data sciences and operations (dso)

Data Sciences and Operations (DSO)

USC Marshall School of Business

Anybody interested in consulting, operations, manufacturing, or entrepreneurship.

In a recent study of supply chain job ads for MBAs, sourcing and supplier

management was the most important topic, required in 57% of ads.

To provide students with an understanding of the impact that

sourcing and supply management have on the success and

profitability of firms in today’s business environment.

We will look at some of the factors that need to be considered when

making sourcing and supplier management decisions (costs, prices,

contracts, ethics, globalization, risks), and discuss the influence that

sourcing and supply management have on other functional activities,

such as product design, inventory management, etc.

Purchasing and supplier

management

Cost analysis

Total cost of ownership

Prices and contracts

Procurement risks

Supplier selection and

evaluation

Global sourcing

Dual sourcing

Environmental and social issues

in sourcing and purchasing

Who should take the course?

Course Objectives

Key Concepts

Course Description

DSO-506 (16299)

Sourcing and Supplier Management

Wednesday

2:00PM – 4:50 PM (2nd half)

Professor Alireza Kabirina

Data Sciences and Operations


MBA students seeking to obtain an understanding of the transformative role of

business analytics on various domains and functions of an organization while also

developing their analytical toolkits.

This course exposes students to various analytics tools, including Python, R, Google

Analytics, Tableau, and Gephi (among others). It is comprised of four modules,

where each module provides students with an opportunity to obtain hands on

experience regarding a technical aspect of the business analytics process. Each

module also incorporates case studies that address the impact of business analytics

on specific domains. Therefore, while gradually building up the technical skills

required to analytically examine business problems, students also obtain a

managerial perspective on the importance and function of analytics across various

domains. Here is an overview of the domains and technical skills that students will

be exposed to in this class:

Who Should Take the Course?

Course Objectives/Structure

DSO-510 Business Analytics ~Fall 2021

Saturday 9:00 - 12:00 PM (Section: 16325)

Tathagata Dasgupta [email protected]

Course Description

Business analytics is the process of utilizing tools and techniques to turn data into

meaningful business insights. This course provides students with foundational

knowledge for business analytics, including strategies, methods, and tools. Students

will obtain the necessary skills for defining business analytics for data-driven decision

making and innovation as well as hands-on experience using analytics to solve real-

world problems. While this course exposes students to a variety of analytics tools, the

focal objective is to provide a managerial perspective on the usage and role of

business analytics in progressive corporations.

Technical/Analytics Tools

Defining business problems and

obtaining/maintaining data,

including geographic/ spatial data.

Descriptive Analytics and

Visualization (Tableau, Gephi).

Analyzing and interpreting the results

of regression analysis, text mining

analysis, clustering, and other

advanced statistical methodologies.

Domains

Finance

Digital Transformations

Social Media and Digital Marketing

Human Recourses

Product Management

Healthcare

Sports

mailto:[email protected]



Graduate students seeking to obtain an understanding of the transformative role of

business analytics on various domains and functions of an organization while also

developing their analytical toolkits.

This course exposes students to various analytics tools, including Python, R, Google

Analytics, Tableau, and Gephi (among others). It is comprised of four modules,

where each module provides students with an opportunity to obtain hands on

experience regarding a technical aspect of the business analytics process. Each

module also incorporates case studies that address the impact of business analytics

on specific domains. Therefore, while gradually building up the technical skills

required to analytically examine business problems, students also obtain a

managerial perspective on the importance and function of analytics across various

domains. Here is an overview of the domains and technical skills that students will

be exposed to in this class:

Who Should Take the Course?

