Product Economics And Profitability

Product Economics And Profitability

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Forecasting can be broadly considered as a method or a technique for estimating many future aspects of a business or other operation. There are numerous techniques that can be used to accomplish the goal of forecasting. While the term "forecasting" may appear to be rather technical, planning for the future is a critical aspect of managing any organization;business, nonprofit, or other. In fact, the long-term success of any organization is closely tied to how well the management of the organization is able to foresee its future and to develop appropriate strategies to deal with likely future scenarios. Intuition, good judgment, and an awareness of how well the economy is doing may give the manager of a business firm a rough idea of what is likely to happen in the future. Nevertheless, it is not easy to convert a feeling about the future into a precise and useful number, such as next year's sales volume or the raw material cost per unit of output. Forecasting methods can help estimate many such future aspects of a business operation.
All forecasting methods can be divided into two broad categories: qualitative and quantitative. Many forecasting techniques use past or historical data in the form of time series. A time series is simply a set of observations measured at successive points in time or over successive periods of time. Forecasts essentially provide future values of the time series on a specific variable such as sales volume. Division of forecasting methods into qualitative and quantitative categories is based on the availability of historical time series data (Ulrich, et al, 2004).
Qualitative forecasting techniques generally employ the judgment of experts in the appropriate field to generate forecasts. A key advantage of these procedures is that they can be applied in situations where historical data are simply not available. Moreover, even when historical data are available, significant changes in environmental conditions affecting the relevant time series may make the use of past data irrelevant and questionable in forecasting future values of the time series. Three important qualitative forecasting methods are: the Delphi technique, scenario writing, and the subject approach.
Quantitative forecasting methods are used when historical data on variables of interest are available—these methods are based on an analysis of historical data concerning the time series of the specific variable of interest and possibly other related time series. There are two major categories of quantitative forecasting methods. The first type uses the past trend of a particular variable to base the future forecast of the variable.

