Analytical - Competency
Definition: Analytical skills are the ability to think critically, be open-minded, and reduce complex issues into more manageable parts. The ability to collect, validate, and analyze data is important for making decisions, forecasting, and developing models. Attention to detail and a willingness to work with quantitative data are needed. Having a good understanding of systems, how to present data, and how to conduct research is useful. Analytical skills also require a certain degree of curiosity.
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360-Feedback Assessments Measuring Analytical Skills:
Survey 1 (4-point scale; Competency Comments)
Survey 2 (4-point scale; Competency Comments)
Survey 3 (5-point scale; Competency Comments)
Survey 4 (5-point scale; radio buttons)
Survey 5 (4-point scale; words)
Survey 6 (4-point scale; words)
Survey 7 (5-point scale; competency comments; N/A)
Survey 8 (3-point scale; Agree/Disagree words; N/A)
Survey 9 (3-point scale; Strength/Development; N/A)
Survey 10 (Comment boxes only)
Survey 11 (Single rating per competency)
Survey 12 (Slide-bar scale)
Survey 13 (4-point scale; numbers; floating anchors)
Survey 14 (4-point scale; N/A)
What are Analytical Skills?
Analytical skills include critical thinking using data and logic; performing reductive analysis to make complex systems and problems more manageable; maintaining an open mind to consider different perspectives and viewpoints; and the ability to collect, validate, and analyze data. Analytical skills require attention to detail and fluency with quantitative data to develop forecasts and models of systems. An orientation toward research and the ability to format and visualize data for presentations are important. Core Components of Analytical Skill
- Thinking Critically: Evaluating information objectively, questioning assumptions, and applying structured reasoning to develop well-founded conclusions. Performing an impartial assessment of evidence, identifying gaps in data, understanding complex issues, countering biases with logic, and analyzing problems from multiple viewpoints.
- Reductive Analysis: Breaking down complex problems, processes, or datasets into fundamental components to better understand key elements to dissect large issues into smaller, manageable parts, reducing complexity to core elements, and structuring information for deeper analysis.
- Open Minded: Embracing diverse perspectives, questioning assumptions, and being flexible in adjusting viewpoints based on credible evidence to explore alternative strategies, consider opposing viewpoints, adapt to new methods when traditional approaches fall short, and remain receptive to innovative solutions.
- Problem-Solving: Applying structured techniques to identify, prioritize, and implement solutions effectively to define issues, determine root causes, select optimal solutions, and execute resolution strategies through a methodical approach.
- Validating Data: Ensuring the accuracy, credibility, and relevance of data before it is used for decision-making requires verifying sources, checking consistency across multiple references, validating assumptions, and implementing techniques to ensure precision.
- Data Analysis: Interpret, process, and extract insights from data to uncover meaningful patterns and trends. This may require applying statistical methods, synthesizing information from various sources, using logical reasoning to determine relevance, and identifying useful correlations.
- Quantitative Ability: Using numerical data, financial metrics, and mathematical models to assess costs, risks, and performance outcomes to interpret balance sheets, calculate financial ratios, develop budgets, apply algorithms, and measure portfolio value under market conditions.
- Forecasting and Modeling: Using historical data, trends, and mathematical models to predict future events and guide business planning to identify patterns, model financial scenarios, project revenues and expenses, recognize relationships in complex systems, and make recommendations based on anticipated outcomes.
- Attention to Detail: Carefully examine specifics, detect discrepancies, and ensure precision in analysis and execution to perform auditing of financial transactions, verifying product quality, maintaining rigorous documentation, and identifying hidden inconsistencies in reports and processes.
Why Analytical Skills important in the workplace?
Analytical Skills are important for several reasons:
- Critical Thinking: Uses data and logic to help ensure desireable outcomes to situations.
- Reductive Analysis: Decomposes and deconstructs complex tasks and systems into smaller components.
- Open Minded: Following the data and facts may require flexibility in adopting new positions or viewpoints.
- Data Collection: Collecting precise information that is up-to-date.
- Data Validation: Ensuring information is accurate, valid, and reliable.
- Data Analysis: Interpret and analyze data.
What are key aspects of Analytical Skills?
