Analytical Thinking Skills for Problem Solving


Analytical Thinking Skills for Problem Solving

Employees of an organization face a large number of problems of various natures in their work life. The employees need to have personal resilience to handle the challenges and pressure which the problems bring along with them. It becomes easier for them to solve those problems if they have analytical thinking approach to the problems, have the required analytical skills with them, and know the use of various analytical tools.

Analytical thinking is a powerful thinking process for understanding the parts of a situation. It is defined as the ability to scrutinize and break down facts and thoughts into their strengths and weaknesses and developing the capacity to think in a thoughtful, discerning way, to solve problems, analyze data, and recall and use information.

Analytical thinking skills enable the employees to think through issues and to focus on priorities for action.  It not only supports the problem-solving but also helps in judgment and decision-making, and ensures action is followed through. The employees’ capacity to demonstrate analytical thinking skills make them give importance to a rigorous, logical and reflective approach to situations and issues which help in turn to stick to the art of the possible, and prevents burn out. These skills also help the employees to make best use of the resources to secure improvements and to bring results.

With analytical skills, employees are able to identify and define problems, extract key information from data and develop workable solutions for the problems identified in order to test and verify the cause of the problem and develop solutions to resolve the problems identified. Employees having analytical skills are able to (i) evaluate information or situations, (ii) break them down into their key components, (iii) consider various ways of approaching and resolving them, and (iv) decide on the most appropriate of these ways.

Solving of the problems involves both analytical and creative skills. Which particular skills are needed vary, depending on the problem, the prevailing situation, and the role of the employee in the organization, but the following skills are key to the problem solving.

  • Analytical ability
  • Lateral thinking
  • Initiative
  • Logical reasoning
  • Persistence

Analytical thinking skills help employees to evaluate the problem and to make decisions. A logical and methodical approach is best in some circumstances, for example, they need to be able to draw on their theoretical knowledge and experience to identify solutions of a practical or technical nature. In other situations, using creativity or lateral thinking may be necessary to come up with ideas for finding solution for the problem and find fresh approaches. Not everyone has these two types of skills in equal measure. For this reason acquisition of these skills by the employees through training is an important aspect which needs to be pursued by the management.

It is essential that the employees develop analytical thinking so that they can solve problems meaningfully in their work situations. According to Bloom, an analysis may be classified into three parts namely (i) analysis of elements is the ability to classify and analyze significant elements, i.e. to find a summary of content and to differentiate facts and opinions, similarities and differences, and causes and effects, (ii) analysis of relationships is the ability to relate concepts and reasons, i.e. to compare and analyze consistent and/or contrary or irrational information, and (iii) analysis of organizational principles is the ability to search for principles of relationships between elements of information, i.e. to identify key matters by taking into account relevant stories and being able to summarize the relevant information into one concept.

Analytical thinking follows the scientific approach to problem solving. The analytical thinking cycle has got five components as shown in the Fig 1. These components are (i) defining of the problem, (ii) hypothesis, (iii) facts, (iv) analysis, and (v) solution.

  • Defining of the problem – A problem is a situation that is judged as something that needs to be corrected. It implies that a state of ‘wholeness’” does not exist. It is the job of the employees to make sure that they are solving the right problem. The right problem may not be what appears to be obvious but what needs correction. Most of the obvious problems have real problems in the background. Defining of the real problem clearly improves focus and it drives the analytical process. Getting to a clearly defined problem is often discovery driven and starts with a conceptual definition and also through analysis (root cause, impact analysis, etc.), employees can shape and redefine the problem in terms of issues.
  • Formulating the hypotheses – Hypotheses are tentative explanations for an observation that can be tested (i.e. proved or disproved) by further investigation. It starts at the end. Figuring out the solution to the problem, i.e. ‘hypothesizing’, at the start helps the employees in building a roadmap for approaching the problem. Hypotheses can be expressed as possible root causes of the problem. Breaking down the problem into key drivers (root causes) can help formulate hypotheses.
  • Collection of facts – After formulation of the hypotheses, next step is the collection of the facts. Facts are the meaningful information which has merit and they are not false. Facts can be qualitative (expert opinions) or quantitative (measurable performance) information which are helpful for the decision making. Gathering of relevant data and information is a critical step in supporting the analyses required for proving or disproving the hypotheses. The basic concepts for the data collection include (i) to know where to dig, (ii) to know how to filter through information, (iii) to know how to verify (has happened in the past), and (iv) to know how to apply (relates to the problem which the employees are trying to solve).
  • Conducting the analysis – The analysis is the deliberate process of breaking a problem down through the application of knowledge and various analytical techniques. Analysis of the facts is required to prove or disprove a hypothesis. Analysis provides an understanding of issues and drivers behind the problem. It is generally better to spend more time analyzing the data and information as opposed to collecting them. The goal is to find the ‘golden nuggets’ that quickly confirm or deny a hypothesis. Some of the analytical techniques which can be applied are root cause analysis, storyboarding, and force field analysis etc.
  • Developing the solution – Solutions are the final recommendations presented to the management based on the outcomes of the hypotheses testing. Solutions are to be capable of solving the problem. It is important to ensure the solution fits the organizational prevailing environment. Solutions are useless if they cannot be implemented. Running an actual example through the solution is an effective way of testing the effectiveness and viability of the solution