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As this category of forecasting methods simply uses time series on past data of the variable that is being forecasted, these techniques are called time series methods (Ulrich, et al, 2004).
The forecasting method that fits Reliance Communications is the Technological Forecasting method used to analyze the market for new and existing products/services.
The Technological Forecasting method is used to analyze the market for the life span of an existing technology to determine if its close to end of like and to see if a new product or technology is ready to enter an existing market. It is also used to identify competing new technology and to forecast sales. Before a new innovative product enters into the market Technology Forecasting is one of several methods used to determine if customers will buy it. The Technology method should always be used in conjunction with other tools to identify prospective customers, prototypes, focus groups, interviews, market testing, internet polls and other tools to get a better understanding of the market.
The major techniques for technological forecasting is numeric data and judgmental. Numeric data-based forecasting extrapolates history by generating statistical fits to historical data. Judgmental forecasting can also be based on past projection but like the Delphi method it relies on the subjective judgment of experts. Keep in mind that technological forecasting is most appropriately applied to capabilities, not to the specific characteristics of specific devices. Technological Forecasting in conjunctions with other tools helps the company identify prospective customers, timing for new products/services entering the market and when a current product/service or piece of equipment is reaching end of life span. The company is continuously entering new global markets where they need to identify prospective customers and determine which products are ready to be introduced in the market. Global markets are always difficult to forecast because of the different cultures and the use of Technological Forecasting can help with market analysis. Reliance communications collects data through surveys, focus groups, customers and supplier's interviews and feedback. They also test the market by sending out sample products/services to customer, suppliers and employees and then solicit feedback. Reliance Communications goal is forecasting business performance more often, more effectively and simplified, standardized, to lower-cost work streams throughout the company (Reliance Communications, 2008).
Research Methodology
Objectives of research
• To study the purchase patterns of Reliance Communications customers in Indore
• To identify the influencing factors on the consumer’s buying process
• To profile the customers on the basis of their characteristics into different clusters
• To study where Reliance is lacking in the terms of important service attributes
• To study the overall service attributes and find out their percentage contribution to overall satisfaction of a Reliance Customer
The research method applied was to first conduct an exploratory research in the form of focus group discussions. Two focus group discussions were carried out to gain an insight into the preferences of the consumers and factors on why they chose their family plan services. The participants were first informed that the discussion was to be based upon their preferences in selecting a family plan service. The participants were encouraged to discuss various issues and views about their current and past services. These discussions were moderated in an attempt to gain the maximum insight into customer preferences. These discussions were recorded and salient points were noted down. On the basis of the findings from the focus group discussions, a questionnaire was designed to extract information for the project. The questionnaire tested certain beliefs and attitudes of the customers on parameters by which they select any particular service.
The Sampling Methodology
This tool was then applied on a sample of 78 respondents in the city of Indore.
Due to constraints, a probability sampling was not possible. Neither was only one particular method followed while using the tool.
The following analysis techniques were then applied to the collected data,
• Discriminant Analysis
• Attribute Mapping
• Fishbien Analysis
• Perception Maps
Discriminant Analysis
A Discriminant analysis was done to see how these clusters map in the scatter distribution to the various attributes important to a product obtained through factor analysis.
Fishbein Behavioral Intention Model
To judge the overall brand perception, the factors’ contribution to the overall brand perception is measured. The following equation is derived from the analysis
Service Perception = 0.36*CR + .28*NC + .22*RR + .18*PS
Where CR = Call Rates; NC = Network Coverage; RR = Response to service Requests; and PS = Promotional Schemes
This means that the most important feature contributing to brand perception is the Call Rates with a 36% influence. This is also in line with the cost consciousness of the average Indian consumer. After Call Rates, we have the network coverage contributing 28% to the perception of the service. With more and more people traveling across India these days, both on business as well as pleasure trips, not having wide network coverage is seen as a major minus. Network coverage has started to be perceived as a hygiene feature. At 22%, response to service request occupies the next slot for contribution to perception. With increasing mobile subscribers, so will the number of service requests. A prompt response is looked upon quite favorably by the end users of the product. Promotional schemes, with 18% contribution to the brand perception is something we can see quite openly around us with almost all the major players in the market coming up with several promotional offers over the entire year.
Attribute Mapping
Reliance scores the highest on call rates. Reliance is also just behind Hutch on promotions. This is another indication that because Reliance offers so many schemes and promotional offers over a wide range, its prices are perceived to be quite competitive. Hutch is also leading the way in service response where Reliance is lagging, coming third from last. In terms of network, Airtel is by far the best with Reliance a tight third.
Perceptual Mapping
This technique is used to see how a particular service is perceived on the various attributes taking two at a time. The Call rates in the minds of the consumers are one of the highest for Reliance compared to other service providers. Further, the consumer seems to be spoilt with promotional offers, with almost all the players offering various promotional schemes. Reliance, Hutch, Airtel, Idea, and Tata have nearly the same perception about Promotional schemes among the consumers. From the survey it was found that the selection of a service was very much dependent upon both Price of the connection and call rates as well as the Promotional schemes that the company launches.
Network and Service Response were not rated highly by the users of the mobile phones. They were more or less resigned to the fact that there would be network problems and as well as unanswered service requests. The essence was that incase TRAI comes up with one number across all service providers then the attributes would become more important.
Recommendations
The segments thus formed and the components extracted indicate that different buyer groups have different decision variables, use mobile for different purposes and have varied perceptions about services/products. All the segments require different pricing strategies and hence Reliance should come out with different plans specifically targeting different groups. Reliance has an image of having high call rates and usage costs. Further, it comes out that Reliance is a user friendly service provider. Users have taken to Reliance essentially because of low call rates among inter-reliance calls. To call made to other networks its charges are higher compared to other service providers. Hence, Reliance should aim to providing higher network coverage, lower call drops, and more efficient response requests. This could be done by setting up more network towers and having a more customer friendly focus. Analysis indicates clearly reliance is popular among the youth because of low reliance-to-reliance calls. Family plans can attract more families to switch to Reliance because of the low cost. These callers use phone to call up their families. This target segment can be attracted by advertising in Television and internet. Also, word of mouth publicity clearly scores above all forms of information search, primarily because of it’s convenience and source credibility.
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