Competitive advantage from smart usage of data
After the industrial and digital revolution, some suggest we are now facing an artificial intelligence revolution that will have far-reaching effects on firms and society.
The immense promise of big data to reveal new opportunities (smart products) and deliver practical business results (better management decisions) has so far been focused on the technologies and models used to transform big data into value. There has been less attention for the managerial challenges of staffing roles and processes to take advantage of big data’s promise. The technology may be abundant, but developing, recruiting and hiring the people to use it is becoming an acute challenge for Fortune 1000 companies. Defining the roles, recruiting talented practitioners, setting up center of competence structures, establishing data governance across business units, and tying advanced data and analytics to the results of those businesses is lagging the deployment of tools and the collection of the data.
The McKinsey report on Big Data suggests the U.S. alone faces a shortage of roughly ten analytically-competent managers for each deep analyst. To make your company successful in the artificial intelligence area, you have to start by gathering a critical mass of these managers. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers.
Are you ready as a business leader to steer your organization in an everchanging world? This course teaches you the concepts you need to change your company into a data-driven company and gives you the first encounter with tools your staff-member will use. This course will give you a good understanding of the challenges and opportunities that arise in this new world. Central in this course is a project that helps you define a prototype of an intelligent product that would create strategic value to your company.
- Makridakis, S. (2017). The Forthcoming Artificial Intelligence (AI) Revolution: Its Impact on Society and Firms. Futures.
- Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity.
- Brown B & Henstorf B. (2014). Making the most out of scarce data-mining talent. Harvard business review, retrieved from https://hbr.org/2014/01/make-the-most-of-scarce-data-mining-talent
Complex Problem Solving
25 - 29 Sep 2017
At the end of this program you will:
- Be able to understand the decision context you are in, select and apply the right decision tool
- Understand what big data, data science and artificial intelligence is and what it can do for your company
- Understand how to perform a simple data science project
- Build visualizations that help to explore data but also to explain findings to help you impact decisions.
|Morning||Decision making context||Data visualization||Introduction to Machine Learning||Introduction to Big Data Tools||Making better decisions when little data is available|
|Lunch||Lunch @ MSM||Lunch @ MSM||Lunch @ MSM||Lunch @ MSM||Lunch @ MSM|
* Introduction to Big Data and the data driven process
|Data visualization||Introduction to Machine Learning||Project||Project|
- An introduction to applied decision sciences
- Data driven decision making with the help of big data and artificial intelligence
- Data visualization with Tableau
- How to marry expert knowledge with facts and data to make better decisions
- How data can be used inside your company
- A first encounter with big data machine learning on AzureML (Microsoft).
- Case studies
- Online excercises
- Business leaders that want to know what opportunities and threats artificial intelligence possesses for their industry
- Managers who want to change their company into a data-driven company
- Team leaders of a data-intensive team that want to gain subject matter-knowledge
- Product managers who develop intelligent services or products
The ideal student has a background in business and a deep interest in learning to make better data driven decisions. He/she should have a first exposure to descriptive statistics.
Davy Cielen, MSc, is Senior Lecturer in Business Data Analytics at Maastricht School of Management. He holds a BSc in Commercial Engineering from Solvay Management School, Vrije Universiteit Brussel (2011) and an MSc in Applied Economics from Vrije Universiteit Brussels (2016). Davy is pursuing a PhD at IESEG School of Management (Lille, France) in Big Data Analytics for Business since 2015.
"Because of Artificial Intelligence, you can be that creative person you always wanted to be. You now have systems that don’t require you to become a mathematician".
Davy Cielen, lead trainer of the course
The full tuition fee
The tuition fee of this course is € 2,499.
Tuition fee includes all course materials and study materials. Tuition fee does not include housing, food and living expenses. Participants are required to arrange their own housing facilities. MSM can assist in finding hotel accommodation.
15% for 2 participants coming from the same organization within 1 academic year
25% for 3 particpants coming from the same organizatin within 1 academic year
40% for 4 - 6 participants coming from the same organization within 1 academic year
For > 6 participants we will offer a tailor made program
European Star Scholarship:
50% for European citizens and long term residents. Submit a 2 - 3 page essay on the topic: "What will be the positive change for my organization and me after participating in this course?"
Alumni Lifelong Learning:
15% discount for Maastricht School of Management registered Alumni
Dean's Development Fund:
Select your country below to see the actual price of the program (full tuition fee-/-DDF scholarship)
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The application fee is € 20.
MSM reserves the right to postpone or cancel the program in case the number of participants does not meet the MSM requirements for minimum number of participants. Any payment made to MSM for tuition fee will be refunded. In the case of postponement or cancellation of the program MSM will inform the enrolled candidates at least six weeks before the planned start of the program.
By the participant:
If an admitted participant decides against participation, she/he or, if applicable, the sponsor is liable for the following cancellation costs:
• 25% of the tuition fee if cancellation is between eight to seven weeks before the start of the program.
• 50% of the tuition fee if cancellation is between six to four weeks before the start of the program.
• 75% of the tuition fee if cancellation is within four weeks of the start of the program.
• In case cancellation is done after the program has started no money will be refunded.
• No cancellation charges are incurred if the enrolled candidate or the client, with written consent of MSM, will be replaced by another candidate before the start of the course. Refunded tuition fees will only be reimbursed to the sponsoring party and cannot be forwarded or redeemed by any other party.
Candidates who were not granted a visa to enter The Netherlands, can be fully reimbursed if written official documentation is provided of such visa denial.
28 August 2017
Applicants should have the ability to function academically and professionally at Bachelor level and should have an adequate level of spoken and written English.
Reasons to follow the Turn Big Data into Competitive Advantage program
- Your project is directly actionable inside your company
- The course handles the concepts of what drives the automation of knowledge workers
- Easy-to-use tools make the field acessible for non-engineers
- One of the most sought skills in the labor market
- Understand technology that changes industries.