Analytical thinking cycle

Fig 1 Analytical thinking cycle

Defining of the problem

A problem becomes known when an employee observes a discrepancy between the way things are and the way things ought to be.  Problems can be identified through (i) comparative/benchmarking studies, (ii) performance reporting which provides assessment of current performance against goals and objectives, (iii) SWOT analysis which is the assessment of strengths, weaknesses, opportunities, and threats, (iv) complaints, (v) surveys, and (vi) any other technique.

Sometimes the thing employees think is a problem is not the real problem, so to get at the real problem, probing is necessary.  Root cause analysis is an effective method of probing. It helps identify what, how, and why something happened. Root cause is the specific underlying cause. It is the cause that can reasonably be identified and that management has the control to fix.

Techniques for the root cause analysis include (i) ‘five whys’ which refers to the practice of asking, five times, why the problem exists in order to get to the root cause of the problem, (ii) ‘fishbone diagram or cause and effect diagram’ which is an analysis tool that provides a systematic way of looking at effects and the causes that create or contribute to those effects and which provides a method for categorizing the many potential causes of problems or issues in an orderly way and in identifying root causes, (iii) ‘force field analysis’ which visually show forces that impact the problem or issue, (iv) ‘scatter diagrams’ which are graphs showing the relationship of two variables and quantifies the correlation, showing how one variable influences another, (v) ‘process mapping’ which shows ‘as is’ flow of activities of the process and which look for excessive handoffs, redundancies, and other root causes of inefficiencies, and (vi) ‘benchmarking’ which compares existing performance to the performance of another internal or external source, identifies issues not otherwise revealed through other techniques.

Basic questions which are to be asked for defining of the problem (regardless of the technique used) are ‘who’, ‘what’, ‘where’, ‘when’, ‘why’, and ‘how’.

Formulating the hypothesis

Issue diagram is an effective method for breaking down problems and for formulating of the hypothesis. A problem may be due to several issues and each issue may have several hypotheses. Issue diagrams provide a framework for brainstorming and documenting the issues driving the problem and identifying the facts (i.e. data) required to support conclusions and recommended solutions. Hypotheses and the key questions help shape data collection requirements and ensure that only relevant data is collected. Formulation of hypotheses and key questions is an evolving process. They need to be revised as new insights and discoveries are made. A typical issue diagram is shown in Fig 2.

Typical issue diagram

Fig 2 Typical issue diagram

Issues are the questions which need to be answered or topics which need to be explored in order to solve a problem, hypotheses are the speculative answers for issues that are phrased as questions and/or areas of exploration for issue phrased as topics, and key questions are those that probe hypotheses and drive the primary analysis required to solve the problem.

Key to the solving of the problem is to develop a comprehensive list of all possible issues related to the problem and then to reduce the comprehensive list by eliminating duplicates and combining overlapping issues. The major issues (usually two to five issues) are then selected using consensus building.

There are some pitfalls against which precautions are necessary. Pitfalls with respect to issues are (i) too broad, which expand beyond the objectives, (ii) too narrow, (iii) too many to be easily remembered, (iv) being of uneven weight, and (v) not sequenced effectively. Pitfalls with respect to hypotheses are (i) too few to cover the issue, (ii) too many to be easily remembered, (iii) not supportable by data, and (iv) not directly relevant. Pitfalls with respect to key questions are (i) too few to test the hypotheses, (ii) too many to be easily remembered, (iii) irrelevant to the hypotheses, and (iv) not answerable with data.

Collection of facts

Collection of factual information is necessary in order to answer the key questions and validate the hypotheses. Data collection is a critical stage in problem solving. If it is superficial, biased or incomplete, data analysis becomes very difficult.

First critical steps are to identify what information, i.e. data elements, is required and develop a data collection approach/technique. Depending on the type of problem being solved, different data-collection techniques can be used. Combining a number of different techniques allows looking at problems from different perspectives.

Data collection techniques are (i) collection of already available information, (ii) observing, (iii) interviewing, (iv) getting filled up a questionnaire from the employees working in area where problem exist,  and (v) conducting meeting with focused group with selected participants where free discussions on the specific topics are facilitated.

