organizational productivity in Syngenta AG’s.

The high rate of growth in the business sector over the past few decades has increased the level of competition between the players. One aspect of this increased competition that has become significant and remained so in a sustained manner is the customer. Bose (2002) reiterates the concept of a good understanding of the importance of the customer in all business growth and productivity endeavors as key. Coupled with economic uncertainty, tough competition has continued to drive the strategy of many business organizations as they seek not only to remain afloat in these tough economic times, but also to grow in a sustainable manner.

All successful business enterprises have come to acknowledge the importance of a satisfied customer as one of the prime ingredients of growth and productivity. On the other hand, dissatisfied customers are sure to affect the sales performance due to a spread in the bad buying and business experience (Chou et al, 2002). Consequently, these two factors, business growth, and reputational factors have both come to rely on a relatively new aspect of the business’s promotional and marketing practice – customer relations management.

The need and importance of the customers’ feedback cannot be ignored in any discussion or even mention of marketing and promotional activity as they relate to the business organization. Chen and Popvich, 2003) state the importance of this crucial aspect of the business’s endeavor to improve its customer experience. As part of the interdepartmental approach to the business organization’s customer relations management, customer feedback and related aspects contribute a great deal to the organization’s awareness of the performance of its services and goods with regards to the customer’s satisfaction. Therefore, customer relations management is a combination of customer relations management tools and information management instruments, all combined to create increased organizational productivity through customer satisfaction (Chou et al, 2002). Peelan (2003) also reiterates the same point by stating how customer relations management is a specialized information technology that fosters customer segments, organizes customer satisfaction variables, and enables processes, which cater to customer satisfaction all in a bid to optimize revenue growth within the organization.

Chou et al (2002) categorize Syngenta AG as a leading specialized chemicals firm that originated from Switzerland and majors in agricultural seeds and pesticides. In addition, the company also deals with biotechnology and genomic research in many European countries such as the UK, all centered around improving on the seeds and their disease-resistance, or productivity properties. From a commercial perspective, Syngenta AG takes third place globally in terms of total volumes of seeds sold and marketed (Chen and Popvich, 2003). Bose (2002) states that Syngenta AG employs more than 3000 workers globally who assist the company’s operations in more than 90 countries rake in gross annual revenues in excess of 12 Billion US Dollars. Therefore, these facts place Syngenta AG in the top tier globally in terms of performance among its industry competitors.

Recently, Chen and Popvich (2003) reported how top management at Syngenta AG noticed the need to optimize their customer relations management practice by improving its information technology aspects. Subsequently, this research will try to establish if there exists any relationship between the performance attributes of Syngenta AG and its customer relations management practices.

Background to the Study

All business firms that understand the importance of productivity optimization rely on a wide variety of tools and techniques to improve it. Chou et al. (2003), attaches Syngenta AG to this fact by recognizing its modernized approach to customer relations management as part of the wider endeavor to optimize revenues through customer satisfaction. However, the firm’s management has noticed some slight deficiencies in the CRM aspects of the company in the currently dynamic competitive business environment. According to Chen and Popvich (2003), these deficiencies affected the company’s utilization of resources thus affecting work flow by incurring more-than-optimal resources such as time and funds. Ideas were suggested to the effect that information technology was one of the avenues through which the organization would improve its customer relations management practice. However, these suggestions faced the immensely crucial problem of the probability of success. Thus, Syngenta AG’s management faced a huge dilemma concerning the existence of the relationship between improved performance and customer relations management. The company needed to ascertain the extent of the relationship between productivity and customer relations management and identify the resultant collaborative and operational customer relations management strategies would assist the organization boost its performance in terms of corporate productivity (Bose, 2002).

Rationale of the Study

As the global business and corporate scene faces a recessionary wave, many business organizations face stiff business conditions that continue to affect their sales revenue and profit margins. Syngenta AG is no exception. As Chen and Popvich (2003) point out, the global agricultural inputs magnate also faces periods of hardship that the management thinks can be reversed through an age-old, proven, productivity-based strategy. According to the strategists, the currently unfavorable business indicators can be driven back to favorable levels through the productivity-based strategies redeeming performance and reputational losses the company has been incurring alongside other international companies in the current economic downshift.

Scholars and industry heavyweights have identified the effects blends of customer relations management and customer feedback through optimized information technology has on the firm’s performance. Therefore, customer feedback could be essential as part of Syngenta AG’s endeavor to return profitability levels back to the desired levels through satisfying customers in a more pronounced manner (Chou et al, 2002).

A major determinant of productivity is customer relationship management whose efficient process will increase the overall organization’s productivity in multiple views (Bose, 2002).In academic perspectives, this study will add huge valued towards Syngenta AG’s concerns and towards aspects of customer relationship management by figuring out the level of association between corporate productivity terms and customer relationship management in a material business sense.

Development of the research idea, question, objectives, and hypothesis

Research aim: The concerned research endeavor aims at identifying the extent to which customer relations management is related to corporate productivity as a means to optimizing sales revenues.

Research objectives:

Obtain a relevant definition of the term and concept of productivity through Syngenta AG’s perspective.
Identify the extent of the relationship between organizational productivity and customer relations management.
Establish the extent of the present rate of success in Syngenta AG’s customer relations management.
Identify the presence of deficiencies in Syngenta AG’s customer relations management.

