In concluding one of the project management classes, where I had to assess the understanding of the process stability using control charts with some design of experiments requiring data collection and data analysis, it became quickly apparent to me that amidst the many types of classifying and categorizing data, the fundamental characteristics of data itself is not adequately understood. While people look at objective and subjective data of details collected from the documentation, surveys, interviews, and observations, there is not a strong understanding of the classification of data as continuous or discrete, categorical or numerical, nominal or ordinal, interval or ratio, etc. On top of it, the datatype as mentioned in programming and database systems, such as the integer, float, double, boolean, string, varchar, identity, and datetime have added enough murkiness for many middle management roles to delegate their responsibility of understanding the data to subordinates, such as the data analyst, business analyst, etc.

Image Credit: Created by Sriram Rajagopalan as a brief overview

As I pondered over this dilemma, I found out that even professionals were unable to differentiate the three critical things any descriptive data analysis. The measures of central tendency, symmetry, and dispersion were not readily coming up in one of my talks touching on the house of quality. If the business is collecting so much data, how can the lack of understanding of the classification, categorization, and type of data be taken for granted? If the information contained in data is meant to be serving the management to make decisions, then, how can the lack of basic data analytics be an optional criterion in the job descriptions for roles managing products, projects, programs, and accounts? 

Image Credit: Created by Sriram Rajagopalan as a brief overview

According to Standish Report (Hastie & Wojewoda, 2015), the number of failed projects is decreasing, but the number of projects challenged from inception to closure has increased while the number of successful projects has remained flat. The same story is entirely different if we take the size of the project into account where a higher proportion of large size projects embrace failure. With so many tools available for middle management, such as earned value metrics, failure mode effect analysis, and Six Sigma, why is the attention to detail missing? While such a detailed review is beyond the scope of this particular blog article, brief research on data and business intelligence (n.d.) from QGate provides a compelling summary of data may be speaking but we may not be understanding.

We don’t stop at addressing this complexity with more mandatory education and training on understanding data and using data analytics for business solutions. Instead, we compound it further by introducing big data with its own value, volume, velocity, veracity, and variety. Press (2014) notes twelve different definitions for big data that one can choose from which doesn’t address the fundamental requirements of how to systematically identify the right data to look at, analyze it, and make proper decisions using hypothesis testing, regression analysis, etc. 

There is a world outside with data analytics focusing further on multivariate analysis, ANOVA studies, factor analysis, and selecting various distributions to choose from based on how the samples represent the population. While such advanced requirements may be referred to data analyst professionals, can we not mandate a good understanding of data (classification, categorization, and type) and fundamental data analysis (central tendency, dispersion, and symmetry)?

After all, if we all agree data is King to business, data analysis is the Queen of business operations. Both the King and Queen are critical to making the right decisions, sustaining the proper business operations, and maximizing the right business opportunity. With the explosive growth of data due to the advances in technology, as noted by Ginni Rometty (2016), CEO of IBM in her speech to World Health Congress, digital [data] is becoming the foundation and data analytics is the basis for subsequent cognitive understanding.


Tell me your thoughts in the comments and let’s open a dialog. I would be excited to hear other opinions on this topic.

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Sriram Rajagopalan

Sriram Rajagopalan

Contributing Author

Dr. Sriram Rajagopalan has more than 20 years of professional experience with exposure to multiple industries. He currently works as the Vice President of Training and Organizational Excellence at Aptus Health. Previously, he worked in the same capacity establishing the Proposition Delivery and Program Management Office. He also established a Project Office in West Notifications Group. He has delivered numerous projects for clients such as eFunds, Northwest Airlines, CVS Pharmacy, Prime Therapeutics, US Airways, Blue Cross Blue Shield, and several pharmaceutical firms, such as GSK, Novartis, AstraZeneca, Astellas, Depomed, and Boehringer-Ingelheim.

Sriram received the international prestigious Eric Jenett award on the Best of the Best Project Management Excellence award in Oct 2017 and was also a finalist for the Kerzner award for process excellence in 2012. He frequently blogs at, has published peer-reviewed scholarly international journals, articles at Scrum Alliance and PM Network on topics related to project management, agile transformation, and about the TONES© and PARAG© framework to middle management transformation through self-initiated postdoctoral work. He is also an active speaker speaking about these topics in professional conferences.

Sriram also holds several professional certifications (PgMP, PMP, PMI-CP, PMI-RMP, PMI-SP, CSM, CSPO, CSD, CSP, IT Project+, ACC, SCM, SCPO, SCD, SAMC, SCT, CSOXP and Six Sigma Green Belt). With extensive experience in strategic project and program delivery, he promotes the scholar practitioner approach teaching as Assistant Teaching Professor at Northeastern University and University of Riverside. He is also an active volunteer at PMI Mass Bay having served in the capacities of Director of Speaker’s Bureau, Vice President of Marketing and Communication, and as a past-board member. He also volunteers at Agile Alliance conferences and is a mentor at NAAAP.

Sriram also engages actively in training project management and agile concepts including certification preparation through his own business, Agile Training Champions ( and also in spreading project management as a discipline to younger children in schools and colleges through his initiative on Projecting Leaders of Tomorrow (PLOT) initiative (

He graduated with a Bachelor’s degree in Electronics and Communication Engineering from the University of Madras, India, Master’s degree in Computer Engineering from Wayne State University, Michigan, MBA degree in Management from Concordia University, Wisconsin, and a doctorate degree in Organization and Management from Capella University, Minnesota.


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