'll gather information about a company by observing business practices and procedures, examining financial data, and conducting employee interviews. Then, you'll study and evaluate the information and make recommendations to help the company run more effectively.  

Read more: What Is a Business Analyst? Career Guide

2. Cybersecurity analyst

Median annual US salary (BLS): $112,000 [ 2 ]

Job outlook: 32 percent job growth [ 2 ]

Job requirements: A cybersecurity analyst often holds a bachelor's degree in cybersecurity or computer and information technology.

Beneficial skills to have: Analytical skills, attention to detail, communication, computer skills, and problem-solving

Tasks and responsibilities: A cybersecurity analyst develops and monitors methods for safeguarding computer networks and systems within an organization. Additional tasks involve creating security standards and procedures, writing security reports, and providing tech support for employees installing or learning new security software.

3. Data scientist

Median annual US salary (BLS): $103,500 [ 3 ]

Job outlook: 35 percent job growth [ 3 ]

Job requirements: A data scientist usually holds a bachelor's degree but may hold a master's or PhD in data science, computer science, mathematics, or statistics.

Beneficial skills to have: A nalytical skills, logical reasoning, communication, computer skills , and proficiency in math  

Tasks and responsibilities: A data scientist gathers, analyzes, and interprets data. Your additional duties in this role include presenting findings of data analysis and making recommendations based on findings. Types of industries that use data scientists include business, education, government, health care, and professional sports.

4. Financial analyst 

Median annual US salary (BLS): $96,220 [ 4 ]

Job outlook: 8 percent job growth [ 4 ]

Job requirements: A financial analyst commonly holds a bachelor's degree in finance, business, or a related field like accounting, economics, or statistics.

Beneficial skills to have: Analytical skills, attention to detail, communication, computer skills, decision-making, and proficiency in math

Tasks and responsibilities: Generally, a financial analyst offers guidance to individuals or businesses regarding finances and investments. Different types of financial analysts include financial risk analysts, fund managers, portfolio managers, and ratings analysts. 

Read more: What Is a Financial Analyst? (+ How to Become One)

Tips for improving your analytical thinking skills 

The ability to think analytically offers benefits in your professional and personal life. To improve your analytical thinking skills, go through some key steps when problem-solving or decision-making:

Do your research.

Gather information.

Think of several ideas or solutions.

Analyze your ideas or solutions and choose the best one.

Evaluate the success of the idea or solution. 

Consider these additional tips for becoming a more analytical thinker:

Take an analytics class or classes.

Riddles, crossword puzzles, jigsaw puzzles, or strategic board games like chess or checkers can boost analytical skills.

Take a math class to enhance your ability to analyze a problem and break it down into steps. Equations and world problems require careful examination, and you may have to engage in trial and error before solving them. 

Read books about data analytics or other types of analytics that interest you.

Network with analytics professionals.

Next steps on Coursera

To determine if you would enjoy a career in analytics, consider the Google Data Analytics Professional Certificate on Coursera. You'll have the opportunity to learn how to gather data, clean and organize it for analysis, and conduct analysis using various computer programs. 

When you finish this eight-course series, you may have as much knowledge as many junior-level data analysts. You'll also receive a Professional Certificate highlighting your data analytics expertise.

Article sources

US Bureau of Labor Statistics. " Occupational Outlook Handbook: Management Analysts , https://www.bls.gov/OOH/business-and-financial/management-analysts.htm?utm_source=fit/programs/8422/ms-information-technology-database-administration/classesutm_medium." Accessed February 23, 2024.

US Bureau of Labor Statistics. " Occupational Outlook Handbook: Information Security Analysts , https://www.bls.gov/ooh/computer-and-information-technology/information-security-analysts.htm." Accessed February 23, 2024.

US Bureau of Labor Statistics. " Occupational Outlook Handbook: Data Scientists , https://www.bls.gov/ooh/math/data-scientists.htm." Accessed February 23, 2024.

US Bureau of Labor Statistics. " Occupational Outlook Handbook: Financial Analysts , https://www.bls.gov/ooh/business-and-financial/financial-analysts.htm." Accessed February 23, 2024.

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Coursera staff.

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Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Tips for Online Students , Tips for Students

How to Improve Your Analytical Skills

Updated: July 12, 2022

Published: April 27, 2021

Wondering how to improve your analytical skills? There are many skills that would make a person a desirable candidate when it comes time to look for work, and one that’s at the top of the list is your analytical thinking skills.

Analytical thinking skills allow people to make well-thought-out decisions — and in the workplace, this is a valuable skill that can ultimately save businesses time and money. Having reliable analytical skills can also lead to a smarter life in general.

You can attain analytical thinking skills in school, or improve on analytical thinking skills you already possess.

What Are Analytical Thinking Skills?

Every day, we make hundreds of decisions , whether it’s choosing what clothes to wear to work or what we should eat for dinner. But some decisions — like those we make in school or at the workplace — are harder to make, and require a person with strong analytical thinking skills.

Analytical thinking skills are not influenced by emotion, but rather by certain abilities that when utilized, allow a person to make an educated decision.

Visualization

Visualization is characterized by a person’s ability to look at something — for instance, data collected over a long period of time — to predict what the outcome will be. This could involve looking at charts, pictures, graphs, or lists.

Critical Thinking

Critical thinking is just as it sounds. It’s a person’s ability to think critically about a decision, without letting personal emotions get in the way. It involves evaluating information and thinking outside of the box in order to find the most logical solution.

A large component of a person’s analytical thinking skills comes from their ability to, well, analyze. This means that you should have some computing skills, such as being able to make calculations and work with numbers in order to inform your decision.

Problem-Solving

Analytical thinking skills are not just making decisions, but finding solutions to complicated problems. It’s taking steps using strategies like trial and error, checking your work, and taking a step back if something doesn’t work the first time around, in order to achieve a goal as efficiently as possible.

Resource Management

A single person may not have all the answers on their own, but good analytical thinking skills means you know how to utilize your resources as best as possible to find what you’re looking for. This could mean feeling comfortable enough to call on someone who may know about a specific topic better than you do, or knowing where to find information that’s not easily accessible.

Paying Attention to Details

A person with good analytical thinking skills is very detail-oriented. They know how to find small details that others may not notice, which can end up being very useful in solving problems or coming up with big ideas.

How Does Analytical Thinking Help You?

Analytical thinking skills may be more desirable in some careers than others, but they can really be applied to any profession. They allow you to consider an idea or make a decision based more on facts, trends, and rationale than emotions, which is an important trait to have no matter what your job is. These skills are also important in your personal life, because they allow you to make smart choices short and long term.

Analytical Skills Make You Marketable

A person with analytical skills naturally becomes more marketable in the eyes of a human resources department. These skills can set you apart from the competition, making it easier to land a job.

Analytical Skills Make You a Better Problem Solver

Instead of just getting frustrated when there’s a problem to address, analytical skills give you the ability to solve problems more effectively and efficiently , based on data, history, research, and logical thinking.

Analytical Skills Encourage Critical Thinking

A person with analytical skills is able to translate them into critical thinking capabilities, which will come in handy when you have to weigh the pros and cons and consider the risks and rewards of any given decision.

How to Gain Analytical Skills in School

Analytical thinking skills are no doubt extremely useful when you enter the workforce. There’s no better place to gain these skills than in an academic setting. Or, in other words, school. With the right academic program, you will easily be presented with opportunities to learn analytical skills.

Participate in Analysis-Based Student Projects

In school, you should take on the opportunity to gain analytical skills by participating in an analysis-based student project. Here, you’ll have a chance to not only learn the skills necessary to complete the project, you’ll put those skills to the test every step of the way. Your professor will likely guide you through this, by assigning a project that asks you to call on analytical skills to solve problems.

Focus on the Analytical Skills Relevant to the Project

With a project, you’ll be able to see which analytical skills will be the most useful in completing your goal. Will you need more computing skills or more critical thinking skills? Or will these skills help you work with a complicated team member?

Practice Your Analytical Skills Regularly

Once you’ve gained analytical skills, whether through a project or other assignments in school, don’t forget to regularly practice those skills so that you don’t lose them! Honing in those analytical skills frequently will help you fine-tune them, so you’ll be prepared to use them when another situation calls for them.

Identify Analytical Tools and Resources That Can Help

If you’re struggling to solve a problem in one of your courses, there are various analytical tools, resources, and strategies that can help. For instance, something as simple as a mind-map can help you think about how you want to approach something before jumping into it.

