• Explain the emergence of Big Data and what Big Data is (i.e., structured/ unstructured) from the perspectives of the nine V's (Viewpoint, Volume, Variety, Velocity, Veracity, Validity, Visually, Volatility, and Value) and how each V contributes to business insights.
• Identify and explain how structured/unstructured data, including internet of things (IoT) might improve internal processes, logistics, and supply chain as well as insights into strategic processes and thereby reduce costs for both the organization and customers/clients/patients.
• Analyze and explain how structured/unstructured data might help improve strategic customer insights, and thereby create value for both an organization and its customers/clients.
• Explain how the strategic use of Big Data technology, analytics, and dashboard might lead to innovative and potentially disruptive ideas (including platforms, co-creation etc.).
• Explain the role of social media in sensing and connecting with consumers (including the theoretical underpinnings of sentiment analysis, crowdsourcing, CRM, etc.).
• Explain the usefulness of insights from neuro-science methods (EEG, eye-tracking, fMRI) and the senses (e.g., embodied cognitions), and what type of consumer insights each method provides.
• Explain Deep (Small) Qualitative Data and their usefulnes in idenifying deep semi-subconscious drivers in B2B and B2C settings.
• Explain the socio-psychological underpinnings of managerial mindsets (i.e., mental models and emboied cognition), including why mindsets are so influential as well as difficult to change, and how different managerial mindsets lead to different use of digital technologies, strategic orientations and decisions.
• Explain the theoretical distinction between technology and mindset determinism, and how the two domains might both contribute to and/or obstruct innovative ideas.
• Identify and discuss legal and ethical considerations related to the collection and use of data.
• Analyze and explain organizational theories on organizational challenges to the use of Big Data and different managerial mindsets (e.g., resistance, resources, incentive structure, skillsets, buy-in, motivational issues), and why organizations are located on various paths toward achieving digital maturity, and how to overcome these challenges.
• Present clear and coherent arguments for your selection of key theories and models to address the exam question, and follow academic conventions in your written presentation.

Big Data and AI as well as new managerial mindsets have the potential to revolutionize the art of management and marketing. Yet, in spite of its high operational and strategic impacts, less than a one-third of companies that invest in Big Data and AI technologies benefit financially from it. In fact, studies show that companies that benefit the most have a clear alignment between their strategic mindset and customers' mindsets (related to their expectations of companies). The latter companies have a strategic approach to collecting, processing, sharing, and proactively using data both internally (i.e., logistically) and externally (i.e., value creation) across relevant contact points with stakeholders, including customers. The companies that typically fail are the ones that use Big Data and AI technologies as simple extensions of their existing strategic orientation rather than exploring new available opportunities to engage with the market.Otherwise, they risk ending up being expensive old companies, because managers are stuck in old thought patterns and silo thinking. In addition, we look at how deep qualitative data (Small Data) also might help innovate companies' existing strategic mindsets

Thus, to fully benefit from new digital technologies, managers need both to appreciate what type of data might be useful and what the market prefer in terms of type of engagement. To attain disruptive innovations companies typicaly need to embrace both a disruptive strategic mindset and use new disruptive technologies. We look at how companies best deal with this challenge.  

Aim of the Course

The aim is for students to appreciate how Big and Small Data as well as managerial mindsets can be used to improve/transform both internal procedures (logistics, production etc.) and external market interaction in B2B and B2C settings.

The course prepares students to work conceptually with many types of data (e.g., structured/unstructured, big/small) and to assess the usefulness of such data to address a given managerial task (e.g., logistics, consumer value, unique positioning). It provides the basis for developing insights into how managerial mindsets both enable/prevent managers from identifying potential disruptive opportunities from data. Finally, it sensitizes students to identify organizational and structural challenges that slow down digital transformation/maturity and how to overcome these. The course prepares students for an exciting career in digital and strategic marketing. The course does not require any technical expertise in terms of an IT or data analytics background.    

Course Progression

Big (and Small) Data Commercial Strategies is a foundation course in the study program.

Disclaimer: This course will not embark on the analytical side of (big) data analytics, but rather take a conceptual approach to understanding mindsets, the use of data, and new digital technologies. A more analytical focus will be part of the ‘Business Intelligence and Customer Insight’ course during the second semester.

Indicative literature (more literature will be announced upon enrollment):

Required Book

Rydén, Ringberg, Østergaard-Jacobsen (2017) Disrupt your Mindset to Transform your Business with Big Data.