Research questions:

How is the term and concept of productivity defined from Syngenta AG’s perspective?
How are concepts of customer relations management and organizational productivity related?
Identify the present status of Syngenta AG’s customer relations management.
What deficiencies exist in Syngnenta AG’s customer relations management?

Hypothesis:

Null hypothesis 1: There is no relationship between customer relationship management and organizational productivity.

Alternative hypothesis 1: There is relationship between customer relationship management and organizational productivity.

Null hypothesis 2: There is no relationship between operational customer relationship management program and organizational productivity.

Alternative hypothesis 2: There is relationship between operational customer relationship management program and organizational productivity.

Null hypothesis 3: There is no relationship between collaborative customer relationship management program and organizational productivity.

Alternative hypothesis 3: There is relationship between collaborative customer relationship management program and organizational productivity.

Null hypothesis 4: There is no relationship between analytical customer relationship management program and organizational productivity.

Alternative hypothesis 4: There is relationship between analytical customer relationship management program and organizational productivity.

Research Access, Limitations, and Resources

Due to the status of authorization attached to this research endeavor, based solely on the university’s permission to proceed, the opportunities to collect relevant information from various sources among other data collection efforts presented no problems. In addition, due to the applicability of the research endeavor and any accurate findings on an international agricultural company, the issues of research material applicability would be met. So much, the researcher anticipated her research findings to find use in other similar industrial and corporate scenarios.

The fundamental limitations of this research endeavor would revolve around the limited sample size and resource pool. Additionally, some degree of bias was expected from the respondent resulting in both systematic and non-systematic disorders in the research findings.

Finally, the researcher should be noted to be fully competent and a holder of all pertinent skills, conceptual and analytical, required in executing such business-oriented research.

Research outline

In the dissertation, the researcher is going to discuss the definition of customer relationship management, the definition of productivity, the ways productivity can be measured using tools and techniques for efficient customer relationship management using tools and techniques.

Furthermore, in the research methodology part of the study, the research philosophy, research designs, research approaches, data collection techniques, sampling framework and the ways to cover ethical aspects of this business research are explained.

Within the discussion and analysis portion of the business research, the researcher has delineated the statistical tools and techniques, which had been used to depict the different layers of relationship that exist between customer relationship management and productivity. The researcher compared research outcomes with the academic findings and tried to explain the gaps among the literatures. Finally, the conclusion portion of the study depicted with a set of actionable recommendations to improve the present condition of organizational pr

Chapter 2 – Literature Review

2.1 Introduction

This part of the research is primarily concerned with identifying the series if academic evidence relating to the researcher’s area of research. As such, the section will present a discussion that forwards the pertinent issues, supporting views, as well as any conflicting perspectives the academic community related to this research area has identified and put on record. Therefore, the various definitions of customer relations management, productivity concepts, and goals as well as objectives of customer relations management will be discussed. In addition, the significance and measurement procedures of the value of customer relations management on the business’s value will be investigated from the literature available.

2.2 Reviews on customer relations management

Both scholars and industry players have identified the importance of investigating the relationship between the customer’s satisfaction and their organization’s productivity as a subject of great interest. According to Baird and Parasnis (2011), the idea of CRM is new and with the concurrent advancement of information and enterprise software, it has adopted great importance in real-life business practices. The idea of customer relationship management has evolved from the relationship marketing techniques with the core objective of CRM being to promote a long-term profitable relationship with customers’ thorough improved productivity and customer service in organizations. CRM practices have been augmented in practical organizations because of the diverse customer base with differentiated preferences and buying behavior (Baran et al, 2008).

The currently competitive nature of business operations, especially in a global perspective, has forced the business community to embrace CRM practices in order to increase their customer’s portfolio value as one of the marketing and promotional methods of increasing profitability through tailored offerings (Buttle, 2008). In addition, Buttle (2012) points out how the customer relationship management efforts encompass a coordinated effort of all the departments in an organization. The application of CRM is a complicated process, which includes mining of all the customers’ data in order to obtain a good overall view of all the customers’ organized information for enabling firms to provide much efficient services (Chaturvedi, 2009). CRM helps a firm to focus effectively on the exact type of customers and market segments for sustainable future profitability and corporate growth (Coltman, 2007).

Consequently, the idea of CRM has been identified as one of the most crucial tactics that business organizations can manipulate as part of the larger marketing and promotional business practice to achieve two core goals – satisfy the customer better, and achieve increased profitability.

2.3 Defining customer relations management (CRM)

Customer relationship management has been defined as the core concept surrounding the business strategy and information technology concepts, integration of which helps an organization improve their efficient service criteria and promote productivity while catering to customers’ demands. Ernst et al (2011) define CRM as a collection of strategies that the organizations use to augment business value and create increased productivity through more customer-focused offerings.

Additionally, Homburg and Seiben (2008) add value to the process of creating an all-inclusive definition of CRM by stating that it is a collection of all business practices surrounding marketing, sales, and customer relations that aim at creating more productive business relationships between the customer and business organization. CRM adds extra advantage to the cost reduction, increase interaction values that ensure high sales revenue with the same resources. The theory of total quality management, backed by technological advances, has a severe impact over the development and shaping up of the modern customer relationship management, at least in recent times (Huang, 2007).

