Hypothesis
By its nature performance measurement is a diverse subject. Researchers with functional backgrounds as diverse as accounting, operations management, marketing, finance, economics, psychology, and sociology are all actively working in the field. As discussed in the Preface this incredible diversity brings with it both challenges and opportunities. The diversity results in a fascinating richness, but makes it extremely difficult for generations of researchers to build on each other’s work. A significant barrier stems from the fact that traditionally the way academic careers develop is through functional specialization. Accountants talk to accountants. Operations managers meet with operations managers. Marketing specialists network with other marketing specialists. The result is deep and rich streams of functionally specialized research, with little cross-fertilization (2002).
The role of financial performance measurement is to help keep the organization on the financial straight and narrow track. The measures are used primarily by financial specialists, and the action taken as a result of such analysis may also be exclusively financial. Nevertheless, it is also clear that evidence of financial problems may occur because of deficiencies in other areas of business operations. In this case, ratios can provide the finance director with the information necessary to convince other managers that operating action needs to be taken in order to avoid financial distress. However, the primary role served by this type of performance measurement lies within the province of the finance function, and is concerned with the effective and efficient use of financial resources ( 2002).
Firms and non-business organizations alike can no longer afford to avoid bedrock issues of performance measurement. For the last decade, discussion of performance measurement has been dominated by the balanced scorecard. What is missing from the spin surrounding the balanced scorecard is a simple fact about performance measures, the significance of which is not widely appreciated: common-sense measures used to gauge the performance of a firm are generally uncorrelated. In other words, across a large number of firms or their business units people will find that profitability, market share, customer satisfaction, and operating efficiency are weakly and sometimes negatively correlated (2002). These measures move in different directions about as often as they move in tandem. Social scientists have known this for years and have drawn two conclusions.
First, measuring performance is difficult since it is not clear that performance is a single construct. Second, the choice of performance measures is often arbitrary since it is difficult to prove that any one measure is better than others. Though neither of these conclusions is particularly useful, they would not surprise managers ( 2002). Performance measures can be weakly correlated. Each contains different information about the performance of the firm, and scorecards utilizing multiple measures are needed to capture the performance of the firm completely. In other words, customer satisfaction, operational performance, and innovation must be measured alongside financial results. Unfortunately, the logic lying behind the scorecard approach to performance measurement can go awry when measures are put to use. While there are good reasons to measure multiple dimensions of performance, there are also strong pressures to appraise performance along one dimension: better or worse. These pressures are strongest when compensating and rewarding people’s performance, but they are also present when making investment decisions. Whenever managers ask whether firm A performs better than B, whether division C performs better than D, or, most poignantly, if employee E is a better performer and hence should be compensated more generously than F, G, and H, they are tacitly if not explicitly trying to reduce performance to a single dimension (2002).
Positioning begins with the customer. Customers think about products and companies in relation to other products and companies. What really matters is how existing and potential customers think about a company in relation to its competitors. Customers set up a hierarchy of values, wants, and needs based on empirical data, opinions, word-of-mouth references, and previous experiences with products and services. They use that information to make purchasing decisions. Market leadership can catch a consumer’s attention and can be an important factor for the customer to consider, but there is more than one leader in almost every market segment today. Most often several companies share the top position, one being the technical leader, one the market leader, another pricing leader, and still another challenging upstart. Many companies can establish unique positions in the marketplace for themselves, their products, and their services. This capability is a powerful force in marketing (1991). Indeed, at the heart of every good marketing strategy is a good positioning strategy. Differentiation, from the customer’s viewpoint, is not something that is product or service related as much as it is related to the way companies does business. In the age of information, it is no longer possible to manufacture an image. The distinction between perception and reality is getting finer. Further, in a world where customers have so many choices they can be fickle. This means modern marketing is a battle for customer loyalty. Positioning must involve more than simple awareness of a hierarchy of brands and company names. It demands a special relationship with the customer and infrastructure of the marketplace. If companies are to develop a marketing style suited to this era of rapid change, they must start with a new approach to positioning (1991).
Based from the Questionnaire the different hypothesis includes
1. The first hypothesis is the company is continuously and constantly finding out new business processes and procedures to make sure that the best products and services can be produced by the company so that total and a different kind of satisfaction can be given to the company’s clients.
