Parisian Breakfast Workshop

On September 8th, the Business Analytics Institute and the organizational and management consulting firm Silamir hosted a breakfast conference on "Data Science's Dirty Little Secrets" for a select group of twenty senior managers in Paris.

PBWorkshop.png

Last Friday morning Lee Schlenker, Principal of the Business Analytics Institute, led a 60-minute executive “workout” in managerial decision-making with twenty senior executives from a wide range of French industries in Silamir's training facilities in the heart of Paris.

The workshop was designed to help the executives understand the value of data-driven decision making using a variety of actual business examples, simulations, and methods taken from a decision and data science, as well machine learning and big data technologies.  

Five questions were introduced, illustrated, and discussed in a convivial setting:

  • How can an organization improve managerial decision-making? 
  • How can each manager measure a "better" decision? 
  • What is organizational data "worth" today? 
  • To what extent should we trust the "experts"? 
  • What does each manager need to learn about data science? 

The payout for the executives was on several levels:  the ability to evaluate their own data readiness, the opportunity to benchmark their own experiences with those of their colleagues in other industries, and the proposal to develop an action plan for improving managerial decision-making in their own organizations.

For more information on BAI's training offer, please contact Lucile Sorenson at <info@baieurope.com


 In this issue :

studentsparis.jpg What is the who, where, and when of Data Science education?   Ever since the Harvard Business Review declared five years ago that Data Science was the “sexiest job on Earth”, students have flocked by the tens of thousands in pursuit of degrees in the field.  arrowfold.jpg
Bayonne2.png Our 2018 Summer School  is designed to explore the mission critical skills in applying data science to business decision-making in fields ranging from marketing, operations, finance...  arrowfold.jpg
School2.jpg The Business Analytics Institute is a service provider dedicated to helping both managers and management improve their ability to take tough decisions...  arrowfold.jpg
 Student2.PNG On September 8th, the Business Analytics Institute and Silamir hosted a breakfast conference on "Data Science's Dirty Little Secrets" for a select group of twenty senior managers in Paris.   arrowfold.jpg
LinkedIn-Logo.png The LinkedIn Group on Analytics for Management offers a number of free resources for management students and graduates interested in developing their analytical skills.
 arrowfold.jpg

 7wdata2.png

The Business Analytics Institute and 7WData join forces in a strategic media partnership to promote data-driven decision making.   arrowfold.jpg

 

This Newsletter  has been created specifically by the  Business Analytics Institute to foster conversation around the use of analytics in improving business decision-making. You will find our latest contributions on the subject, a desciption of our service offer, and our recommendations of recent articles from the trade press. 

 

Last Friday morning Lee Schlenker, Principal of the Business Analytics Institute, led a 60-minute executive “workout” in managerial decision-making with twenty senior executives from a wide range of French industries.

The workshop was designed to help the executives understand the value of data-driven decision making using a variety of actual business examples and methods taken from decision and data science, as well machine learning and big data technologies.  

Five questions were introduced, illustrated, and discussed in a convivial setting:

  • How can an organization improve managerial decision-making? 
  • How can each manager measure a "better" decision? 
  • What is organizational data "worth" today? 
  • To what extent should we trust the "experts"? 
  • What does each manager need to learn about data science? 

The payout for the executives was on several levels:  the ability to evaluate their own data readiness, the opportunity to benchmark their own experiences with those of their colleagues in other industries, and the proposal to develop an action plan for improving managerial decision-making in their own organizations.