Find Ways to Keep Improving Your Analytical Skills

Don’t be afraid to give yourself more opportunities to continuously improve your analytical skills. Take on your own projects and try to step out of your comfort zone to ask feedback on your work, thoughts, and ideas.

While taking on a comprehensive project is a good way to learn and apply analytical skills through practice, there are other ways to improve your analytical skills.

Be Inquisitive

Asking questions regularly is a good way to improve your analytical thinking skills. Be curious about topics you aren’t familiar with, and look for answers by utilizing helpful resources.

Read More Frequently

Reading is a great way to improve your analytical thinking skills. No matter what genre you prefer, there are many ways to think about the characters, theme, plot, facts, or the author’s message that will sharpen your analytical skills.

Write Often

Reading and writing usually go hand-in-hand in many aspects of life, and it’s no different when it comes to analytical thinking skills. Pick up a pen and a notebook and write about anything that comes to mind. It could be a story, your feelings, or a journal entry recording your activities of the day. Getting ideas on paper helps to think about things more clearly.

Listen to Podcasts

Listening to podcasts about mindfulness, analytical thinking, and other related skills can help you improve your own, especially if you don’t have time to read or write.

Play Brain Games

Playing brain games is a great way to improve your analytical thinking skills. This could be in the form of logic puzzles, crossword puzzles, word searches, sudoku, etc. There are many apps available where you can do a little mind-work every day.

Exercise Your Body

In addition to exercising your brain, you should also exercise your body. Being in good, healthy shape can keep your mind sharp, which naturally improves analytical thinking skills.

Practice Problem Solving

Even though it’s good to sometimes let problems work themselves out, forcing yourself to problem solve in any situation you can will definitely make you a better analytical thinker long-term.

Meet Others and Have Discussions

One aspect of analytical thinking is to utilize resources and seek feedback from others. By socializing, attending conferences, studying together, or simply talking to other people, you can improve your analytical thinking skills.

Take Courses, Online Courses, and Use Analytical Tools

Taking academic or hands-on courses — not just on analytical thinking, but any topic — is a good idea if you want to improve your analytical thinking skills.

If you’re looking for a more direct answer to how to improve your analytical skills, University of the People (UoPeople) may be your answer. UoPeople allows students the opportunity to take courses online , which means you can work on your own time. The university also offers potential undergraduate certificate programs that can give one’s career the right boost. Best of all, we’re tuition-free and US accredited.

Remember to extract various analytical thinking tools, resources, and strategies to help you excel in your courses.

Related Articles

6 Analytical Skills Marketers Need and How to Improve Them

Updated: November 19, 2021

Published: September 16, 2021

If you've ever tried to solve a Rubix Cube, you've put your analytical skills to the test. Making the colors match up requires problem-solving, logical reasoning, and pattern recognition.

While the majority of marketers will never make it to the next speedcubing competition, the skills you learn with puzzles like this are essential to a successful marketing career.

In today's workforce, nearly one in four workers have a job in which analytical skills are considered the most important factor. Companies want to hire for these skills because it shows a candidate's ability to think logically and use data to inform decision-making. In fact, Indeed found the most in-demand skills for employers — and several analytical skills top the list.

That's why it's important to know how analytical skills apply to your career and what you can do to develop these skills over time.

What are analytical skills?

Analytical skills refer to the ability to collect information, analyze it, and draw conclusions in order to solve problems and make effective decisions. Often divided into categories like critical thinking, data analysis, and research, these skills make it possible to recognize patterns and creatively solve complex problems.

As a marketer, being able to understand problems and provide solutions is essential to a long, successful career. It means you can take a critical lens to the details of a problem to fully understand it. This helps you notice trends, understand the steps needed to take action, and offer novel solutions. But that doesn't mean you have to throw creativity out the door. Using analytical skills to problem solve can look like a structured, methodical approach or a more creative one.

We'll explore the various types of analytical skills later on, but first, let's look at how analytical skills differ from critical thinking skills.

Image Source

Analytical Skills vs. Critical Thinking

A person who uses logic to find patterns, brainstorm, analyze data, and make decisions based on that information has analytical skills. One of the skills required to do that is critical thinking.

In other words, critical thinking is just one of many skills you need to be an analytical thinker.

You probably use critical thinking more often than you imagine, like when you:

• Question whether a piece of information is a fact or an opinion.
• Break problems down to understand the reasoning behind them.
• Draw conclusions from data, rather than a gut feeling.
• Make intentional, rational, and goal-oriented decisions.

Marketers who have strong critical thinking skills make reasonable, logical judgments and think through every decision. They provide facts and logical arguments to back their choices, which leads to smart decisions and improves company success.

While each role has its own analytical skill requirements, there are several that will benefit any marketer throughout their career.

Example of Analytical Skills

If you're looking for a marketing role that leans towards analytics, such as a market research analyst position, it's best to develop analytical skills specific to that position and your desired industry. Analytical skills are soft skills, so you'll also want to develop hard role-specific technical skills .

For an analyst, that means mastering technical skills like Google Analytics and statistical software, while also having analytical skills such as creating data collection methods and presenting findings to senior leadership.

But across the board, all marketers can benefit from developing these in-demand analytical skills.

1. Critical Thinking

Any position across all levels of a company can benefit from critical thinking skills. It's the ability to question an idea or examine why a problem exists. This can lead you to tackle issues others thought impossible and understand whether resolving a problem is worth the time, money, and effort. Critical thinking can take many forms in marketing, such as:

• Decision-making
• Content and brand auditing
• Prioritization
• Troubleshooting
• Case analysis
• Correlation
• Data interpretation
• Market research analysis

2. Data Analysis

Neil Hoyne, Chief Measurement Strategist at Google, once said, "The companies that are going to win are the ones who are using data, not guessing."

Interpreting data is more than collecting and reading information — it's making sense of what's before you by connecting patterns and recognizing trends. Strong data analysis skills allow you to pull insights from a large volume of data, which you can share with key decision-makers. This skill can show up in marketing role requirements in a few common ways.

• ROI analysis
• SWOT analysis
• Data visualization
• Pattern recognition
• Process analysis
• Industry and market research
• Presentation skills
• Measuring customer satisfaction
• Marketing analytics
• Customer segmentation strategies
• Predictive analysis

3. Creative Thinking

I once had a manager who was known for saying, "The first answer isn't the answer." She knew the role creativity played in problem-solving and pushed our team to view a possible solution from all angles. Marketers with this analytical skill work to find out-of-the-box solutions and patterns that others brush past. And if you need any more convincing, 'creativity' ranks on Indeed’s top 20 list of most in-demand skills for today's workforce. At work, creative skills involve:

• Brainstorming
• Collaboration
• Adaptability
• Search engine optimization (SEO)
• Strategic planning
• Organizational restructuring
• Predictive modeling
• Campaign development

4. Communication

Employers consistently rank communication as a must-have skill — and for good reason. Being able to explain your idea for a project or give feedback is essential as a marketing professional.

Communicating clearly helps you keep everyone on the same page when rolling out a campaign or diffuse a problem with a deadline when it (inevitably) arises. Strong communication skills needed in marketing include:

• Written and verbal communication
• Body language
• Interpersonal skills
• Active listening
• Conducting presentations
• Confidence and clarity of expression
• Sharing feedback
• Responsiveness
• Delegating responsibilities
• Respect and empathy

5. Problem-solving

Deciding how to respond to a harsh customer comment on social media. Distributing an advertising budget. Prioritizing which roles to hire for as a growing team.

All of these situations require analytical problem-solving skills, and all will pop up through a marketing career. Here are the problem-solving skills every marketer can benefit from developing:

• Data collection
• Checking for accuracy
• Risk-taking
• Attention to detail
• Dependability
• Team-building
• Logic and reasoning
• Organization
• Crisis management

6. Collaboration

Good collaboration skills can improve your working relationships, help you accomplish tasks on time, and reach your short- and long-term goals.

And nearly every marketing team has to collaborate with sales, product, business development, and creative teams to get anything done, knowing how to create synergy with your colleagues will make work smoother and more enjoyable.

The most common collaboration skills for marketers today are:

• Time management
• Negotiation
• Giving and receiving feedback
• Emotional intelligence
• Open-mindedness
• Process improvement
• Adapting to change

How to Improve Analytical Skills

Developing analytical skills takes time and effort. Unlike technical skills that have a structured approach to follow, analytical skills are more difficult to define and develop. There's a process to learn how to use Google Analytics for SEO, but the steps to become an effective communicator are more fuzzy and undefined.

Fortunately, analytical skills can be honed. Here how you can go about boosting your skills and contributing to your company's productivity and success.

Take courses, certifications, or on the job training.