- Critical Thinking
- Reductive Analysis
- Keeping an open mind
- Data Collection
- Data Validation
- Data Analysis
- Quantitative Ability
- Forecasting/Modeling
- Attention to Detail
- Systems Thinking
- Data Presentation
- Curiosity
How can I improve my Analytical Skills?
- Continuous Learning: Enroll in courses or workshops that focus on data analysis, critical thinking, and problem-solving. There are many online platforms like Coursera, LinkedIn Learning, and Udemy that offer courses in these areas.
- Practice with Real Data: Use actual business data to practice your analytical skills. Analyze sales data, customer feedback, or financial reports to gain insights and make data-driven decisions.
- Seek Feedback: Share your analyses with colleagues or mentors and seek constructive feedback. This can help you identify areas for improvement and gain new perspectives.
- Stay Curious: Cultivate a habit of asking questions and seeking out new information. Curiosity drives deeper understanding and innovation.
- Use Analytical Tools: Familiarize yourself with analytical tools and software like Excel, Tableau, or SQL. These tools can help you manage and analyze data more efficiently.
- Collaborate with Others: Work with others on projects that require analytical thinking. Collaborating can help you see how different people approach and solve problems.
- Work on your Attention to Detail: Pay attention to the small details in data and reports. This can help you catch errors and identify important trends.
What questions could be included on a 360-degree survey that measure analytical skills?
When creating a questionnaire to measure analytical skills, be sure to include items that measure the critical thinking, reductive analysis, keeping an open mind, data collection, data validation, and data analysis. When creating a 360-degree or other performance assessment, try to select one or two items from each group. Questionnaire Items to Include
Critical ThinkingCritical Thinking focuses on evaluating information objectively, questioning assumptions, and applying structured reasoning to develop well-founded conclusions. This dimension highlights impartial assessment of evidence, identifying gaps in data, understanding complex issues, countering biases with logic, and analyzing problems from multiple viewpoints. It prioritizes thoughtful evaluation and intellectual discipline, ensuring that decisions are based on rigorous analysis rather than intuition or personal biases.
- Understands how to develop critical and analytical thinking.
- Applies critical and analytical thinking to the situation.
- Evaluates the integrity and comparability of data and identifies existing gaps.
- Uses cognitive skills or strategies that increase the probability of a desirable outcome.
- Uses analytical thinking to make desirable outcomes more probable.
- Uses a more analytical and careful approach to solving issues.
- Evaluates evidence objectively, regardless of whether it supports or contradicts current ideas.
- Clearly identifies the issue to be resolved.
- Utilizes data and logical reasoning to address and challenge personal biases in decision-making.
- Evaluates evidence impartially, especially when it challenges existing beliefs or ideas.
- Employs data and logic to counter personal biases of others.
- Understands complex issues and problems.
- Examines problems in depth and from multiple points of view.
- Understands and capitalizes on relationships between conflicting goals.
Reductive AnalysisReductive Analysis focuses on breaking down complex problems, processes, or datasets into fundamental components to better understand key elements. This dimension highlights dissecting large issues into smaller, manageable parts, reducing complexity to core elements, and structuring information for deeper analysis. It prioritizes structured breakdown and simplification, ensuring that analytical tasks are divided into digestible segments for enhanced comprehension and resolution.
- Analyzes issues and reduces them to their component parts.
- Able to dissect a problem into its core elements.
- Distills issues down to their core items.
- Easily able to separate a process/procedure into its component parts.
- Reduces issues to their fundamental elements.
- Decomposes problems into smaller, manageable parts.
- Decomposes complex information into smaller, manageable parts to understand the details better.
- Divides complex problems or tasks into components/parts for further analysis.
Open MindedOpen Minded focuses on embracing diverse perspectives, questioning assumptions, and being flexible in adjusting viewpoints based on credible evidence. This dimension highlights exploring alternative strategies, considering opposing viewpoints, adapting to new methods when traditional approaches fall short, and remaining receptive to innovative solutions. It prioritizes intellectual flexibility and adaptability, ensuring individuals are willing to revise their understanding based on new insights.
- Is willing to seek out and consider alternative viewpoints.
- Is open minded and receptive to considering opposing evidence.
- Ready and capable of exploring alternative viewpoints and strategies.
- Is willing to listen to different perspectives.
