- MORS-455-5, Strategy Implementation
Two-thirds of business and corporate strategies fail not due to poor strategy or flawed logic but poor execution. However smart a new strategy may be, it takes informed managers and strong leadership to make it a successful one. Expanding on the lessons from STRT 431, this course focuses on strategy implementation, with emphasis on the decisions, actions, structures, and conditions that facilitate the successful attainment of strategic objectives. Our guiding framework involves applying principles of social organization to mobilize the necessary resources to pursue a given strategy.
- KACI-950-5, Human and Machine Intelligence
An executive's most prized network contact for crafting new strategies and making evidence-based judgments may no longer be a person, but a machine. Machines help solve complex problems, lessen decision bias, scale human effort, and spot hidden patterns in big data. However, they lack the creativity and insight that top executives possess. Together, executives and machines have the potential to make powerful “thought partnerships.” Using hands-on cases and applications --- including IBM’s Deep Blue and Google’s AlphaGo that beat Chess and Go Grand Masters --- this course shows how to use a critical set of machine learning decision tools, such as natural language processing, sentiment analysis, and pattern recognition to discover new competitive strategies, turn raw numbers into convincing stories, and make less biased judgments. The overarching goal is to enable you to confidently lead data science and design teams, know the expansiveness and limits of machine-learning complex decision support tools, and be capable of applying human+machine thought partnerships to grow businesses or disrupt Grand Masters in any field.
- STRT 469, Analytics for Strategy
Most strategic decisions businesses make require an assessment of cause and effect. What will happen to prices and sales if I open a new location in a particular geographic area? How will consumers respond if I begin posting the caloric content of my food products at the point of purchase? What is the effect of seasonal bonuses on employee productivity? This course covers in depth the empirical tools that are most valuable for linking cause to effect: regression analysis and field experiments. You will learn how to perform convincing data analyses to answer specific questions, how to evaluate analyses others have done, and how to present data analysis in a clear and accessible way.
- MKTG 482, Customer Analytics and AI
Firms are increasingly obtaining data not just about purchase decisions, but also about individual consumers' pre- and post-purchase behavior. But few firms have the managerial and data analytics expertise to act intelligently on such data. For the key marketing problems in customer acquisition, development, and retention, this hands-on course introduces sophisticated data analytics techniques tailored to those problems, including predictive analytics and large-scale testing. Students apply each technique to a large consumer-level database, learning how to target consumers individually and how to derive customer insights
- MKTG 462, Retail Analytics and Pricing
How does a "sale" sign change customer behavior? How has the Internet changed customer price sensitivity? How has the expansion of retail stores, factory stores, and the Internet changed customer behavior? This data- and analytics-driven course seeks to answer these questions and provides a cohesive framework for studying consumer behavior. Most of the data is from real-world managerial problems, and students learn how to make informed pricing and retailing decisions using data.
- MKTG 479, Critical Thinking in Digital and Social Media Marketing
The objective of this course is to develop a strong conceptual and practical understanding of how to use digital data to improve marketing decisions. Students will gain familiarity with key areas of digital marketing including search and display advertising, search engine optimization, and social media marketing. Working with real data sets, students will practice using quantitative tools to improve campaigns, estimate ROI, and gain customer insights.
- MORS 457, Social Dynamics and Network Analytics
Social Dynamics and Network Analytics covers cutting edge research on social media, digital data, and crowdsourcing, and provides you with the tools to practically apply this research in your own career. By the end of the course you will know how to: measure volume and location of Internet search data to understand and forecast trends; measure volume and sentiment of Twitter conversations; collect network data and create meaningful network visualizations; use the wisdom of crowds, including setting up a prediction market, to create better forecasts; and use Amazon Mechanical Turk for crowdsourcing.
- STRT-440, People Analytics and Strategy
This course was formerly known as MGMT 440Hiring, developing and retaining the right employees is crucial for success in modern firms. Big data is transforming how firms recruit and develop talent. Hiring, training and promotion practices increasingly rely on both economic principles and quantitative analysis. The purpose of this course is to introduce a powerful set of economic concepts for human resource management and to use analytics to make better informed decisions on personnel strategy. For example, we will use statistical software to predict the potential of applicants to improve hiring decisions or we will use experimental designs to evaluate the effectiveness of training and talent development programs. Examples of additional topics covered in the course are productivity estimation, turnover and employee satisfaction, promotions, and discrimination. In modern firms, these topics take up a significant mindshare of CEOs and other senior leaders. This course is designed for MBA students who aspire to start, lead, and build businesses; this is not a course for those interested in careers as administrators of human resource management systems.
