Traditional Strategic Business Consulting

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From the course by Duke University

Business Metrics for Data-Driven Companies

4249 ratings

Duke University

Business Metrics for Data-Driven Companies

4249 ratings

Course 1 of 5 in the Specialization Excel to MySQL: Analytic Techniques for Business

In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.

From the lesson

Working in the Business Data Analytics Marketplace

Welcome! This week, we will meet some great people - all former students of mine - now working at super-interesting and exciting jobs as business analysts, business data analysts, or data scientists. We’ll explore what they do, how their role relates to big data, and the skills they needed to get hired! Our hope is this information will give you a better understanding of the type of data-related job you might apply for once you've completed this specialization, and a sense of the type of company you would find most appealing to work for. By the end of this week, you will be able to: differentiate among different job roles within a company that work with data; identify how each role works with data; and describe the skills required to perform each job role. You will differentiate how different types of companies relate to big data culture, and rank any company according to a 20-item checklist. You will also learn to differentiate how different types of companies relate to big data culture. Included in this week’s materials is a 20-item checklist to rank companies. This week also includes in-video polls so you can see how others are ranking their businesses.

Overview of 5 Types of Companies as They Relate to Big Data4:08

Traditional Strategic Business Consulting4:40

Bricks-and-Mortar Companies7:27

Barnes and Noble Case Study4:08

Meet the Instructors

Daniel Egger
Executive in Residence and Director, Center for Quantitative Modeling
Pratt School of Engineering, Duke University
Jana Schaich Borg
Assistant Research Professor
Social Science Research Institute

Strategic business consulting firms provide expert advice

about best practices to companies.

That want to stay competitive in the constantly changing conditions

of the global digital economy.

Much of a strategic consulting company's work is based on collecting and

analyzing data.

Using that data to recommend business process changes to their clients.

For this, they need business analysts in large numbers.

The largest firms of this type are Deloitte Consulting,

McKinsey, Boston Consulting Group and Bain.

With annual consulting revenues over 6 billion, 5 billion,

3 billion, and 2 billion respectively.

Mostly, the data that the business analysts work with belongs to a client.

Technical staff at either the consulting firm or the client.

Extract data that the client already has stored in various databases, but

is not using dynamically.

They provide it to the business analyst,

typically in the form of an Excel spreadsheet.

The business analyst studies it and applies various models.

To discover opportunities for business process improvement.

A variation on this situation are the specialized group of consulting

firms that have developed their own proprietary databases.

And related predictive models about a particular industry or market sector.

These consulting firms tend to need more business data analysts.

And some data scientists as well.

Examples of this type of consulting firm, are credit bureaus.

Which collect information about people's debts and payment history.

And sell that information to banks and others offering credit.

To help them decide, whether they should risk a loan with that person.

The three leading credit bureaus are Equifax, TransUnion and Experian.

A fourth company called FICO, formerly called Fair Isaac,

uses the data originally gathered by the credit bureaus.

To generate a single number, the FICO score, that predicts credit worthiness.

FICO scores range from 300, which is terrible, to 850,

which is outstanding credit.

FICO is one of the original data driven predictive analytics companies.

And its numbers are used to make

over 24 million lending decisions in the United States each day.

That's 90% of all US lending decisions.

Two other examples of strategic business consulting companies.

That built thriving consulting practices around proprietary data.

Are comScore and Argus information and advisory services.

Tracking web and mobile click streams,

with user permission, comScore observes how much traffic goes where.

And there's a kind of Nielsen rating for the web.

comScore quote, measures what people do when they navigate the digital world.

It had 339 million in revenues last year.

Argus combines credit card transactions,

balances and payments across most of the credit cards in the industry.

So it has transaction level purchasing information that

the credit bureaus don't have.

Credit bureaus only know how much you owe on a card.

And whether you've been late making payments.

Not what you bought and when.

Argus combines credit card transactions, balances and payments.

Across most of the credit cards in the industry.

It has transaction level purchasing information

that the credit bureaus don't have.

Credit bureaus know only how much you owe on a particular card, and

whether you've been late making payments.

Not what you buy and when.

Argus builds models about consumer behavior, segmenting potential customers.

And helping banks with marketing promotions for new credit cards.

As well as with managing credit risk.

Argus revenue's are not broken out separately.

But it is part of various analytics with $1.8 billion in annual revenues.

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