We are now at the era of big data. Companies are able to collect tremendous amount of data, very often more than necessary, with ease. “Information is Power” is no longer valid if companies are not able to make correct decision timely out of the data. The use of business analytics for modelling and decisions represents the future of best practices for tomorrow’s success companies.
This course prepares students with fundamental theory and basic instruments to capture business insights from data and thus make good managerial decisions. Quantitative models and tools such as Decision Analysis, Simulation Modelling and Mathematical Optimisation are covered to demonstrate the use of scientific methods in business decision making. Practical examples and cases with rich data are used to stimulate students’ interest and understanding in Business Analytics.
All organisations have an operations function that is primarily responsible for the production and delivery of their products and services. The management of operations function (Operations Management) therefore not only affects final product quality but also impacts customer service and the overall competitiveness of the organisation. The primary objectives of module DSC2006 are to provide students with an introduction to, and an understanding of, the substantive knowledge which has developed over the years in the field of Operations Management (OM), and to highlight the relevance and strategic significance of the Operations function in enterprises.
This module will build around the traditional foundational topics of OM, we will nevertheless attempt to highlight some of the more current issues in the field. Students will be exposed to topics such as product and process design, quality management, capacity planning and inventory management as well as supply chain management in both manufacturing and service organisations.
“Most companies today have plenty of data. However, creating intelligence and gleaning real insights from this data is what continues to elude organisations.” – Competing on Analytics: The New Science of Winning.
Business decisions are often made under uncertainty. In the modern business environment, technological advances facilitate the collection of huge amounts of data, which can potentially improve the decision-making process. Successful businesses make use of Business Analytics and Business Intelligence, which are fundamentally based on quantitative statistical methods and optimisation procedures, to identify patterns and trends in their data, which eventually lead to realistic predictions and insightful strategies.
The sister module, DSC1007 Business Analytics—Models and Decisions (Business Analytics I), focuses on models and processes. This module is more concerned with data and tools, and introduces students to the fundamental concepts of statistical inference such as parameter estimation and hypothesis testing, as well as to statistical tools useful in business analytics, such as regression analysis and time series forecasting. This continues the theme of delivering hands-on experience in modules focusing on analytics and operations.
This module was co-designed, and is co-taught, by the Department of Decision Sciences in the NUS Business School and the Department of Statistics and Applied Probability in the Faculty of Science, to draw upon the relevant expertise from the two Departments.
The module provides all BBA students with a common statistical grounding for Business Analytics, upon which specialisation may be built depending on each student’s chosen field. For the truly visionary student, a natural follow-on could in time be the NUS MSc(Business Analytics), or MSBA, . Biz undergrads may take some MSBA classes (see http://msba.nus.edu); e.g. BMA5002 is an extension of DSC2008, while BDC5101 is of DSC1007.
In keeping with the principles of Rigor and Relevance, also emphasised in DSC1007, students are expected to acquire the following knowledge and abilities.
This module builds on DSC2006 Ops Management, is companion to DSC3202 Purchasing & Materials Management, DSC3203 Service Operations Management, DSC3218 Physical Distribution Management, and prepares for continuation into DSC4211 Seminars in Ops & Supply Chain Management and Field Service Projects. Our objectives of this course are to allow the students to:
• Develop a systematic framework for analysing the behaviour of large and complex supply chain networks.
• Understand the relationship and motivations of suppliers and distributors to ensure supplies of raw materials and markets for finished goods.
• Discover the state of the art technologies and approaches that reduce production, inventory and transportation costs as well as supply lead time.
• Integrate production and inventory control methods in multi-plant distribution strategies.
Best-in-class Purchasing and Materials Management (P&MM) functions support corporate performance by delivering the appropriate balance of Cost, Quality and Speed-To-Market. The function can include sourcing, costing, supplier relations, logistics, and goods storage.
While organisations buy varying combinations and amounts of raw materials, manufactured parts/components, and services, they all have to perform this procurement function efficiently and effectively. In many organisations, the value of purchased goods and services could account for more than 80% of their total spending. Therefore, P&MM represents a significant area for generating competitive advantage by improving Cost of Goods Sold (COGS) and SG&A (Sales and General Administration).
Students will learn about supply chain strategy, and then align the P&MM strategy and tactics. Negotiations, supplier relationship management (SRM), contract performance management, and Actionable Intelligence are foundational elements in the class.
Each class session is run as a business meeting with regular coaching on how to be prepared for the business environment including: ideation sessions, making persuasive arguments, and delivering business cases.