- Is willing to revise own views when presented with new, credible information.
- Open and adaptable to exploring innovative perspectives and techniques when conventional methods prove ineffective.
- Is flexible in adopting new perspectives and approaches when traditional methods fall short.
- Open to investigating novel approaches and methods.
Problem-SolvingProblem-Solving emphasizes applying structured techniques to identify, prioritize, and implement solutions effectively. This dimension centers on defining issues, determining root causes, selecting optimal solutions, and executing resolution strategies through a methodical approach. It prioritizes practical application and solution-driven execution, ensuring that problems are not only analyzed but also efficiently addressed.
- Identifies problems and issues needing resolution.
- Prioritizes various actions to be taken when solving a problem.
- Uses a methodical approach to the understanding and resolving of problems.
- Selects the solution that offers the best outcome based on the analysis.
- Uses appropriate techniques to solve problems.
- Identifies the root cause of a problem.
- Determines important parameters or issues to take into account when solving problems.
Data CollectionData Collection emphasizes gathering, measuring, and ensuring the accuracy of relevant information before analysis begins. This dimension centers on obtaining data from various sources, maintaining precision in measurements, recognizing missing information, and verifying relevance. It prioritizes information acquisition and validation, ensuring that analytical decisions are based on robust, well-sourced data.
- Ensures that information is current and up-to-date.
- Uses standard data collection practices.
- Is precise in the measurement of variables, leading to more accurate data collection.
- Recognizes areas of missing data and suggests other ways to obtain the needed information.
- Collects relevant data and facts about a situation.
- Prioritizes precision in the data collection process.
- Implements a variety of data gathering techniques.
- Gathers information from a variety of sources.
- Understands the importance of maintaining current, accurate information.
- Takes the steps to maintain precision when collecting and measuring data.
- Maintains precision when collecting and measuring data.
- Considers the context in which information was produced.
- Uses a variety of data collection methods.
- Uses data from a variety of sources.
Data ValidationData Validation emphasizes ensuring the accuracy, credibility, and relevance of data before it is used for decision-making. This dimension highlights verifying sources, checking consistency across multiple references, validating assumptions, and implementing techniques to ensure precision. It prioritizes quality control and reliability, making sure that conclusions are based on trustworthy and error-free information.
- Implements data validation techniques and methods.
- Determines the relevance and accuracy of information.
- Determines if sources of information are reputable, reliable, and credible.
- Evaluates the validity and reliability of data and research findings.
- Assesses the validity and correctness of the data before using it to draw conclusions.
- Ensures that the foundation of an analysis is based on reliable and relevant data.
- Verifies that information is accurate and updated.
- Checks that the information is both precise and up-to-date.
- Evaluates assumptions before taking actions.
- Critically examines the information presented to determine its truthfulness and applicability to the topic at hand.
- Evaluate if information is detailed and relevant.
- Check the credibility of information sources.
- Checks facts by cross-referencing the evidence with other reliable sources.
- Evaluates evidence for accuracy and relevance.
- Determines if facts are consistent across multiple sources.
- Validates the accuracy of data collected.
Data AnalysisData Analysis focuses on interpreting, processing, and extracting insights from data to uncover meaningful patterns and trends. This dimension centers on applying statistical methods, synthesizing information from various sources, using logical reasoning to determine relevance, and identifying useful correlations. It prioritizes interpretation and strategic insights, ensuring that data is leveraged effectively to inform decisions and optimize performance.
- Analyzes data using statistical methods.
- Analyzes and consolidates data from several sources to develop logical insights.
- Determines the relevance and accuracy of information.
- Analyzes data to meet the needs of clients.
- Evaluates whether the information is specific enough to be meaningful.
- Analyzes data to meet constituent needs.
- Able to interpret and analyze data.
- Uses statistics to find hidden patterns, connections, and trends in data.
- Uses logic and reasoning to identify which pieces of information are useful and which are not.
- Selects the appropriate techniques for analysis.
- Analyzes data and information from several sources and arrives at logical conclusions.
- Synthesizes data from multiple sources to draw logical conclusions.
- Can effectively interpret and analyze data.
- Uses alternate tools for analysis to check the reliability of previous analyses.
