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Conference Day Two

09:00 AM - 09:45 AM Registration and Coffee

09:45 AM - 10:00 AM Chair’s Opening Address

10:00 AM - 10:40 AM EE Case Study: EE Big Data as a Direct Revenue Generator

  • Assessing group patterns and behaviour to provide insights to monetise data externally
  • Demonstrating how using the full power of Big Data is key for making big decisions: Advertising, retail, transport
  • Identifying the considerations when positioning your organisation to benefit from new Big Data capabilities
  • Determining the future business reality of Big Data: How can you use data to drive the progression of your business?

10:40 AM - 11:20 AM Tele2 Case Study: Monetising Aggregated Location Data by Looking at Traffic Flows for Cities

  • Processing existing data and aggregating it to analyse traffic flows for bigger cities
  • Insights in traffic flows to creat value for city planners, decision makers and infrastructure investments for public transport companies
  • Demo of how the platform is built up transforming already existing telecom data into a valuable service

11:20 AM - 11:50 AM Morning Coffee and Networking Break

11:50 AM - 12:30 PM Establishing How Real-time can Increase Customer Capability

  • Examining how increasing mobile data with the ability of real-time can increase customer capability and data versatility
  • Overcoming regulations: Examining how working with privacy commissioners and increasing anonymous formats can support wider data usage
  • Analysing the business intelligence possibilities of new data and data sets in the forms of latitude and longitude in 1 square meter calling pixels
  • Assessing how formatting of data can increase access within location and sonification to increase customer mobile services at real-time in their networks

12:30 PM - 1:00 PM Viavi Solutions Panel Discussion: Enabling Operators to Generate Smart to Increase Data Monetisation

  • Moving away from static models: Identifying alternatives to the increasing investment into data processing and shifting this to analysing data to achieve insights for monetisation use cases
  • How can you move away from enormous volumes of data, to a situation where only the relevant data is processed
  • Understanding how to utilise a combination of measurements and data points, to gain insights without processing all of your data
  • Creating smart data: Examining strategies to stripping irrelevant detail, extracting value, and then making that valuable piece of information available

1:00 PM - 2:00 PM Lunch Break

2:00 PM - 2:40 PM Identifying the Value of your Network Data to Ensure you are Identifying Potential Revenue Streams and Increase Savings

  • Analysing how identifying the value of your data can support you in the business case for new revenue streams of monetising data
  • Identifying the data circles relevant to your data to further your understanding of your data’s potential monetising avenues internally and externally
  • Evaluating the potential within developing the infrastructure of big data to monetise your efforts alongside your enterprise
  • Assessing framework strategies to evaluate how you can generate revenue from customer data networks

2:40 PM - 3:20 PM Multifaceted Use-Case Study: Creating a Customer Centric Business Case when Monetising Data to Maximise Internal Revenue

  • Improving benefits for customers to maximise the customer experience and increase customer retention rates
  • Utilising big data to ensure you are creating customer focused use-case packages to encourage an increase in data and revenue
  • Incorporating feasibility studies and running pilots to support and enable trust from customers and identify a wider variety of data collection schemes
  • Monitoring and controlling traffic to support your collection of valuable key use-case data
  • Utilising customer data traffic and insight: Designing region specific and customer centric products

3:20 PM - 3:50 PM Afternoon Tea and Networking Break

3:50 PM - 4:50 PM Roundtable Discussion: Assessing the Realms of Privacy, Security and Protection to Encourage Rather than Hindering your Revenue Streams and Customer Retention

  • Debating the legal question of who owns the data operator or customer?
  • Above the line: Analysing how you can utilise your big data through customers to ensure an increase in revenue whilst adhering to security and privacy regulations
  • Collecting data from a variety of sources and avenues to increase access to the customers data and reduce difficulties in rights to use of data
  • Introducing benefit schemes and discounts alongside waivers and opt-out schemes to avoid stringent data protection laws and increase the benefit of the customer

4:50 PM - 5:00 PM Chairmans Closing Remarks and End of Conference