STEM applications and examples

Service costing and profitability analysis

Every responsible carrier business must measure the unit costs of the services it provides as a critical benchmark for determining a pricing strategy for long-term survival.

Market-driven tactical pricing must be balanced with the fundamental requirement to cover costs with a core margin in the long term. Operational efficiency improvements can also only be made based on an initial understanding of the cost breakdown of services.

An integrated service provider may deliver tailored solutions to customers in a variety of service packages, drawing on core capabilities in PSTN, Internet, and data connectivity. Understanding the underlying costs, and especially the common network costs (the synergy which defines the modern carrier business) will depend critically on the ability to relate each separate offering to a common, manageable and forward-looking network cost model.

While enabling an operator to evaluate the impact of multiple pricing scenarios on its short-term cashflow and long-term profitability, STEM (Strategic Telecoms Evaluation Model) also automatically calculates the unit costs of all services provided on a telecoms network, broken down at the modeller’s discretion into access costs per line, backbone network costs per Mbyte or simply total costs per minute.

STEM is closely integrated with Excel, allowing the analyst to benefit from the power of STEM’s template replication technology: automatically reproducing sub-models across separate regions or network areas for greater market segmentation and accounting separation, while keeping the inputs and outputs compact and accessible.

Modelling the network business

STEM is optimised towards the rapid development of service costing models, enabling the modeller to develop a high-level, GUI-driven view of the network business structure:

  • Describe the network business in terms of the service packages offered to customers, the underlying network capabilities which carry those services (such as PSTN, Internet or server hosting), and then the specific technological configurations in the network.
  • Model the individual factors which relate the connection and traffic load on the network to the physical infrastructure, making critical allowances for geographical deployment, forward planning, overhead capacity and redundancy.
  • Extend the cost and revenue analysis to capture the human and administrative functions of the business in the same consistent framework, factoring in the economic value of these functions and elasticity of demand with respect to perceived quality of service.
  • Use a simple ARPU model to short-circuit the complexity of discounted calling schemes and bundled-minutes packages and focus directly to the reality of users’ spending constraints and the implications for the business model.

Service costing process

Cost allocation on a causal basis

Unlike an OSS-driven costing exercise, which may deliver unchallenged accuracy and detail in the current or recent costs of a network, STEM links forecast demand scenarios directly to forward-looking revenue and cashflow projections, enabling you to:

  • measure the sensitivity of future profitability to variations in actual service take-up on the basis of adaptable month-by-month model outputs up to 24 months ahead
  • explore the potential for increased revenue yield on the fixed asset base of the existing business through the re-configuration of service packages and the underlying network
  • evaluate offline the implications of tentative cost-cutting programmes, using product and customer profitability metrics to balance engineering and service objectives.
Overall revenue and charge per customer Service profitability by segment

STEM’s intrinsic cost-allocation mechanism automatically associates network costs with those services which require the corresponding capacity. Where multiple services share the same capacity, costs are allocated in proportion to demand by default. Optionally, and for each individual element, these proportions can be artificially weighted or driven by revenue rather than demand. This causal model determines robust benchmarks for service pricing decisions based on fully-allocated and activity-based cost results, plus direct-cost results which identify the cost of the fully efficient network for optimal competitive pricing.

Our expert practitioners can work with you to help develop these ideas as they apply to a business, working closely with the STEM development team to extend the existing algorithms where necessary to meet the exacting requirements of our clients.

Professional network modelling tool

STEM is purpose built for creating cost models of large networks and is optimised to manage very large, repetitive model structures. The built-in cost-allocation functionality is made feasible by the logical separation of structure, data and generated calculations which enables these models to be agile with respect to modification and extension. It would be almost impossible to guarantee the integrity and consistency of such calculations if they were made on an ad hoc basis.

STEM has the power to communicate business logic, and to iterate model structures with speed and confidence. Decision makers will have greater confidence in models built on a reliable, industry-standard business-modelling platform.

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