Is leadership just an illusion in an economy in which everyone is talking rather than listening?



With a regularity surpassing that of the annual migration of Artic terns, I ask my management students to explore and explain how birds flock together. After discussing whether birds have leaders and followers, we explore various hypotheses of where they learned to fly south. We then compare such bird flocks to markets, corporations, and territories with similar questions about leadership, followship and organizational learning.  In an “attention economy”[i], not to mention in a classroom, in which everyone is talking and no one seems to be listening it is bemusing to believe that any one “bird” has the vision, information, and charisma to lead the flock.

 Our perceptions of market and organizational dynamics reflect two basic models of how we use data in decision-making that I’ve referred to as the “Ladder of Initiatives.[ii] In the first model we accept that our leaders have exceptional vision. They understand where the market is going, and intuitively what the organization can produce in the months ahead. They announce the intended results and count on management to define the actions that will produce decisions about what types of knowledge are pertinent to solve the problems at hand. This knowledge then will define in which contexts organization needs to work to collect the data to design, produce and sell.

An alternative vision suggests that no one leader has the answers or the insight to seize future market opportunities. Rather than working top-down, this vision suggests that the organization should begin by collecting and aggregating the market data available to elucidate the contexts in which the organization operates. This context conditions both what knowledge needs to be acquired and how to transform knowledge into action. Organizational results are not the product of outstanding leadership, but of collective decision making based on constant scanning of the data.


The ladder of initiatives describes two models of decision-making that reflect contrasting beliefs about leadership, vision, and the pertinence of data. The first focuses on the importance of the individual, best practices, and the need for process optimization. The second privileges collective decision making, the importance of network dynamics, and the need to learn to explore the context in which we work. They reflect deterministic and stochastic decision environments associated with structured and non-structured learning. These visions models underpin how we teach decision science and how we practice management.

The practice of business analytics is heart and soul of the Business Analytics Institute. In our Summer School in Bayonne, as well as in our Master Classes in Europe, we put analytics to work for you and for your organization. The Institute focuses on five applications of data science for managers: working in the digital age, managerial decision making, machine learning, community management, and visual communications. Data-driven decision making can make a difference in your future work and career.


Lee Schlenker
March 24th, 2017

[i] Chatfield, T.. (2013). Does each click of attention cost a bit of ourselves? [online] Available at: [Accessed 21 Mar. 2017]..

[ii] Schlenker, L. and Matcham, A. (2005). The effective organization. 1st ed. Chichester: J. Wiley.

If business analytics is simply statistics applied to business, why are business analytics skills so rare?

BABlogPic.jpgMuch 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, The U.S. Bureau of Labor Statistics predicts that business-analyst jobs will increase by 22 percent by 2020,.

[2] TechTarget, Business Analytics,

[3] Winslow, Frederick (1911), The Principles of Scientific Management, New York, NY, USA and London, UK: Harper & Brothers

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