Title: Big Data Analytics: Actionable Insights for the Communication Service Provider

Authors: Ericsson

Date: October 2015

White Paper Link: wp-big-data

Summary of Content of Paper

This white paper describes and explains how big data analytics can provide value for CSPs (Communication Service Providers). CSPs are facing many challenges to understand the value and the role of big data analytics in their business. Some of the CSPs still perceive big data as data storage and still haven’t really figured out how to extract useful insights. Other CSPs were able to gain insights of their business and used it to improve their businesses. This paper argues and defends that big data analytics is mandatory for CSPs. In the first section it describes the transformation of data into insight and its related complexity, fast growth and increased number of services. In the following section, the paper claims that the objective should not be anymore the three Vs of big data (Volume, Variety, Velocity), but it should be the three As (Adequate, Accurate, Actionable). In other words it will require a major shift in mind-set of businesses utilizing big data analytics using the three As principle. The three As principle places more weight on the business insights, rather than the data itself.

The subsequent sections the paper tackles important topics such as user privacy and new business opportunities.

Big data deployments in CSPs raise serious issues of privacy as many clients use their smartphones. Furthermore there is a lack of proper data regulation, which makes it more challenging for CSPs to use the data generated from their networks. However there are possible mechanisms and tools to ensure data privacy, which should be undertaken by the CSPs.

In the new business opportunities, the paper highlights how having a smarter network and real-time user experience could actually help to prevent from subscribers to churn out to another network. Moreover, data brokerage and selling it to third-party companies provide new data monetisation opportunities for the CSPs. Furthermore the paper suggests that marketing should seriously consider the value proposition of the emerging big data analytics. Xu, et al. (2016) have researched on the effects on the effects of new product success (NPS) in 2 different types of analytics: the traditional marketing analytics (TMA) and big data analytics (BDA). The conclusion is that companies should well understand in which analytics to use in which case, as both could provide benefits. Furthermore, it is of utmost important to understand the big data analytics not as a technology, but to build a framework (Erevelles, et al., 2016)  in order to enable the business to create value. Moreover Fana, et al. (2015) proposed marketing should be adopting big data management framework, consisting of different perspectives: People, Product, Promotion, Price and Place. This framework will become the foundation of marketing intelligence.

Quality of the Research

The paper does not specify how the research was conducted. Nevertheless there are 6 different references at the end of the white paper. Typically white papers tend to promote a company or a product, thus could not be considered as academic paper. The target readers are IT experts, executives and technologists. It is obvious that Ericsson is promoting their products and services especially to CSPs.

Overall the paper is interesting and extremely important to better assist in strategic planning of CSPs.

The Research Method

As mentioned earlier, the paper is not of research nature, although there are several references to other authors who have researched on the big data analytics topic. 

Quality of Presentation

The paper is very well-structured, easy to understand and not very long. Typically white papers tend to be short, as the target readers are executives with busy schedule. Moreover, the paper includes diagrams, which illustrate many of the ideas introduced.

Conclusion

In conclusion, the white paper has demonstrated the importance of big data analytics and how it’s potential could be utilized to gain customer insights and in some cases even generate new sources of income.

Additional Notes

The paper was written in October 2015 which means all the proposed topics are valid as there was no major changes till date in the field of big data analytics.

References

Erevelles, S., Fukawa, N. & Sw, L., 2016. Big Data consumer analytics and the transformation of marketing. Journal of Business Research, Volume 69, pp. 897-904.

Fana, S., Lau, R. Y. & Zhao, L. J., 2015. Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix. Big Data Research, Volume 2, pp. 28-32.

Järvinen, J. & Karjaluoto, H., 2015. The use ofWeb analytics for digital marketing performance measurement. Industrial Marketing Management, Volume 50, pp. 117-127.

Xu, Z., Frankwick, G. L. & Ramirez, E., 2016. Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective. Journal of Business Research, Volume 69, pp. 1562-1566.