Course Objectives/Structure

DSO-510

Business Analytics Fall 2021

Monday 12:30-3:20 or 6:30-9:30

Tuesday 12:30-3:20 or 6:30-9:30

Mohammed Alyakoob

[email protected]

Course Description

Business analytics is the process of utilizing tools and techniques to turn data into

meaningful business insights. This course provides students with foundational

knowledge for business analytics, including strategies, methods, and tools. Students

will obtain the necessary skills for defining business analytics for data-driven decision

making and innovation as well as hands-on experience using analytics to solve real-

world problems. While this course exposes students to a variety of analytics tools, the

focal objective is to provide a managerial perspective on the usage and role of

business analytics in progressive corporations.

Technical/Analytics Tools

Defining business problems and

obtaining/maintaining data,

including geographic/ spatial data.

Descriptive Analytics and

Visualization (Tableau, Gephi).

Analyzing and interpreting the results

of regression analysis, text mining

analysis, clustering, and other

advanced statistical methodologies.

Domains

Finance

Digital Transformations

Social Media and Digital Marketing

Human Recourses

Product Management

Healthcare

Sports


In business forecasting, time series models are used to analyze data that are collected over timeto develop forecasting models for revenues, earnings, inventory, sales, budgets and new productdevelopment.

Because time series data arise in so many different business areas, forecasting methods apply toproblems in finance, marketing, real estate, production, operations research, internationalbusiness, and accounting.

Knowledge of forecasting methods is among the most demanded qualifications for businesspeople working in either private or public sector of the economy. This course provides those skillsand also opens possibilities for a forecasting management position in business.There is a shortage of well-trained MBA’s for these positions.

Students learn simple and sophisticated methods and obtain forecasting skills and experience by completing several projects. There is a comprehensive final exam but no midterm. The course projects provide practical experience developing forecasting models for actual business operations.

The general aim is the development of sophisticated professionals, able to critically analyze business data and create business forecasting reports.

Topics to be covered include the concept of stationarity, autoregressive and moving average models, identification and estimation of models, prediction and assessment of model forecasts, seasonal models, and intervention analysis. The course goals are for each student to understand time series methods and obtain "hands on" experience using, analyzing, and developing forecasting models for business applications.


DSO-522 (16240)

Applied Times Series Analysis for Forecasting

Tuesday/Thursday 2:00PM – 3:20PM

Business Forecasting Time Series Models

Professor: Robertas Gabrys EMAIL: [email protected]

Forecasting Methods Regression and Box-Jenkins

Why take the course?

Course Objective

Key Concepts

Course Description

DATA SCIENCES AND OPERATIONS (DSO)


Students who plan to have a career in Business Analytics and interested in knowing more

about Big Data and Predictive Analytics should take this class. Students who have previous

knowledge in Analytical Models not don’t know how to use it in Business should take this class.

Managers who want to combine Analytics with Business Analysis should take this class.

To provide students with concepts, frameworks, analytical thinking, critical

thinking and creative thinking skills for converting Company Data + Big Data into

actionable form and building analytical models for monetizing data.

To provide practical knowledge (cases), skills, methods, tools, KPIs and resources

for conceiving, building and solving new paradigms in Big Data Analytics space.

To give a Big Picture view of Big Data Analytics

The course focus is to give a Big Picture view of Business Analytics, its components

and platforms. To build sophisticated business analytical models from raw data

using Desk top and Industry level tools for Classification, Clustering and Association

Problems. To show how to leverage the readily available “Big Data” from third party

sources for enriching and monetizing data. To develop data mining and business

analysis skillset to gain inference from your analysis, from Executive, Business and

Statistical point of view. To provide a systematic approach to build Analytical

Models. To provide the missing link between Analytics and Business Analysis.

