Strategic Use of Big & Small Data at MBA

Data (big and small) has the potential to revolutionize the art of management.

Data (big and small) has the potential to revolutionize the art of management. Big data is typically associated with behavioral (correlational) data, whereas small data is associated with causality and meaning-based insights into the deep emotive motivators that underpin consumer behavior. Although there is still a paucity of empirical research to assess the business value of both big and small data, the studies that exist show that companies that do best are those that use data as a key strategic tool. These companies embed data centrally in their strategic decision-making. They collect, process, share and proactively use data to improve both internal processes (e.g. production, logistics) and external interactions with key stakeholder (e.g. supply chain, stakeholders, and customers). Often there is a focus on the internal data even though external data gives the highest value in terms of loyalty and life-time value.

In contrast, the companies that are likely to fail first and fast are the ones that overlook the usefulness of data all together and/or keep them in silos across the organization.  Especially SMEs are under-users of new methods and technologies that generate new insight based on big and small data. Big (structured and unstructured) and small data (qualitative) make it possible to improve both Market Effectiveness by meaningful customer experiences leading and Internal Efficiency by optimizing logistics, the value-chain, and internal organizational processes.

It follows, that the ability to rethink (exploit) current strategic orientations and explore new opportunities (internally as well as externally) requires both technological savviness and socio-cognitive insights are based on data stemming from fa range of sources, such as social media, sensors, Apps, neuromarketing, embodied cognition, mindset tests, and deep, subconscious investigations of consumer needs. Such data often challenges organizational routines and current market approaches, and are ignored by existing strategic and managerial mindsets. A major hurdle in the use of big and small data to create innovative solutions is not so much the access and use of new technology to innovate their businesses as it is managers’ lack of cognitive agility, introspection, and ability to embrace new and innovative perspectives. With only new technology at hand and not the right mindset companies risk becoming expensive old companies (i.e., lots of data and new technologies but insufficient managerial capital).  Thus, to utilize big and small data optimally, managers need to open their mindsets to explore and exploit insights based on existing and new types of big and small data.

We cover four managerial mindsets, each of which affects the way in which managers interact with the market. An online test is taken by each participant from which he/she gains insights into his/her personal managerial mindset, enabling each participant to modify his/her mindset and explore new and potentially disruptive initiatives within the current business/industry.  We also provide a toolbox that provides a hands-on, step-by-step approach to identify and implement new initiatives in the organization based on insights from big and/or small data.

This course addresses, among other, following issues:

  • How to interpret data and communicate findings internally as well externally such that it creates value for both the organization and end-users.
  • How to optimize market effectiveness by relevant and targeted interactions based on customer insights.
  • How to improve logistics and market interaction through data (big and small), hereunder develop new strategic interactions with the market.
  • How to proactive collect and work with big (structured and unstructured) and small (qualitative) data, including performance management and strategic positioning.
  • How the brain works, including the significant biases from embodied cognition (the senses) as well as internalized mental models (i.e., mindsets).
  • How platforms, crowd sourcing, and co-creation might work for your organization.
  • How to deal with organizational resistance, change management, and support for introducing knowledge sharing based on data across siloes within the organization.
  • How best to deal with moral, ethical, and especially legal issues in relation to data collection and use.
MODULE TYPE Elective module
COORDINATOR Professor Torsten Ringberg, Department of Marketing, Copenhagen Business School.
Per Østergaard Jacobsen, External Lecturer, Department of Marketing, Copenhagen Business School
SCHEDULE May 14, 15 and 16, 2020
All days 9 am to 6 pm
LOCATION Copenhagen Business School
EXAM Individual written exam assignment. Max 10 pages (+appendices)
Hand-in of exam assignment: June 25, 2020 at 12 noon
PRICE 10.000 DKK + expenses for materials


Sidst opdateret: Master of Public Governance // 27/09/2019