Developing Alternative Third-party Revenues With Big Data
2018.06.04   |   27 pages   |   Digital Transformation

Author:
Nicola Warren


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Operators are searching for new revenue streams in the face of continuing declining profitability of core products.  Digital transformation initiatives have emphasised the internal value of MNO data to the business, but they have also highlighted the potential for this resource to add value for external parties.
This report examines what operators should consider to leverage their data assets beyond their own use.  It looks at how other data owners are already capitalising on their data and the involvement of MNOs in this opportunity area to date, to help guide MNOs considering how they can access alternative, third party revenue streams using Big Data.

 

 

Companies: Singtel, Telefonica O2, Orange, Google, Facebook, Experian, Datastreamx, Visa, John Deere, Amadeus, Acxiom, Smartpipe Solutions, Zeotap, Teralytics, DataSpark, Weve, Axonix,

Countries: Singapore, UK, France, Global, EU, US, Germany, Switzerland,

Keywords: data visualisation, data interpretation, new revenue, Datavenue, intelligence, analytics tools, data security, advertising exchange, big data infrastructure, programmatic advertising, data analysts, Business & Decision, data scientists, raw data, data skills, data aggregator, Insights-as-a Service (IaaS), location, Group Digital Life, machine learning, data storage, mobility, trust, commercial model, technical investment, third party revenue, data platform, data protection officers, big data professional services, Flux Vision, digital ecosystem, analytics capabilities, GDPR, data asset, data analysis, digital transformation, data value chain, data engineers, analytics, data privacy, data marketplace, Big Data, data insight, monetisation,

1

Overview

1

2

Introduction

2

2.1

Background to the Report

2

2.2

Report Content

2

2.3

Currency and Conversions

3

2.4

Further Questions and Feedback

3

3

The Big Data Business Case

4

3.1

Opportunity

4

3.2

Risk and Investment

5

3.2.1

Data Identification

5

3.2.2

Technology Investment Levels

6

3.2.3

Investment in Data Skills

7

3.2.4

Uncertain Commercial Models

8

3.2.5

Data Privacy and Security

8

3.2.6

Trust

9

4

Big Data Monetisation Options

10

4.1

Introduction

10

4.2

Selling Raw Data

10

4.3

Selling Analysis and Analytics Capabilities

11

4.4

Selling Value-add Data-based Insight Services

12

4.5

Selling Big Data Professional Services

14

5

External Party-led Monetisation

17

5.1

Introduction

17

5.2

External Party MNO Data Service Providers

17

6

Operator-led Monetisation

20

6.1

Singtel Dataspark - Singapore

20

6.2

Telefónica O2 Weve – UK

22

6.3

Orange Business Services – France

23

7

Findings and Conclusions

25

8

Recommendations

27

 

Appendix – Feedback Questions

28

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