Posted: September 2007 C: Business Intelligence Posted by: K. Panayotakis
The very complex issue of business intelligence in telecoms is tackled in this paper. The complexity stems from the fact that both the market and the internal organization of a telecom operator are very complicated and dynamically changing.
The imperative need for competitiveness & flexibility in the highly dynamic & competitive market environment, is rendering the issue of business intelligence extremely important.
In the modern era, a telecom provider is operating in a
highly complex (regulated, internationally linked), fast changing, and
extremely competitive environment in which new competitive products and
services are launched almost every week. Many market factors are changing
frequently (competitors, new entrants, mergers & acquisitions, economic
conditions, positioning of competitive products, technology factors enabling
new products or value added services, regulatory decisions) thus affecting
the market balance and the relative strategic positioning of competitors
while producing opportunities
The complexity of a telecom business is very high, given
operations (focusing on some of the most critical process areas) like:
• Telecom network resource management: a telecom operator has to manage
efficiently complex telecom network resources, in order to optimize the
telecom service offered: improve the quality of service, reduce the time to
order fulfillment, reduce the number of network infeasibilities. The
complexity of various telecom networks owned by a large operator (e.g. fixed
& mobile telephony infrastructure, data networks and the involved
resource-facing business units (respective technical departments))
• Customer relationship management: a telecom operator with a complex
product portfolio offered to a complex set of customer segments (residential
& business) via a complex organisation of Customer touch points (CTPs), has
to deal with the support of very complicated CRM operations on: customer
inquiries, order management, sales management, billing & collections,
problem & fault handling, QOS/SLA management. Handling different customer
segments and channel segments can be a very challenging task.
• Partner relationships management: a telecom operator is exchanging
information on network usage (CDRs) with other operators and may be
reselling products of other telco providers. Order management and billing
systems of both parties, need to be synchronized.
Major Telcos generally manage thousands of discrete
business processes, to run their operations. To automate a subset of
critical processes, they typically operate tens or hundreds of BSS/OSS
software applications. Moreover, to achieve end-to-end process automation,
application integration is required. Consequently, process automation
complexity is high.
In the modern era Telecom providers have to go far beyond
:
• the product centric approach
• the ‘blind’ support of operations (not being able to identify improvement
opportunities )
• The ignorance of residential customer’s profile leading to impersonal
handling and inability to achieve satisfaction & loyalty
• The manual /personal / empirical handling of business customers by the
Account manager
• The unfocused ‘mass marketing’ which entails massive cost and an ROI which
is not competitive
• The aggregated only understanding of cost structures which may produce a
biased picture (aggregates lie!)
• The design of telecom network development plans based on semi-manually
processed and aggregate picture of service demand
• The limited understanding of customer needs/ preferences (voice of
customer) as well as the limited understanding of the customer value (past,
current, future value potential)
Modern telecoms business intelligence involves many different subject areas:
• Customer intelligence • Operations intelligence • Profitability & Cost structure intelligence • Product performance intelligence • Pricing analytics • Competitive intelligence • Network resource demand, availability & utilization intelligence
Achieving state of the art competencies, in all above mentioned subject areas does not come easy or in a single project. Therefore each Organization should set value driven priorities in developing the above business intelligence capabilities.
In the following sections we shall analyze each of the above subject areas.
Customer intelligence is a complex business intelligence discipline in telecoms given, the varying Customer groups (personal, household, small business, large business) and the respective differences in needs, products offered and service channels (customer touch points) used.
Customer analytics Information can be captured via multiple customer touch points (call centers, web channels, shops, account managers) and external sources. Achieving the Customer’s Holistic view should be a goal and may be a challenging initiative. (view recent article on Customer information architecture).
Customer intelligence may support business goals like: • Understanding customer preferences in order to adapt products accordingly • Customer retention & value building • Value based Customer management
In the area of telecoms, there is a high potential to capture Customer behavior by using the CDR (call detail records) and/or IPDR (IP detail records). A wealth of information on the Customer behavior vis-a-vis usage of the telecom service can be derived from these records. A series of traffic metadata can be derived from these records.
Moreover, info captured on the BSS/OSS of the telecom provider related to customer interactions can be used to compile the Customer Holistic view.
Furthermore, the telecom provider is able to perform customer surveys in order to further develop its understanding of Customers (gathering of qualitative data on customer needs, preferences, key drivers of customer behavior and decisions).
In order to apply Value based management on Customers, a value ranking needs to be measured for each customer. Value ranking on telecoms customers may vary according to the ranking complexity- sophistication:
• Revenue only based ranking (based only on invoiced- collected amounts by a customer in a given period) • Profitability based ranking which takes into account revenue and cost information. Cost information involves cost to market / sell / serve / maintain telecom services and respective customers. It may be complicated to assign these costs per customer. In that case an average cost may be applied to yield a Customer profitability proxy.