Infinite resources exist both in-person and online that can help you improve your analytical skills. Universities and online companies like Coursera offer online schooling, HubSpot Academy offers free certification courses, and many companies provide stipends for continuing education.

Start by identifying which skills you want to improve and do research to find the resources that are right for your skill set and budget.

Find a mentor.

You likely know someone who is an excellent negotiator or always crafts the perfect email. Noticing how these people approach a situation and problem solve can help you hone your skills. Take notes, save examples, and apply their process to your work.

To take it a step further, ask them to chat over coffee or a phone call to discuss how they developed their skill. They can likely point you in the right direction or provide guidance on what you need to do to excel at the skill.

Try practice problems.

Role-playing is incredibly effective when working to improve analytical skills. Instead of simply reading a case study about an innovative digital media campaign, find a tool to help you develop your brainstorming skills.

Depending on the skill, you can find a practice book or an online resource to walk you through various mental models and scenarios. Work on an idea, and then present it to a trusted colleague or mentor to get feedback.

Play games to improve your analytical skills.

Spending hours on your phone playing Sudoku has more benefits than the personal satisfaction of beating your top score. Games that test your mental agility and memorization can improve your ability to think logically and challenge norms. While game trends are constantly changing, there are several classics that have withstood the test of time.

• Jigsaw puzzles
• Board games (i.e. Scrabble, Settlers of Catan, Splendor, Pictionary, and Bananagrams)
• Computer or mobile games (i.e. Lumosity, Elevate, and Peak)
• Crossword puzzles

Analytical Skills for Your Resume

Once you gain or improve your analytical skills, make sure to update your resume to reflect those strengths. Your resume should include a list of 10 to 20 skills, with a mix of both hard and soft skills. Note at least five to 10 analytical skills so potential employers know you have the knowledge to get your job done.

When choosing which skills to highlight, look to the job requirements section. A role may involve managing the company's social media accounts, but this typically includes collaborating with multiple teams to get the content and analytics you need to do that successfully. Showcasing a blend of technical and analytical skills is what makes you a competitive candidate.

As your career develops, you'll likely need to keep your analytical skills sharp. Be proactive by practicing and paying attention to people who have the skills you want to acquire, and you'll be on your way to solving complex problems with ease.

Don't forget to share this post!

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How to Improve Analytical Skills

Last Updated: March 30, 2024 Fact Checked

This article was co-authored by Emily Listmann, MA . Emily Listmann is a private tutor in San Carlos, California. She has worked as a Social Studies Teacher, Curriculum Coordinator, and an SAT Prep Teacher. She received her MA in Education from the Stanford Graduate School of Education in 2014. There are 14 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 513,496 times.

Analytical skills describe our ability to understand and solve problems using the information we have available. These skills are extremely important for our professional, social, and intellectual lives. As a result, many people have good reason to want to improve their analytical skills. But while improving your analytical skills is not easy, there are a number of things you can do to both passively and actively improve your analytical skills. At the same time, you'll want to test yourself and challenge yourself constantly to keep up and sharpen your skills.

Using Active Approaches

• Practice complicated math problems that include long division, algebra, calculus, and more. These problems will help you develop your logic and reasoning skills and as a result improve your analytical ability.
• Identify math problems in everyday life, then take time to solve them.
• Enroll in a college level math course. Many college level math courses will help you cultivate your analytical skills. [2] X Research source

• One example of a brain game are logic puzzles. Logic puzzles vary and include crossword, riddles, Sudoku, and more. Logic puzzles are available on the internet or at a bookstore near you.
• Play board games. Many board games require you to use your analytical skills and to develop them further. Perhaps the best of these are games like scrabble, some strategy games, and games like chess or checkers.
• Find video games that encourage the development of your analytical skills. A wide array of video games help to improve analytical skills. Some of the best, though, are strategy games and other games that challenge us to solve problems and achieve broad goals. [4] X Trustworthy Source American Psychological Association Leading scientific and professional organization of licensed psychologists Go to source

• Book clubs will allow you to talk about what you’ve observed reading a specific piece of literature. You’ll also have the ability to discuss and interact with others who may have a different take on a given piece of literature.
• Debate clubs are excellent ways to hone our analytical skills because our perspective and arguments will be constantly challenged by others who are working on their own debate ability.
• Most any social group that encourages the free exchange of ideas and the pursuit of knowledge will help you to actively develop your analytical skills.

Using Passive Techniques

• Reading extensively. Don’t just focus on one subject or genre.
• Subscribing to newspapers or informational magazines like National Geographic to learn more about the world around you.
• Attending lectures and academic talks and conferences.
• Going back to college or finding free educational classes in your community. [6] X Research source

• Use any opportunity you have to think things over and to examine different scenarios. For example, if you are going to take a pawn with your castle in Chess, instead of just quitting after thinking about the first (or most likely) response your opponent will take, think out all of the possible responses.
• Consider multiple sides of a problem before picking a solution.
• Avoid picking the easiest and simplest solution right away. However, don't rule out the easiest solution, as it might be worthwhile. [7] X Research source

• Try to think about different ways of viewing the world. Do this by trying to step outside of your religious, political, and cultural suppositions about truth.
• Try to understand and even work to defend positions and ideas you would normally dismiss. You can do this by taking important political positions and working to rationalize and defend the opposite viewpoint that you accept.
• Meet with and surround yourself with people who are very different from yourself. Finding people who have different backgrounds and ideas than you will help you understand and accept ideas different than those you are familiar with.

• Think about things in terms of cause and effect. Consider the repercussions of a prolonged drought. What is the impact of the drought? Look beyond the obvious.
• Think about the similarities between things. How are all living things the same? What similar things do both humans and spiders need to exist?
• Think about connections in history. What cycles, patterns, or other common trends do we see? For instance, in American history, consider how periods of reform are often ended by conflict (the Progressive Era and World War One, the New Deal and World War Two, the Great Society and the Vietnam War). [9] X Research source

• For example, when viewing a forest, try to view individual trees and the uniqueness and place each tree has in the forest.
• When meeting new people make sure to memorize their names, what they’re wearing, and any features that set them apart from everyone else. [10] X Research source

• Never take the easy answer. Always keep questioning.
• If you see a dog, observe what it's doing. Ask yourself why it is doing that. Even if it is a simple action. If it is running to fetch a ball or stick, is it doing this for fun? What about hunting instincts? Is it showing loyalty to its owner by doing that? Is the dog looking motivated, or lazy? Why might it be motivated or lazy? [11] X Research source

Putting Your Skills to Work

• Apply for a promotion or a better job. Moving into a more challenging position at work will enable you to further work on and show off your sharpened analytical skills.
• Take on some volunteer positions. Certain volunteer positions like being a scout leader, little league coach, or a tutor for at risk kids will allow you to use your analytical skills and help others. [12] X Trustworthy Source HelpGuide Nonprofit organization dedicated to providing free, evidence-based mental health and wellness resources. Go to source

• Try to solve complex problems without aid. Instead of using a calculator to compute a math problem, do it in your head or on paper.
• Avoid the easiest solution or path. While it might seem like a no-brainer to always do the quickest, simplest, or easiest thing to solve a problem, do not. Instead, test yourself by picking the harder way to solve something. [14] X Research source

• Mentor others at work.
• Consider starting a blog where you can share your experience with others.
• Work with your children, friends, or family, who might be struggling with education or professional issues. [15] X Research source

How Do You Improve Critical Thinking Skills?

Expert Q&A

You might also like.

• ↑ https://math.as.uky.edu/where-can-math-take-me
• ↑ http://online.stanford.edu/courses/mathematical-thinking-winter-2014
• ↑ https://www.entrepreneur.com/en-in/lifestyle/how-online-gaming-can-increase-your-productivity/303860
• ↑ https://www.apa.org/monitor/2014/02/video-game
• ↑ https://eric.ed.gov/?id=EJ1294499
• ↑ http://www.criticalthinking.org/pages/higher-education/431
• ↑ http://www.intropsych.com/ch07_cognition/analytic_vs_holistic_thinking.html
• ↑ https://www.psychologytoday.com/us/blog/curious/201812/10-book-recommendations-expand-your-worldview
• ↑ https://www.businessphrases.net/analytical-skills/
• ↑ http://www.careers.manchester.ac.uk/experience/skills/analyticalskills/
• ↑ https://www.helpguide.org/articles/healthy-living/volunteering-and-its-surprising-benefits.htm
• ↑ https://www.health.harvard.edu/blog/challenge-your-mind-and-body-to-sharpen-your-thinking-skills-201510298507
• ↑ http://www.criticalthinking.org/pages/critical-thinking-in-everyday-life-9-strategies/512
• ↑ http://www.parentingscience.com/teaching-critical-thinking.html

About This Article

To improve your analytical skills, practice doing math problems, read new books, and play brain games in your free time. Board games like chess and Scrabble are great for cognition. If you can, join a reading or debate club so you can discuss your ideas with others. If you can't, spend more time thinking about the world and asking "Why?" For example, try to figure out the causes and effects of historical or environmental issues. For advice from our Education reviewer about how to put your analytical skills to work, read on! Did this summary help you? Yes No

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Analytical Skills: Why They Matter and How to Develop Them

Analytical skills involve collecting, analyzing, and interpreting information to solve problems. They are crucial in work and daily life, and can be developed through practice. This article explores their importance and ways to improve them.

