Analytical Skills Comments
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.
Questionnaires 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)

The statements below can be used in your self-assessment (self-feedback) or performance appraisal as examples to demonstrate your "analytical skills". Your ability to work in a dynamic environment. To be flexible, accommodating and responsive. It requires being creative, aware of the situation, willing and capable.
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.
- I understood how to develop critical and analytical thinking.
- I evaluated the integrity and comparability of data and identified existing gaps.
- I clearly identified the issue to be resolved.
- I evaluated evidence impartially, especially when it challenged existing beliefs or ideas.
- I utilized data and logical reasoning to address and challenge personal biases in decision-making.
- I understood complex issues and problems.
- I used cognitive skills or strategies that increase the probability of a desirable outcome.
- I applied critical and analytical thinking to the situation.
- I used analytical thinking to make desireable outcomes more probable.
- I evaluated evidence objectively, regardless of whether it supported or contradicted current ideas.
- I employed data and logic to counter personal biases of others.
- I used a more analytical and careful approach to solving issues.
- I understood and capitalize on relationships between conflicting goals.
- I examined problems in depth and from multiple points of view.
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.
- I was able to dissect a problem into its core elements.
- I divided complex problems or tasks into components/parts for further analysis.
- I decomposed complex information into smaller, manageable parts to understand the details better.
- I analyzed issues and reduced them to their component parts.
- I was easily able to separate a process/procedure into its component parts.
- I distilled issues down to their core items.
- I decomposed problems into smaller, manageable parts.
- I reduced issues to their fundamental elements.
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.
- I was open and adaptable to exploring innovative perspectives and techniques when conventional methods prove ineffective.
- I was willing to seek out and consider alternative viewpoints.
- I was willing to revise my own views when presented with new, credible information.
- I was flexible in adopting new perspectives and approaches when traditional methods fell short.
- I was willing to listen to different perspectives.
- I was open minded and receptive to considering opposing evidence.
- I was open to investigating novel approaches and methods.
- I was ready and capable of exploring alternative viewpoints and strategies.
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.
- I identified problems and issues needing resolution.
- I identified the root cause of a problem.
- I prioritized various actions to be taken when solving a problem.
- I selected the solution that offered the best outcome based on the analysis.
- I used appropriate techniques to solve problems.
- I used a methodical approach to the understanding and resolving of problems.
- I determined 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.
- I considered the context in which information was produced.
- I gathered information from a variety of sources.
- I recognized areas of missing data and suggests other ways to obtain the needed information.
- I used standard data collection practices.
- I understood the importance of maintaining current, accurate information.
- I implemented a variety of data gathering techniques.
- I maintained precision when collecting and measuring data.
- I collected relevant data and facts about a situation.
- I prioritized precision in the data collection process.
- I took the necessary steps to maintain precision when collecting and measuring data.
- I ensured that information was current and up-to-date.
- I was precise in the measurement of variables, leading to more accurate data collection.
- I used data from a variety of sources.
- I used a variety of data collection methods.
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.
- I checked the credibility of information sources.
- I validated the accuracy of data collected.
- I checked facts by cross-referencing the evidence with other reliable sources.
- I ensured that the foundation of an analysis was based on reliable and relevant data.
- I determined the relevance and accuracy of information.
- I evaluated if information was detailed and relevant.
- I evaluated evidence for accuracy and relevance.
- I assessed the validity and correctness of the data before using it to draw conclusions.
- I evaluated assumptions before taking actions.
- I checked that the information was both precise and up-to-date.
- I implemented data validation techniques and methods.
- I verified that information was accurate and updated.
- I determined if sources of information were reputable, reliable, and credible.
- I critically examined the information presented to determine its truthfulness and applicability to the topic at hand.
- I evaluated the validity and reliability of data and research findings.
- I determined if facts were consistent across multiple sources.
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.
- I was able to interpret and analyze data.
- I used statistics to find hidden patterns, connections, and trends in data.
- I determined the relevance and accuracy of information.
- I synthesized data from multiple sources to draw logical conclusions.
- I used logic and reasoning to identify which pieces of information were useful and which are not.
- I analyzed data and information from several sources and arrives at logical conclusions.
- I analyzed and consolidated data from several sources to develop logical insights.
- I selected the appropriate techniques for analysis.
- Interpreted and analyzed data.
- I analyzed data using statistical methods.
- I analyzed data to meet constituent needs.
- I evaluated whether the information was specific enough to be meaningful.
- I analyzed data to meet the needs of my clients.
- I used 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.
- I created detailed budgets that guide financial planning and decision-making.
- I used financial metrics of similar companies to estimate the value our company.
- I am comfortable working with numbers and data.
- I measured and assessed the potential loss in value of a portfolio under normal market conditions.