Quantitative AbilityQuantitative Ability focuses on using numerical data, financial metrics, and mathematical models to assess costs, risks, and performance outcomes. This dimension highlights interpreting balance sheets, calculating financial ratios, developing budgets, applying algorithms, and measuring portfolio value under market conditions. It prioritizes data-driven precision and numerical analysis, ensuring organizations make decisions based on measurable financial factors.
- Develops quantitative measures of performance.
- Uses financial metrics of similar companies to estimate the value our company.
- Creates detailed budgets that guide financial planning and decision-making.
- Measures and assesses the potential loss in value of a portfolio under normal market conditions.
- Calculates and interprets financial ratios (such as liquidity ratios, profitability ratios, and leverage ratios) to assess the financial health of the company.
- Able to interpret financial data, reports, balance sheets, and cash flow analysis.
- Measures costs associated with various programs and policies.
- Is comfortable working with numbers and data.
- Uses algorithms and quantitative models to determine the costs/benefits of different programs based on mathematical and statistical analysis.
Decision MakingDecision Making focuses on assessing available information, weighing risks and costs, and selecting the most effective course of action based on solid evidence and reasoning. This dimension highlights optimizing limited resources, balancing trade-offs, evaluating different sources of information, and making rational judgments. It prioritizes strategic choice and optimization, ensuring decisions align with efficiency, feasibility, and business objectives.
- Organizes information for decision making.
- Makes decisions based on solid, credible evidence rather than personal biases or preconceived notions.
- Considers both risks and costs alongside the potential benefits and success rates when making decisions.
- Uses current data for decision making.
- Optimizes limited resources, such as time and money, by finding the most efficient solutions to problems.
- Maximizes the efficient use of scarce resources such as time and money.
- Weighs the risks and costs of certain decisions.
- Makes reasonable decisions about the importance of different sources of information.
- Balances risks and costs with the rewards and probabilities of success when making decisions.
Forecasting/ModelingForecasting/Modeling emphasizes using historical data, trends, and mathematical models to predict future events and guide business planning. This dimension centers on identifying patterns, modeling financial scenarios, projecting revenues and expenses, recognizing relationships in complex systems, and making recommendations based on anticipated outcomes. It prioritizes predictive analytics and trend recognition, ensuring organizations make informed decisions with forward-looking insights.
- Able to project future data points based on historical data.
- Analyzes various legal and business situations to find patterns and draw conclusions that others might miss.
- Connects experiences, analyzes the facts and spots issues across a wide array of legal and business issues to see patterns and draw conclusions not readily apparent to others.
- Analyzes financial statements over multiple periods to identify patterns and trends in revenue, expenses, and profits.
- Looks for trends in the data.
- Identifies trends and patterns in data can lead to valuable insights and strategic decisions.
- Analyze market trends, forecast sales, and optimize supply chain operations.
- Finds trends in data to helped make important decisions.
- Builds mathematical models to represent real-world problems to help in understanding complex systems and predicting outcomes.
- Determines averages and trends in the data.
- Models future customer behavior from previous trends.
- Builds complex financial models to project future revenues, expenses, and cash flows based on historical data and assumptions.
- Looks for patterns, trends, and relationships within the data.
- Recognizes patterns, draws logical conclusions, and makes recommendations for action.
Attention to DetailAttention to Detail emphasizes carefully examining specifics, detecting discrepancies, and ensuring precision in analysis and execution. This dimension centers on auditing financial transactions, verifying product quality, maintaining rigorous documentation, and identifying hidden inconsistencies in reports and processes. It prioritizes accuracy and meticulous scrutiny, ensuring that minor errors do not compromise outcomes and that processes are carried out flawlessly.
- Reviews tasks, deadlines, and resources needed to ensure smooth completion of the project.
- Meticulously records and maintains logs of observations/measurements.
- Examines patient orders to determine the proper dosage of medicines.
- Identifies patterns in conflicting information, events, or data.
- Examines for tiny defects in products which could lead to product failures and/or returns.
- Maintains high attention to detail to ensure tests/experiments are replicable and results are reliable.
- Identifies deviations from stated goals and objectives.
- Examines material specifications to ensure structural integrity of the building/craft/machine.
- Audits financial records to detect fraud or errors.
- Reviews contractual documents for clauses and specifications to ensure binding agreements are free from disputes.