Have you ever wondered what analytical skills are and why they are important? Analytical skills are the ability to collect, analyze and interpret information to solve problems and make decisions. These skills are highly valued in the workplace and also in our daily lives.

In today's fast-paced world, we are constantly bombarded with information. Whether it's in the form of news, social media, or data, we need to be able to analyze and interpret this information to make informed decisions. Analytical skills are essential for success in many fields, including business, finance, science, and technology.

While some people may possess natural analytical skills, they can also be developed and improved with practice. In this article, we will explore what analytical skills are, why they are important, and how you can improve them. Whether you're looking to advance in your career or simply want to make better decisions in your personal life, enhancing your analytical skills can have a significant impact.

What are Analytical skills?

Analytical skills are vital for any successful professional seeking to provide quality solutions to problems. These skills involve the sharpness to detect patterns, formulate theories, and observe data for the detection of discrepancies or similarities. It requires organizing of information systematically gathered from facts and opinions leading to a logical conclusion or solution.

Analytical skills require the ability to identify the problem and its cause and correlate it with available data to discover an appropriate course of action or an optimal result.

Employers typically wish to see individuals with these increasingly important analytical skills when searching for job candidates. The individuals must demonstrate the capability of having good problem-solving abilities and applying them in creative ways that bring about a successful outcome.

This combination allows companies and organizations alike greater flexibility when faced with various problems and unique situations requiring quick solutions.

How Does Analytical Thinking Work?

Analytical skills are an essential component of many job roles today. They enable you to evaluate different scenarios to solve problems that may not have obvious answers and identify the most beneficial solution for your organization.

An example of such a problem can be seen in our restaurant manager, who has been going over budget on food for the past two weeks. After reviewing the menus, customer orders, and food costs from suppliers, they identified that seafood prices had risen due to supply chain disruption caused by bad weather.

Using their analytical skills, they could connect the dots between these variables. This enabled them to come up with a new strategy for dealing with this issue which involved talking to their seafood supplier and working out a new deal with them to bring costs back down.

This is just one example of how analytical skills can help people extensively in their day-to-day job roles, allowing them to make better decisions and produce more successful outcomes for their organization.

Why are Analytical Skills Important?

Analytical skills are vital in most professional environments and help ensure good decision-making. Analytical skills involve breaking down, analyzing, and debugging intricate puzzles or situations to find the best resolution for any problem. These skills are transferrable to different positions as they indicate a mindset that prioritizes the situation's unique factors.

This means they can be used across multiple sectors as employers look for those who can use their analytical thinking within the organization's specific context, such as marketing research analysts, management executives, budget planners, or financial managers.

Good analytical skills not only give an individual a competitive edge when it comes to career prospects but also aid in navigating interpersonal relationships revolving around one's job. Working with data is important for understanding how a team works together, how negotiations should be conducted, or simply brainstorming potential strategies for training employees or solutions for problems posed by outside contractors.

As a result, having highly developed analytical skills can give someone an advantage over their peers in career growth prospects and allow them to identify new opportunities owing to their experience.

Key Analytical Skills

Here are some key analytical skills that employers look for when assessing job candidates:

Problem-Solving

Problem-solving skills are essential for effectively tackling any situation. These skills involve the ability to navigate complex systems and identify possible solutions. After an issue has been identified, research needs to be conducted to understand the problem better and find potential solutions. The next step is using creative problem-solving skills to design a solution that could potentially work for all parties involved. It's important to consider other people’s input as well, so asking for feedback can also provide valuable insights into how effective a proposed solution is.

For example, if the manager of a recreation center wanted to introduce new exercise classes for members, they would need to determine which classes are popular among members and when the classes should take place. In this case, surveys could be used to collect data from the members and gain insight into everyone’s preferences. With the relevant data collected, problem-solving skills can then be utilized to create a workout schedule that meets the needs of both members and staff. To make sure the schedule works, it's also important to collect feedback from members on how effectively their needs were met with the new class schedule.

Critical Thinking

Critical thinking is an essential skill for any business, no matter the size or scope. By utilizing critical thinking techniques, individuals and organizations can think outside the box to come up with innovative solutions to common problems. This is particularly true in terms of process-based systems, such as inventory management.

A great example of this would be a logistics company that has been using the same system for decades but could benefit from an updated approach. With critical thinking, an operations manager might identify areas where the existing system needs to be improved or replaced completely with something more efficient and cost-effective.

These are just some of the ways critical thinking can help businesses evolve beyond traditional practices and explore new approaches that will result in increased efficiencies. Through questioning preconceived notions and exploring new ideas, companies can hone their processes, innovate products and services, and ensure they remain viable in their respective markets.

Also, effective critical thinkers can potentially steer businesses away from costly blunders when making decisions that will affect people or resources. It is easy to see why strengthening an understanding of critical thinking is beneficial to highly successful businesses worldwide.

Analytical skills are key for many professional roles, but sometimes they alone aren’t enough. This is where creativity comes in. Creative thinking involves looking beyond traditional approaches and finding innovative solutions to problems. It gives analytical people the edge when it comes to big-picture thinking and problem-solving.

For instance, in the workplace, creativity could be used to devise a new product feature based on customer feedback or propose a data-driven presentation. Creativity is an important skill for many industries including data science, finance, marketing and more. With creative thinking, analytical minds can work smarter, not harder - combining their expertise with imagination to develop out-of-the-box solutions.

Examples of analytical creativity skills include ideation (generating creative ideas), innovation (turning those ideas into tangible solutions) and collaboration (working with others to bring a concept to life).

By improving analytical skills through creative thinking, professionals can bring unique value and perspective to their work and stand out in a crowded field.

Communication

Communication skills are an important asset to have when it comes to analytical thinking. Without the ability to communicate your ideas effectively, they wouldn't have any impact on a team. Breaking down complex analytical questions and data into more digestible pieces is a vital communication skill for teams to take away actionable insights.

For example, presenting data visualizations clearly and concisely can give team members an understanding of company performance or project progress. Similarly, verbal communication is important for taking the high-level findings from a statistical analysis and making them easily understandable for everyone.

When it comes to communicating analytical information to teams, storytelling is also key. By narrating the story behind data and its interpretation, you can make abstract concepts easier to comprehend as you bring it all together.

Research is often a vital part of finding solutions to problems and ensuring that the best way forward is chosen. It entails connecting with knowledgeable individuals, gathering facts from various internal and external sources, and understanding what data plays in solving the problem at hand.

Additionally, research in certain fields may involve running experiments or testing products or strategies as part of the greater research process. Overall, research skills involve being aware of which information sources are valuable or integral to finding a solution to a specific issue; this could mean vetting potential experts in an area of knowledge for consultation or seeking user insights through surveys and polls outside of an organization.

Along with giving one access to useful resources, strong research skills also involves understanding how all the pieces of data fit together so that a logical conclusion can be formed.

How to Improve Your Analytical Skills

Improving your analytical skills offers a wide range of benefits for your career. As one of the most sought-after qualities in the job market today, demonstrating your ability to think critically and objectively is key for setting yourself apart in an increasingly competitive hiring process. To maximize the impact of these skills, here are a few tips on cultivating your analytical capabilities and reinforcing their importance for future job opportunities.

First, seek out leadership roles that involve making tough decisions requiring a high level of thinking. Examples include positions such as project managers or administrators. In these roles, you’ll be encouraged to ask probing questions, brainstorm solutions, evaluate risks, and develop strategies accordingly.

Even if you don’t manage a team yet, there are plenty of ways to practice analytical thinking at all levels; consider tweaking tasks assigned by your team leader as an opportunity to apply creative approaches or suggest alternative solutions that might improve efficiency. Enrolling in data-driven decision-making classes can also help reinforce these concepts further by focusing on practical tools such as Excel spreadsheets or statistical methods used in business scenarios.