The class also has speakers from industry to discuss real-world situations.
In this course students will learn how to deliver best-in-class P&MM results by:
– Studying P&MM strategy, tactics and capabilities used by corporations today
– Practicing negotiations in-class
– Delivering senior management level presentations with cost/benefits of recommended strategies and tactics
By the end of the course, students will be ready to be active and contributing members of a P&MM function. They will have the foundational knowledge to support senior management in strategy development and building cases for tactical improvements in People, Processes, and Technology.
The ever increasing role and presence of the Service Sector:
Today the service sector is dominating the economies of most developed nations. In the United States, service sector accounts for over three fourth of the GDP and almost 85% of employment. In Singapore, the services sector, a vital engine of growth, contributes to over 75% of employment and to over 60% of the GDP.
In today’s environment almost each and every manufacturing firm also as a part of business strategy has specific business units providing service operations. This is in order to have competitive edges against its competitor and increase customer satisfaction.
Importance of operational efficiency in Services:
Under these circumstances, while the efficiency is one key ingredient for a successful firm, for service industry this is especially true wherein non-tangible aspects play key role in customer satisfaction.
Thus understanding the concepts of how to successfully manage service operations will provide a significant advantage to graduates who are very likely to find themselves employed by a service based or service-oriented firm, in the present environment.
Service Operations Course Focus:
1. The intent of this service operations management course will be to provide students with an understanding of how to analyse service operations, how decision making differs and how implementation hurdles are addressed while operating services.
2. Studies have shown that a “strategic service vision” is a necessity for successful service companies, whether they are banks, airlines, hospitals, utilities, retailing, restaurants, or theatre groups. Consequently, the course will explore basic elements of the service operations strategy. These concepts will be illustrated with wide range of examples from health care, financial services, retail, delivery services, airlines, etc.
3. In this class we will develop and discuss both quantitative tools and qualitative models that will help us to manage in this complex environment.
4. We will also look at key role IT has started playing in redefining service operations.
Two aspects which will form the background of the course are:
• The importance of aligning the design and management of services with the marketing strategy of the firm and
• The impact and management of variability in services.
In this module, the strategic roles of information systems and technology (including the Internet) in business organisations are examined. Frameworks for analysing the strategic impact of information technology on organisational and industry structures are introduced. Information systems that support or shape an organization’s competitive strategy, as well as information systems that are used to re-engineer business processes in organisations are discussed.
This course is directed at business managers who must have a basic understanding of the current and potential strategic impacts of information technology and the Internet. Business managers do not need to be experts in information technology. Rather they need to be comfortable with using information technology applications as well as to have the necessary knowledge to exploit information technology to achieve strategic business objectives. In particular, business managers need to understand the management issues involved in exploiting information technology for competitive advantage.
This module introduces students to the theory and applications of modern optimisation techniques. Formulation and modelling of real life optimisation problems via sophisticated software tools will be emphasised to strengthen students’ understanding of various fields in optimisation. Throughout the course, references will be made wherever appropriate, to business applications, such as portfolio selection and others. Students who are interested in computer and quantitative approaches in business will learn many useful techniques in large business system management from this course.
Stochastic Models in Management make use of analytical methods (in particular, probabilistic method) to distil intelligence for business leaders’ decision-making. Thus, this module is concerned with modelling, analysing and solving quantitative problems in management, and shall find applications in fields like finance, economics, marketing science, operations management, service management, logistics, and engineering.
As an introductory module, we strive for breadth, giving an overview of several practical approaches, as well as sufficient depth, so as to provide a substantial feel for the discipline and a good foundation for further studies. Topics will include discrete-time Markov chains, continuous-time Markov chains, the Poisson process, the renewal reward theory, Markov decision processes, queueing models, stochastic inventory model, reliability models, production models, customer brand-switching models, insurance contract models, and optimal staffing problems in service management.
It aims to portray forecasting as art and science, integrating sensibility and methodology. The course will make productive use of forecasting tools available in MS Excel (and dedicated add-ins), SPSS and Mini tab. The finality is the applicability of the forecasting results towards managerial decision-making.
Everyone makes decisions, but few people think about how they do so. Numerous researches have shown that in many simple decision situations, people make decisions that upon close examination they regard as wrong. While no decision methodologies can guarantee good outcomes, this module introduces an approach, called Decision Analysis that aims to provide clarity of thoughts so that one can make good decisions. This systematic approach to decision-making is normative and applicable to decisions in various domains, including business, medical, personal, technological, etc. This module will cover the underlying foundations of decision analysis as well as its practical applications. The use of spreadsheet software is required.
