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- Faculty Publications (18)
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- August 2023
- Supplement
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Amram Migdal and Susan Pinckney
Arla implemented a data based price incentive systems to measure, track, and influence climate friendly changes to reduce CO2 emissions across the world’s fourth largest dairy cooperative.
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Keywords:
Dairy Industry;
Business Earnings;
Earnings Management;
Environmental Accounting;
Agribusiness;
Animal-Based Agribusiness;
Acquisition;
Mergers and Acquisitions;
Decision Making;
Decisions;
Voting;
Environmental Management;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Global Strategy;
Ownership Type;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercialization;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Agriculture and Agribusiness Industry;
Europe;
United Kingdom;
European Union;
Germany;
Denmark;
Sweden;
Luxembourg;
Belgium
- August 2023
- Case
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal
Arla implemented a data based price incentive systems to measure, track, and influence climate friendly changes to reduce CO2 emissions across the world’s fourth largest dairy cooperative.
View Details
Keywords:
Dairy Industry;
Business Earnings;
Agribusiness;
Animal-Based Agribusiness;
Acquisition;
Mergers and Acquisitions;
Decision Making;
Decisions;
Voting;
Environmental Management;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Global Strategy;
Ownership Type;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercialization;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Europe;
United Kingdom;
European Union;
Germany;
Denmark;
Sweden;
Luxembourg;
Belgium
- August 2023 (Revised August 2023)
- Case
Sparking Innovation in the U.S. Air Force
By: Michael Parzen, Alexander Farrow, Paul Hamilton and Jessie Li
Parzen, Michael, Alexander Farrow, Paul Hamilton, and Jessie Li. "Sparking Innovation in the U.S. Air Force." Harvard Business School Case 624-002, August 2023. (Revised August 2023.)
- April 2023
- Technical Note
An Art & A Science: How to Apply Design Thinking to Data Science Challenges
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
We hear it all the time as managers: “what is the data that backs up your decisions?” Even local mom-and-pop shops now have access to complex point-of-sale systems that can closely track sales and customer data. Social media influencers have turned into seven-figure...
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Parzen, Michael, Eddie Lin, Douglas Ng, and Jessie Li. "An Art & A Science: How to Apply Design Thinking to Data Science Challenges." Harvard Business School Technical Note 623-070, April 2023.
- April 2023
- Case
Fizzy Fusion: When Data-Driven Decision Making Failed
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
This is a case about a fictional New York beverage company called Fizzy Fusion. The business is facing supply chain and inventory management challenges with its new product, SparklingSip. Despite seeking help from a data science consulting firm, the machine learning...
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Keywords:
Supply Chain Management;
Production;
Risk and Uncertainty;
Analytics and Data Science;
Food and Beverage Industry
Parzen, Michael, Eddie Lin, Douglas Ng, and Jessie Li. "Fizzy Fusion: When Data-Driven Decision Making Failed." Harvard Business School Case 623-071, April 2023.
- October 2022 (Revised June 2023)
- Case
On Ramp to Crypto
Bojinov, Iavor, Michael Parzen, and Paul Hamilton. "On Ramp to Crypto." Harvard Business School Case 623-040, October 2022. (Revised June 2023.)
- June 2022 (Revised July 2022)
- Module Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...
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Keywords:
Causal Inference;
Causality;
Experiment;
Experimental Design;
Data Science;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Module Note 622-111, June 2022. (Revised July 2022.)
- March 2022 (Revised July 2022)
- Module Note
Exploratory Data Analysis
This module note provides an overview of exploratory data analysis for an introduction to data science course. It begins by defining the term "data", and then describes the different types of data that companies work with (structured v. unstructured, categorical v....
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Keywords:
Data Analysis;
Data Science;
Statistics;
Data Visualization;
Exploratory Data Analysis;
Analytics and Data Science;
Analysis
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Exploratory Data Analysis." Harvard Business School Module Note 622-098, March 2022. (Revised July 2022.)
- March 2022 (Revised July 2022)
- Module Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to...
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Keywords:
Data Science;
Linear Regression;
Mathematical Modeling;
Mathematical Methods;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Module Note 622-100, March 2022. (Revised July 2022.)
- March 2022 (Revised July 2022)
- Module Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...
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Keywords:
Machine Learning;
Data Science;
Learning;
Analytics and Data Science;
Performance Evaluation
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Module Note 622-101, March 2022. (Revised July 2022.)
- March 2022 (Revised July 2022)
- Module Note
Statistical Inference
This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic...
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Keywords:
Data Science;
Statistics;
Mathematical Modeling;
Mathematical Methods;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Statistical Inference." Harvard Business School Module Note 622-099, March 2022. (Revised July 2022.)
- August 2021 (Revised July 2023)
- Case
Data Science at the Warriors
By: Iavor I. Bojinov and Michael Parzen
An introductory case for a data science course, which provides an overview of the data science pipeline.
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Keywords:
Data Science;
Digital Marketing;
Analysis;
Forecasting and Prediction;
Technological Innovation;
Information Technology;
Sports Industry;
San Francisco;
United States
Bojinov, Iavor I., and Michael Parzen. "Data Science at the Warriors." Harvard Business School Case 622-048, August 2021. (Revised July 2023.)
- August 2021
- Case
Precision Paint Co.
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case.
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Bojinov, Iavor I., Chiara Farronato, Janice H. Hammond, Michael Parzen, and Paul Hamilton. "Precision Paint Co." Harvard Business School Case 622-055, August 2021.
- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...
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- February 2021
- Tutorial
T-tests: Theory and Practice
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with...
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- February 2021
- Technical Note
Probability Distributions
By: Michael Parzen and Paul Hamilton
This technical note introduces students to the concept of random variables, and from there the normal and binomial distributions. After a brief introduction to random variables, the note describes the standard properties of the normal distribution: a single peak, and a...
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Parzen, Michael, and Paul Hamilton. "Probability Distributions." Harvard Business School Technical Note 621-704, February 2021.
- January 2021
- Case
The FIRE Savings Calculator
By: Michael Parzen and Paul Hamilton
This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the...
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- January 2020
- Case
Kaggle 2019 Data Science Survey
By: Yael Grushka-Cockayne, Michael Parzen, Paul Hamilton and Steven Randazzo
Grushka-Cockayne, Yael, Michael Parzen, Paul Hamilton, and Steven Randazzo. "Kaggle 2019 Data Science Survey." Harvard Business School Case 620-091, January 2020.