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Case studies in business analytics with ACCENTURE

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Curso 3 de 4 en SpecializationStrategic Business Analytics

Who is this course for ? This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors. The objective is to give you an helicopter overview on what's happening in this field. You will see how the tools presented in the two previous courses of the Specialization are used in real life projects. We want to ignite your reflection process. Hence, you will best make use of the Accenture cases by watching first the MOOC and then investigate by yourself on the different concepts, industries, or challenges that are introduced during the videos. At the end of this course learners will be able to: - identify the possible applications of business analytics, - hence, reflect on the possible solutions and added-value applications that could be proposed for their capstone project. The cases will be presented by senior practitioners from Accenture with different backgrounds in term of industry, function, and country. Special attention will be paid to the "value case" of the issue raised to prepare you for the capstone project of the specialization. About Accenture Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With more than 358,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com.

De la lección

Introduction to case studies in business analytics with Accenture

In this introductory module, Fabrice Marque, Managing Director Customer Strategy Practice Lead for France, Belgium and the Netherlands, also in charge of the ESSEC-Accenture Strategic Business Analytics Chair, will first introduce the MOOC in general. Then Michael Svilar, Global Accenture Data Science Group Lead, will identify the general trends in this sector. In this module, we will cover three different real-life examples. First, Rohit Banerji, Accenture business lead responsible for big data analytics for the resource sector, will present an example from a water utilities company. Second, Cian O’Hare, Managing Director at Accenture Digital, will present a case study from a global communication provider. Finally, Christopher Gray, public service expert at Accenture, will discuss challenges arising in the public sector where Analytics and Big Data can provide effective solutions. At the end of each example there will be quiz questions. Note that those questions may require you to collect additional information from that which was delivered during the videos. Do not hesitate to consult additional books, websites and examples about this topic: some of the answers can actually be found directly thanks to open access research engines or online encyclopedias! The objective with this final MOOC in the Strategic Business Analytics specialization is to assess whether you now master the different concepts that are implemented within this field.

Big data & advanced analytics in the Communications industry - Cian O’Hare4:10

Conoce a los instructores

Nicolas Glady
Associate professor, at ESSEC Business School
Marketing Department

[MUSIC]

Hello, my name is Cian O'Hare and I'm a Managing Director at Accenture Digital.

I lead a number of exciting engagements with our clients in the UK and

Ireland in the big data and advanced analytics domain.

The case study I would like to share with you today

is from a global communications provider.

This company operates in over 26 countries and

has an excess of 400 million customers across the globe.

It serves both the consumer and enterprise sectors.

The company wanted help in creating a big data capability as a strategic asset.

They recognize the opportunity to derive significant commercial value from

analytical insight by combining and

processing vast quantities of structured, unstructured, and third party data.

The main challenges the company face could be split into two.

Firstly, organization.

The current analytics organization was fragmented, didn't have the right skills,

and lacked a commercial focus.

Its main function was KPI and historical reporting.

It also lacked a cross functional approach to analytics and

operated very much in silence.

Secondly, technology.

There was a gap in the current technology to enable cost effective

processing of the data.

In fact, the company only processed less than 5% of the data that it generated

across its networks and systems.

This also required a shift in the traditional IT operating model of wanting

to control and limit an access to data, to an approach where data is democratized for

exploratory purposes.

The client has the ambition to deliver an incremental $500 million

of annual EBITDA in five years.

Accenture worked with a client to mobilize a big data program split into three

workstreams.

The first workstream was focused on organization.

This included designing a new big data and

advanced analytics organization that had a hub and spoke model across many countries.

The client is looking to build this team to 150 people over the next two years

focused on both hypothesis-driven and exploratory analytics.

The second workstream was focused on technical architecture.

Accenture helped to find a target reference architecture for analytics and

business information.

We also ran a selection process for a Hadoop distribution.

Following the selection of a Hadoop distribution, Acccenture deployed a number

of instances, as well as supported the load of data into these environments.

The data loaded into the network events, CRM, BI and marketing data.

And this was the first time these data sets were brought together.

The third workstream is where we work jointly with the clients to develop

analytical use cases.

These use cases were focused in a number of domain areas.

Firstly, customer analytics, where we combine network, customer, and

marketing data.

We then helped develop predictive models to correlate network events and

experience with churn.

We then extended this to include text data from customer care agent notes.

Mining the text data allowed us to start to build a view of the overall sentiment

of the customer, and provide a health score, and

likelihood of this customer to churn.

Having this information allowed for

the developer to proactive retention, cross sell and

up-sell campaigns that were launched across a number of outbound channels.

Secondly, fraud analytics.

Using advanced analytics techniques such as machine learning to understand

the likelihood of new customers not paying for expensive smartphones.

Thirdly, network analytics.

Using predictive algorithms to detect faults before they occur on the network.

This has a net result of improving the customer experience and

significantly reducing costs from unplanned maintenance,

calls to customer care, and customer churn.

These used cases have recently been launched as production

marketing campaigns.

Already the results are very positive with many millions of

dollars in benefits being realized.

One of the main aims is to reduce network experience related churn by 10%.

This will have a significant impact commercially

as well as delivering a better experience for the end customer.

I hope you found this case study interesting, and

it is one we're starting to see play out across the communications industry,

where organizations that leverage new tools, techniques, and

their data as a strategic asset is helping drive significant competitive advantage.