Kuwait’s Viva Telecom implements a data warehouse and business intelligence (DWBI) solution to benefit business operations, Pallavi Sharma reports.
As part of its ambitious path of strategic growth, Saudi Telecom operator (STC), began expanding its footprint beyond the Kingdom’s borders to international markets, forming
a network of businesses and investments in a number of countries across the GCC, Asia and Africa.
After an extensive feasibility research, emphasising the prospects it held for attracting international investments STC ventured into the Kuwait telecommunications space with its subsidiary Viva to deliver new, meaningful value to the market in Kuwait through
diversified outstanding services.
Launched in December 2008, Viva Telecom became the youngest telecommunications service provider in Kuwait. Key among the many challenges that the new service provider had to face was the task of having to compete with, and claim success over, two veteran players in the Kuwait telecommunications market- Zain and Wataniya.
Viva’s objective was simple enough – extend state of the art services to its clients while optimising staff performance. According to Arnold Ali Cender, DWBI (data warehousing/business intelligence) project manager, Viva Telecom, Kuwait the ability to
enhance relationships with new customers through the provision of innovative services built on a robust network, meant that first and foremost, the company needed to focus on the way the company was generating, storing and using its information.
“Faced with increasing competition in the local telecommunications market, we realised that it was essential to provide different stakeholders with timely, accurate and relevant information about the business and its operations. Sharing and storing information not only enables us to build transparent relationships with our customers and shareholders but also provides us the ability to cope with change and competition through more collaboration between the different business departments,” Cender says.
Calling the shots
For its launch in 2008, Viva Telecom had only made investments in the technology that was needed first to get the company up and running. To fulfill it’s information needs, Viva had invested in a reporting portal that provided basic operational reports. As the business and demand for Viva’s services began to grow, so did the need to invest in a more elaborate dand efficient data warehousing mechanism.
“We needed a solution that generated department specific reports, to cater to the unique information requirements of each business function. For instance, where the marketing department may require information associated with product launches such as cost of product, sales and revenue in comparison to other competitors in the segment, the sales department would require details associated with the performance of a particular customer segment, overall revenue, product or service specific revenue etc,” says Cender.
The senior management also felt that a data warehousing solution would serve well the organisation’s need to store and archive huge amounts of information in a more secure and convenient environment, and minimise costs associated with human errors, loss or damage, money and time.
In February of 2009, having clearly understood the need for a data warehouse solution and outlined the basic functionality that it wanted from the solution, Viva Telecom began looking out for a comprehensive data warehouse and business intelligence solution that would serve the needs of the organisation’s current as well as future information needs.
Cender says that when deciding on a vendor to work with, Viva Telecom takes in account not just the technical solution and its ability to integrate with the existing architecture, but also the vendor’s approach and ability to implement the project in the shortest span. “We also try and analyse the vendor’s expertise in the telecom vertical and consider references from other users who have worked with the vendor,” he says.
“We looked at various vendors such as Teradata, IBM and even some of the lesser known names. We analysed Gartner reports to study the different vendors. At around the same time, Oracle announced the launch of the Oracle Exadata machine and, although it may seem like a bit of a risk for us to have chosen a wholly new solution, it met our requirements best,” he adds.
According to Cender, the Exadata launch was a defining step for Oracle, which prior to the launch of Exadata separated hardware components from software elements. “The Exadata, machine integrated both components and provided a BI tool, data mining tool, data integrator and Extract Transform and Load tool (ETL). And these made up the main components of Viva’s data warehouse infrastructure,” he said.
Once Viva Telecom made its decision on the right platform to deliver its requirements, it began looking for a company that would act as the solution provider and project manager for the entire implementation.
“The search for these partners was done through RFP, where we invited a number of different players based on recommendations from Oracle to bid for a complete solution. We invested time in a detailed process of evaluating how the vendor, systems integrator, the solution and our existing infrastructure all fit together Mahindra Satyam scored the highest points and were chosen for the project,” says Cender.