Although there is confusions around different definitions of customer relationship management by different authors in their researches but the core ideas evolve around customer relations and management, customer retention, personalization and marketing strategies (Huang, 2007). Some firms in technology intensive industries consider CRM as the ultimate technological solution to the customer management and tools for sales force automation, which integrates marketing and sales activities too (Iriana and Buttle, 2007). According to Keramati et al (2010), CRM is a function of sales and marketing departments wholly concentrated on individual customer communication management functions. On the other hand, King and Burgess (2008) argued that CRM has its major focus on two-way communication between customers and suppliers to build profitable long run relationship over time with the help of information technology strategies and resources.

From an information technology perspective, CRM entails an organization-wide integration of all the data warehouse, internet, intranet, extranet, phone, production, marketing, and sales technologies. As per Knox et al (2012), CRM must use information technology to amass data for developing organized information to build up much personal interaction with customers to ensure a higher lifetime value to the firm. According to Krasnikov et al (2009), customer relationship management, if implemented successfully, enables businesses to maintain a customer driver, cross-functional and technology oriented business process strategies for maximizing relationship benefits. Krasnikov et al (2009) also argued CRM as not a mere technology application but rather a systematic combination of sales, marketing and service activities.

2.4 Objectives of CRM

From an industrial and practical perspective, Kumar (2010) stated that the goals of CRM surround two major issues: developing promotional processes efficiency and augmentation of process organizational efficiency. The ultimate goal of any business-focused firms’ investment in customer relationship management activities is to reduce operational costs and augment profitability (Kumar, 2010). Such objectives can better be achieved thorough activating sales and customer centric CRM activities from all aspects. As per Lin et al (2010), increased customer contentment and building customer loyalty should be the major CRM objectives for a business organization. Any organization can achieve business goals such as efficient sales management, simplified marketing and sales process, gathering new customer and retaining the old ones through improved customer service with an improved focus on customer relationship management (Berry and Linoff, 2011). Such activities will also provide room for more sales revenue and long run profit potentials.

Hence, any CRM practice needs to be at the intersection of customer processes augmentation, and an enhancement of organizational processes aimed at boosting both organizational performance and customer satisfaction.

2.5 The types of CRM

There are five broad categorizations of CRM. The most basic is between reactive and proactive CRM practices. The next include analytical, operational, and collaborative.

2.5.1 Operational CRM

Within the realm of operational CRM, customers can interact with a company through a number of approaches. The organization itself and its employees facilitate the direct connection with customers with several junctions called as touch points (Ngai et al, 2009). Customer relationship management aspects that are enabled with sale transactions, due payments, seeking information, suggestions, queries, and complaints through operational touch points are called operational CRM or front office customer relationship management. Such CRM practices affect the promotional and marketing aspects of the organization quite severely if not well addressed.

2.5.2 Collaborative CRM

Osarenkhoe and Bennani (2007), outline the specific functions of a corporation, which facilitate any two-way communication among companies and its customers via the number of channels for enabling and improving customer interaction quality, are defined as collaborative CRM. Collaborative CRM concentrates on establishing a cooperative effort with the business partners of a business organization. These partners can be business agents, distribution channels and/or other stakeholders (Raab et al, 2008). Interestingly, collaborative CRM does not encounter direct customers for the purpose of increasing productivity. Rather, such CRM’s idea is to maintain a well performing relationship with partners for better business coordination.

2.5.3. Proactive and reactive customer relationship management

Mendoza et al, (2007) state that proactive CRM comes into being while a company forecasts the market movements and responds to customers’ trending needs by itself with innovative strategies. Conversely, when a company adapts to the suggestions, requests, recommendations and complaints of customers, suppliers and other parties, the activities are defined as reactive customer relationship management (Nambisan and Baron, 2007). Proactive business firms concentrate on analyzing the customers changing demands and market movements to be prepared for future product and service needs and offer superior values through such actions at the evolution of customers’ need. Firms practicing proactive customer relationship management focus more on the personalization needs and individual marketing efforts.

Figure 1 Types of CRM mapped against degree of personalization

Source: Baird, C. H. and Parasnis, G. (2011) ‘From social media to social customer relationship management’ Strategy & Leadership, Vol. 39, No. 5

2.5.4 Analytical CRM

Analytical customer relationship management, otherwise called strategic CRM, sits at the top tier of CRM types in terms of importance from a business productivity perspective. Business analysts are the key persons with responsibilities such as sort of customer relationship management (Reimann et al, 2010). Such analysts facilitate the major objective of analytical CRM by sorting out various preferences, tastes and activities of customers for offering custom-made solutions of their needs. Such analytical CRM works with capturing data from numerous touch points and subsequently analyzing them to find generalized consumer behavior. In addition, they develop solutions according to the findings of their analysis (Richards and Jones, 2008). Analytical CRM requires widespread use of management information system and information technology.