This course helps students to appreciate the strategic importance of good distribution operations planning in the context of supply chain management in Asia. A strategic framework of physical distribution system design is presented to help build critical analytical skills for decision making in the management of physical distribution and transportation of goods and services.
The course emphasises the application of quantitative and analytical techniques to physical distribution system design (facility location, vehicle routing and fleet planning) and transportation management in Asia. Where available, Asian cases will be used to highlight and educate students on unique business operations in this region.
The objective of this course is to INTRODUCE & INTEGRATE knowledge in this area with applications in logistics and supply chain management. It exposes students to the work environment and the diverse challenges faced by business analysts, logistics planners and supply chain managers. The teaching method will be a combination of lectures, problem-based learning and class discussion on assigned reading topics and case analysis. Active class participation by students is expected.
Today’s successful manufacturing / service organisation, has to delicately juggle between the customer’s requirements of lowest cost, best quality, prompt delivery and flexibility to ensure products of their choice. In the 80’s and even early 90’s, these four strategic options were viewed from a trade-off perspective (e.g. improving quality would result in higher cost etc.). However, in today’s world, it has been accepted that these strategic options are not mutually exclusive but need to be addressed more than one at a time. In many industries it is even necessary to manage all the four imperatives for success, with ability to prioritise between the imperatives as the situation demands.
This course is structured to focus on how to achieve the multiple objectives of “make it cheap”, “make it good”, “make it fast and on time” & “cater to changes in demand and product features”. The class will provide a framework to describe and formulate an operations strategy, and to understand and evaluate the key decisions in operations that can make a substantial difference in a firm’s bottom line.
Matching demand and supply is one of the key questions in today’s business. While traditionally demand management and supply management are isolated and delegated to independent business functions within a firm, joint control of demand and supply is clearly a more powerful approach a company can use to improve revenues and profits. Yet it is not well and systematically understood how to match supply and demand, i.e., how to sell the right product to the right customer at the right price and at the right time.
Coined as the “number-one emerging business strategy” by The Wall Street Journal, revenue management (RM) and dynamic pricing (DP) is the state-of-art tool to improve the operational management of the demand for their products (goods or services) to more effectively align it with their supply and extract the maximum value from demand and supply imbalances.
The course is designed to provide you: (1) a bundle of tactical knowledge and multi-disciplinary tools that are readily applicable to real life business applications to deliver optimal price recommendations; (2) conceptual frameworks that synthesise strategic principles, underlying logics, and high-level managerial insights needed by general managers and management consultants.
The topical matter is pricing, but from a non-traditional perspective, that combines marketing, economics and operations management. Key features that differentiate this course from standard pricing courses are:
• Emphasis on multi-pricing, across products, markets, segments, channels, and time
• Focus on value, as opposed to cost-based pricing
• Tactical approach that integrates pricing with sales and product design decisions
• Specific attention to managing demand risk within the firm’s operating constraints
• Modern, technology driven approach to pricing
Companies such as Nike, HP, Unilever and Coca-Cola have started to reap the benefits from building sustainability into their operations. A focus on reducing environmental impact not only allowed these companies to comply with increased regulations but also to reduce their costs, to improve the quality of their products and to enhance the reputation of their brands. The objective of this course is to study how a company can use its operations to improve environmental performance and contribute to business success at the same time. Students will learn how citizens, governments, customers and employees are creating pressures for more sustainable development and how operations managers are responding to these pressures with waste reduction, pollution prevention, and product stewardship. Students will also study specific tools and methods such as environmental management systems, life cycle analysis, green buildings, green purchasing, design-for-environment, recycling, remanufacturing, servicisation and industrial symbiosis. Through the course students will also learn how to craft a successful strategy for sustainable operations by incorporating it into a company’s business strategy, improvement planning, product and process design, supply management, risk management and both internal and external reporting systems.
This module is an advanced level course on operations and supply chain management. We will focus on two of the important topics in operations and supply chain management: coordination and flexibility. Our objective is to provide our students further understanding on these three selected topics by discussing a variety of related issues and modelling Analysis tools. The students should have taken DSC2006 Operations Management and DSC3201 Supply Chain Management (or similar courses) before taking this course so that they have a general understanding of the problems, issues, and basic modelling tools in operations and supply chain management.
