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Rotterdam School of Management

Leadership Challenges With Big Data and Analytics

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Description

Artificial Intelligence will without any doubt change the way we will do business in future. As a matter of fact, it is already changing many businesses that we are involved in today. But what is needed to make Artificial Intelligence a valuable part of the way we do business ourselves? Many experts believe that successful Artificial Intelligence applications hinge on the so-called b-smact technologies (Blockchain, Social media, Mobile use, Analytics, Cloud and Things-on-the-internet or better known as IoT). The fuelling component of those technologies is Big Data.

Start your transformation towards data-driven

This insight will require a whole new set of business skills. Understanding and working with new technologies for big data collection, analysis and prediction will not create only huge opportunities for business, but also ethical, legal, privacy and technical issues concerning every part of the organisation. It will influence customer relationships, redefines how firms develop new products and services, changes how operations are organised and managed, improves demand and supply networks, and provides the basis for new business models. It will demand a data driven focus of everyone involved.

Organisations transforming towards becoming data-driven are guided and supported by the eight-day ‘Leadership Challenges with Big Data and Analytics’ programme at RSM Executive Education. It connects professionals in technical- and methodology-oriented data science with professionals engaged in business analytics, links them to best business practices, and actively involves senior executives. This programme has been developed and organised by the Erasmus Centre for Data Analytics with a wide range of partners from the industry.

Learning objectives

After participating in this programme, you will be able to:

provide professionals engaged in data science and business with academically sound and new ways to apply big data technologies in order to design and implement innovative and successful business applications

improve the business skills of technically focused data scientists by exploring business thinking, business-case creation, and problem solving from a business angle

improve the technical skills of business focused executives as they acquire new knowledge and understanding of data science methodologies and techniques

increase collaboration between data scientists and business executives by increasing mutual understanding

provide a cross-industry learning platform for professionals to learn from experiences in other relevant industries

broaden data scientists’ and business executives’ understanding of privacy and security as to provide solid data-driven and GDPR compliant business applications.

engage participants with senior executives and supervisors to facilitate implementation of business applications.

The programme uses a holistic approach by participation in multi-disciplinary and multi-hierarchical teams from various industries and a learning-by-doing approach from peers and via coaching by top academics and business experts.

Curriculum

The course is divided into four blocks to allow the application of the concepts learned.

BLOCK 1: INTRODUCTION AND PREPARATION SESSION

Two days of preparation sessions, during which each participating company is expected to bring at least one case study to which the teams can apply the concepts they have learned. During this part of the programme, you will focus on the strategic importance of data-driven organisations, terminology, leadership challenges and readiness of companies, including their enterprise architecture and digitised platform. It includes case studies from other companies and short presentations from participating companies.

BLOCK 2: CORE PROGRAMME PART 1

Two days including one evening session during which you explore the basic technology challenges of a data-driven company; technologies for analysis, prediction and visualisation. The evening session will focus on exchanging information and insights between the participants including a get to know each other social event with an academic touch.

BLOCK 3: CORE PROGRAMME PART 2

Two days including one evening session during which you explore the basic management challenges of data-driven company; business cases, legal and privacy issues, change management and implementation. The evening session will focus on the company use case, consulting with both academic- and business coaches.

BLOCK 4: FINAL SESSION

Two days for fine tuning the gained knowledge and turn it into applicable wisdom. Discuss challenges you have experienced in transforming your business and the implementation of your proposals. In the afternoon of the second day each team’s case study results will be presented to an expert panel and discussed in the class.

Who should attend

This programme is suited for company teams from data-intense industries with one or more data scientists and one or more business analysts working with business models and applications, as well as senior executives and supervisors. Professionals in non-profit organisations and governments, particularly those who work on smart city concepts, may also benefit.

Experts

Dr Jason Roos is an associate professor of marketing at RSM. His research considers how consumers and firms learn and adapt in information-rich environments such as Internet news and online advertising. His work has been published in top academic journals including Marketing Science and Managemen...
Prof. Gui Liberali is Professor of Digital Marketing at the RSM. Gui has successfully developed and applied methods for designing and customizing digital products and interactions, and adaptive online experimentation methods to online display advertising and website design, in research collaborat...
Prof. Peter Vervest is professor of information management and networks at RSM who says big data is automated decision-making combining big amounts of distributed, often poorly aligned and non-authenticated data from many sources. He sees the Internet of Things as presenting a set of technologica...
Iuliana Sandu holds a Senior Lecturer position in the department of Accounting & Control at Rotterdam School of Management. She earned her master’s degree in Economics and Finance of Aging at Tilburg University, her master’s degree in Accounting, Audit and Management Information Systems and h...
Dion Bongaerts is an Associate Professor of Finance at RSM Erasmus university. He specializes in the behavior of credit rating agencies, the pricing of credit risky instruments, and the origins and effects of market illiquidity. His work has been presented at major conferences around the world, i...
Jan van Dalen is Associate Professor of Statistics at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University. He has a background in econometrics and obtained his PhD in quantitative modeling of wholesaling. His main research interests are in qu...
Eric van Heck is Professor of Information Management and Markets and Chairman of the Department of Technology & Operations Management, Rotterdam School of Management, Erasmus University (RSM). His research concentrates on the role and impact of business architectures and digital platforms to...
Ting Li is the Endowed Professor of Digital Business and the Academic Director of MSc Business Information Management at Rotterdam School of Management (RSM), Erasmus University. She is the founding member of the Erasmus Centre for Data Science and Business Analytics. Ting Li is an expert in Digi...
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