• Value ranking according to the proactive customer interactions: sales inquiries, orders, service inquiries, billing inquiries, fault declarations, complaints, marketing campaign contacts, service upgrades, are events which can be captured and used in order to evaluate the Customer’s relationship, attitude towards the telecom provider and ultimately Customer’s value.
• Long term value ranking (also called Lifetime Value ranking ) requires an estimate of the future revenue expected from a Customer. A prediction on the customer tenure and the average value per period is needed. This prediction is not an easy task.
The ability to monitor operations and measure important operations performance aspects is a prerequisite in order to manage these operations efficiently and aim at continuous improvement.
The operations of a mature Telecom enterprise can be very complex as described above. Different customer segments may be served by different channels, by employing varying process steps or activities. Furthermore, internal operations (non customer facing operations) to develop network resources, to enable marketing of new services, to activate service requests, may be complex and may vary according to the service type.
The ability to measure all involved steps, as well as the whole end-to-end process, in terms of: • Time to complete (a factor related to productivity) • Cost to complete (in terms of man hours spend and infrastructure / material usage) • Process Quality (i.e. in terms of following the right steps in the process) • Information quality (in terms of capturing complete/accurate/clear information during the process), allows the analysis of operations. Analysis relates to: • the comparison of actual performance with acceptable levels of operations in terms of time/cost/quality • the identification of deviations from the acceptable operations levels • the identification of trends
and aims at developing actionable insight: analyzing causes of findings and producing ideas on ways to handle issues. The reporting framework should enable this ‘actionable insight’ mechanism by providing rich context for the findings.
According to the Enterprise structure and the current Enterprise status, priorities may be set vis-à-vis operations performance improvement. The above prioritization may provide guidance in order to steer the operations measurement and analysis efforts. Critical KPIs specific to telecom operations may relate to: • Order handling & service activation of high demand services (like ADSL) as well as data products which have complex & time consuming service activation steps (like MetroEthernet) • Fault handling & resolution processes • Product lifecycle management processes • Marketing campaign management processes
Apart from the Profitability & Cost structure per Customer, which can support Customer-value based management (alternatively called ‘value based servicing’), a Telecom Organization needs to measure cost efficiency and profitability at all potentially important operations levels. In the case of a Telecom operator, such levels are ( in a bottom-up reference according to TMF’s eTOM standard value chains): • Network resource management lifecycle • Other resource management lifecycle (i.e. IT infrastructure) • Product/ service management lifecycle • Customer relationship management • Channel management lifecycle • Cost or profit center (i.e. a NOC)
Following a more detailed process view, cost /profit analytics may focus on per service order use cases (i.e. service activation order, fault resolution order).
Cost structure intelligence supports the development of competitive product pricing.
The Organizational ability to capture cost accounting information at a detailed operations level, enables the above mentioned analytics capability.
Competitive pricing analysis (gather competitive info and produce a comparative analysis on competitive product prices, for various telecom service usage scenarios), is very valuable in order to understand the positioning and the market threats.
Identify the optimum price plan for a specific Customer, based on telecom service usage. Identify the ‘distance’ between actual price plan & optimum price plan for a given Customer (distance in terms of invoiced amounts).
Impact of price discounts on revenue (in an advanced approach this revenue impact evaluation can be carried out, based on actual CDR repricing).
Furthermore, new price plans may be developed by analyzing telecom service usage (based on CDR analysis and use of clustering techniques (data mining)).
Finally the degree of cost sensitivity of certain Customer segments in the telecoms market, may be evaluated via Customer surveys (price elasticity of demand for various price ranges may also be valuable, to evaluate the effect of price changes on Customer demand).
In a dynamically evolving telecom market, in which every week new services / new product bundles / new price plans or discount plans are offered, proactively monitoring & analyzing competitive offerings in terms of product specs / product pricing / discount plans, is a challenging task which telecom operators cannot afford not to carry out. The ability to perform this task in a timely fashion, in order to analyze fast the competitive landscape and proactively & timely steer own product positioning, is of great importance.
Apart from competitive analysis on pricing, Competitive intelligence may involve analysis of other strategic factors, which may lead to competitive advantage or disadvantage. The knowledge of competitor performance in terms of Customer service contributes to the understanding of market positioning. I.e. the ability to analyze competitor performance and/or differentiation on Call Centers or Web channels, is important.
Analyze network resource demand trends & produce forecast for the future demand. In order to carry out this analysis, core network utilization can be monitored on the network management systems on selected network resources.
Analyze resource availability in order to combine resource availability & additional demand forecast and drive plans for informed network resource upgrades.
Moreover, network resource availability can be measured on the access network. Ports on Customer edge network nodes, available to offer services in specific geographic regions, is an important factor which should be compared to the demand of the respective service, in order to sustain service availability and support service order fulfillment in an effective way.