In this course, we not only aim to introduce the students a variety of recent developments and business insights in these two topics, but also want to teach the students how to conduct analysis to gain these insights. A lot of modelling/analysis tools discussed in this course will be quantitative based. In particular, the students should be prepared to apply mathematics concepts such as probability and calculus throughout the semester. In addition, it will be helpful if the students have taken DSC2003 Management Science.
The first part of this course is to expose students to a variety of modelling tools available for their analysis. In the second part of this course, we will cover articles from the academic literature on coordination and flexibility issues in operations and supply chain management. The focus will be on articles that offer management insights and/or present novel and applicable algorithmic ideas for new supply chain models. Supplementary readings will be used to enhance the understanding of the issues involved.
How did ZARA become one of the fastest growing and most profitable brands in fashion retailing? How did Wal-Mart grow to be the world’s largest retailer? To a large extent the answer is that ZARA and Wal-Mart view their operational capabilities as an important and integral part of their competitive advantage. As do other successful companies, such as Procter & Gamble, Toyota, and Coca Cola, they invest strategically in physical plants and facilities, in process and information technology, in employee, supplier, and distributor relationships, and perhaps most importantly, in organisational practices and know-hows. The objective of this course is to provide students with a set of qualitative frameworks and quantitative tools to analyse and guide the long-term, strategic decisions for a company’s operations function. The course is recommended for those interested in consulting, general management, or operations careers, but also for finance specialists interested in assessing the risks, the opportunities, the competitive advantage, and ultimately the value embedded in a company’s operations.
The objective of this course is to help you understand and improve the quality of business decisions and become a better decision maker. Decision-making is becoming increasingly challenging in a fast-paced business world where managers must make frequent decisions in the face of rising uncertainty and complexity. This course will take a systematic view of management decision making from both normative and descriptive perspectives. While the normative perspective focuses on what rational managers should do in order to make optimal decisions, the descriptive perspective offers critical insights about how real managers make judgment and decisions. Class discussion will be organised around the contrasts between what decision-makers should do in a normative sense and how they actually do in a descriptive sense. The normative approach may help decision makers to identify, structure, and analyse decision problems in a systematic and logical manner. On the other hand, the descriptive approach has provided insightful understandings of how people deviate from rational decision-making and fall into common decision traps easily. This course will teach you how to think critically about the decisions you and other people make, how to avoid common decision pitfalls, and how to improve your decision making skills by offering a comprehensive cross-disciplinary knowledge of decision making and more importantly its real life applications.
When you go on holiday, how do you choose a hotel? If each hotel was charging the same rate, which one would you choose? Would it be a Hilton, Marriott, or something else? Why?
The reason people choose one offering over another is based on the principles of service design. In its simplest terms, service design is a process that can be used to develop the framework for a business to deliver superior service for it’s target customers. What makes service design different from traditional disciplines, such as finance, management, and accounting, is that it is a new, complex field and must be looked at from an interdisciplinary approach. The best way to study service design is to first look at the ways that a business needs to engage its customers, and then design programs and facilities to match their customer’s wants and needs.
This course will examine the principles of service design in the context of the attractions and hospitality industry, one of the fastest growing in Asia. Using both theory and practical examples, students will learn how to approach the challenges in designing exceptional service. While it is useful to discuss examples in a classroom setting, there is no substitute for hands-on experiences, and one of the final components in the module will be a site visit to Resorts World Sentosa to see the results of good service design in action.
Decisions supported by timely data analyses are the norm in this “Big Data” era. Many industries including (but not limited to) supply chain management, marketing, finance, human resources, and sports, rely on analytics-savvy analysts/consultants to improve efficiency, profitability, customer satisfaction, and performance. This course aims to equip students with a scientific/analytical mind-set to carry out and to think critically about such analysis.
Through case analyses and their presentation, participants will gain exposure to the following:
• Decision and Risk Analyses i.e. systematic assessment of Strategies, Risks, and Payoffs using Decision Trees and Sensitivity Analyses.
• Business Optimisation Models i.e. Productive allocation of scarce resources e.g. Optimal Product / Advertising Mix, Revenue Management, Portfolio / Supply Chain / Cash Flow / Production Network Optimisation.
• Simulation for hard-to-analyse applications e.g. hedging decisions, Market Share Dynamics, Buy / Sell now or later? Fund returns scenarios,
• Data Mining and Statistical Tools: Applications of regression analysis, logistic regression, simulation and regression.