Data collection techniques are either qualitative or quantitative. Qualitative techniques are flexible and produce qualitative data that is often recorded in narrative form. These techniques are useful in answering the ‘why’, ‘what’, and ‘how’ questions. They typically include (i) loosely structured interviews using open-ended questions, (ii) focus group discussions, and (iii) observations. Quantitative techniques are less flexible and they answers to questions which can be counted or can be expressed numerically. They are typically structured questionnaires designed to quantify pre- or post-categorized answers to questions. They are useful in answering the ‘how many’, ‘how often’, ‘how significant’ etc. questions. A skillful use of a combination of qualitative and quantitative techniques normally provides a more comprehensive understanding of the topic.

Conducting the analysis

This step in problem solving consists of ‘the making sense, of the information and data collected. There are several analytical techniques that can be applied for understanding the information and data collected. The selection of the appropriate analytical techniques is to match the key question and the collection of the facts. Some of the analytical techniques are given below.

  • Benchmarking – It compares and measures the performance of a process or activity against the performance of similar processes or activities from an internal or external source. The differences indicate possible performance issues. Normally it is difficult to collect the comparable measurement data. Usually comparing ‘best in class’ performance is better than comparing average performance.
  • SWOT analysis – It is the assessment of strengths, weaknesses, opportunities, and threats. The analysis indicates the things which are good, the things which are not good, things which are to be done, and the things which are not to be done. It is probably the most common analytical tool for strategic planning. The tool is somewhat subjective but easy to understand and follow. It is very useful tool for identifying the core competencies of the organization.
  • Force field analysis – The analysis visually shows the significant forces that impacts the subject problem and the overall environmental landscape. Forces tend to be those factors that promote or hinder a solution to a problem. With this analysis, it is possible to prioritize forces between direct (more important) and indirect (less important). Normally the analysis needs brainstorming to generate ideas to list all forces.
  • Cost benefit analysis – The analysis compares total equivalent costs (all the minuses) against equivalent value in benefits (all the pluses). It identifies all expected costs and benefits to make sure the decision has economic merit. Costs include all tangible outlays (time, money, etc.) and intangible /qualitative factors where some value can be assigned. It compares using a set of decision criteria based on similar things. The analysis looks at the net changes between making the decision with the situation if the decision is not made.
  • Impact analysis – It is ‘what if’ type of analysis for the assessment the impact of change on the organization and the consequences of not acting on the problem. The analysis identifies broad and diverse effects or outcomes associated with a problem and/or the proposed solution. The objective of the analysis is to minimize adverse or negative impacts of going forward. Cost benefit analysis is very useful in assessing risks of different proposed solutions and it helps in reaching the right solution. Several tools can be used to assess impacts. These tools are (i) ‘scenario playing’ or storyboarding which tells how the future will unfold between alternatives of ‘do nothing’ vs. ‘solution’, (ii) decision tree analysis that builds a tree and assign probabilities to each alternative to arrive at the most likely solution, (iii) simulation which is the modeling of a process and seeing how it changes when one or more variables change, and (iv) prototype model which builds and tests the solution on a small scale before implementation to know the short coming of the solution before the same is implemented on a regular scale.
  • Pareto chart – It is bar chart which categorizes issues or other attributes in terms of importance. Pareto chart quantifies what is most important on a graph following the ‘80:20’ rule. It puts focus on the significant problems or issues. While doing the analysis one must group problems or issues based on a common and measurable attribute (such as reworks, errors, downtime, hours, etc.) usually on the left vertical axis of the bar chart. Also one must categorize problems or issues (poor quality, long wait times, etc.) usually on the right horizontal axis of the bar chart. In Pareto chart the data and rank is plotted according to frequency generally in descending order from left to right.

It is necessary not to rush out and collect information until one knows what analytical tools he needs for use. Each tool has its own information needs. Normally a combination of tools is used to cover all the bases. Since all decisions involve some assumptions, hence one never has all the facts. Analysis is a discovery driven process and it moves incrementally in baby steps. One learns, adjusts and goes through numerous iterations until he has insights; i.e. he can now take action on the issue or problem.

Developing the solution

The solution that has the greatest impact on solving the problem need to be selected and planned based on the analysis. Usually a solution rating matrix is used to weigh different solutions based on selection criteria (costs, probability of success, and ease of implementation). The solutions are to have support from the previous step of analysis. It is better if the solutions can be tested as much as possible by using some of the impact analysis tools.

However one is to understand that 100 % out-of-the box solutions do not exist. No solution is a guarantee and one is to be flexible with implementation and be willing to revisit one’s requirements. Solutions rarely work unless there is buy-in and commitment from the employees who have to implement. If the employees who have to implement refuses to accept the solution, it will not work. Also it is necessary to back up the solution with an implementation plan, complete with milestones to measure performance.