Data to Decision: What Does it Mean for Telco Industry
Recently posted a blog on analytics blog, repeating it here. The bitly for the published blog is above.
Are you able to seamlessly access data from your switches, network or transactional systems, instantly and painlessly to make decisions? Seems like a dream, doesn’t it? But what if you did have a business intelligence (BI) architecture that enabled you to access and process large amounts of data at line-level detail and in real time?
You might say that it isn’t possible today. The data volumes would be too large to be handled by the limitations of your current IT infrastructure. And besides, the response times would be too slow to be practical.
But that’s not true. The innovations in BI systems are moving in just that direction. Thomas Davenport is a Visiting Professor at Harvard Business School, where he teaches in the Technology and Operations Management unit. Davenport has worked with SAP to draw a distinction between “systems of record,” which are transactional systems like ERP and CRM, and “systems of engagement,” which are data warehouses/data marts used for analysis and interaction and that engage employees in collaboration, networking, exchange of information etc. With innovations in BI, this distinction is beginning to blur, making it easier for decision maker to access real-time data as it changes in transactional systems.
The business decision maker and information worker of tomorrow will have sophisticated data discovery tools and fast BI appliances, in-memory data bases capable of handling millions of rows of data and processing queries in real-time. These will make “Data to Decision” a reality for BI, and the two systems will blur together, enabling very fast access to data and decision making.
In-memory databases are providing 3000 times better query performance and are handling millions of rows of data in sub-second response times. For those of you in the Telco industry, it means that you can analyze millions of call detail records (CDRs) directly off of your switches or data off of your network before summarization to find many aspects related to customer experience like number of call attempts, dropped calls, call aborts, etc. and enhance customer experience by responding to it in real time.
Consider the example of a subscriber or number of subscribers playing an on-line game on a slow-speed line or a line that is congested. If you could analyze this information in real time and market higher bandwidth to them by reaching to the network of players while the session is still running with an offer to upgrade to a higher bandwidth for the duration of that session, you could not only improve customer experience but also generate more revenue.
If you could detect fraud as it’s happening and stop it, or you could combine and analyze your subscriber data with network data, segment your customer more granularly and predict their behavior with accurate predictive models that the business users can create and modify themselves, then you would achieve the promise of self-service BI. You could provide daily monitoring of campaigns and promotions like a major US mobile operator is doing and have the mobility to modify them based on popularity and take-up by the target segments, and team up with retailers and specialty service providers to make just-in-time offers and promotions based on subscriber location and interests.
The possibilities are endless and the technical capabilities to make it happen exist today. To learn more about how SAP can enable your vision of the future with innovations available today, visit www.sap.com/BI.