Midwest Manufacturing Accounting Conference Improving Critical Thinking Through Data Analysis* Kurt Reding May 17, 2018 *This presentation is based on the article, “Improving Critical Thinking Through Data Analysis,” published in the June 2017 issue of Strategic Finance. Outline . Critical thinking . Diagnostic data analysis . Merging critical thinking with diagnostic data analysis 2 Critical Thinking . “Bosses Seek ‘Critical Thinking,’ but What Is That?” (emphasis added) “It’s one of those words—like diversity was, like big data is— where everyone talks about it but there are 50 different ways to define it,” says Dan Black, Americas director of recruiting at the accounting firm and consultancy EY. (emphasis added) “Critical thinking may be similar to U.S. Supreme Court Justice Porter Stewart’s famous threshold for obscenity: You know it when you see it,” says Jerry Houser, associate dean and director of career services at Williamette University in Salem, Ore. (emphasis added) http://www.wsj.com/articles/bosses-seek-critical-thinking-but-what-is-that-1413923730 3 Critical Thinking . Critical thinking is not… − Going-through-the-motions thinking. − Quick thinking. 4 Critical Thinking . Proposed definition: Critical thinking is a manner of thinking that employs curiosity, creativity, skepticism, analysis, and logic, where: − Curiosity means wanting to learn, − Creativity means viewing information from multiple perspectives, − Skepticism means maintaining a ‘trust but verify’ mindset; − Analysis means systematically examining and evaluating evidence, and − Logic means reaching well-founded conclusions. 5 Critical Thinking . Although some people are innately more curious, creative, and/or skeptical than others, everyone can exercise these personal attributes to some degree. Likewise, while some people are naturally better analytical and logical thinkers, everyone can improve these skills through practice, education, and training. 6 Critical Thinking . Activities conducive to critical thinking: − Complete a capital budgeting project. − Conduct a due diligence investigation. − Assess business risks and controls. − Evaluate potential IT solutions and select the best option. − Conduct a “how to” training seminar. − Perform a SWOT (strengths, weaknesses, opportunities, and threats) analysis. − Prepare a new business venture proposal. − Apply statistical sampling and draw a conclusion. − Create a software macro. − Write a thought-provoking journal article. 7 Critical Thinking . Critical thinking self-assessment questions: − How often do I ask insightful “why” questions? − How frequently do I generate compelling new ideas? − How inclined am I to challenge the validity of new information? − How vigorously do I tackle unfamiliar, complex problems? − How adept am I at making decisions under uncertainty? 8 Critical Thinking . Exercising your critical thinking skills should make your head hurt. The adage, no strain—no pain—no gain, pertains to your brain. 9 Diagnostic Data Analysis . Diagnostic data analysis is a manner of analysis that involves – . Examining data; . Identifying anomalies if they exist; . Investigating the root causes of anomalies detected; and . Formulating a remedial action plan. 10 Diagnostic Data Analysis . Anomalies are data abnormalities that signal potential problems, such as . Inefficient operations, . Noncompliance with applicable laws, or . Fraud. 11 Diagnostic Data Analysis . Analysis of aggregated data – − Example: Financial statement analysis. − Illustrative procedures: • Vertical analysis (i.e., common-size financial statements). • Horizontal analysis (i.e., trend analysis). • Ratio analysis. • Benchmarking. 12 Diagnostic Data Analysis . Analysis of disaggregated data – − Example: Transaction analysis. − Illustrative procedures: • Validity tests – are all recorded transactions valid? • Completeness tests – are all valid transactions recorded? • Limit tests – are recorded transaction amounts ≤ a prescribed upper limit or ≥ a prescribed lower limit? • Cutoff tests – are transactions recorded in the proper period? • Cycle time tests – are transactions processed efficiently? 13 Diagnostic Data Analysis Gross Margin Percentage Days’ Sales in Accounts Receivable 60 44 55 42 50 40 45 38 40 36 35 34 30 32 25 30 20 Total Store 1 Store 2 Store 3 Store 4 Store 5 Total Store 1 Store 2 Store 3 Store 4 Store 5 2015 2016 2015 2016 . What do these aggregated data analysis results indicate? . What disaggregated data analysis might these results trigger? 