Data Mining

Business Intelligence

Data Warehousing

Big Data Platforms

MAGIC framework

JMP Software

SAS Enterprise Miner

MAGIC - Framework

Classification & Clustering & Association

Decision Tree, Logistic Regression, KNN

Neural Network, Naïve Bayesian

Partitional and Hierarchical Clustering

KPIs – Business and Statistical

Search Engine Marketing

Enrichment, Star Schema, Dash Boards

Introduction to many industry tools


Course Objectives

Key Concepts

Course Description

DSO-528 (16227)

Data Warehousing, Business Intelligence and Data Mining (AKA – Big Data Analytics)

Prerequisites: Statistics Class

Tuesday/Thursday (section16227)

Professor Arif Ansari

BRI 401R

[email protected]

(213) 821-5521

[email protected]



DSO-530 (16305)

Applied Modern Statistical Learning Methods Monday, Wednesday; 11:00am-12:20pm

Professor Inga Maslova


Knowing how to implement modern statistical methods will give you an edge

over less quantitatively competent MBAs.

Course Objectives

To give students an understanding of modern non-linear statistical

methods and how to apply them in real business situations.

Key Concepts

• Modern statistical learning

approaches

• Shrinkage methods

• Non-linear regression

• Tree methods

• Boosting and Bagging

• Support Vector Machines

• Statistical methods for Option

Pricing

• Using the statistical software R

• Neural networks

Course Description

This course aims to provide an applied overview to such modern non-

linear methods as Generalized Additive Models, Decision Trees, Boosting,

Bagging, Neural Networks and Support Vector Machines as well as more

classical linear approaches such as Logistic Regression, and Nearest

Neighbors. We will cover these approaches in the context of Marketing,

Finance and other important business decisions.



Aspiring finance professionals, business analysts, quant-savvy entrepreneurs, and

management consultants need spreadsheet modeling skills to draw insights and

build projections amidst uncertain conditions.

Using MS Excel as the platform, this course trains professionals to

become effective modelers: to translate industry challenges into

well-formulated spreadsheet models, and then use those models

to drive decision-making.

The course teaches spreadsheet modeling skills as well as industry best

practices and expectations. Modeling skills are developed throughout the

course using examples from many functions and industries. In addition to

general modeling skills, the course will teach a handful of frameworks and

tools useful to drawing managerial insights.

Particular emphasis is placed on the understanding of the fundamental

drivers to quantitative decision-making as well as the communication skills

necessary to drive organizational change.

Spreadsheet Modeling

Sensitivity Analysis

Monte Carlo simulation

Optimization

Financial modeling

Scenario analysis

Decision analysis .

(decision trees)

Data tables & Pivot Tables

Risk Analysis

Multiple regression modeling


Course Objectives

Key Concepts

Course Description

DSO-547

Designing Spreadsheet-Based Business Models

Offered in multiple sections/times with different Instructors. (Please refer to the schedule of classes.)



DSO 551 Fall 2021 (Section 16278R)

Digital Transformation in the Global Enterprise M/W 11:00am12:20pm

Professor Ann Majchrzak majchrza@@marshall.usc.edu

Who should take the course? Come and check out the most recent developments in digital transformations and be ready to lead the

charge. Learn to design digital initiatives for hyperpersonalization, edge computing, digital twins, data

monetization, blockchain, digital workplace, distributed AI, no-code app development, mesh

architectures, and API economy. Job titles: Any business unit manager or consultant since you can’t

ignore the new digital technologies coming down the pike), ANY financial investment broker wanting to

ensure that digital investments will provide payout, business process analyst since a firm can no longer

simply improve their processes but must disrupt the industry, ANY business data analyst since data can

simply be analyzed, it must be strategized.

Course objectives

1. Gain hands-on practice in the 10 skills for designing and leading the most recent

development in digital transformation to compete in a fast-changing digital world.

2. Gain hands-on lab practice with SAP, blockchain, no-code app development, Platform as

a Service, and distributed AI in order to know how to design digital initiatives using them

3. Gain hands-on practice with customer journey mapping, business opportunity mapping,

and disruptive technology mapping

How is this class different?

Co-taught with a CEO of a consulting firm doing this for a living!

Hands-on projects with clients interesting in digitally disrupting their business

if your ideas are good enough, and hiring you to carry it out Not just talk about cases, but hands-on labs actually touching the stuff

Exposure to lots of case examples of companies successfully making these

transformation to serve as role models.