- I calculated and interpreted financial ratios (such as liquidity ratios, profitability ratios, and leverage ratios) to assess the financial health of the company.
- I measured costs associated with various programs and policies.
- I interpreted financial data, reports, balance sheets, and cash flow analysis.
- I developed quantitative measures of performance.
- I used 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.
- I organized information for decision making.
- I made decisions based on solid, credible evidence rather than personal biases or preconceived notions.
- I considered both risks and costs alongside the potential benefits and success rates when making decisions.
- I maximized the efficient use of scarce resources such as time and money.
- I optimized limited resources, such as time and money, by finding the most efficient solutions to problems.
- I used current data for decision making.
- I weighed the risks and costs of certain decisions.
- I made reasonable decisions about the importance of different sources of information.
- Balanced risks and costs with the reward 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.
- I determined averages and trends in the data.
- I found trends in data to helped make important decisions.
- I modeled future customer behavior from previous trends.
- I connected experiences, analyze 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.
- I built mathematical models to represent real-world problems to help in understanding complex systems and predicting outcomes.
- I analyzed market trends, forecast sales, and optimize supply chain operations.
- I analyzed various legal and business situations to find patterns and draw conclusions that others might miss.
- I looked for trends in the data.
- I recognized patterns, draws logical conclusions, and makes recommendations for action.
- I projected future data points based on historical data.
- I analyzed financial statements over multiple periods to identify patterns and trends in revenue, expenses, and profits.
- I looked for patterns, trends, and relationships within the data.
- I built complex financial models to project future revenues, expenses, and cash flows based on historical data and assumptions.
- I identified trends and patterns in data which led to valuable insights and strategic decisions.
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.
- I reviewed contractual documents for clauses and specifications to ensure binding agreements are free from disputes.
- I reviewed tasks, deadlines, and resources needed to ensure smooth completion of the project.
- I meticulously recorded and maintained logs of observations/measurements.
- I identified deviations from stated goals and objectives.
- I examined for tiny defects in products which could lead to product failures and/or returns.
- I audited financial records to detect fraud or errors.
- I identified discrepancies and inconsistencies in reports.
- I ensured financial transactions were recorded accurately and completely.
- I ensured staff recorded financial transactions accurately and completely.
- I identified patterns in conflicting information, events, or data.
- I examined material specifications to ensure the structural integrity of the building/craft/machine.
- I maintained high attention to detail to ensure tests/experiments are replicable and results are reliable.
- I performed checks on data accuracy and quality.
- I examined patient orders to determine the proper dosage of medicines.
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.
- I identified opportunities for progress and innovation.
- I recognized that all parts of a business are connected where a change in one area can impact others in unexpected ways.
- I integrated customer feedback loops, market trends, social media influence, and brand perception to create a cohesive strategy.
- I established connections between different pieces of information to see the bigger picture.
- I understood the relationships between component parts.
- I helped employees see that changes in one part of the business can affect other parts.
- I understood how supplier relationships affected inventory levels, production schedules, and customer satisfaction.
- I identified 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.
- I looked beyond immediate cause-and-effect to understand deeper, systemic causes.
- I used analytical techniques to assure that adequate resources are available to meet the needs of the department.
- I examined how the new software would affect workflows, employee morale, customer interactions, and long-term scalability.
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.
- I presented data clearly and concisely to support strong, evidence-based arguments.
- I prepared appropriate visualizations of data in charts, graphs, and reports.
- I actively sought constructive feedback from others.
- I made graphs and charts to explain data clearly.
- I presented data in a format that made comparisons easier.
- I was able to recall relevant information when needed.
- I formatted data to facilitate easy comparisons.
- I organized data in a way that simplified its interpretation and comparisons.
- I presented quantitative data in a clear and concise manner aiding in making persuasive and evidence-based arguments.
- I created presentations that were straight forward to understand.
- I designed presentations that were easy to digest.
- I created graphs, charts, and other visual representations of data making it easier to interpret and communicate findings.
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.
- I increased understanding through the cautious application of logic and research.
- I looked at problems from different perspectives and viewpoints.
- I identified potential problem areas.
- I created new ways of interpreting the data.
- I sought to understand where potential problems may occur.
- I figured out where issues might arise.
- I helped employees to understand the issues better by using logic and research carefully.
- I created new visualizations of the data.
- I asked the "right" questions to size up or evaluate situations.
- I sought 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.
- I tested hypotheses, analyze experimental data, and draw conclusions.
- I understand the basic principles of research.
- I proved hypotheses and theories using data and experiments.
- I tested hypotheses and validated theories through empirical evidence.
- I used methods to confirm theories with real-world evidence.
- I applied scientific and empirical methods to test hypotheses.
- I am well-versed in fundamental research concepts.
- I have a solid grasp of basic research methodologies.