The study of customer selection and profit estimation –Q company as an example

• Main Authors: Chan, Leo, 詹吉鏞
• Other Authors: Kuo, George
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/40772094856170786175

碩士 === 國立政治大學 === 經營管理碩士學程(EMBA) === 99 === In order to evaluate cost performance, companies generally analyze individual customers’ business performances to gasp a main idea. However, most companies are unable to screen out specific customers afterward based on the results. This study hopes to provide companies a way to screen clients with higher credibility and estimate likely profits generated from different clients. Many Master degree dissertations in the past have touched topics related to evaluating customers’ profitability. Yet, there are not many papers defining figures throughout the evaluating process. Many ongoing research papers are in view of constructing profit models that emphasis on evaluating marketing and strategy analysis, while papers on in-depth customers’ business performance are comparably less and more difficult to conduct because actual information on business operation arerather difficult to obtain, and even with information at hand, the adequacy of the data must be taken into concern. Fortunately, I was able to acquire the relative data on appointed companieswithin a specific time interval, allowing me to study further into evaluating customers’ profitability. Hence, this study will be use existing data along with statistical analyzing tools to estimate return profits. This thesis investigates the server industry, including respectively four groups, the brand owner, network operators, system integrators and carriers- the main customers of this industry. The case studied in the thesis is an ODM server manufacturing foundry, which currently hasbusiness interaction with all four groups of customers. Taiwan's server industry is mostly confined to playing a role in ODM or OEM, whereas its contribution of server systems builds up to more than 40% of the production worldwide, excluding the barebones and motherboard components, where some customers require the final assembly to take place overseas, or to directly embed the motherboardinto the hardware rack of a specific data base.Accumulatingthese productions as well, Taiwan produces over 90% of the world supplies. With a growing set of customers,how to select customers now becomes incredibly important. With alimited amount of talented human capital, it is difficult to pick out a profitable customer to cooperate with. The case studies the actual operation of the server division of the company every month for the last five years, and uses it as the basis for further customer screening. In this study, we use the profitability of each customer as dependent variable, and manpower input and net profit contribution that significantly affect profits as independent variables. Using customer characteristics as dummy variables, we construct a model with multiple regression analysis identifying different customers’profitability, and compared it with actual operating conditions. Next, we used the regression analysis model we obtained on forecastingfuture profitability; finally, we explored how many existing customers and new customers can meet the screening criteria. The study found that selecting different amount of customers’ firms will result in a different regression model, but if there are a closeamount of major clients, its results of the expected profit will be very similar in reality in terms of direction. However, deviation in terms of forecasting profits can be more reasonably larger. Finally, the study can be summarized as follows: (1) the regression model can provide direction about profit, but can not precisely predict the value of exceeding profit. (2) after a period of time, it is required to re-examine the regression model, adding the follow-up information on new business performance, to ensure its applicability of evaluating current operation situation. Keywords： Customer selection Profit estimation Regression analysis