Finding managerial insights through analytics

Large amounts of interconnected data, vast computational and communicational powers and speed, and the availability of advancing analytics techniques are having a profound impact on how businesses organize, compete, and ultimately deliver value.   In order to manage effectively in this dynamic environment, you need to develop the skills to make data-driven decisions, and leverage analytic frameworks as you consider how to address business situations or opportunities. Data-Driven Decision-Making will introduce you to new tools and new approaches to leverage data. You'll also review best practices to incorporate into your own analytics work, and how to use evidence-based decisions to influence your organization. You’ll gain experience with:

 

  • Machine Learning and Data Analytics
  • Decision Modeling and Computation
  • Information Management in Interconnected Markets

This program will review both core and state-of-the-art analytics methodologies and evidence-based approaches to address managerial decision-making challenges.

Get Started Today

Sasa Pekec on the broad application and up-to-date learning in Data-Driven Decision Making

Who Should Attend?

The focus of this course is about creating frameworks that enable creativity, innovative thinking, and evidence-based decision-making. Managers who want to improve their effectiveness and profitability within their organizations, and who aspire to make evidence-based managerial decisions, regardless of their quantitative experience, will benefit from this program, including:

  • General managers looking to enhance their skillset with state-of-the-art analytics skills
  • Executives interested in incorporating an evidence-based approach to managerial decision-making processes in their organizations
  • Strategy/business development executives
  • Senior managers throughout an organization making decisions that impact the overall strategy of their function

Note: This program is designed to meet the needs of managers rather than analysts looking to expand their technical skills. The program will discuss a variety of analytic methodologies, going into depth about the techniques and methodologies, but only to the level that non-technical managers need to understand; when to request specific analyses; and key questions to ask to ensure sound analyses that will lead to evidence-based decisions.

More about this program

Increase Effectiveness with Data-Driven Decisions

As the amount of data available to your organization continues to grow exponentially, and as the computational capabilities advance, you will be required to find ways to employ these valuable resources to improve the performance of your group or organization, and to ensure your managerial skills are up-to-date.

This program will introduce you to quantitative decision-making frameworks, and to analytic tools and approaches, as well as illustrate best practices across businesses and industries. You’ll be empowered to incorporate data-driven decision making in your professional role and across your team or organization.

 

Topics

Selected topics covered during the intensive three-day program include:

Machine Learning and Data Analytics

  • Data-Centric Approach to Business
  • Predictive Modeling for Decision Making
  • Causal Modeling and Measuring Impact
  • Artificial Intelligence and Deployment of Solutions in Business

Decision Modeling and Computation

  • Dynamic Decision Making under Uncertainty
  • Algorithmic Decision Making
  • Risk Analysis and Mitigation
  • Contract Design and Negotiation Analysis

Information Management in Interconnected Markets

  • Information Aggregation
  • Decision-Making Strategies for Large Markets
  • Decentralized Information Processing and Decision-making
  • Emerging Data/Information Privacy and Security Issues

 

Program Objectives

At the conclusion of this program, you will be able to:

- Know the basics of analytics literacy for modern managers

  • Understand the principles of core and state-of-the-art analytics models, when to use each, and how to best communicate their impact on  your recommendations and decisions
  • Structure complex business  problems in order to leverage analytics when  reaching a sound decision
  • Develop innovative frameworks for leveraging data and information to maximize the impact of analytics techniques on the quality of your decision-making and ultimately on your business

- Become current with the way analytics are used in business, whether by one of the most valuable companies in the world (e.g., Apple, Amazon, Facebook, Google, Microsoft), where analytics is at the core of their business model, or by one of many  startups

Most importantly, you will have the ability to observe your team’s work or your business’s performance from a data-centric viewpoint.  You will be equipped to assess where there are opportunities in your processes, strategies, incentive systems, and marketplace tactics to improve efficiencies, redirect resources, or compete more effectively, and make the decisions to implement strategies designed to address those opportunities.

 

Get set for three days of fast-paced, stimulating, and challenging exercises, group discussions, lectures, and case studies. You’ll gain substantial insights into how to leverage data analytics in your everyday role in your organization. You'll also enhance your ability as a manager to use data to navigate uncertainty, which will be extremely valuable to your organization and its stakeholders.