Keeping up-to-date with industry trends would ultimately allow you to stay informed about innovative approaches while consolidating fundamental concepts along the way.

Finally, stay on top of the latest methodologies and practices related to analytical thinking. Reading industry-specific articles or attending seminars can provide a great opportunity to learn about new ideas and trends in the field.

Additionally, consider reaching out to mentors or colleagues who are well-versed in this area for advice or guidance; having an experienced set of eyes review your work and provide feedback is invaluable in helping you make the best decisions and grasp the fundamentals of analytical thinking.

How to Highlight Your Analytical Skills

Analytical skills on your resume.

Analytical skills are an important asset for any job seeker to have on their resume. They can reflect a candidate’s problem-solving and critical thinking abilities, qualities that many employers value in a potential hire.

The most obvious way of adding analytical skills to your resume is to include them in your skills section. However, to show off your analytical expertise, make sure to utilize it in both your summary and professional history sections.

The summary section is a great place to showcase how you can employ analytical skills successfully. Describing an instance or success story showing off your problem-solving abilities can be invaluable when sought after by employers. This allows readers to get a snapshot of the types of challenges you faced previously and how you solved them using quantitative and qualitative data gathered from various sources.

Additionally, within the work experience section, providing details about particular projects you worked on as applicable can allow readers a better understanding of your ability with analytics.

Adding more detail here can further demonstrate your capacity for complex analysis and implementation of solutions based on analytics-driven sources of data.

Analytical Skills in an Interview

Interviewers often gauge applicants' analytical skills by how well they demonstrate them during the job interview. While this is particularly important for positions requiring a high degree of analysis, such as data analysts or software developers, it still applies to almost any job.

Employers want to know that applicants can think critically and make sound decisions.

To demonstrate analytical skills in an interview, utilize the STAR method when answering questions where you can highlight your abilities. The STAR method consists of identifying a Situation or Task, detailing Actions taken by yourself (or your team), and highlighting the Results that stem from those actions.

Explaining this all in detail shows employers how you were able to assess various factors and apply solutions resulting in positive outcomes. Furthermore, simple things like writing down notes during interviews to demonstrate the ability to gather relevant information and analyze it can also prove helpful.

Analytical skills are essential to many professional and personal tasks. They enable people to make sound decisions and think critically, which is important for many jobs and roles. Developing and showcasing these skills is important to increase the chances of success in any field. While it is important to demonstrate these skills on your resume, it is equally important to showcase them during the interview process as well.

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10 Analytical And Quantitative Skills and How To Improve Them

Discover 10 Analytical And Quantitative skills along with some of the best tips to help you improve these abilities.

Analytical and quantitative skills are important for many jobs, including finance, accounting, engineering, science and research. These skills involve the ability to collect data, analyze it and draw conclusions. Improving your analytical and quantitative skills can help you get a job, perform better in your current position and make better decisions in your personal life. In this guide, we’ll discuss what analytical and quantitative skills are, how you can improve them and how having these skills can improve your life.

Financial Modeling

Data analysis, statistical analysis.

Financial modeling is a process that uses data to create a financial model, which is a tool used to analyze and predict the financial performance of a company or project. Financial models are used by companies to make decisions about whether to invest in a project, whether to go public, or whether to acquire or merge with another company.

Financial modeling is a complex process that requires strong analytical and quantitative skills. Financial models require the use of advanced math and statistics, such as calculus, to create and analyze. Financial models also require strong data analysis and data visualization skills to be able to understand and communicate the results of the analysis.

Data analysis is the process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusions and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, while being used in different business, science and social science domains.

Data analysis is a process for obtaining raw data and converting it into information that can be used to make decisions. Data analysis is the process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusions and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, while being used in different business, science and social science domains.

Statistical analysis is the process of collecting, organizing, analyzing and interpreting data. It’s used to make decisions based on data. Statistical analysis is used in a variety of fields, including business, finance, healthcare, marketing, psychology and more.

Statistical analysis is important because it allows you to make decisions based on data rather than just relying on your own judgment. It can also help you identify trends and patterns in data that you might not have noticed otherwise. When used properly, statistical analysis can help you make better decisions and improve your decision-making process.

Research is an important analytical and quantitative skill because it allows you to gather information and data to support your arguments or claims. When you are doing research, you are looking for evidence to support your position. This evidence can be in the form of statistics, studies, surveys or other data. When you are doing research, it is important to be objective and to look at all sides of the issue.

Research is a valuable skill because it allows you to make informed decisions and arguments. When you are able to support your claims with evidence, you are more likely to be taken seriously and your arguments are more likely to be accepted.

Excel is a software program used for data analysis and manipulation. It is a powerful tool for creating spreadsheets, graphs and charts. Excel is used by businesses and organizations for a variety of purposes, including budgeting, forecasting, reporting and analysis.

Excel is a valuable skill for anyone in business, finance or analytics. It can help you make sense of large amounts of data, identify trends and patterns, and make better decisions. Excel can also be used to create visualizations and presentations that will help you communicate your findings to others.

PowerPoint is a presentation software program that is used to create presentations. A presentation is a visual display of information that is intended to inform or persuade an audience. PowerPoint presentations are often used in business settings to make a case for a proposal, to introduce a new product or service, or to make a sales pitch.

PowerPoint is a valuable tool for creating effective presentations because it allows you to create a visually appealing and organized presentation that is easy for your audience to follow. When used properly, PowerPoint can help you make a strong impression on your audience and convince them of the merits of your argument.

SQL, or Structured Query Language, is a language used to query and manipulate data in databases. It is a fundamental skill for anyone working in data analytics or data science. SQL is used to create and run queries, to retrieve data from databases, to manipulate data and to create reports.

SQL is a powerful language that can be used to solve a wide variety of data problems. It is important to understand how to use SQL because it can make it easier to work with data, to find the information you need and to solve analytical problems.

SAS is an important Analytical and Quantitative skill because it is a software program that can be used to perform statistical analysis. SAS can be used to generate reports, perform data analysis, create graphs and charts, and more. SAS is a valuable skill for those in the Analytical and Quantitative field because it can help them to perform their jobs more efficiently and effectively.

R is a statistical programming language that is used for data analysis and visualization. It is an important skill for those in the field of analytics because it allows them to quickly and easily analyze data and create reports. R can also be used to create visualizations, which can help to better understand data.

Python is an important Analytical and Quantitative skill because it is a programming language that is used for data analysis. Python can be used to create charts and graphs, to manipulate data and to create models. Python is a very versatile language and it can be used in a variety of applications.

Python is a popular language for data science because it is easy to learn, it is versatile and it is fast. Python can be used to create complex models and to run sophisticated analyses. Python is also used for machine learning because it can be used to create algorithms that can learn from data.

How to Improve Your Analytical And Quantitative Skills

1. Use online resources There are a number of online resources that can help you improve your analytical and quantitative skills. Websites like Coursera and Udemy offer online courses on a variety of topics that can help you build these skills.

2. Use practice problems One of the best ways to improve your analytical and quantitative skills is to practice. You can find practice problems online or in workbooks. Once you have completed the practice problems, check your work against the answer key to see how you did.

3. Use online calculators There are a number of online calculators that can help you with mathematical problems. These calculators can be helpful when you are working on practice problems or when you are trying to solve real-world problems.

4. Use online tools There are a number of online tools that can help you with data analysis. Excel and Google Sheets are two examples of online tools that can be helpful.

5. Use online tutorials There are a number of online tutorials that can help you with statistical analysis. These tutorials can be helpful when you are working on practice problems or when you are trying to solve real-world problems.

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What are research skills?

Last updated

26 April 2023

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Broadly, it includes a range of talents required to:

Find useful information

Perform critical analysis

Form hypotheses

Solve problems

It also includes processes such as time management, communication, and reporting skills to achieve those ends.

Research requires a blend of conceptual and detail-oriented modes of thinking. It tests one's ability to transition between subjective motivations and objective assessments to ensure only correct data fits into a meaningfully useful framework.

As countless fields increasingly rely on data management and analysis, polishing your research skills is an important, near-universal way to improve your potential of getting hired and advancing in your career.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

What are basic research skills?

Almost any research involves some proportion of the following fundamental skills:

Organization

Decision-making

Investigation and analysis

Creative thinking

What are primary research skills?

The following are some of the most universally important research skills that will help you in a wide range of positions:

Time management — From planning and organization to task prioritization and deadline management, time-management skills are highly in-demand workplace skills.

Problem-solving — Identifying issues, their causes, and key solutions are another essential suite of research skills.