Seemingly, the principal focus of any organization is naturally remains over the operational items. Nevertheless, being proactive in CRM tactics and attending these policies from the analytical point of view will help to cater a better level of results in business indicators.

2.6 Definition of productivity

Sharma et al, (2008), describe productivity as the relationship between one or more related resources consumed, and the output produced in the process of business-oriented processes of production. The choice of a suitable concept of productivity relies on the objectives of measurement, data availability, and a research preference. A measure of productivity is considered a ratio of outputs produced to that of inputs used. Besides, Sinisalo et al (2007) discuss the need for the observer to contemplate over different choices regarding the nature and scope of both the resources and outputs considered. For instance, outputs may be measured for delivered product while resources may be measured for cost or effort. Numbers of productivity may be used in many various means, e.g., for the estimation of project and the evaluation of process. A measure of productivity assists an organization in making effective decisions about investments in methods, tools, processes, and outsourcing (Tamošiūniene and Jasilioniene, 2007). In addition to the wide area of inputs and outputs to be measured, other factors such as changes in requirements and quality of service delivery may influence the interpretation of the outcome of productivity measure.

2.7 Importance of Productivity

The significance of productivity revolves around what can be measured to determine growth rate or level. A high level of productivity or high growth rates point out a forceful and growing economy or prospective industry. Therefore, to keep alive in the competitive marketplace, a nation or her discrete industry will try to make efforts to develop her growth of productivity (Urbanskienė et al, 2008).

Commonly, productivity can be used at four levels: project/site, organization/firm, individual industry, and entire economy. As measures of productivity, prevail largely to be compared, it is better to use measures of production as performance indices (Venkatesan et al, 2007). By means of empirical production functions, when inputs and outputs have been calculated in constant prices, ratios of real outputs to individual real inputs can be measured to determine single productivity measures; and ratios of real outputs to all related real inputs can be measured to determine an MFP or TFP (Buttle, 2008). Single productivity measures reveal both productive efficiency changes and factor substitutions resulting from relative factor prices changes. Conversely, MFP or TFP has widely been recognized as a better sign of efficiency of productivity than conventional partial productivity for the measurement of effective resources utilization.

2.8 Single productivity concepts

The first measure of productivity, Labor productivity (Q/L), is a ratio measure of outputs produced to labor inputs used (Chaturvedi, 2009). Since labor is the only one of the factor of inputs, changes in productivity of labor are influenced by changes in factor substitution and by changes in factor substitution as calculated by multi-factor or total factor productivity (Coltman, 2007).

Other concepts of single productivity are intermediate productivity and capital productivity, which measure the relationship between output and intermediate input and the relationship between output and capital input, respectively. The most commonly used measure is labor productivity among the three concepts of single productivity.

2.9 Typical Calculations of Productivity

Interestingly, and from a perspective of unitary productivity measurement, measures of size and resources may be integrated in many various manners. The three common approaches to outlining productivity are referred to as physical, functional, and economic productivity.

2.9.1 Physical Productivity

Herein, the ratio of the amount of products to the resources used (usually effort) is calculated. Ernst et al, (2011) identify how products may be calculated with respect to screens, classes, code, or any other unit of product. Normally, effort is calculated with respect to staff hours, days, months, or years.

2.9.2 Functional Productivity

Here, the ratio of the amount of the functionality delivered to the resources used (usually effort) is calculated. The functionality may be determined with respect to requirements, use cases, features, or function points as suitable for the type of software and the method of development. Usually, and as pointed out by Homburg and Sieben, (2008), effort is determined with respect to staff hours, days, months, or years.

2.9.3 Economic Productivity

In this ratio, the amount of product produced to the cost of the resources consumed to produce it is calculated (Homburg and Sieben, 2008) as part of a larger economic productivity identification endevor. Economic productivity assists in assessing the efficiency of an organization’s economy. For the calculation of economic productivity, we have to use the following equation:

ECONOMIC PRODUCTIVITY = VALUE/COST

The cost is easier to determine, whereas, the value is recognized as integration of functionality and price. More functionality reflects higher prices. The amount, which the customers are willing to pay, denotes its value. Regrettably, the value of revenue may be calculated when the product has completed its worthwhile life (Mendoza et al, 2007). Therefore, the value must be calculated to determine economic productivity, considering all the factors that affect the decision-making of customer to purchase. Accordingly,

VALUE = f (PRICE, TIME, QUALITY, FUNCTIONALITY)

Poor quality may results in liability and guarantee costs that offset revenue, either planned or actual. Likewise, time must be taken into consideration while determining a product’s economic value. Thus, the quantity of revenue paid back by it will be unfavorably affected. As a result, in the case of calculating the value for economic productivity, we must take account of quality and price, as well as timeliness and functionality (King and Burgess, 2008).

2.10 The business value impact of CRM on productivity

Compared to old-fashioned network technologies, the latest CRM applications are able to arrange and coordinate customer data with a lot less cost implications (Coltman, 2007). CRM system manages the data accumulation, storing, maintenance and distribution of customer knowledge throughout the organization (Knox et al, 2012). (Ngai et al, 2009) explained that CRM provide added advantages in product and service innovation, tailored product, consolidated customer view, and customers’ lifetime value calculation; if effective information management is enabled. Customers’ profitability and loyalty can be evaluated with the assistance of CRM systems as it examines the customers’ repeat purchase history, longevity and amount spent on different items (Sinisalo et al, 2007). Because there has been so many technology solutions prevail in organization, some views consider CRM a part of pure technology misleadingly.

