Few people would disagree that data should be used more in the decision-making of every organisation. The creation of valuable insights or “data monetisation” has become the catch-phrase for two distinct activities in using data and data insights.
- External data monetisation – The use of data to create insights on people or entities that can be sold to partners for advertising and market insights. Data monetisation platforms (DMP) hold data and make insights available for these use cases.
- Internal process optimisation – The use of insights to optimise internal process for personalisation of customer interactions, optimisation of operational processes, utilisation of capital assets and resources. Insights are made available through emending them in applications, through analytics tools/ platforms or through just providing insights through API’s.
Many telecom operators have been looking at external data monetisation, but few have committed to rolling it out. Data privacy regulations have been a key factor in suppressing demand in the EU and other regions, as well as the significant web-scale competition that dominates the market. Other challenges however, include the ability to provide appropriate insights, the implementation of the right tools and possessing the staff with the right data science skills. In addition, operators need to create entirely new sales and marketing capabilities to sell this very different type of service.
These challenges have therefore led most operators to concentrate on the optimisation of internal processes. These optimisations are not only more attainable but are likely to be more significant in the short and medium term. The key focus areas for optimisation have been in supporting personalisation of customer interactions. These include the offering of the right services at the right time for each subscriber. However, zero-touch processes for service assurance, customer care and a network planning are all areas where AI and machine learning are being applied. The complexity of 5G and NFV/SDN for provision are also attracting considerable interest.
Who controls and manages data insights within operators is not clear, most are in a federated model based around traditional departmental areas, however this model tends to limit the data sources available for analysis and sharing of skills across the operator. More centralised approaches help over-come this but has its own challenges.
Whichever model is adopted having a clear understanding of the value of insights is important, balancing the current needs focused on internal use cases against looking for new sources of revenues with external monetisation.
This industry-wide survey will look to capture some of the key indicators of what the industry is planning. As part of this survey we can make the results available to you if you’re interested.