Microsoft Excel (e.g. SOLVER, PivotTable) and add-in software e.g. Precision Tree, Stat Tools, @RISK will be used as analytical enablers throughout the module.
Successful supply chain visualisation projects require: A business problem, validated data, visualisation for initial insights, and statistical analysis for predictive insights. Students will glean insights from real world data, answer strategic business questions, create an Information Strategy for Supply Chain, Visualise and monetise Big Data.
Real data sets from supply chain, retail, and social media will be placed in cloud technology like Google or Amazon. The students will use a state-of-the-art Business Intelligence Software, Qlikview, to create amazing supply chain visualisation. In the process, students will learn about the critical elements how to make visualisation succeeds in telling a convincing story. Practically, students will also learn about types of data available in a typical corporation, how this data may be collected, shortcomings, bureaucratic/company’s cultural issues.
To round out the course we will review the ethical and legal considerations of acquiring and using certain types of data. At the end we will develop the next generation of business analytics using cross-industry data mashups. The skills learned will be usable in other industries and the core concepts are technology agnostic.
We analyse price formation and economic performance in imperfectly competitive markets by using optimisation, statistical and stochastic methods. Strategic interactions between the participants in these markets are emphasised and a theoretical framework is laid out.
Theoretical models are analysed with industry examples and datasets.
This module provides an opportunity for students to learn BA topics that complement other courses in MSBA and prepare themselves to work with organisations. This education focuses on working on different practical instruments for exercising BA work in enterprises, identifying important organisational issues, detecting critical information sources, collection and analysis. Through action-based learning that spans a full year, the module aims to develop personal capabilities, professional competencies, and academic knowledge for real business settings.
This course aims to provide a holistic overview of the modern Statistical Learning toolbox. Different from traditional Statistics courses, this course (1) emphasises on understanding the intuition behind the tools and not on deriving the underlying mathematics; (2) incorporates real-world datasets and analytics projects to help you bridge theories and practices; and (3) equips you with hands-on experiences in using data analysis software (R and Python) to visualise the concepts and ideas and also solve exercises.
The course covers most of the commonly used analytics tools such as logistic regression and decision tree. Two exceptions, Support Vector Machine and Neural Network (which are
Arguably more of Computer Science tools), are left to other modules.
The students are expected to get their hands really dirty by applying (and even messing up) the tools in analytics software (R or Python).
The goal of this course is to expose students to the art of practical problem solving involving analytics, with emphasis on applications in the finance industry. We will cover a range of topics and applications from data science to stochastic finance, giving students a sample of real challenging yet exciting problems where analytics concepts and techniques are applied.
Supply chains have become far-flung and global. At the same time, increasing macroeconomic volatility and uncertainty create a more difficult operating environment for companies. Companies will have to look at the design of the supply chain to improve both system and process flexibility, as well as to work with others to improve overall coordination and to manage and share risks.
The growth of emerging markets, evolving government regulations, and regional trade agreements will further impact the structure of a company’s operations.
Thomas Davenport, in his article titled “Competing on Analytics” in Harvard Business Review, 2006, has said “Some companies have built their very businesses on their ability to collect, analyse and act on data. Every company can learn from what these firms do.”
The focus of this course is learning Analytics – data based decision making – the art of analysing, making sense out of and strategising from data – whether you are flooded with or when faced with little data.
The belief in this course is Analytics talent in 21st century is as important and significant as programming language was in 1980’s and 1990’s.
We will address the course from a consulting perspective – as we deal with
The aim of this course is to provide an introduction to the probability and statistical methods to model market, credit and operational risk. Topics addressed include loss distributions, multivariate models, dependence and copulas, extreme value theory, risk measures, risk aggregation and risk allocation.
Disruptive technologies are reshaping the business landscape and redefining critical roles and functions within global supply chains.
In this course, we will take a conceptual approach and explore the dynamics that drive optimisation and risk management in global supply chains. Lectures and case studies will go beyond typical SCM and will focus on economic trends, regulatory environments, global trade management and tax regimes.
We will emphasise the impact of information technologies such as the Cloud, the Industrial Internet of Things (IIOT) and real-time data analytics in global supply chains.
Increasingly, supply chain models are requiring “greener” and more environmentally sustainable solutions. As such, the course will devote time to this important subject.
Finally, the curriculum will explore how ethical and anti-corruption standards, export controls and sanction regimes effect global supply chains.