Digital Business OperationsCornell

Certificate Program

For a modern business to stay competitive, they must digitize business operations then harness the power of that gathered data.

In this foundational course, you will explore the required elements of digital operations by analyzing examples from the manufacturing, service, and retail industries. The key question that you will explore is: How can you improve an organization's capability to be data driven in its operations?

You will determine how digitization affects operations and apply a process-based approach for designing digital operations for a case study. By the end of the course, you will have discovered proven ways to gather, evaluate, and utilize data to improve a company's operations and overall performance.

Accurate forecasting or predictive analytics is an essential component of digital and data-driven businesses. The digital transformation of a company will require forecasting variables such as the time duration required to complete a customer order or verification and the total volume of demand expected in the future.

Accurate forecasting requires imagination and creativity to complement models, data, and good processes. In this course, you will practice and develop skills in demand forecasting so that you can tackle forecasting tasks in complex time-series data sets that include seasonality and trends as well as causal or regression-based forecasting methods for other types of data sets.

The following course is required to be completed before taking this course:

• Designing Digital and Data-Driven Business Operations

Market experiments are an important way companies can test new products, examine pricing options, and continue to be industry leaders through innovation. Today, experimentation has become even more important because the use of algorithms and AI in businesses implies that companies can make faster decisions at a fine granularity and vast scale; e.g., by customizing product offerings for each geography or changing prices many times a day. It is not possible for human beings to manage, validate, and improve decision making at such a scale without using experiments. Ultimately, experiments help companies make decisions about what is working, what isn't working, and what could work in the marketplace.

In this course, you will explore the types and uses of experiments, design experiments, analyze experiment results, and apply techniques to ensure your firm's experiments produce reliable results.

The following courses are required to be completed before taking this course:

• Designing Digital and Data-Driven Business Operations
• Exploring the Fundamentals of Forecasting Demand

By utilizing data, machine learning, and various regression models, predictive analytics helps companies forecast demand, evaluate the effect of pricing strategies, anticipate customer purchasing decisions, and the like. In essence — and as the name suggests — predictive analytics helps organizations predict future outcomes.

Prescriptive analytics then goes one step further by using these predictive models along with decision rules and desired objective functions to make the best possible dynamic, automated decisions. Some examples include personalized advertising, online recommendation systems, surge pricing, promotional decisions, and stocking and fulfillment choices.

In this course, you will examine the foundational elements of prescriptive analytics, including how to use forecasts as input to build models for dynamic and automated decision making. You will then further analyze these concepts to ensure that these decisions align with and contribute positively to business goals and performance objectives.

The following courses are required to be completed before taking this course:

• Designing Digital and Data-Driven Business Operations
• Exploring the Fundamentals of Forecasting Demand
• Designing Experiments in Retail and Online Businesses

Harnessing technologies as they emerge can lead to improvements but only if implemented effectively. Accurate measurements and careful analysis are necessary components of strategic managerial decision making.

In this course, you will explore the dimensions of marketplaces and the ways they differ from offering products. You will examine the importance of network externality and the methodology to measure it. With an accurate measurement, you can make decisions about augmenting positive externality and determining an effective pricing strategy. You will also analyze matching supply to demand and make strategic decisions for improvements. Furthermore, you will explore the front-end technologies companies utilize to monitor, gather, and examine customer data, enabling them to enhance business-customer engagement and boost customer fulfillment.

The following courses are required to be completed before taking this course:

• Designing Digital and Data-Driven Business Operations
• Exploring the Fundamentals of Forecasting Demand
• Designing Experiments in Retail and Online Businesses
• Optimizing Decisions Using Demand Forecasts

The financial performance metrics of businesses vary based on their industry and strategy. To effectively manage a business, it's important for analytics professionals and leaders to recognize these differences and influence the company's performance accordingly.

In this course, you will consider the effects of experimentation, forecasting, and optimization on financial performance. This entails understanding which financial performance metrics are affected by which aspect of operations, computing and interpreting those performance metrics, and building models to develop performance benchmarks.

The following courses are required to be completed before taking this course:

• Designing Digital and Data-Driven Business Operations
• Exploring the Fundamentals of Forecasting Demand
• Designing Experiments in Retail and Online Businesses
• Optimizing Decisions Using Demand Forecasts
• Marketplaces and Emerging Technologies