Data Analytics, Data People, and Project Management
The combination of this module’s assigned readings focuses on two important factors affecting the data analytics component of the corporate infrastructure: those individuals (roles) responsible for supporting data analytics efforts and the project management (PM) techniques they utilize (or do not utilize) to complete the required initiatives.
Bartlett (2013) describes the various roles of key organizational leaders and practitioners in the data analytics field including “on-topic business analytics leaders” and “expert leaders” (Bartlett, 2013, p. 85). “The on-topic business analytics leader and expert leaders possess the training and experience to understand what the analytics team provides and how to use it in the business”, and “they ensure quality and speed through review” (Bartlett, 2013, p. 88).
The terms quality and speed are important because they tie directly to the traditional PM methodology and represent two of the three classic primary measures of project success. “(PM success) is usually measured based on the iron triangle (time, budget and scope/quality)” (Sanchez et al., 2017). In this case, time (e.g., days, weeks, etc.) is used as the metric for speed in PM. Hence, the roles of on-topic and expert data analytics leaders includes PM as a framework for managing efforts (including system design, program or department formations, etc.) and assessing progress in accordance with business expectations.
Ahmed & Pathan (2019) stress the importance of PM approaches (e.g., the PM Body of Knowledge (PMBOK), Agile, and PRINCE2, etc.) and their applicability to data analytics initiatives, including the supportive and restraining features. For example, “PMBOK can be tailored to suit the inherent nature of big data projects, but PMBOK insists on defining project scope and description during the planning phase which does not suit the nature of (software based) big data projects” (Ahmed & Pathan, 2019, p. 224). According to Ahmed & Pathan, PRINCE2 is another PM approach that was developed in the United Kingdom (UK) and used heavily in Australia, but it “does not provide a project framework that can resolve the PM challenges faced by big data projects” (Ahmed & Pathan, 2019, p. 226).
The source and evolution of PM is difficult to trace. “Stories about the evolution of PM go back to the building of the pyramids” (Ahmed & Pathan, 2019, p. 220). From Biblical and historical perspectives, Egypt has demonstrated effective PM, in some form(s), throughout its history. Consider how God used Joseph’s experience, knowledge, and efforts to mitigate the effects of the coming famine in Genesis 41 (English Standard Version Bible, 2001). He was appointed to a role of authority and responsibility, and from a business perspective, he became an expert leader and a project manager.
“Now therefore let Pharaoh select a discerning and wise man, and set him over the land of Egypt…so that the land may not perish through the famine” (English Standard Version Bible, 2001, Genesis 41:33, 35). There is little doubt regarding the extent of the authority granted. Pharoah told Joseph “‘I am Pharaoh, and without your consent no one shall lift up hand or foot in all the land of Egypt’” (English Standard Version Bible, 2001, Genesis 41:44).
In Genesis 41:46-49, Joseph proceeded to manage the people, the supply chain, and the food stocks to prepare for the coming famine (English Standard Version Bible, 2001). In the end, “there was famine in all lands, but in all the land of Egypt there was bread” (English Standard Version Bible, 2001, Genesis 41:54). This evidence of PM also included measurement and analysis, at least for the first portion of the effort. “Joseph stored up grain in great abundance, like the sand of the sea, until he ceased to measure it, for it could not be measured” (English Standard Version Bible, 2001, Genesis 41:49).
In my experience, the combination of PM with the more technical aspects of data analytics (e.g., designing data lakes or warehouses, implementing the right software solutions, or constructing the best model) is often overlooked and sometimes simply avoided due to the perceived complexities involved. Selection criteria for the right leaders for these initiatives, including on-topic business analytics leaders and expert leaders, should include proven PM capabilities and experience. Some of the common metrics involved in many PM approaches, specifically adherence to quality, time, and scope expectations, align directly to corporate performance measures and may simplify the discussions and decisions surrounding data analytics efforts.
References
Ahmed, M., & Pathan, A. (2019). Data analytics. CRC Press. https://doi.org/10.1201/9780429446177
Bartlett, R. (2013). A practitioner's guide to business analytics: using data analysis tools to improve your organization’s decision making and strategy. McGraw-Hill.
English Standard Version Bible. (2001). ESV Online. https://esv.literalword.com/
Sanchez, O. P., Terlizzi, M. A., & de Moraes, Moraes, H.R.d.O.C.d. (2017). Cost and time project management success factors for information systems development projects. International Journal of Project Management, 35(8), 1608-1626. https://doi-org.ezproxy.liberty.edu/10.1016/j.ijproman.2017.09.007