Critical thinking — The ability to make connections between data points with clear reasoning is essential to navigate data and extract what's useful towards the original objective.

Communication — In any collaborative environment, team-building and active listening will help researchers convey findings more effectively through data summarizations and report writing.

What are the most important skills in research?

Detail-oriented procedures are essential to research, which allow researchers and their audience to probe deeper into a subject and make connections they otherwise may have missed with generic overviews.

Maintaining priorities is also essential so that details fit within an overarching strategy. Lastly, decision-making is crucial because that's the only way research is translated into meaningful action.

• Why are research skills important?

Good research skills are crucial to learning more about a subject, then using that knowledge to improve an organization's capabilities. Synthesizing that research and conveying it clearly is also important, as employees seek to share useful insights and inspire effective actions.

Effective research skills are essential for those seeking to:

Analyze their target market

Investigate industry trends

Identify customer needs

Detect obstacles

Find solutions to those obstacles

Develop new products or services

Develop new, adaptive ways to meet demands

Discover more efficient ways of acquiring or using resources

Why do we need research skills?

Businesses and individuals alike need research skills to clarify their role in the marketplace, which of course, requires clarity on the market in which they function in. High-quality research helps people stay better prepared for challenges by identifying key factors involved in their day-to-day operations, along with those that might play a significant role in future goals.

• Benefits of having research skills

Research skills increase the effectiveness of any role that's dependent on information. Both individually and organization-wide, good research simplifies what can otherwise be unwieldy amounts of data. It can help maintain order by organizing information and improving efficiency, both of which set the stage for improved revenue growth.

Those with highly effective research skills can help reveal both:

Opportunities for improvement

Brand-new or previously unseen opportunities

Research skills can then help identify how to best take advantage of available opportunities. With today's increasingly data-driven economy, it will also increase your potential of getting hired and help position organizations as thought leaders in their marketplace.

• Research skills examples

Being necessarily broad, research skills encompass many sub-categories of skillsets required to extrapolate meaning and direction from dense informational resources. Identifying, interpreting, and applying research are several such subcategories—but to be specific, workplaces of almost any type have some need of:

Searching for information

Attention to detail

Taking notes

Problem-solving

Communicating results

Time management

• How to improve your research skills

Whether your research goals are to learn more about a subject or enhance workflows, you can improve research skills with this failsafe, four-step strategy:

Make an outline, and set your intention(s)

Know your sources

Learn to use advanced search techniques

Practice, practice, practice (and don't be afraid to adjust your approach)

These steps could manifest themselves in many ways, but what's most important is that it results in measurable progress toward the original goals that compelled you to research a subject.

• Using research skills at work

Different research skills will be emphasized over others, depending on the nature of your trade. To use research most effectively, concentrate on improving research skills most relevant to your position—or, if working solo, the skills most likely have the strongest impact on your goals.

You might divide the necessary research skills into categories for short, medium, and long-term goals or according to each activity your position requires. That way, when a challenge arises in your workflow, it's clearer which specific research skill requires dedicated attention.

How can I learn research skills?

Learning research skills can be done with a simple three-point framework:

Clarify the objective — Before delving into potentially overwhelming amounts of data, take a moment to define the purpose of your research. If at any point you lose sight of the original objective, take another moment to ask how you could adjust your approach to better fit the original objective.

Scrutinize sources — Cross-reference data with other sources, paying close attention to each author's credentials and motivations.

Organize research — Establish and continually refine a data-organization system that works for you. This could be an index of resources or compiling data under different categories designed for easy access.

Which careers require research skills?

Especially in today's world, most careers require some, if not extensive, research. Developers, marketers, and others dealing in primarily digital properties especially require extensive research skills—but it's just as important in building and manufacturing industries, where research is crucial to construct products correctly and safely.

Engineering, legal, medical, and literally any other specialized field will require excellent research skills. Truly, almost any career path will involve some level of research skills; and even those requiring only minimal research skills will at least require research to find and compare open positions in the first place.

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Analytical and Research Skills

Critical and analytical thinking Being able to objectively analyse an issue or problem, and critically appraise different aspects or solutions. This includes being able to reason well, define and review the work of others, apply theories or abstract concepts and explain your thinking methodically to others. This skill may also be described as ‘problem-solving’ in relation to particular issues.

Research design and question formulation Being able to identify and define a particular problem, and then design a research question or project to adequately address the problem. This includes the appropriate use of research methods, the creation of a suitable question and an understanding of research ethics and requirements.

Experience of qualitative research Being able to conduct qualitative research e.g. interviews, focus groups, participant observation, and knowing when to use these methods and the benefits and drawbacks of each. Conducting research in an ethical way, and drawing appropriate conclusions from the evidence.

Experience of quantitative research Being able to conduct quantitative research e.g. using polls or questionnaires, or manipulating existing data, and knowing when to use these methods and the benefits and drawbacks of each. Conducting research in an ethical way and drawing appropriate conclusions from the evidence.

Numeracy skills Being comfortable with basic numerical data and manipulating this to provide information or analysis e.g. calculating ratios, percentages and forecasts based on previous data. Also, being able to integrate numerical and non-numerical information where necessary, and to explain the meaning of data to a larger issue or question.

Artificial intelligence in strategy

Can machines automate strategy development? The short answer is no. However, there are numerous aspects of strategists’ work where AI and advanced analytics tools can already bring enormous value. Yuval Atsmon is a senior partner who leads the new McKinsey Center for Strategy Innovation, which studies ways new technologies can augment the timeless principles of strategy. In this episode of the Inside the Strategy Room podcast, he explains how artificial intelligence is already transforming strategy and what’s on the horizon. This is an edited transcript of the discussion. For more conversations on the strategy issues that matter, follow the series on your preferred podcast platform .

Joanna Pachner: What does artificial intelligence mean in the context of strategy?

Yuval Atsmon: When people talk about artificial intelligence, they include everything to do with analytics, automation, and data analysis. Marvin Minsky, the pioneer of artificial intelligence research in the 1960s, talked about AI as a “suitcase word”—a term into which you can stuff whatever you want—and that still seems to be the case. We are comfortable with that because we think companies should use all the capabilities of more traditional analysis while increasing automation in strategy that can free up management or analyst time and, gradually, introducing tools that can augment human thinking.

Joanna Pachner: AI has been embraced by many business functions, but strategy seems to be largely immune to its charms. Why do you think that is?

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Yuval Atsmon: You’re right about the limited adoption. Only 7 percent of respondents to our survey about the use of AI say they use it in strategy or even financial planning, whereas in areas like marketing, supply chain, and service operations, it’s 25 or 30 percent. One reason adoption is lagging is that strategy is one of the most integrative conceptual practices. When executives think about strategy automation, many are looking too far ahead—at AI capabilities that would decide, in place of the business leader, what the right strategy is. They are missing opportunities to use AI in the building blocks of strategy that could significantly improve outcomes.

I like to use the analogy to virtual assistants. Many of us use Alexa or Siri but very few people use these tools to do more than dictate a text message or shut off the lights. We don’t feel comfortable with the technology’s ability to understand the context in more sophisticated applications. AI in strategy is similar: it’s hard for AI to know everything an executive knows, but it can help executives with certain tasks.

When executives think about strategy automation, many are looking too far ahead—at AI deciding the right strategy. They are missing opportunities to use AI in the building blocks of strategy.

Joanna Pachner: What kind of tasks can AI help strategists execute today?

Yuval Atsmon: We talk about six stages of AI development. The earliest is simple analytics, which we refer to as descriptive intelligence. Companies use dashboards for competitive analysis or to study performance in different parts of the business that are automatically updated. Some have interactive capabilities for refinement and testing.

The second level is diagnostic intelligence, which is the ability to look backward at the business and understand root causes and drivers of performance. The level after that is predictive intelligence: being able to anticipate certain scenarios or options and the value of things in the future based on momentum from the past as well as signals picked in the market. Both diagnostics and prediction are areas that AI can greatly improve today. The tools can augment executives’ analysis and become areas where you develop capabilities. For example, on diagnostic intelligence, you can organize your portfolio into segments to understand granularly where performance is coming from and do it in a much more continuous way than analysts could. You can try 20 different ways in an hour versus deploying one hundred analysts to tackle the problem.

Predictive AI is both more difficult and more risky. Executives shouldn’t fully rely on predictive AI, but it provides another systematic viewpoint in the room. Because strategic decisions have significant consequences, a key consideration is to use AI transparently in the sense of understanding why it is making a certain prediction and what extrapolations it is making from which information. You can then assess if you trust the prediction or not. You can even use AI to track the evolution of the assumptions for that prediction.