Recently, as more firms has found the strategic significance of CRM in building better customer relationship and increasing their organizational productivity, CRM should be considered as a business value endeavor instead of just some technology-centric activities related to business intelligence or promotional activity (Coltman, 2007). Accordingly, if CRM strategies can be properly backed by information technology, it could leverage the major customer interaction points to maximize profitability. Keramati et al (2010) explains that the core drivers behind increased importance of CRM in modern businesses are skyrocketing competition, product and service innovations, technological advancements, increased internet accessibility. These factors inspired firms to allocate their resources to CRM activities more in customer access points for high profitability. Customers get the most out of business’s CRM activities in the form of tailored products and services, process simplicity and transaction convenience as the interaction channels are more proactive (Knox et al, 2012).) viewed CRM as enabling firms to get a competitive edge over the rivals with sustainable growth opportunity. Liu (2007) supports the view by acknowledging the ever-changing pattern of competition in international business where firms are unable to grab customers through easily imitable strategies. In such case, CRM helps firms to build long lasting profitable relationship by which firms can benefit in real terms. Successful businesses are those, which can deliver customers’ value as wanted by them with a perfect blend of relationship acknowledgement Buttle (2012).

According to Lin et al (2010), customer relationship management practices help find customers that are abandoned by other companies for their unprofitable propositions (Mendoza et al, 2007). The mentioned view is totally supported by many scholars and industry players as they explain that CRM provide ways to recognize worthy new customers, profitable customers to retain and untapped areas of market. Potential customers with strategic benefits are pointed out and so does the sectors of customer whom should be curtailed. As per Lin et al (2010), CRM improves a customer’s total lifetime value, which provides great benefit in increasing the real economic value of a business.

Successful customer relationship management strategies inspire customers for being engaged in buying, staying loyal and having effective communication with a particular firm. With perfect resource allocation in right time and right place, CRM helps to build customer satisfaction to a new height

2.11 Summary

After the thorough analysis of the existing literature, it is evident that customer relationship management has a wider grip on different aspect of marketing, selling concepts, customer behaviour analysis and so on. On the other hand, productivity concepts evolved from the firms’ concern for offering quality products with least costly processes and efficient resource consumption (Linoff and Berry, 2011). However, there had been very many researches on diverse aspects of customer relationship management and productivity concepts on a standalone basis, there had not been any noteworthy study on how customer relationship management influences the productivity dimensions (Maklan et al, 2008). Therefore, this significant research gap will be concentrated throughout this research for better process outcome for Syngenta AG

Chapter 3 – Methodology

3.1. Introduction

Syngenta AG’s senior management is concerned with the present productivity dimensions and wants to find out the drawbacks in the present CRM practices. In addition, the management also tried to acquire a thorough understanding of the nature of the relationship that exists between customer relationship management and organizational productivity. Therefore, it is obvious that there had been an evident and specific research problem needing urgent notice.

Business-oriented research does not fall into the category of routine jobs in business organization (Cohen, Manion & Morrison, 2000). Such researches are carried out for some special intention to resolve a problem, finding alternative courses of action, listing ways for better resource management or focusing on any particular flank of business activities, etc. To conduct a research in a coherent and systemic fashion, the researcher needs a proper guideline and such guidelines are delineated accurately in a research proposal.

Researchers in a business-oriented environment such as this have to focus on covering different significant areas of the research matter to be handled (Patton, 2002). The major parts highlighted should be the research design, research approaches, philosophy of research, research strategies, data collection methods, proper framework for sampling and ethical issue compliance-related with the particular research. After these related issues are taken care of, the researched will step forward for data collection through survey instruments. Usually, as pointed out by Silverman, (2005), sampling mechanisms are followed to gather the required data. Once data collection processes are completed, the researcher goes through diverse analytical tools to check hypotheses and find solutions to mentioned research problem (Creswell, 1994).

Figure 2 Research onion model

Source: Kumar, R. (2005) Research Methodology: A step-by-step guide for beginners. Second Edition. London, SAGE.

Consequently, this business research demonstrated how the researcher followed all the mentioned proceedings for a professional business research environment assuring all stakeholders that this business research had been conducted with a systematic procedure.

3.2 Defining research philosophy and the selection of research philosophy

Within the realms of business research, there are two types of research philosophies commonly utilized. One is the very popular phenomenology and the other is positivism. Concerning phenomenology and positivism, phenomenology is measured a ballpark echo of actual situation (Cohen, Manion & Morrison, 2000). For steering this professional study on compensation package, the researcher is ardent to practice phenomenology as the definitive exploration philosophy. Phenomenology takes a supplementary advantage above positivism as it deliberates diverse socio-cultural issues while accompanying the research in material sense. The overall assessment about respondent’s choices is that they may make irrational decision on every occasion and recons systematic favoritisms. Thus, bearing in mind all these matters, phenomenology will act as the superior choice as it considers societal and behavioral configuration of respondents (Patton, 2002).

