CIOs of Telco companies understand the benefits of big data, as it provides them the ability to collate, correlate and normalize data across a variety of both structured and unstructured sources. Big data is comprehensive compared to the previously siloed approach used by organizations while structuring the data. The ability to deal with humungous volumes of data at relatively lower data loading speeds gives CIOs the agility to produce the kind of adhoc reports and data modeling their business counterpart’s demand from them in this dynamic environment. And while doing so, big data setups keep the overhead (in terms of data compression, storage costs, maintenance costs and support costs) considerably lower than classical analytics. To summarize, the three key big data 3 key business drivers for CIOs are:
- Comprehensive coverage
- Business agility
- Lower costs
On the other hand, while the business users’ priorities and focus may vary, the top 3 reasons for investing in big data are usually:
- Increase revenue: New revenue streams & upsell opportunities through dynamic profiling & customer segmentation
- Reduction in CAPEX/OPEX: Mostly focused around networks optimization
- Customer loyalty, churn reduction and enhancement of customer experience through pre-emptive customer care etc.
Simplifying business operations and business flexibility are secondary drivers.
Do all of the operators have the same priorities and focus on leveraging big data?
We have observed that the core drivers for big data vary. Even the approach towards executing these drivers differs.
- For instance, AT&T and Verizon have used big data extensively for new revenue creation, whereas operators like Telefonica & SingTel focus on extracting the information for retail insights, sentiment analysis, product positioning, mobile advertising etc. Meanwhile, US operators like AT&T and Verizon play on their volume base and go down the route of reselling the anonymized data to other business organizations.
- Operators like British Telecom, Sprint and T-Mobile focus on using big data for network congestion analysis, service assurance, cell-site optimization, etc., and, where applicable, subscriber-centric wireless requirements offloads. Therefore, the focus is internal and specifically focused on cost optimization.
Though there are no absolutes, the focus may vary from operator to operator depending on their market positioning and future roadmap.
Are they missing any key objectives?
In our experience, one of the areas that have not been explored is leveraging big data for enhancing employee experience and streamlining and optimizing internal processes. For example; when big data is used for CAPEX/OPEX reduction from a network perspective, some of the data could also be used to assess the productivity of field engineers. This could be to understand the top 5 reasons why they were not able to complete their appointments; tools, site safety, data maps etc. Today, most Telcos do not analyze all the data that is captured. Bringing in insights from big data could help optimize the truck loads of data for Telcos, which is one of their significant cost items.
Exploring big data for CAPEX/OPEX reduction of other internal processes remains largely unexplored. It is predicted that once the larger cost optimizations at the network level are completed, other internal processes will also becoming involved in big data initiatives.