How A3 Can Support Covid-19 Related Priorities

The diagram highlights A3 priority products into the mid-term.

Business Priorities for Telcos into the Mid-Term

  • Ongoing cost reductions and investment deferral
  • Moves to benefit from the increasing use of digital products/digital transformation by consumers and businesses
  • Longer term trends towards moving customers to unassisted channels and decentralisation of the contact centre

Mid-term ability to execute large cost saving initiatives

Increased downward pressure on revenues into the mid-term can only push forward larger automations and other cost saving projects which include analytics and AI.  The cost saving projects which offer largest, most immediate savings are related to the transformation of the network and projects around large teams such as contact centre and field services.   In the network, recent research suggest that there is a good amount of cost benefit in simple rules based automations such as NFV life-cycle management.  But there will then be some delay before full cost savings are realised – with the need to invest in top level orchestrations (e.g. SDN MDSO) and develop trustworthy intelligence – to enable the bigger closed-loop automations.

A number of additional tools can be deployed to deal with any mid-term shift in network traffic: including additional machine learning (ML) in capacity management and network planning. ML to improve the quality of information on network inventory and more sophisticated routing tools including dynamic root cause analysis.

Taking benefit from increased use of digital products and enterprise customer digital transformation

Automated fulfilment of services has been a priority for telcos in the last few years. If telcos are to benefit from any increase in the digital habits of consumers and businesses, this will continue to be a priority especially as markets grow for low-margin IOT products.  There should be some short-term benefits in additional deployment of ML to understand new behaviours and find unexpected issues in network customer data.

Decentralising the contact centre and moving customers to digital channels

Many uses of ML and AI in care channels our linked with understanding employees or customers and then optimising performance/experience.  If the numbers of agents working remotely increased significantly, there will be a need for new tools for improving agent quality and training.  Also, increase numbers in digital channels will need closer monitoring and understanding of behaviour.

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