3.3 Defining research approach and the selection of research approach

Research approaches are the systems in which the whole research work will be accomplished. There are two major approaches for business research namely deduction and induction research approaches. In the case of deduction approach of research, the null hypothesis is formed and then, based on gathered data, these null hypotheses are tested. In such a process, academic theories help the researcher to recognize the researcher’s area of interest in a better way. However, the deductive approach’s main objective is not to develop theory formulation. In another sense, while the researcher takes into account the induction techniques, they opt for generalizing patterns and end up with new theories in the respective business research (Silverman, 2005). That is how the formulation of theories is considered as the lone objective of induction research approach.

In this business research, the researcher has followed the deductive approach to business-oriented research as some null hypotheses are established and these hypotheses should be tested on the grounds of academic theories.

3.4 Defining research design and the selection of research design

There are three basic types of research designs: qualitative, quantitative, and mixed design processes. Among the three basic research designs, our particular business research will be based on a mixed design process. In a qualitative research design, researchers use numerical data and research outcome is identified in a numerical form in most cases as outlined by Amber and Putoni, (2004). In a qualitative research design, testing null hypothesis is much easier and researcher can easily judge the extent of reliability and validity of research. However, as data is collected through sampling mechanisms, the data authenticity and reliability may be in question at times (Johnson, 2007). On the other hand, the qualitative research design deals with different data set and variables, which are hard to put into the form of numerical. Focus group discussion has proven as a good source of collecting qualitative data from a population and the researcher present findings in qualitative form (Johnson, 2007). Testing research validity and reliability are often much difficult is this research design. Again, the researcher will not be able to test any null hypotheses in this research design as that will need some quantitative treatment. Finally, for this very business research, the researcher opts for going with the mixed research design that includes the benefits of both the qualitative and quantitative research designs. Mixed research design also ignores the pitfalls of both aforementioned designs (Narver and Slater, 1990). The research topic in consideration needs solely the analysis of quantitative data to bring outcome from the hypotheses. Therefore, this research endeavor has prompted the researcher to follow the quantitative method of data collection as research area is numerical data-dependent making it will be easier to handle this sort of data with a quantitative research design (Creswell, 1994).

3.5 Preferred research Strategies

Research strategy is the mechanism through which collection of data and the sampling procedure is conducted. Examples of major forms of research strategies are experiments, grounded research, survey, case studies etc. In this professional business research, the researcher wants to have a survey technique as a research strategy. The scarcity of information with much ensured quality was prevalent at the time when the researcher started research process. Another view was the longitudinal timing orientation, which matches perfectly with the research design. Marshall and Rossman (2006) state the mentioned the constrains associated with insufficient data as why the researcher preferred survey technique to conduct this professional research.

3.6 Time Horizon

During the conduction of business-oriented research, the duration and frequency of time are two core decisions needed while the exercise commences. For the cause of shortages in resource, the research needs a longitudinal timing approach very essentially as the researcher is concerned with specific time frame and assured robustness, which may not be possible in cross-sectional analysis (Creswell, 1994).

3.7 Research Instruments

As an integral part of research methodology, this part will cover the different instruments used in the research process such as the sampling framework, mechanism for data collection and tools and techniques for data analysis.

3.7.1. Sampling framework

If consideration goes to the shortage of resources, and some other practical constraints, such as inaccessibility of all the population, the researcher has to go for sampling techniques instead of census method as stipulated by Saunders, et al, (2003). The management level employees in different branches of Syngenta AG will be the part of population taken as sample. Among various methods of acquiring sample from population, the simple random sampling method is most suited for this research, as every single element of population will then have the same chance to be included in the sample (Mikkelsen, 2005). Because of shortages in resource, the population could not be divided into homogenous segments and that is why the stratified random sampling is not used here, even though it could do a better job.

3.7.2. Data Collection mechanism

To collect information, several data collection techniques are available such as questionnaire, focus group discussion and interviewing techniques. In questionnaire-based techniques, it is much easier to spread out the data collection materials over a large horizon (Cooper & Schindler, 2009). Even though, the reliability concern for the responses against questionnaire will be a big issue for the researcher(Creswell, 1994). To be very precise and effective in such data collection, having a self-filled up questionnaire or collecting data with the face-to-face interview will ensure a high level of data accuracy (Klenke, 2008). The important fact is to ensure a very high rate of response and data authenticity. Focus group discussion will ensure an open and free discussion in the researcher’s area of interest and very significant data can be attained in this process. Thus for collecting the primary data, the researcher opts for primary data collection mechanism based on questionnaire. The questionnaire include systematically related, simple and easily understandable questions for accurate data collection (Nykiel, 2007). The questionnaire was sent to 42 sample respondents out of them 30 respondents provided with necessary information. Therefore, there was a 70 percent response rate with full answers to the queries so made.

The researcher needs secondary information for conducting this research. The corporate website of Syngenta AG provided a good amount of necessary information. In addition, the various academic journals and industry reports were used in precious information collection relating the research objectives. Some textbooks materials helped to find useful information about the research questions (Ragin, 1994). While collecting the secondary information the researcher ensured the timeliness and relevant criteria properly.

