Information And Methods In Business - Research Paper Example

INFORMATION AND RESEARCH METHODS IN BUSINESS This paper addresses two sets of fundamental questions of methodology in business research. First, how can we use statistical analysis to identify, summarize, and analyze product quality problems? Second, how can we organize a good information loop so the relevant information reaches the right people? Related to this, how do we assess, organize, and implement a good information loop within a business? We address first the former question and then the latter and generalize the relevance of research methods in business and how problems and needs for information can be considered as fundamental research questions that can be continually addressed in a business research system. Immediately prior to the generalization, however, we review the recent literature immediately available on the topic to reexamine our perspective and build our generalizations on a more stable foundation. 1.0. Statistical Analysis in Product Quality Problems There are three basic ways of identifying, summarizing and analyzing product quality problems. One basic way is to identify, summarize, and analyze product quality problem from the point of view of the consumer. The second basic way is to identify, summarize, and analyze product quality problems from the viewpoint of distributors. The second will only be applicable for businesses that tap distribution companies for a product. The third basic way is to identify, summarize, and analyze product quality problems from the point of view of our retailers. Like the second, this will not always apply for all types of businesses. Finally, the fourth basic way is to identify, summarize, and analyze product quality problems from the perspective of quality control and of a quality control system. 1.1. Product Quality Problems as Perceived by our Consumers In identifying product quality problems as perceived by our consumers, we can implement two kinds of research. One research can identify, summarize, and analyze product quality problem as perceived by the consumers of our product. The second research can focus on the target consumers of our product and identify, summarize, and analyze product quality problems as perceived by the target consumers of our product. In doing a research on quality problem among our consumers, we may want to follow the statistical protocol with regard to computation of the percentage of our consumer who desires certain changes or improvements in our product. A good material for this is Walpole et al. (2007, p. 299-302). For estimation related to means, Walpole et al. (2007) is also useful but one may wish to supplement the discussion on the material with insights from Dekking (2005, p. 341-355) and Urdan (2005, p. 7, 25-31). For our consumers, it may pointless to ask if they are satisfied with our products because most likely we would be repeating the research and their use of our products is an indication enough that they like our products. However, we may want to find out why they patronize our products and what improvements they desire for our products. The information will be important for product design and development. In contrast, in doing a research on both the users of our products and the users of the products of our competitors, we may want to find out why they like a product and what improvements that they want from the product that they are using. Again, the statistical protocol on population proportion estimate based on sample proportion estimate will be useful. Doing a consumer research we have described require an investment of a considerable sum. If we have serious budget constraints, we may focus either on the first or on the second. Both researches can result to information that will be useful in improving our product quality. Of course, one possibility is that our product is actually services and a “simple” product quality research applicable for our business concern is to hand a customer satisfaction questionnaire for our client as well as questionnaire integrated to this questionnaire that inquires how we can improve the quality of our service to our clients or consumers. 1.2. Product Quality Problems as Perceived by Distributors (when applicable) In identifying product quality problems as perceived by our distributors, our business can conveniently create a simple quality check system. The focus can be on the question: did our product reach you in their best quality? A simple yes or no answer supplemented with requests for an explanation from respondents who answered “no” to the question can suffice. The quality check questionnaire can be brought to our distributor on every delivery and we can request them to assign the appropriate personnel who can serve as our respondent for the questionnaire. There must be a space on the questionnaire to identify the batch deliveries covered by the questionnaire and the questionnaire can address quality checks on previous deliveries unless, of course, there are immediate concerns related to the current deliveries. We need not be strict on who our distributors will assign to fill up the questionnaire but our delivery personnel must be keen on requesting the right person who will be filling up the questionnaire. After all, we are using the time of our distributors and not of our personnel. Our questionnaire, of course, must have a space so the respondent can fill up his or her name and her position in the distributor company. The business organization implementing the product quality check should assign the appropriate personnel who will process the questionnaires received from our distributors. The summaries can be simple. First of all, we can identify the percentage who responded “yes” and “no” to our question. We should try to get a “yes” or “no” answer but it is also possible that our distributor will not make a response and so there must be space to accommodate this possible kind of a response from our distributor. Our main interest will be on the “no” answers. Beside the “no” response should be an open-ended question like “why?” and there must be about eight lines where our respondents can write the reasons why they responded “no” to the question “did our product reach you in their best quality?”