Executive summary
More and more of business insights are locked up in human data, which has traditionally sat outside the data warehouse. By identifying these new data sources and implementing new approaches for processing them, telecommunications companies can make the efficiency savings they need, increase cross-selling and improve customer experience, and ultimately make an impact on their bottom line.
In today’s increasingly competitive and cash-constrained operating environment, telecommunications companies are seeking to extract maximum business value from the data they collect. To address these challenges they are turning to data warehouses which offer tried and tested technology and familiar processes. However, more and more of the business insights are locked up in human data, which has traditionally sat outside the data
warehouse. By identifying these new data sources and implementing new approaches for processing them, telecommunications companies can make the efficiency savings they need, increase cross-selling and improve customer experience – and ultimately make an impact on their bottom line.
A missed opportunity
In an increasingly competitive, regulated and financially-constrained market, the future for telecommunications companies – telcos – looks challenging. The price they are able to charge for ‘business-as-usual’ voice traffic has declined by 10-15% per annum over the last decade, and European legislation is continuing to drive down roaming charges and termination rates. The ‘data explosion’ has driven up network costs yet revenues from consumer data services have failed to fill the gap because ‘overthe- top’ service providers are invading markets traditionally dominated by large telcos. To add to their woes, the current economic crisis is also reducing discretionary spend on communications.
These challenges are increasing the pressure on telcos to deliver new revenue streams while simultaneously improving operational efficiency, and identifying revenue leakage from fraud and bad debts. In their attempts to achieve this difficult balance, operators are turning to data warehouses – monolithic stores of structured data collected from across the enterprise – to gain operational and customer insight.
However, telcos are failing to unlock the full value in their data. More and more of the data they are able to collect or access is unstructured – such as customer service complaints or emails – or does not fit the ordered model needed by most data warehouses. This data is often ignored because, although it might provide valuable business intelligence, it is too difficult to analyse or simply not perceived as being important. For example, on the operational side, this data typically records hundreds of millions of detailed transactions each day – for instance, call records or network events – and therefore generates vast data volumes which can only be stored for short periods before being overwritten. Low-level transactional data often requires extensive manipulation and transformation before it is in a fit state to be analysed and exploited effectively. This pre-processing requires extensive data-processing infrastructure and specialised skills, both of which many operators lack. To make matters worse, much of this data is stored in core operational systems where largescale extraction of data is neither easy nor common practice, and some information systems departments have been traditionally resistant to scheduling large data extraction tasks which may potentially interfere with mission-critical production.