Seminar format


-+



Interested in being a full participant in designing and launching new products and services

over digital platforms in established or start-up companies? Would you like to learn how to

design, assess and generate innovative digital business models? Would you like to have a

career in business development or product management /marketing in the telecom/ media/

gaming/ entertainment/ e-commerce/ retail industries? Would you like to understand how to

establish digital platform leadership? Do you want to learn how to transform a traditional

company into a platform business model company in an ecosystem?

Increasingly, all industries are being- “flipped” with the digital platform becoming the

foreground while physical activities are becoming the background. Digital platform

leadership is increasingly vital for strategic advantage. Even more so in a post Covid-19

world! This course gives MBA/MS participants a competitive advantage in career

preparation for full participation in aspects of business development and business model

innovation in any industry where products & services are offered through digital platforms.

Recent case studies, articles, industry reports, current happenings.

Cases include ScaleFast, Niantic Pokemon Go, Intuit, LinkedIn, Twitch,

Pinduoduo, ByteDance, Lemonade, Vestas, and Stripe. Updates in summer.

Frequent senior executive guest speakers who provide current practice insights.

Mid-term and end-term team projects: Developing digital business model

innovation proposal for company, digital platform ecosystem strategic moves.

Course guide posted in Fall Schedule of classes under DSO 556.

Course Reference Text: Platform Revolution (2016).

Fosters interactive discussion & peer learning. Online discussion forum.

General management multi-disciplinary orientation.

How to design & manage a business model in a digital platform ecosystem

Scoping and assessing digital business platform ecosystem niches

Leveraging partner capabilities through governance and APIs in digital

business platform ecosystems

How to establish digital platform leadership

Digital business strategy in dynamic and disruptive environments

How to identify, design, and assess innovative digital business models

Different types of digital business models (open innovation, user-generated

content, Internet of things, sharing economy models, social commerce…)

Who should take the course? Aany

Course objectives

Key concepts

Course description

DSO 556 Fall 2021

Business Models for Digital Platforms Wednesdays 6:30 to 9:30 pm Sec 16301 / 16302 Thursdays 3:30-6:20 pm (JKP 202) Sec 16185 / 16231

Professor Omar El Sawy https://www.marshall.usc.edu/personnel/omar-el-sawy

[email protected]

310-991-6627 mobile

https://www.marshall.usc.edu/personnel/omar-el-sawy



Students interested in marketing, product development, business

analytics, content strategy or information architecture who need to use

web traffic and other audience behavioral data to manage digital

platforms.

To give students a foundation to formulate data-based

findings and recommendations for optimizing websites, e-mail

newsletters and Facebook Pages, the workhorses of a digital

marketing strategy.

Both e-commerce and content-based sites need a

measurement strategy, or a roadmap that defines what to

measure and why. Covering the conceptual and

technical aspects of digital metrics, this eight-week course

will explore both standardized metrics and metrics

available through customizing the tracking code or

changing the site architecture. Students will work in teams

to analyze the data and present findings and

recommendations.

Measurement models, or defining the role of digital platforms

in achieving overall business objectives.

Behavioral vs. attitudinal vs. voice-of-customer data.

Key Performance Indicators for visitor acquisition, visitor

behavior and outcomes; funnels. Baselines and targets.

Hands-on experience with data from Google Analytics,

MailChimp, Facebook Insights and other sources.

Data visualizations and infographics for C-level audiences.

Course objectives

Key concepts

Course description

Diga DSO 572

Strategies for Digital Analytics

Thursday 6:30- 9:30 PM

Who shoul d ta ke t he course?

Prof essor Umi [email protected]

• Students learn about real life applications of data analytics in strategy formulation and

execution through cases, business / leadership expert and business analytics

practitioners as well as projects. The course provides a comprehensive framework for

devising dynamic strategies within a continually changing and increasingly competitive

business environment. The objective of the course is to provide the students the

knowledge, the conceptual framework and the methods required to effectively

leverage Data Analytics to shape winning strategies and execution plans. And to help

students ready for a critical role as a translator that can work with both Data Science

and business teams to identify and solve business problems.