3.7.3. Data analysis tools

To analyze the information, the researcher has used various sorts of data analysis tools and techniques. The data and secondary information was condensed from a huge pile with special reference to accuracy and relevance (Johnson, and Duberley, 2000). We had used regression techniques, descriptive statistics and testing of hypothesis for analyzing the information. Regression serves to express the linear or multiple functionality among variables and the researcher tested some multiple regressions throughout the research. Hypothesis testing examines the genuineness of any research problem statement and for testing hypothesis; the researcher has enabled t-test based on one sample (Munhall & Chenail, 2008). The one-sample t-test serves as the barometer to check if there is any difference between sample statistics and population parameter and whether the difference is significant or not. Mean and standard deviation measures are included in the descriptive statistics segment where mean served as a central tendency measure and standard deviation measures the implied difference of average data set from mean (Johnson, et al. 2007). Two of the famous statistics software namely E-views and SPSS are used to analyze such data set and statistical measurement.

3.8 Applicability of research validity and reliability

The research is a valid based on several considerations, most of which rely on the researcher being able to attain all mentioned research objectives. As by changing the research methodology part to a little extent and shifting the data set will enable the researcher to achieve similar sort of research outcome, the research is sure to be considered as a reliable research (Creswell, 1994).

3.9 Ethical considerations

Ethical consideration is a key fact for any quality research work. In this business research, ethical practices will be upheld in all the process of data collection and processing. All the research objectives will be made clear to respondents before gathering any data and voluntary participation will be ensured (Munhall & Chenail, 2008). Data so collected by surveys will be maintained and preserved properly with due diligence.

3.10 Summary

The research methodology fragment of this very research elucidates and delivers a clear knowledge about controlled and organized manner has actually directed through a systematic progression. However, to be very specific, the actuality were a little dissimilar from the predictable courses of actions and made to have evidence of overlapping steps in research process at times. The unpredicted hardships in attainment of data, resource restrictions and other issues intersecting at research process made the research endeavor encounter issues that promoted the process of hypothesis emanating into reality (Kumar, 2005).

Chapter 4 – Results and Analysis

4.1 Introduction

The basis of this research is the comprehensive questionnaire due to its ability to get useful insights about the CRM processes and its relationship with the productivity issues with a core focus to the case of Syngenta AG. The researcher was dependent on the responses from the sample respondents in line with the questionnaire specially prepared and disseminated among them.

This research endeavor’s introductory chapter delineated the researcher’s core area of interest Therefore, this analysis segment of the research will involve the researcher’s use of an extended variety of analytical tools based on the gathered data to cover the all four key objectives of the research.

The definition of the term productivity that is prevalent in the perspective of Syngenta AG Corporation. With information from different secondary sources of data about Syngenta AG such as the website of the company, financial records published, articles, newspaper citations and so on, the researcher gathered the essential information. The questionnaire also provided much of the knowledge about such a fact.
The accurate extent of relationship between customer relationship management and organizational productivity had been comprehensively assessed based on the survey results from the questionnaire through regression based study.
The actual status of customer relationship management in Syngenta AG had been comprehensively assessed based on the survey results from the questionnaire.
The loopholes prevailing in the existing customer relationship management programs in Syngenta AG were duly identified through the data obtained from the questionnaire.

However, before embarking on a thorough analysis with different statistical tools, the researcher tried to present a summarized view of the concurrent CRM practices so prevailing in Syngenta AG for achieving business productivity.

Customer relationship management criteria	Practices at Syngenta AG
Defining and dynamics	Although the core focus of any CRM approach should be on the establishment of a better and profitable customer relationship management, the concurrent practices at Syngenta AG offer evidences about more concentration over the efficient management of data. Customer relationship management is defined through the proper data management however, not with the implementation of such data. On the other hand, CRM in Syngenta AG is blessed with excusive opportunity of customization but have major drawbacks with the end user involvement in the CRM process.
Productivity and CRM	Based upon the discussion with this research endeavor’s respondents while they go through the questionnaire, the prevailing productivity condition was found to be short of the mark in the case of effectiveness. Syngenta AG defines the term productivity from the costing criteria as more productivity means less cost in organizational processes. Through automating processes, the top-level management now is concentrating less about the productivity concept, which is not a good sign from practical business aspect. At Syngenta AG, productivity is considered from the functional perspective only but for better business practice, productivity should be focused on the economic standpoint. However, a massive extent of agreement is found among the employees about the effectiveness of CRM packages over enhancing productivity, while using properly.

4.2 Findings from the descriptive study

This section entails a thorough idea about the analysis covering the descriptive statistics concentrating on the impact of CRM on the productivity dimensions at Syngenta AG. Many insights had been revealed about the prevailing CRM practices and issues about CRM needing emergent focus were pinpointed here. However, the researcher would try to delineate a comprehensive discussion over the respondents’ demography before starting the analysis from descriptive statistics.