“Another reason for choosing Mahindra Satyam, was what they call iDecisions, a telecommunications BI application framework. It’s a framework for different business sectors with data models and business reports, which we felt gave us a head start in terms of deployment. We had a set of basic guidelines that helped us decide how to begin and proceed with the implementation,” he adds.
Initiation
Viva began the implementation of the solution with the process of defining the sources of basic data, such as customer usage data, billing and payment data among others.
The next step was to analyse the information that could be gained from the different kinds
of data and the business areas that this information would relate to. Knowing all too well that a data warehouse implementation can take well over a year before reaping any semblance of benefit from it, the team decided to go ahead and follow the iDecisions framework to help them deploy the solution using a phased approach.“We needed the implementation to be up and running in a span of six months,” says Cender.
“The iDecision framework entails 17 different subject areas which we then split into four different phases based on business criticality. The implementation began in November 2009, with phase 1 including the deployment of the Exadata DW machine, BI servers and five key subject areas. This went live by the end of June 2010. Phase 2 went live by the end of September 2010, phase 3 by the end of November 2010 and phase 4 by the end December 2010. The entire deployment was expected to take 16 months but was successfully completed in a span of 14 months,” adds Cender.
“Applications and related data are listed and integrated to the data warehousing solution through this Oracle ETL tool. Each time, we had to do this, we got the owners of the operation systems to make the data available to us in an operational data store on a timely basis that fit into our schedule. The information was then extracted from that data store,” he explains.
According to him, the key thing for Viva was identifying the data required, building the operational data store [which skims the application desk to extract the data] and finally, pouring this data into the data warehouse or Oracle data integrator tool.
“The integration is a one way street from the operational systems into the data through
what we call the operations data store warehouse as project manager it was my job to coordinate with the different parties both internal and external. We set up a project steering committee which included representatives from Viva IT, Mahindra Satyam and Oracle. The steering committee met monthly in addition to holding weekly project meetings to keep an eye on the implementation progress,” he adds.
Reaping rewards
Cender says that the implementation did not pose any major challenges. Deployment was
fairly straightforward and timely due to time spent planning prior to the implementation
actually going live.
“The solution deliver on its requirements through the provision of regular KPI reports,
management dashboards and drill downs. It has also resulted in significant cost savings through the elimination of old reports and human errors associated with manual report
processing,” Cender states.
He believes that as the business continues to thirst for information to help create a unique user experience and gain a significant competitive advantage, the company continues to feel the need to build on top of the existing DWBI platform.
“We have already established an MIS Team to deliver adhoc reports, and are in the process of implementing targeted analytical tools on top of this suite, which will cater to the marketing team’s need for more information,” he says.
“We have also begun working on what we call BI fast reports, more analytical and detailed reports associated with the daily operations. This will make the DWBI platform the single version of the truth, where every department get relevant information from one central repository,” he adds.
In Cender’s opinion, the most important thing is for a platform of this nature to gain credibility amongst its users. “It is natural that where information is concerned, decision makers will check, analyse and reconcile everything to make sure that it is accurate. In that sense, we at Viva have managed to gain the trust of our employees, who are now increasingly comfortable with basing their reports on automatically generated analytics to present their case to a senior manager,” he explains.
“Now that we have the platform, we can build on top of it, we can add more areas, add new types of data and extract more intelligence from wider sources of data. We can link with different network elements to provide more detailed analysis of the customer and provide detailed transaction information. This is what we are looking at now,” says Cender.
He believes that as IT becomes much more central to business operations different stakeholders are increasingly depending on the ability of technology to accurately derive information of consequence from both structured and unstructured sources of data. The use of social networking platforms for business and marketing, have driven the need to study different types of data.
“We are not there yet. While our daily information is sufficient at the moment, in the future, there may be certain areas that would benefit from real time feed like linking trends to the call centre so agents have more insights into what kind of products or services customers are investing in,” Cender predicts.