Those are the levels available today. The next three levels will take time to develop. There are some early examples of AI advising actions for executives’ consideration that would be value-creating based on the analysis. From there, you go to delegating certain decision authority to AI, with constraints and supervision. Eventually, there is the point where fully autonomous AI analyzes and decides with no human interaction.

Because strategic decisions have significant consequences, you need to understand why AI is making a certain prediction and what extrapolations it’s making from which information.

Joanna Pachner: What kind of businesses or industries could gain the greatest benefits from embracing AI at its current level of sophistication?

Yuval Atsmon: Every business probably has some opportunity to use AI more than it does today. The first thing to look at is the availability of data. Do you have performance data that can be organized in a systematic way? Companies that have deep data on their portfolios down to business line, SKU, inventory, and raw ingredients have the biggest opportunities to use machines to gain granular insights that humans could not.

Companies whose strategies rely on a few big decisions with limited data would get less from AI. Likewise, those facing a lot of volatility and vulnerability to external events would benefit less than companies with controlled and systematic portfolios, although they could deploy AI to better predict those external events and identify what they can and cannot control.

Third, the velocity of decisions matters. Most companies develop strategies every three to five years, which then become annual budgets. If you think about strategy in that way, the role of AI is relatively limited other than potentially accelerating analyses that are inputs into the strategy. However, some companies regularly revisit big decisions they made based on assumptions about the world that may have since changed, affecting the projected ROI of initiatives. Such shifts would affect how you deploy talent and executive time, how you spend money and focus sales efforts, and AI can be valuable in guiding that. The value of AI is even bigger when you can make decisions close to the time of deploying resources, because AI can signal that your previous assumptions have changed from when you made your plan.

Joanna Pachner: Can you provide any examples of companies employing AI to address specific strategic challenges?

Yuval Atsmon: Some of the most innovative users of AI, not coincidentally, are AI- and digital-native companies. Some of these companies have seen massive benefits from AI and have increased its usage in other areas of the business. One mobility player adjusts its financial planning based on pricing patterns it observes in the market. Its business has relatively high flexibility to demand but less so to supply, so the company uses AI to continuously signal back when pricing dynamics are trending in a way that would affect profitability or where demand is rising. This allows the company to quickly react to create more capacity because its profitability is highly sensitive to keeping demand and supply in equilibrium.

Joanna Pachner: Given how quickly things change today, doesn’t AI seem to be more a tactical than a strategic tool, providing time-sensitive input on isolated elements of strategy?

Yuval Atsmon: It’s interesting that you make the distinction between strategic and tactical. Of course, every decision can be broken down into smaller ones, and where AI can be affordably used in strategy today is for building blocks of the strategy. It might feel tactical, but it can make a massive difference. One of the world’s leading investment firms, for example, has started to use AI to scan for certain patterns rather than scanning individual companies directly. AI looks for consumer mobile usage that suggests a company’s technology is catching on quickly, giving the firm an opportunity to invest in that company before others do. That created a significant strategic edge for them, even though the tool itself may be relatively tactical.

Joanna Pachner: McKinsey has written a lot about cognitive biases  and social dynamics that can skew decision making. Can AI help with these challenges?

Yuval Atsmon: When we talk to executives about using AI in strategy development, the first reaction we get is, “Those are really big decisions; what if AI gets them wrong?” The first answer is that humans also get them wrong—a lot. [Amos] Tversky, [Daniel] Kahneman, and others have proven that some of those errors are systemic, observable, and predictable. The first thing AI can do is spot situations likely to give rise to biases. For example, imagine that AI is listening in on a strategy session where the CEO proposes something and everyone says “Aye” without debate and discussion. AI could inform the room, “We might have a sunflower bias here,” which could trigger more conversation and remind the CEO that it’s in their own interest to encourage some devil’s advocacy.

We also often see confirmation bias, where people focus their analysis on proving the wisdom of what they already want to do, as opposed to looking for a fact-based reality. Just having AI perform a default analysis that doesn’t aim to satisfy the boss is useful, and the team can then try to understand why that is different than the management hypothesis, triggering a much richer debate.

In terms of social dynamics, agency problems can create conflicts of interest. Every business unit [BU] leader thinks that their BU should get the most resources and will deliver the most value, or at least they feel they should advocate for their business. AI provides a neutral way based on systematic data to manage those debates. It’s also useful for executives with decision authority, since we all know that short-term pressures and the need to make the quarterly and annual numbers lead people to make different decisions on the 31st of December than they do on January 1st or October 1st. Like the story of Ulysses and the sirens, you can use AI to remind you that you wanted something different three months earlier. The CEO still decides; AI can just provide that extra nudge.

Joanna Pachner: It’s like you have Spock next to you, who is dispassionate and purely analytical.

Yuval Atsmon: That is not a bad analogy—for Star Trek fans anyway.

Joanna Pachner: Do you have a favorite application of AI in strategy?

Yuval Atsmon: I have worked a lot on resource allocation, and one of the challenges, which we call the hockey stick phenomenon, is that executives are always overly optimistic about what will happen. They know that resource allocation will inevitably be defined by what you believe about the future, not necessarily by past performance. AI can provide an objective prediction of performance starting from a default momentum case: based on everything that happened in the past and some indicators about the future, what is the forecast of performance if we do nothing? This is before we say, “But I will hire these people and develop this new product and improve my marketing”— things that every executive thinks will help them overdeliver relative to the past. The neutral momentum case, which AI can calculate in a cold, Spock-like manner, can change the dynamics of the resource allocation discussion. It’s a form of predictive intelligence accessible today and while it’s not meant to be definitive, it provides a basis for better decisions.

Joanna Pachner: Do you see access to technology talent as one of the obstacles to the adoption of AI in strategy, especially at large companies?

Yuval Atsmon: I would make a distinction. If you mean machine-learning and data science talent or software engineers who build the digital tools, they are definitely not easy to get. However, companies can increasingly use platforms that provide access to AI tools and require less from individual companies. Also, this domain of strategy is exciting—it’s cutting-edge, so it’s probably easier to get technology talent for that than it might be for manufacturing work.

The bigger challenge, ironically, is finding strategists or people with business expertise to contribute to the effort. You will not solve strategy problems with AI without the involvement of people who understand the customer experience and what you are trying to achieve. Those who know best, like senior executives, don’t have time to be product managers for the AI team. An even bigger constraint is that, in some cases, you are asking people to get involved in an initiative that may make their jobs less important. There could be plenty of opportunities for incorpo­rating AI into existing jobs, but it’s something companies need to reflect on. The best approach may be to create a digital factory where a different team tests and builds AI applications, with oversight from senior stakeholders.

The big challenge is finding strategists to contribute to the AI effort. You are asking people to get involved in an initiative that may make their jobs less important.

Joanna Pachner: Do you think this worry about job security and the potential that AI will automate strategy is realistic?

Yuval Atsmon: The question of whether AI will replace human judgment and put humanity out of its job is a big one that I would leave for other experts.

The pertinent question is shorter-term automation. Because of its complexity, strategy would be one of the later domains to be affected by automation, but we are seeing it in many other domains. However, the trend for more than two hundred years has been that automation creates new jobs, although ones requiring different skills. That doesn’t take away the fear some people have of a machine exposing their mistakes or doing their job better than they do it.

Joanna Pachner: We recently published an article about strategic courage in an age of volatility  that talked about three types of edge business leaders need to develop. One of them is an edge in insights. Do you think AI has a role to play in furnishing a proprietary insight edge?

Yuval Atsmon: One of the challenges most strategists face is the overwhelming complexity of the world we operate in—the number of unknowns, the information overload. At one level, it may seem that AI will provide another layer of complexity. In reality, it can be a sharp knife that cuts through some of the clutter. The question to ask is, Can AI simplify my life by giving me sharper, more timely insights more easily?

Joanna Pachner: You have been working in strategy for a long time. What sparked your interest in exploring this intersection of strategy and new technology?

Yuval Atsmon: I have always been intrigued by things at the boundaries of what seems possible. Science fiction writer Arthur C. Clarke’s second law is that to discover the limits of the possible, you have to venture a little past them into the impossible, and I find that particularly alluring in this arena.

AI in strategy is in very nascent stages but could be very consequential for companies and for the profession. For a top executive, strategic decisions are the biggest way to influence the business, other than maybe building the top team, and it is amazing how little technology is leveraged in that process today. It’s conceivable that competitive advantage will increasingly rest in having executives who know how to apply AI well. In some domains, like investment, that is already happening, and the difference in returns can be staggering. I find helping companies be part of that evolution very exciting.