2. A hypothesis based from the 6th question is that one business process that does not help the company is balanced scorecard. There are many business processes that can help the company provide the best product and service but balanced scorecard is not included in this process.
3. The balanced scorecard has not created such a big damage for the company not to provide excellent service and good products.
4. A hypothesis based from the 8th question that can be made is the company is continuously undergoing performance analysis and checkup to see if they are providing the best products and services.
5. A hypothesis that can be made is that the company is undergoing comparison with competitors and then makes the changes needed to ensure that the rivals will not have competitive advantage.
6. Lastly a hypothesis that can be made is that through the use of business process re-engineering (BPR) the company will have a more efficient and effective way to provide service to its clients. The business process engineering will provide the company not only competitive advantage but it will give it advantage over its competitors by providing the best products and services to clients.
Research Findings
The motivation behind mining data, whether commercial or scientific, is the same the need to find useful information in data to enable better decision making or a better understanding of the world around us. Traditionally, data analysts have turned to data mining techniques when the size of their data has become too large for manual or visual analysis. In the science and engineering domains the size of the data is only one reason why data mining techniques are gaining popularity. Science data in areas such as remote sensing, astronomy, and computer simulations is routinely being measured in terabytes and petabytes. However, what makes the analysis of these data sets challenging is not just the size, but the complexity of the data.
Advances in technology have introduced complexity in scientific data, complexity that can take various forms such as multi-sensor, multi-spectral, multi-resolution data; spatiotemporal data; high dimensional data; structured and unstructured mesh data from simulations; data contaminated with different types of noise; three-dimensional data, and so on (2003). As a result of this complexity, visual data analysis, given its subjective nature and the human limitations in absorbing details, is becoming impractical even for moderate-sized scientific data sets large to massive data sets visual analysis is practically impossible. As a result, science and engineering data sets provide a very rich environment for the application of data mining, one in which the diversity of problems is matched only by the potential benefits obtained when knowledge is discovered in the data ( 2003).
In any study data is taken from different sources. The most helpful of which is the ideas of the people that is affected by the problem. These ideas can come from surveys or interview that uses questionnaires. The idea of the people helps in getting the necessary information to solve the problem. The ideas of the people are essential to formulate recommendations for the problem. After getting the ideas of the respondents it is analyzed and given interpretation. This is done to have a deeper understanding of the respondents. This is also done to have a deeper understanding of the feelings of the respondents. After data collection the next thing to be done is data presentation, interpretation and analysis. It is important that the research output be presented in an organized, coherent and understandable manner so that those who will read the research can propose important decisions about the results of the study. In preparation of the research output the things that should be considered includes the purpose, target reader or target end-user, clarity, appropriate words style, graphic aids (2003).
Target reader / end–user are those who the study wants to reach and attract to read the research. Contents and presentation of the data should be pertinent to the needs of the target reader or end-user. The data should be easily understood and concise for the reader to be attracted to it. The data should be well presented to coincide to the needs of the customer. Clarity is the precision of data. Using words that are specific, measurable, and descriptive will help in illustrating statements and ideas. Logical data organization and a sound interpretation add clarity to a report. In relation to this, n making conclusions and recommendations there should be relative data at hand to make the course of action doable. Appropriate words are words that give more meaning to a statement, appropriate words help to give proper description to the data. Concepts or words with inconsistent meaning should be shunned. Using jargons or languages that are meaningless should be avoided. In making the research, its language should be familiar to the reader or it must be used commonly in day to day business in the field of the reader. Technical terms should be defined since not all readers understand these words.
The study should avoid words which appeal to emotions, being bias, and moral judgment. Style is way the study is presented. The study should have consistency. It should have correct grammar, its spelling should be correct, it should have proper punctuation, and it should compose of short and simple sentences. It should be presented in a manner a reader will be attracted to it. To help enrich the analysis of the data, direct quotation from the answers of the respondents will be beneficial. The discussion can be easier if a section is subdivided into subtopics based on the objectives or hypothesis of the study, to focus on the analysis. Graphical aids are one way to effectively send the message of the study. It can be used as an integral or supplemental part of the text. Graphical aids should be clear and easily understood by the reader. The data should be accurate to prevent miscalculations and misinterpretations. Graphical aids include tables, graphs and charts. Charts can either be a pie chart, vertical bar chart or line bar chart.
