Much has been said in the trade press the last couple of years about the challenges and opportunities of Business Analytics. McKinsey & Co. in particular has pressed this point home in suggesting that by 2018 organizations will face a shortage in the US alone of more than 1.5 million managers, analysts and consultants versed in the principles of analytics.[1] If business analytics is simply statistics applied to business, why are business analytic skills so rare? More importantly, what do one need to know about business analytics to be competitive on the market today? Let’s address each of these questions in turn before concluding with thoughts on what the near future may hold.
Business analytics can be viewed as a set of methods for transforming data into action to improve managerial decisions, actions and revenue. In this view, the mindset is akin to management science as a whole – it is a vision of the interactive, methodological exploration of data on market performance.[2] Business analytics is less about statistics than about a unique approach to managing careers, organizations and markets.
On one level, business analytics is nothing new. The roots of business analytics can be found at the turn of the last century in the principles of scientific management.[3] Henry Ford applied these principles in propelling his organization to the forefront of the automobile industry. A similar emphasis of quantitative measures of success can be found at the heart of the enterprise applications involving Materials Requirement Planning in the 1970’s and today in the successive incarnations of Enterprise Resource Planning.
On another level, the obsession with measuring performance as an inherent factor in how value is produced in modern economies is new. Perceptions of customer or stockholder value are no longer tied to the exchange of products and services but to the experiences that individuals have in engaging with companies, organizations and networks. Information Technology has fueled this shift in managerial perceptions in producing an increasingly incalculable amount of data on individual and organizational beliefs, objectives, and actions. Measuring performance has taken a backseat to larger concerns with what performance means and more importantly how and why organizations go about measuring it.
The current fixation with normative measures of success is closely tied to the evolution of modern organizations themselves. In global markets, organizations are increasingly faced with the pressures of hyper-competition and the need for continuous innovation. As a result, networked organizations are demonstrating their competitive advantages by pooling financial, intellectual and physical resources at a lower cost than there more traditional counterparts. Management prescriptions ranging from Six Sigma, lean management, and digital transformation reinforce this trend in focusing on the primacy of the physical, financial and ultimately informational flows across organizations and markets. Digital solutions provide management with structured and unstructured data to explore individual and group behaviors, objectives and actions.
The impact of this evolution of markets and organizations has had far-reaching consequences on management thinking. If decision-making has always been the very essence of leadership, managers are increasingly evaluated on their ability to make sense of the vast amounts of data collected on all dimensions of their business. Making sensible decisions requires understanding the relationship between the data and reality, how the different sources of data can be put together in meaningful wholes, and how the data can be transformed into actionable objectives. Talent in today’s economy is no longer measured in a manager’s ability to describe the problem, but in analyzing how it can best be resolved.
Each of these trends has contributed to importance of data in management today. To begin with, the need for reliable statistics has fueled “Big Data” initiatives around operating performance, customer profiles, and point of sales transactions. Collecting the data isn’t enough, for management must be able to tell stories with the data to help his or her audience focus on what matters. Since customers, managers and stakeholders react differently to the data, understanding the fundamentals of the behavioral sciences is critical in transforming data into actionable initiatives. Most importantly, using the data to change the mindsets about business practices and beliefs is what makes business analytics so valuable.
We are currently developing a number of fundamental business analytics courses for management education to address these points. The course “Working in the Digital Age” explores how the digital revolution has influenced the nature of business today. “Business Analytics” places data science in the context of the different business logics of specific industries and markets. “Managerial Statistics” reviews the what, the how and especially the why of measuring organizational performance. “Data-driven Decision-Making” explores how data can positively influence both decision-making and managerial action. Finally, “Data Visualization” investigates how managers can use data to design effective design stories to encourage stakeholder engagement. The topics will be addressed in turn in our future blog posts.
[1] McKinsey & Company big data report, http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation. The U.S. Bureau of Labor Statistics predicts that business-analyst jobs will increase by 22 percent by 2020,.
[2] TechTarget, Business Analytics, http://searchbusinessanalytics.techtarget.com/definition/business-analytics-BA
[3] Winslow, Frederick (1911), The Principles of Scientific Management, New York, NY, USA and London, UK: Harper & Brothers
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