Reducing the Uncertainty of Techno-Economic Evaluations in the Telecom Sector

1. Reducing the Uncertainty of Techno-Economic Evaluationsin the Telecom Sector Erik Vanhauwaert, Sofie Verbrugge, Mario Pickavet Erik.Vanhauwaert@intec.ugent.be • www.ibcn.intec.ugent.be/te Techno-Economic Evaluations Important Input Parameters • Market penetration over time • Typically an S-curve (e.g. Rogers, Bass, …) • What about competition effects? • What in case of failed launch? • Initial prices of relevant components • Estimated using list prices of (similar) equipment, but • B2B prices often unknown to outsiders • What about equipment that is not yet available? • Price erosion • Assumed to follow the Extended Learning Curve principle • Real price modifications occur in jumps • Can Telecom equipment be classified in more detail? Goal: 1. InputsE.g. Number of users Improve the Assumptions 2. ModelingE.g. Network dimensioning Implementation 3. EvaluationE.g. Net Present Value Example: Mobile Video Costs & Revenues • Network Operator LinkyWinky wants to launch a mobile video service for its customers. • Critical input assumptions • Number of customers • Cost of mobile network equipment • … • Technical solution • New network required (e.g. LTE) • Video streaming servers • … • Techno-economic evaluation • Bill of Material for network infrastructure • Operational costs (wages, energy,…) • Revenues • … •  LinkyWinky knows better what to expect: Reducing the Uncertainty of Techno-Economic Evaluations • Why? • Telecom projects = huge budgets & rapidly changing environment •  High stakes • Garbage In, Garbage Out-syndrome • How to improve (use of) existing models? • Use historic data for • Model fitting & selection • Parameter classification system • Identification of influencing factors • Investigate post-launch corrections of the model • This can be used pre-launch for Real Options Techno-economic Model or ?