Sample Schedule

/ /

Arrival

Check-in available
3:00 PM

Data-Centric Approach to Business
3:30 PM - 4:30 PM

Predictive Modeling for Decision-making
4:30 PM - 5:30 PM

Welcome Dinner
6:00 PM - 8:00 PM

Day 1

Breakfast
7:00 AM - 9:00 AM

Causal Modeling & Measuring Impact
9:00 AM - 10:30 AM

Artificial Intelligence & Deployment of Solutions in Business
10:30 AM - 12:30 PM

Lunch
12:30 PM - 1:30 PM

Dynamic Decision Making under Uncertainty
1:30 PM - 3:30 PM

Risk Analysis & Mitigation
3:30 PM - 5:00 PM

Optional Campus Tour
5:15 PM - 7:00 PM

Dinner
6:00 PM - 8:00 PM

Day 2

Breakfast
7:00 AM - 9:00 AM

Real Options
9:00 AM - 10:30 AM

Dynamic Incentive Management
10:30 AM - 12:30 PM

Lunch
12:30 PM - 1:30 PM

Processing & Aggregation of Decentralized Information
1:30 PM - 3:30 PM

Decision-Making Strategies for Large Markets
3:30 PM - 5:30 PM

Dinner
6:00 PM - 8:00 PM

Day 3

Breakfast
7:00 AM - 9:00 AM

Algorithmic Decision Making
9:00 AM - 10:30 AM

Data Privacy & Security 
10:30 AM - 12:20 PM

Evaluations & Program Close
12:15 PM - 12:30 PM

Lunch
12:30 PM - 1:30 PM

Program Registration Calendar

Registration Cost
$6,900
Registration deadline
May 12, 2024
Register Now
false

Duke Executive Education

Program Calendar

JB Duke Hotel Fuqua Executive Education
Explore our upcoming program offerings.

Executive Education

Contact Us

false
false

Program Location and Accommodations

JB Duke Hotel Fuqua Executive Education
During your time in Durham, you’ll live and learn in the four-star JB Duke Hotel, a contemporary and tranquil retreat on Duke’s campus with state-of-the-art learning facilities.
Insights and strategies about how to thrive in the digital sphere
Duke Executive Education White Paper

Leadership in the Digital Age

true

Faculty

Professor Alex Belloni

Alexandre Belloni

Alexandre Belloni is a Professor of Decision Sciences at the Fuqua School of Business at Duke University. He received his PhD in Operations Research from MIT (2006) and a M.Sc. in Mathematical Economics from IMPA (2002). Professor Belloni’s current research focuses on developing and analyzing methods for model selection in Econometric problems, and for solving Mechanism Design problems.

His research papers have appeared in journals such as Econometrica, Review of Economic Studies, Annals of Statistics, Marketing Science, Management Science and Operations Research. He received a grant from the National Science Foundation, held visiting appointments in other prestigious institutes, and consulted with the electrical energy industry in Brazil.

Professor Peng Sun

Peng Sun

Peng Sun is a Professor in the Decision Sciences area at Duke’s Fuqua School of Business. He researches mathematical theories and models for resource allocation decisions under uncertainty, market and mechanism design, and incentive issues in dynamic environments. Professor Sun’s work in decision models spans operations management, finance, marketing, health care, and sustainability.

Professor Sun is an Associate Editor at Operations Research, and at Management Science, two leading academic journals of the profession of Operations Research and Management Science. At Fuqua, Professor Sun has taught Decision Models, Strategic Modeling and Business Dynamics in the MBA and various EMBA programs, and PhD course Dynamic Programming and Optimal Control.

Professor Sasa Pekec

Saša Pekeč

Saša Pekeč is an Associate Professor in Decision Sciences at Duke’s Fuqua School of Business. Professor Pekeč’s research is interdisciplinary and revolves around decision-making in complex competitive environments. He has published articles in Management Science and Operations Research, as well as in top academic journals in other fields. His work on combinatorial auctions had been widely cited and had influenced design of a new generation of now standard procurement auction procedures in a variety of industries.

Professor Pekeč’s consulting experience includes banking, internet, pharmaceutical, retail, and telecommunications industries. He serves on the Supervisory Board of Atlantic Grupa, one of the leading FMCG companies in SE Europe. Professor Pekeč was a member of the Council of Economic Advisors to the President of Croatia from 2010 to 2015.

How to Register

For more information about how to register, please see our detailed instructions.

Registration Instructions

Frequently Asked Questions

For additional information about our Executive Education programming, please visit our FAQ page.

Frequently Asked Questions

Get Started




Certificate Requirements: Attendance to the Duke Leadership Program and three electives within a three year period. More