The participating companies of the Career Experience 2017 were:
- MSG Global
- Willis Towers Watson
The case description of MSG Global:
Students are divided in teams of 4-5. Each group will create their own “broodfonds” (Bread fund).
The Bread fund consists of 50 fictive people: 15 people <35 years, 15 people 35-45 years, 10 people 45-55 years and 10 people 55-67 years. The teams have to come up with rules/premiums/benefits per population group to create a working Bread fund. The teams will receive an excel file on which the teams can find mortality rates and disability rates per population group to help them in coming up premium rates. After creation of the Bread fund, the game will be simulated 10 years and 20 years in the future to discover if the teams have created an effective Bread fund. Every team will receive a card, which tells the team how many fictive people have left the Bread fund and how many people received benefits during these 2 time-periods. Lastly, every team will need to create a short presentation in which they will display what rules they used to set up their Bread fund and how effective their Bread fund worked.
The case description of Capgemini:
This case is about Blueberry Fashion Inc., which is a large clothing company headquartered in Utrecht, NL and has 800.000 employees worldwide. They serve more than 150.000 stores in countries all over the world with over 160 million customers creating 10 billion dollars in revenue.
10 years ago Blueberry Fashion Inc. invested 80.000 euros in each country to set up their own website in order to serve customers through online channels. But now in 2017, Coco Blueberry CEO of Blueberry Fashion Inc. (and great granddaughter of Peter Blueberry) feels that they are losing customers to new online competitors and startups. Coco Blueberry has the ambition for Blueberry Fashion Inc. to become world leader in online fashion within the next three years. She hired Capgemini to help her tackle the challenges. In order to understand the problem, Capgemini will conduct several interviews with employees of Blueberry Fashion Inc. At the end of the process they will present their project approach to Coco and the board.
The case desciption of Accenture:
In this case you will encounter a market sizing issue. The case consists of two parts, where we will try to challenge you to use your analytical and numeric skills to solve this challenging capacity issue.
The case description of MIcompany:
Everybody is talking about Big Data! It is the number 1 board topic in many blue chip companies. But how do you get beyond big words? How do you really create impact with data? How do you transform a company to a data driven organization? With more than 10 years of experience in this field, MIcompany is the number 1 agency in creating sustainable impact with Data Analytics. And this is your chance to experience what we really do. In our Data Analytics case you will perform a MIcompany project from start to finish – extremely rapidly! Will you discover your own analytical X-factor that we are looking for?
The case description of Willis Towers Watson:
Tijdens deze case kruip je in de huid van een consultant en krijg je een indruk van wat een consultant bij Willis Towers Watson zoal voor werkzaamheden doet. De case is vooral gericht op Retirement, Investment, Risk and Reinsurance. We zullen een beroep doen op je analytisch vermogen en creativiteit, maar bovenal op je overtuigingskracht ten opzichte van de opdrachtgever. De voertaal tijdens de workshop is Nederlands. Indien je geïnteresseerd bent in Willis Towers Watson adviseren wij je om deze uitdaging aan te gaan!
The case description of Districon:
Case: Supermarkets receive their goods from a single, central distribution center. Trucks drive routes, visiting multiple supermarkets on their way. When constructing these routes, several constraints should be considered, such as the maximum capacity of a truck and a maximum route length.
Your task: You are the route planner. A basic schedule is already generated, but it does not fulfill all the wishes and constraints of the supermarkets and truck drivers. You will extend the AIMMS model to optimize the schedule, adding new constraints, and create a user interface with your results. The team which presents his solution best wins a prize!