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New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of Stanford Graduate School of Education (GSE), who is also a professor of educational technology at the GSE and faculty director of the Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately worried that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or coach students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of CRAFT (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the Digital Learning initiative at the Stanford Accelerator for Learning, which runs a program exploring the use of virtual field trips to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

ORIGINAL RESEARCH article

This article is part of the research topic.

Actionable Learning Analytics in Education: An opportunity to close the learning loop

Understanding Self-Regulation Strategies in Problem-Based Learning through Dispositional Learning Analytics Provisionally Accepted

• 1 School of Business and Economics, Maastricht University, Netherlands

The final, formatted version of the article will be published soon.

In the ongoing discussion about how learning analytics can effectively support self-regulated student learning and which types of data are most suitable for this purpose, this empirical study aligns with the framework proposed by Buckingham Shum and Deakin Crick (2012) who advocated the inclusion of both behavioural trace data and survey data in learning analytics studies. By incorporating learning dispositions in our learning analytics modelling, this research aims to investigate and understand how students engage with learning tasks, tools, and materials in their academic endeavours. This is achieved by analysing trace data, which captures digital footprints of students' interactions with digital tools, along with survey responses from the Study of Learning Questionnaire (SLQ), to comprehensively examine their preferred learning strategies. Additionally, the study explores the relationship between these strategies and students' learning dispositions measured at the start of the course. An innovative aspect of this investigation lies in its emphasis on understanding how learning dispositions act as antecedents and potentially predict the utilization of specific learning strategies. The data is scrutinized to identify patterns and clusters of such patterns between students' learning disposition and their preferred strategies. Data is gathered from two cohorts of students, comprising 2400 first year students. This analytical approach aims to uncover predictive insights, offering potential indicators to predict and understand students' learning strategy preferences, which holds value for teachers, educational scientists, and educational designers. Understanding students' regulation of their own learning process holds promise to recognize students with less beneficial learning strategies and target interventions aimed to improve these. A crucial takeaway from our research underscores the significance of flexibility, which entails the ability to adjust preferred learning strategies according to the learning environment. While it is imperative to instruct our students in deep learning strategies and encourage autonomous regulation of learning, this should not come at the expense of acknowledging situations where surface strategies and controlled regulation may prove to be more effective.

Keywords: Dispositional learning analytics, Learning Strategies, self-regulated learning, Selfdirected learning, Problem-Based Learning, higher education

Received: 06 Feb 2024; Accepted: 17 May 2024.

Copyright: © 2024 Tempelaar, Bátori and Giesbers. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Dirk Tempelaar, School of Business and Economics, Maastricht University, Maastricht, 6200 MD, Netherlands, Netherlands

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Using ideas from game theory to improve the reliability of language models

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Imagine you and a friend are playing a game where your goal is to communicate secret messages to each other using only cryptic sentences. Your friend's job is to guess the secret message behind your sentences. Sometimes, you give clues directly, and other times, your friend has to guess the message by asking yes-or-no questions about the clues you've given. The challenge is that both of you want to make sure you're understanding each other correctly and agreeing on the secret message.

MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have created a similar "game" to help improve how AI understands and generates text. It is known as a “consensus game” and it involves two parts of an AI system — one part tries to generate sentences (like giving clues), and the other part tries to understand and evaluate those sentences (like guessing the secret message).

The researchers discovered that by treating this interaction as a game, where both parts of the AI work together under specific rules to agree on the right message, they could significantly improve the AI's ability to give correct and coherent answers to questions. They tested this new game-like approach on a variety of tasks, such as reading comprehension, solving math problems, and carrying on conversations, and found that it helped the AI perform better across the board.

Traditionally, large language models answer one of two ways: generating answers directly from the model (generative querying) or using the model to score a set of predefined answers (discriminative querying), which can lead to differing and sometimes incompatible results. With the generative approach, "Who is the president of the United States?" might yield a straightforward answer like "Joe Biden." However, a discriminative query could incorrectly dispute this fact when evaluating the same answer, such as "Barack Obama."

So, how do we reconcile mutually incompatible scoring procedures to achieve coherent, efficient predictions? 

"Imagine a new way to help language models understand and generate text, like a game. We've developed a training-free, game-theoretic method that treats the whole process as a complex game of clues and signals, where a generator tries to send the right message to a discriminator using natural language. Instead of chess pieces, they're using words and sentences," says Athul Jacob, an MIT PhD student in electrical engineering and computer science and CSAIL affiliate. "Our way to navigate this game is finding the 'approximate equilibria,' leading to a new decoding algorithm called 'equilibrium ranking.' It's a pretty exciting demonstration of how bringing game-theoretic strategies into the mix can tackle some big challenges in making language models more reliable and consistent."

When tested across many tasks, like reading comprehension, commonsense reasoning, math problem-solving, and dialogue, the team's algorithm consistently improved how well these models performed. Using the ER algorithm with the LLaMA-7B model even outshone the results from much larger models. "Given that they are already competitive, that people have been working on it for a while, but the level of improvements we saw being able to outperform a model that's 10 times the size was a pleasant surprise," says Jacob. 

"Diplomacy," a strategic board game set in pre-World War I Europe, where players negotiate alliances, betray friends, and conquer territories without the use of dice — relying purely on skill, strategy, and interpersonal manipulation — recently had a second coming. In November 2022, computer scientists, including Jacob, developed “Cicero,” an AI agent that achieves human-level capabilities in the mixed-motive seven-player game, which requires the same aforementioned skills, but with natural language. The math behind this partially inspired the Consensus Game. 

While the history of AI agents long predates when OpenAI's software entered the chat in November 2022, it's well documented that they can still cosplay as your well-meaning, yet pathological friend. 

The consensus game system reaches equilibrium as an agreement, ensuring accuracy and fidelity to the model's original insights. To achieve this, the method iteratively adjusts the interactions between the generative and discriminative components until they reach a consensus on an answer that accurately reflects reality and aligns with their initial beliefs. This approach effectively bridges the gap between the two querying methods. 

In practice, implementing the consensus game approach to language model querying, especially for question-answering tasks, does involve significant computational challenges. For example, when using datasets like MMLU, which have thousands of questions and multiple-choice answers, the model must apply the mechanism to each query. Then, it must reach a consensus between the generative and discriminative components for every question and its possible answers. 

The system did struggle with a grade school right of passage: math word problems. It couldn't generate wrong answers, which is a critical component of understanding the process of coming up with the right one. 

“The last few years have seen really impressive progress in both strategic decision-making and language generation from AI systems, but we’re just starting to figure out how to put the two together. Equilibrium ranking is a first step in this direction, but I think there’s a lot we’ll be able to do to scale this up to more complex problems,” says Jacob.   

An avenue of future work involves enhancing the base model by integrating the outputs of the current method. This is particularly promising since it can yield more factual and consistent answers across various tasks, including factuality and open-ended generation. The potential for such a method to significantly improve the base model's performance is high, which could result in more reliable and factual outputs from ChatGPT and similar language models that people use daily. 

"Even though modern language models, such as ChatGPT and Gemini, have led to solving various tasks through chat interfaces, the statistical decoding process that generates a response from such models has remained unchanged for decades," says Google Research Scientist Ahmad Beirami, who was not involved in the work. "The proposal by the MIT researchers is an innovative game-theoretic framework for decoding from language models through solving the equilibrium of a consensus game. The significant performance gains reported in the research paper are promising, opening the door to a potential paradigm shift in language model decoding that may fuel a flurry of new applications."

Jacob wrote the paper with MIT-IBM Watson Lab researcher Yikang Shen and MIT Department of Electrical Engineering and Computer Science assistant professors Gabriele Farina and Jacob Andreas, who is also a CSAIL member. They presented their work at the International Conference on Learning Representations (ICLR) earlier this month, where it was highlighted as a "spotlight paper." The research also received a “best paper award” at the NeurIPS R0-FoMo Workshop in December 2023.

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MIT researchers have developed a new procedure that uses game theory to improve the accuracy and consistency of large language models (LLMs), reports Steve Nadis for Quanta Magazine . “The new work, which uses games to improve AI, stands in contrast to past approaches, which measured an AI program’s success via its mastery of games,” explains Nadis. 

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• Article: "Game Theory Can Make AI More Correct and Efficient"
• Jacob Andreas
• Athul Paul Jacob
• Language & Intelligence @ MIT
• Computer Science and Artificial Intelligence Laboratory (CSAIL)
• Department of Electrical Engineering and Computer Science
• MIT-IBM Watson AI Lab

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