In the first question the gender of the respondents was asked. Most of the respondents in the questionnaire were male. The gender of the respondents helps in determining what point of view the study will be based on. In the second question the age of the respondents was asked. The age group of the respondents was divided into 18 to 25 yrs old, 25 to 34 yrs old, 35 to 44 yrs old, 45 to 54 yrs old and 55 years old and above. The respondents were on the age limit of 35 to 44 yrs old. In the third question the educational attainment of the respondents were given attention. The educational level was divided into secondary level, post-secondary level, bachelor degree, postgraduate and others. The respondents were college graduates and had bachelor degree. In the fourth question the respondents were asked about their average income. The average income was divided into ,000-,000; ,001 to ,000; ,001-,000; ,001- ,000; ,001 or higher. The respondents earned around ,001 to , 000. They earned a salary not that high and not that low. In the fifth question the respondents were asked about their occupation. The occupation of the respondents determines what part of the problem they saw. The occupation of the respondents determines how wide the knowledge of the respondent has towards the problem. The choices of the respondents were clerical or rank and file; supervisor; manager; senior manager and top executive. The number of respondents was divided into manager, supervisor, and rank and file. The variety of the occupation of respondents gives the study more chance to have ideas coming not only from the management, but the lower branch of the company.
The ideas will not only come from management but it can come from the bridge of the management and the clerks which is the supervisor. These people experience different things in the business and can provide the best incite on things. In the sixth question the respondents were asked what, in the business process they perform, prevent them from satisfying your customers and creating quality products and services. Most of the respondents replied that the use of balanced scorecard prevent them from satisfying customer needs. They believed that although its effect is not that huge it contributes to them not being able to give excellent service. In the seventh question the respondents were asked what does technology or the lack of it do to enhance or inhibit effective process performance. Majority of the respondents believe that the technology they have is satisfying their demands and helps in providing effective performance. The improper use of technology makes it difficult for the respondents to provide effective service. In the eighth question the respondents were asked what does the organization structure do to enhance or inhibit effective process performance. The respondents replied that the company constantly research and discover new methods to produce products and services that will satisfy the clients. The respondents also replied that the BPR being used by the company is slowly promoting effective service to the clients. The BPR is changing the way the employees serve the clients, the employees are starting to become more patient and have a sense of being customer oriented. Moreover as mentioned by the respondents the company is conducting marketing research improve the way the company is serving its clients. Through the use of the marketing research new methods to provide efficient service is discovered and introduced to the personnel. In the ninth question the respondents were asked what do the reward structures do to enhance or inhibit effective process performance. Majority of the respondents replied that the reward systems help boost the personnel spirit thus they assist in bringing an effective process performance. The reward systems give the personnel a different kind of drive to provide an efficient service. These reward systems come in either cash or additional non monetary benefits. In the tenth question the respondents were asked what do the measurement systems or lack of them do to enhance or inhibit process performance. The respondents replied that the measurement system helps the company in correcting their wrong practices, after correcting themselves better products and services is then rendered to clients.
Data Analysis
The questionnaire and the response of the people showed that there is a problem with the business process being used. The business process should be the one making things easier for the company but it is in way ineffective and it does not help the company in providing the best service to clients. The response of the people showed that the company has the best technology available but sometimes it is not used well and the technique of using it does not produce into creating a service that is above standards. The misuse of technology and no proper guidance in using it hampers the company to provide effective service. The response of the people showed that the company is doing everything they can to make the personnel give the necessary effort to provide clients with effective customer service. These methods include using BPR and engaging in marketing research. They are constantly discovering new ways to provide a service that is different from others. Moreover the response of the people showed that reward structures contribute and help in making the personnel of the company extract effort to provide products and services that will satisfy people’s needs.
Reward structures if used can create a positive output to the company. It can help in creating highly reliable employees that can create products and services that can satisfy the needs of the clients. Lastly the response of the people showed that measurement systems help in making sure that the company provides excellent service. Measurement systems provide analysis of how a company provides service to its clients and through it the company can be changed for the better. The measurement systems checks which group in the company are not doing well. After determining the weak part of the company proper actions can be taken against them.
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