- Identifies discrepancies and inconsistencies in reports.
- Ensures staff records financial transactions accurately and completely.
- Performs checks on data accuracy and quality.
- Ensures financial transactions are recorded accurately and completely.
Systems ThinkingSystems Thinking emphasizes understanding interdependencies between different business components and recognizing how changes in one area can affect the broader system. This dimension centers on diagnosing impacts across value chains, integrating customer feedback with market trends, identifying systemic causes beyond immediate effects, and ensuring holistic decision-making. It prioritizes big-picture analysis and interconnected reasoning, ensuring organizations consider broader implications when making strategic choices.
- Identifies opportunities for progress and innovation.
- Establishes connections between different pieces of information to see the bigger picture.
- Understands how supplier relationships affect inventory levels, production schedules, and customer satisfaction.
- Helps employees see that changes in one part of the business can affect other parts.
- Examines how the new software will affect workflows, employee morale, customer interactions, and long-term scalability.
- Looks beyond immediate cause-and-effect to understand deeper, systemic causes.
- Uses analytical techniques to assure that adequate resources are available to meet the needs of the department.
- Recognizes that all parts of a business are connected where a change in one area can impact others in unexpected ways.
- Understands the relationships between component parts.
- Identifies the part of the business value chain that is affected by a particular decision or action, diagnoses the situation, and prioritize what needs to be done and who needs to be involved.
- Integrates customer feedback loops, market trends, social media influence, and brand perception to create a cohesive strategy.
Data PresentationData Presentation focuses on structuring, visualizing, and conveying data effectively to ensure clarity and comprehension. This dimension highlights creating charts, graphs, and reports, organizing information for easy comparisons, designing straightforward presentations, and making data-driven arguments persuasive. It prioritizes communication and accessibility, ensuring that insights are presented clearly and compellingly to various audiences.
- Able to recall relevant information when needed.
- Organizes data in a way that simplifies its interpretation and comparisons.
- Able to prepare appropriate visualizations of data in charts, graphs, and reports.
- Makes graphs and charts to explain data clearly.
- Presents quantitative data in a clear and concise manner aiding in making persuasive and evidence-based arguments.
- Designs presentations that are easy to digest.
- Actively seeks constructive feedback from others.
- Creates graphs, charts, and other visual representations of data making it easier to interpret and communicate findings.
- Presents data in a format that makes comparisons easier.
- Formats data to facilitate easy comparisons.
- Creates presentations that are straight forward to understand.
- Presents data clearly and concisely to support strong, evidence-based arguments.
Curiosity and CreativityCuriosity and Creativity focuses on asking insightful questions, exploring alternative perspectives, and developing innovative ways to interpret data and identify problems. This dimension highlights seeking new knowledge, visualizing data in unconventional ways, considering multiple viewpoints, and using logic to uncover potential issues. It prioritizes exploration and imaginative thinking, ensuring individuals approach problems with openness and ingenuity.
- Increases understanding through the cautious application of logic and research.
- Creates new visualizations of the data.
- Asks the "right" questions to size up or evaluate situations.
- Creates new ways of interpreting the data.
- Looks at problems from different perspectives and viewpoints.
- Seeks to understand where potential problems may occur.
- Identifies potential problem areas.
- Helps employees to understand the issues better by using logic and research carefully.
- Figures out where issues might arise.
- Seeks new knowledge and skills to enhance analytical thinking.
Research OrientedResearch Oriented emphasizes applying structured scientific methodologies to validate hypotheses, analyze experimental data, and derive accurate conclusions based on empirical evidence. This dimension centers on testing theories, utilizing research principles, proving ideas through data-driven methods, and ensuring findings are based on verifiable results. It prioritizes rigorous investigation and empirical validation, ensuring that conclusions are substantiated by systematic research rather than intuition or speculation.
- Proves hypotheses and theories using data and experiments.
- Uses methods to confirm theories with real-world evidence.
- Applies scientific and empirical methods to test hypotheses.
- Tests hypotheses, analyze experimental data, and draw conclusions.
- Has a solid grasp of basic research methodologies.
- Understands the basic principles of research.
- Tests hypotheses and validates theories through empirical evidence.
- Is well-versed in fundamental research concepts.