• The Ultimate goal is the development of leaders that understand and can embrace

both dynamic Strategy and Data Analytics and are prepared to help their organizations

compete and win in the era of Big Data.

DATA SCIENCES AND OPERATIONS

Dynamic Strategy

Powered By D&A

Connected View of

Planning to Execution

Strategic applications of Data

Analytics – beyond tools


• As stated by a previous student, because: “It's the perfect complement to the other analytics

courses offered at Marshall. While the other courses provide tools for performing analytics, this

course provides the all-important "Why?" element.”

• Because the course is designed to help you harness the power of analytics with a broader

enterprise view and to prepare you for leadership roles in corporate strategy and operations as

well as Data Analytics.

Achieving and enhancing competitive advantage through applications of data analytics, continuous insight

discovery, strategy formulation and execution for the next generation of corporate leaders.

This course focuses on the use of Data Analytics for business advantage across the value chain. It addresses

advanced thinking in leveraging Analytics to discover and address business challenges in a functionally

connected and strategically targeted manner. This course is not focused on teaching tools, discussing data

manipulation methods and/or covering statistical and modeling techniques.

• Business Objectives to analytics

connectivity model for Data

Exploration & Discovery

• Value of Unstructured Data

• Dynamic Sustainability of

competitive advantage

• Role of Translators

Why Take the course?

Course Objectives

Key Concepts

Course Description

DSO-573 (16300/16309) Data Analytics Driven Dynamic Strategy & Execution TUESDAY

6:30 PM- 9:30 PM

Professor Sid Mohasseb [email protected]

• Exertive / Dynamic Strategy Concepts

• Connected and living Enterprise

• Shifting Focus and Convergence

• Value Zones of Big Data and business

centric data buckets and signals.




In any position, our graduates will work in projects either as a project manager

or a team member. It is important that they know effective project

management methodologies. This course provides them with necessary formal

project management skills that can be applied all industries

To provide students with tools and skills needed in planning,

managing, monitoring and controlling complex projects with

numerous uncertainties. Also, to teach Microsoft Project, Excel and

simulation models to make quantitative trade-offs while managing

projects

This course begins with project definition and organization concepts.

Then it moves on to planning, estimation, scheduling methodologies

projects. It will also cover risk and resource management and Earned

Value Analysis. Course materials are enriched with guest speakers,

games, software tutorials in MS Project, Excel and Crystal Ball, and

case discussions

Project organization structures

Work Break Down structures

Project evaluation and

selection

Planning and budgeting

Project scheduling

Critical Chain method

Resources management

Time and cost trade-offs

Risk management

Agile and Scrum project

management

Project monitoring with Earned

Value analysis

Microsoft Project

Excel and Monte-Carlo

Simulation models

Why take the course?

Course objective

Key concepts

Course description

DSO 580 - Project Management Section 16283

Tuesday and Thursday - 12:30 pm – 1:50 pm

Professor Murat Bayiz

BRI 307D

[email protected]

213.740-5618


p-


Anybody interested in consulting, marketing, operations, manufacturing, or

entrepreneurship. Firms need a sound knowledge of how supply chains work, what

are the key metrics, and what incentives have to be provided for the systems to

work well.

To provide students with an understanding of the intricacies of

supply chains. To learn tools for management and improvement of

supply chain processes and performance.

We explore important supply chain metrics, the primary tradeoffs in

making supply chain decisions, and the basic tools for effective and

efficient supply chain management, production planning and inventory

control, order fulfillment and supply chain coordination. Several recent

trends and influential innovations such as revenue management, fast

fashion, reverse logistics, RFID and SaaS will be discussed.

