A framework to forecast demand for technology applications and business case for a new service

Abstract

Project Brief: This project will focus on understanding the user need, and forecasting the demand of technology applications. At a broader level the project would also look at forecasting product introductions in the convergence area and the key drivers for products in the web 2.0 era. The Project will specifically examine how the Lotka Volterra system of equations can be used to model adoption rates of technology applications in the presence and absence of relevant market data. An application of this methodology to a real IP and how the adoption rates will affect the business case will also be discussed. Need and Importance of the work: The mobile phone is becoming the least expensive computing device for the common man. With rapid developments in technology more and more applications are being developed for handheld devices and drive the vision of a converged world. A lot of Venture capital is pouring into the wireless handheld mobility space. This project looks at methods of forecasting demand and develops a framework that can be used to evaluate the potential success of mobility technologies and applications. Objectives: The objective of this project is to1) Develop a framework to forecast demand for technology and analyze the critical success factors for developing a business case for such applications. The project would feature a detailed business case as an example.2) Focus on how to arrive at adoption rates in the presence and absence of data given a window of opportunity for a technology.3) A business case will be used to illustrate how significant forecasting adoption rates are in order to evaluate the success of a technology venture. Methodology: 1. Use and enhance existing frameworks to analyze the Key Success Factors that drive adoption of Mobility applications.2. Market research of primary and secondary data for sizing the opportunity and evaluation of the Key Success Factors.3. Market segmentation and Product positioning.4. Competition analysis by studying development and growth of different players in the value chain5. Developing a forecast methodology using the Lotka Volterra equations to arrive at the adoption rate for different segments. The Bass model is used in the preliminary analysis. This model is a special case of these equations. Expected Learning:1. In-depth understanding of forecasting methodologies for new product launches in the presence and absence of data, given a window of opportunity.2. Application of financial forecasting, cash flow projections in the context of, performing scenario, and sensitivity analysis.Methodology:1. Market research of primary and secondary data for sizing the opportunity and evaluation of the Key Success Factors.2. Market segmentation and Product positioning.3. Competition analysis by studying development and growth of different players in the value chain4. Developing a forecast methodology using the Lotka Volterra equations to arrive at the adoption rate for different segments. The Bass model is used in the preliminary analysis. This model is a special case of these equations.5. Developing a pricing strategy for different segments with a focus on costs. The cost of providing this service is critical due to expensive wirelessbackhaul.6. Revenue share figures between alliance partners. Projections of revenues, costs and cash flow. Develop the business case from an operator perspective and ALU perspective Need Identification: This section analyzes the user need for such an application. From a study of end users and their pain points we can conclude that end users would like to have easy access to their data on a mobile device. The process for sharing data, user generated content must be seamless, automatic. Data theft or loss is a major concern and a pain free way of backing up data is very useful. Mobile Easy Share enables the consumer to forget about backing up his/her data. He can access his content anytime, anywhere and can share content generated by him on the move with anybody in a seamless manner. Data is organized in a intuitive manner across various devices and appears as a single unified folder on his mobile device. Market Sizing: This section sizes the overall market. We also make decisions regarding the initial target customer based on certain criteria. The size of the overall market is 1.7 billion subscribers with high end 3G smart phones by 2011. (Source Alcatel-Lucent Corporate Strategy and internal market sizing based on operator interviews).For the purposes of this project and business case we have looked at the Australian market and are working with Telstra a key customer for Alcatel-Lucent. The expected market size by the year 2011 in Australia is 10.3 million 3Gsubscribers. Telstra will have a market share of 37% of this market and close to3.8 million 3G subscribers. The current 3G subscription is at 1.02 million.