. Our delivery personnel must also be instructed to interview further the respondents who made a “no” response to see to it that their response to the “why?” will be detailed enough. While the “yes” and “no” response can be summarized through percentage statistics, our personnel assigned to summarize the response from our distributors must be keen in categorizing the response, if the response to the question “why” are so many. The point would be to identify the concerns or problems expressed by the distributor with regard to our product. Most likely, as they are not necessarily the consumers of our product, the respondents from our distributors would cite problems related to product packaging or problems related to the state of the packaging of our product or problems related to our product that are visually obvious. The personnel assigned to do a summary report on the “yes” and “no” percentage computations as well as the reasons for the “no” should report to management. Management, in turn, should act on the report, of course. Management decisions and actions will be facilitated if the delivery system has a system for assigning delivery numbers to delivery batches and associating the delivery batches with the production batches and production and/or plant units. 1.3. Product Quality Problems as Perceived by our Retailers (when applicable) This will apply for businesses that rely on retailers for the distribution of the product. Service companies or businesses that provide services or goods will probably not require retailers for product distribution. Businesses that rely on retailers must strive to allocate funds for research among retailers. Not all retailers can be covered by the research. A random sample of 30 and above will probably suffice. Several fundamental books in statistics point to 30 as the large sample where statistics related to the mean can be computed at a desired confidence level (usually 90, 95, and 99% confidence level) using the standard normal curve statistics or Z-statistics. Statistics with regard to proportions can also be estimated if the sample size is at least 30 but the standard error will be relatively large. Depending on the availability of funding and personnel time allocation, larger sample sizes should be used based on the sample size protocol using the protocol for estimating population proportions based on the sample proportion. 1.4. Product Quality Problems as Production Quality Control (when applicable) Our production systems must have a built in quality control system. Quality control systems using quality screening based on product characteristics that can be immediately assessed visually must be built into our production system. For example, if our product is soap, then products not meeting the target sizes for our soaps can be screened out either manually or mechanically. In the case of soap, we may also decide to screen out products that do not meet our company standards for the fragrance. If our products are breads and pastries, we may have standards for their sizes and looks and we can immediately screen out the products that do not meet our company standards. However, there are certain products that may have an elaborated quality control system. For instance, we may have life tests for batteries, bulb, and voltage tolerance of electrical products. We may want to do tests on the lives of these types of products based on a sample. Whenever, resources (financial, material, and human) are available for this type of a test, we should do them. Statistical theory has a set of standard protocols that can be used to determine the appropriate sample size for a target error. These protocols must be incorporated in our research design related to production quality control. At the same time, our business involvement may be in the provision of services. In this case, production quality statistics may be easier to gather and assess. For instance, our production quality system may simply focus on whether a target quality was achieved and the time it took us for realizing the target quality. Work can be divided into phases with each phase associated with a target quality. We may want our quality control assessment system to be installed at each phase of the work. 2.0. Creating and Implementing a Good Information Loop in Business The function of creating and implementing a good information loop in business is fundamentally a key function of management. Of course, management can also have the option to create an office to address the function on behalf of management. Alternatively, the office can lead in the design of the information loop proper as well as in the design of the implementation system for the information loop and management may just require the office to improve further the two designs (the system proper and the implementation system for the information loop) or approve the design as management sees fit. An important concern of a good information loop is that we have the relevant information reaching the right people. Assessing problems in the information loop, organizing, and implementing a good information loop is important for business because a good one ensures that management is able to act quickly and correctly. Whether directly initiated by management or initiated by the office assigned by management, the establishment of a good information loop can be undertaken in the following manner. First, call the main offices or personnel business assigned to marketing, sales, distribution, production, and administration to a meeting. One of the first agenda of the meeting is to identify problems with regard to the information loop or to set up one. In the meeting, it is important that the most important personnel are present because it helps ensure that the problems with regard to the information loop are assessed from the perspective of the most important personnel of our business. Another important agenda that must be discussed is to identify the key information that must be monitored by the business. The information may be related to consumer preferences, quality problems as perceived by the consumer, marketing or distribution problems, and collection of payments, personnel performance, and the like. The third agenda must identify the following how the information should be collected how regular the information will have to be collected based on the costs figures of collecting the information assignment of who will have to collect the information with whom the information collected are to be reported and in what form (word files or excel files for instance) the person or office-in-charge of summarizing the information and producing the reports to management the schedule of producing and sending reports the quality desired for the report the sanctions for failure to submit the report in time and in a desired quality. The fourth agenda must identify the regularity for discussing the report and the body who will discuss the report. That body may be a management committee or staff