14 Merging Critical Thinking with Data Analysis While analyzing data strengthens critical Critical thinking, critical thinking in turn helps data Thinking Data analysis. Analysis . Jeff Thomson [president and CEO of IMA®] explains, “Data analysis and critical thinking skills are interdependent. Data analysis requires you to think critically by probing, connecting disparate facts, synthesizing, etc. Likewise, critical thinking is enabled by the ability to think analytically and apply tools to help extract insights and actionable information from data.” (emphasis added) . …Melisa Frazier, a retired vice president for audit and controls for Comfort Systems USA,…said, “Critical thinking is key through each step in the data analysis process. If you don’t do a good job on each step, your result will be flawed or useless.” (emphasis added) 15 Merging Critical Thinking with Data Analysis . Diagnostic data analysis involves a basic process that requires critical thinking: − Identify data analysis opportunities, − Specify the objectives of the analysis, − Develop expectations and define anomalies, − Analyze the data and investigate anomalies, − Evaluate the results, and − Formulate a remedial action plan. Analyzing data through this process requires… curiosity, creativity, skepticism, analysis, and logic. http://sfmagazine.com/post-entry/june-2017-improving- critical-thinking-through-data-analysis/ 16 Merging Critical Thinking with Data Analysis . Identifying data analysis opportunities: Elements of critical thinking: Examples from the case study: . Curiosity – watching for . Emersyn’s curiosity (i.e., her potential data analysis eagerness to learn) prompted her to applications. analyze ACJ Company’s financial . Creativity – considering statements. potential applications from . Her creativity motivated her to different perspectives. analyze ACJ’s financial position and . Skepticism – sensing when performance not only from a company- things just don’t seem quite wide perspective but also from a store- right. by-store perspective. Her Skepticism regarding the abnormalities she uncovered in the aggregated account balance data prompted her to extend her analysis by drilling down into the underlying, disaggregated transaction data. 17 Merging Critical Thinking with Data Analysis . Specifying the objectives of the analysis: Elements of critical thinking: Examples from the case study: . Skepticism – instinctively . Emersyn’s skepticism kicked in focusing attention on unusual when her financial statement circumstances and events analysis uncovered unanticipated observed. abnormalities in specific account . Creativity – Contemplating why balances. observed abnormalities may . Not willing to accept what she had have occurred from multiple discovered at face value and perspectives and setting out to needing to be convinced that her investigate the reasons. concerns were warranted, Emersyn creatively refocused the objective of her data analysis to assessing the integrity of the underlying transactions. 18 Merging Critical Thinking with Data Analysis . Developing expectations and defining anomalies: Elements of critical thinking: Examples from the case study: . Analysis – carefully studying . Emersyn’s store-by-store analysis the environmental factors that revealed anomalies in the aggregated could affect the data. account balance data of one store. Logic – formulating rational . She determined that she needed to expectations regarding data investigate the detected anomalies by analysis outcomes; identifying analyzing the disaggregated plausible indicators of problems transaction data underlying the that may be observed during the account balances. analysis. Based on her financial statement analysis findings, Emersyn logically expected her follow-up transaction analysis to uncover anomalies. 19 Merging Critical Thinking with Data Analysis . Analyzing the data and defining anomalies: Elements of critical thinking: Examples from the case study: . Analysis – systematically . Emersyn analyzed aggregated gathering and examining account balance data using an array of relevant evidence using interrelated data analysis procedures. appropriate procedures. Skeptical about certain evidence she . Skepticism – critically gathered and examined, i.e., the assessing all evidence anomalies pertaining to Store 4’s sales collected, whether it and accounts receivable, she corroborates or contradicts appropriately ascertained that follow- predetermined expectations; up analysis was warranted. continuously questioning and . Accordingly, she analyzed the validity rigorously investigating new of sales transactions included in the evidence, including anomalies account balances. uncovered. 20 Merging Critical Thinking with Data Analysis . Evaluating the results: Elements of critical thinking: Examples from the case study: . Logic – reaching well-founded . Emersyn appropriately determined conclusions by properly that her financial statement analysis interpreting persuasive (i.e., had not yielded sufficient, relevant relevant,