Inventory management

Cycle and safety inventory

Newsvendor model

Distribution system design

Supply chain coordination

Logistics

Forecasting

Network design

Aggregate planning

Enterprise resources planning

Just-in-time manufacturing

Supplier management

IT in supply chains

Sustainability and supply chains


Course Objectives

Key Concepts

Course Description

DSO-581 (16288)

Supply Chain Management

Wednesday

6:30PM – 9:30PM

Professor Bala Subramanian [email protected]




DSO 588 (16327) – “NEW COURSE OFFERING”

Course Title: Supply Chain Finance

Instructor: Professor Christopher Gopal

Email: [email protected]

Who should take the course? Graduate students in Engineering, Marketing, Strategy, Finance and Operations

who aspire to executive and operations roles in the company.

Course Objects: This course is designed to provide insights into supply chain financing and finance,

and provides a unique view of finance within supply chain management. It is

intended to help develop supply chain and operations executives with “business

acumen”, who have an integrated finance-oriented understanding of the operations

of a company. It will give students an understanding of the supply chain impacts on

shareholder value and the financial statements, and provide a grasp of the financial

levers and financing methods for the global supply chain.

Key Concepts

The supply chain, its functions, and the impacts that it has on the strategic

success, shareholder value and financials of a company

analyzing the operations and supply chain performance of a company through its

financials

approaches to optimizing working capital, cash and operational costs, and

financing the supply chain, and the instruments that help finance the operations

of the company while taking risk management in supply chain into account.

Course Description Today’s business environment is uncertain, competitive and risky. More than ever,

it is obvious that individual companies do not compete with each other – supply

chains compete. The focus of a company is usually to integrate and optimize the

flow of goods and information from point of first supply to the end consumer and

back. However, a critical component of the supply chain - the flow of cash and

finance - is typically fragmented. The supply chain typically accounts for 60 – 80%

(and sometimes more) of a company’s costs, while free cash flow from

operations is a primary indicator of business success and sustainability. We will

address operational finance (the issues related to the performance and

financials of a company in terms of cash flow, cost and capital), the costs of

financing, the various methods and instruments used in financing supply chain &

operations, while considering the major risks involved.




DSO 599 (16319) – “NEW COURSE OFFERING”

Course Title: HR AND PEOPLE ANALYTICS

Instructor: Professor Jeffry A Higgins, MBA



Students seeking to apply analytic tools, metrics and methods to

the complex world of people analytics to solve business

problems faced by real organizations that show ROI

Course Objectives Develop/Apply problem solving skills using quantitative

methods to analyze and perform root cause analysis.

Solve complex business human capital questions using data.

Understand new metrics in HR and human capital that impact

upon financial performance.

Learn how to transform data into intelligence for insight and

build a model and business case with data that tells a story.

Key Concepts

Analytic levels, HR standards, KPIs and scorecards

People data sources, pain points and value creation

Transforming data into business intelligence

Interpreting analytic results, statistics vs. financial models

Visualization, presentation and storytelling with data

Course Description

This course covers analytic methods and tools to create a

winning data driven business case and story with financial

impact and ROI.



DSO 599

Course Title: SPORTS PERFORMANCE ANALYTICS

Instructor: Professor Lorena Martin, PhD


Who should take the course? Students that want to learn how models are implemented,

interpreted, and presented in professional sports leagues;

NBA, MLB, ATP, WTA, UEFA, and NFL.

Course Objectives Obtain a practical application of data science in sports

performance, referred to as sports performance analytics.

Apply measurement and statistical modeling to

professional athletes in sports.

Examine professional athletes’ performance and

implication of injuries on financial costs.

Learn how to present data to different pro sports

industry audiences.

Key Concepts

Principles of the measurement model for sports

Exploratory and Multivariate analysis

Wearable Technology Output

Load Management KPIs

Sports Science Data Collection in Pro Sports

Course Description

This course will provide real-world implications for athletes,

coaches, front office executives, and professionals working in

the sports industry.

data sciences and operations (dso)

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