of the business. Agenda 1 to 4 can be done in a single meeting, in a series of meetings, or in management or business conference. From thereon, regular meetings must be done for the following: hear reports on and discuss the information gathered from the information loop hear reports on how the management information loop is being implemented discuss problems encountered with regard to the implementation of the loop and the actions that will have to be done by management assess whether adequate and relevant information are reaching the right people in a timely manner and decide on the corrective measures that management and the organization will have to do based on the situation. The foregoing discussion implies that management will have to make decisions and act. In addition to agenda 1 to 4, it is highly likely that information and survey forms will have to be designed. The meeting or conference should identify the data gathering tools that will have to be designed (making it simple and feasible to implement are important considerations) and may want to decide assignments and timetables for the design of data gathering and report tools, reporting systems, and systems for reporting information summaries. Unavoidably, problems will be encountered during the first months of implementation of the information loop. However, if both management and the organization persist in using and improving the system, business operations should improve and the system can improve as well until the information loop is fully providing adequate and relevant information to the right people in a timely manner. 3.0. Recent Literature Citing the 1991 work of Silver, Gebauer and Schober (2008, p. 1) warns that in developing an information system to support business operations, an “excessive flexibility of an information system can limit the flexibility of the system. Uden (2007, p. 1) reported that information systems complemented by good use of information technology can promote competitive advantages for small and medium enterprises. Welsham and Sahay 2005 (p. 3) pointed out that the prevailing view was that information systems are appropriate only for developing countries and large business but recently it was recognized that even developing countries and small firms could develop and use information systems. Meanwhile, in designing questionnaires for consumer research, Slater and Yani-de-Soriano (2007, p. 3) reminded that we must pay attention to cross-cultural matters. They note that some of theories we use in business have not been tested in “cultures having different languages, traditions and confronted with diverse environmental conditions” (p. 3). With regard to production quality control, Zivojinovic and Stanimirovic (2009, p. 17) emphasized that quality control does not apply only to products but as to how management is practiced. The work of Murrel and Gardiner (2009, p. 1) emphasized that quality control can be tremendously assisted by software and, in the process, emphasized that even quality information monitoring can be handled by computer softwares. In particular, Cunha, Agard, and Kusiaks (2006, p. 4027) recommend the use of data mining---a special kind of statistical method---in quality control research and development. 4.0. Generalizations Our discussion in this paper has strongly indicated the importance of information for business. Management and the business organization need adequate, relevant, and timely information. To ensure that they are adequate, relevant, and timely, the entire organization must be involved in identifying the required or key information they need and must develop targets for units of the organization to help each other acquire adequate and relevant information they need in a timely manner. Management must be in the center of the initiative. It is possible, of course, to delegate the task to a management information system unit or officer but management must see to it that that a system is in place and is functional. At the same time, management should see to it that it does not surrender its leadership to the unit or officer it has assigned to develop an information loop system. It must always retain its prerogative to approve, disapprove, or require the improvement of the system. Systems design and implementation have costs and the costs can work against the profitability of the business. Thus, the system and the system implementation itself must be cost-effective and consistent with the profitability and impact of the costs on the profitability of the business. Meanwhile, our small-scale review of literature identified the importance of cross-cultural factors as well as the use of computer softwares in the research and information systems. Our small-scale review of literature also warned us against being over-flexible in the implementation of our information systems. The review has also warned us that some of our business theories have not been tested in other cultures and languages. References Cunha, C., Agard, D, and Kusiaks, A. (2006). Data mining for improvement of product quality. International Journal of Production Research, 44 (18-19), 4027-4041. Dekking, F., Kraaikamp, C., Lopuhaa, H., and Meester, L. (2005). A Modern Introduction to Probability and Statistics: Understanding Why and How. The Netherlands: Springer-Verlag London Limited. Gebauer, J. and Schober, F. (2005). Information system flexibility and the performance of business processes. Working Paper 05-112. University of Illinois at Urbana: College of Business. Murrel, P. and Gardiner, S. (2009). Quality control for statistical graphics. Journal of Statistical Software, 30(1), 1-28. Slater, S. and Yani-de-Soriano, M. (2007). The value of method design in cross-cultural consumer research. Working Paper M2007/4. Cardiff University: Cardiff Business School. Urdan, T. (2005). Statistics in Plain English. 2nd ed. London: Lawrence Erlbaum Associates, 2005. Uden, L. (2007). How to promote competitive advantages for SMEs: Issues, Ideas and Innovation. Journal of Business Systems, Governance and Ethics, 2 (2), 1-15. Walpole, R., Myers, R., Myers, S., and Ye, K. (2007). Probability and Statistics for Engineers and Scientists. 8th ed. London: Pearson Education Ltd. Welsham, G. and Sahay, S. (2005). Research is in developing countries: Current landscape and future prospects. Working Paper 2/2005. University of Oslo: Working Papers in Information System. Zivojinovic, S. and Stanimirovic, A. (2009). Knowledge management and intellectual capital management coupled to quality management system lead to business success. International Journal for Quality Research, 3 (1), 17-25. Read More