Key demographic variables	Scenario of the surveyed respondents
Age	When we confront the results of the survey from an age-based criteria, there are evidences that 33% of the sample respondents belonged to the below 24 years’ group, 27% belonged to the group of 24-34 years and the remaining respondents belonged to the group of above 34 years. Henceforth, from the perspective of the age criteria of sample respondents, the sampling characteristics tend to depict a normal distribution.
Gender	When we confront the results of the survey from gender-based criteria, there had been evidences that about 44% of the sample respondents were female and the remaining respondents were from male groups. Henceforth, from the perspective of the gender criteria of sample respondents, the sampling characteristics tend to depict a normal distribution.
Income level	When confronting the results of the survey from an income-based criteria, there had been evidences that 42% of the sample respondents belonged to the income earner’s group of less than 40000 GBP and the remaining respondents were from the group having income of more than 40000 GBP per year. Henceforth, from the perspective of the income criteria of sample respondents, the sampling characteristics tend to depict a normal distribution.
Experience	Confronting the results of the survey from the experience criteria, there had been evidences that 36% of the sample respondents belonged to the experience group of less than 4 years and 33% of the sample respondents belonged to the experience group of 4-8 years. The remaining respondents were from the group having experiences of more than 8 years. Henceforth, from the perspective of the experience criteria of sample respondents, the sampling characteristics tend to depict a normal distribution.

Table 1: Demography of respondents

Data collected with the sampling device, in this case, the questionnaire, was mostly categorical in every respect, and due to this reason; the responses from the sample were converted to quantifiable and numeric codes for making them eligible for subsequent analysis. The following table explained the researcher’s method of codifying in line with the questions used precisely to collect data from sample respondents. The researcher clarified the numeric codes behind each options used in the mentioned questions.

Questions asked	Closed-end responses	Coding criteria
1. What is Syngenta AG’s present state in terms of productivity?	Excellent Very Good Moderate Low	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Excellent” option as 1, the “Very good” option as 2, the “Moderate” option as 3 and the “Low” option as 4.
2. How effective isSyngenta AG’s concurrent business proposition from the perspective of their productivity dimensions?	Extremely effective Very effective Moderately effective Slightly effective Not at all effective	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Extremely effective” option as 1, the “Very effective” option as 2, the “Moderately effective” option as 3, the “Slightly effective” option as 4 and the “Not at all effective” option as 5.
3. How does Syngenta AG define the concept of productivity from the perspectiveof organizational performance?	More output Higher sales growth Greater level of customer satisfaction Reduced extent of costs	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “More output” option as 1, the “Higher sales growth” option as 2, the “Greater level of customer satisfaction” option as 3 and the “Reduced extent of costs” option as 4.
4. How much do Syngenta AG emphasize on the issue of the productivity?	Extreme emphasize Much emphasize Moderate emphasize Low emphasize	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Extreme emphasize” option as 1, the “Much emphasize” option as 2, the “Moderate emphasize” option as 3 and the “Low emphasize” option as 4.
5. In which ways do productivity measures get calculated in Syngenta AG?	Physical Productivity Functional Productivity Economic Productivity	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Physical Productivity” option as 1, the “Functional Productivity” option as 2 and the “Economic Productivity” option as 3.
6. How Customer Relationship Management (CRM) has impact over the business value of Syngenta AG?	Reducing costs Process automation Effective management of data Loyal and profitable customers Better customer relationship Increased competitive edge	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Reducing costs” option as 1, the “Process automation” option as 2, the “Effective management of data” option as 3, the “Loyal and profitable customers” option as 4, the “Better customer relationship” option as 5 and the “Increased competitive edge” option as 6.
7. What is the present status of Syngenta AG in terms of CRM?	Excellent Very Good Moderate Low	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Excellent” option as 1, the “Very good” option as 2, the “Moderate” option as 3 and the “Low” option as 4.
8. How effective is Syngenta AG’s customer relationship practices in terms of augmenting productivity?	Extremely effective Very effective Moderately effective Slightly effective Not at all effective	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Extremely effective” option as 1, the “Very effective” option as 2, the “Moderately effective” option as 3, the “Slightly effective” option as 4 and the “Not at all effective” option as 5.
9. What is the core strength of Syngenta AG’s CRM process?	Functional business goals Experienced and trained consultants Exclusive customization opportunities Customer focused processes	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Functional business goals” option as 1, the “Experienced and trained consultants” option as 2, the “Exclusive customization opportunities” option as 3 and the “Customer focused processes” option as 4.
10. Which one do you think is in the most severe condition in Syngenta AG’s CRM aspects?	Immeasurable business goals Alignment of information technology and business Upfront executive support Involvement of end user	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Immeasurable business goals” option as 1, the “Alignment of information technology and business” option as 2, the “Upfront executive support” option as 3 and the “Involvement of end user” option as 4.
11. Is there an adequate measure of training in customer relationship management in Syngenta AG?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,
12. Do the concurrent CRM practices at Syngenta AG offer provisions for measuring, monitoring and tracking progress made in productivity?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,
13. Do the prevailing CRM processes can ensure all-round participation from customers?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,
14. Do you think there is relationship between CRM and organizational productivity?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,
15. Do you think there is relationship between operational CRM programs and organizational productivity?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,
16. Do you think there is relationship between collaborative CRM and organizational productivity?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,
17. Do you think there is relationship between analytical CRM and organizational productivity?	Yes No	While ascribing numerical codes to the categorical answer options – the researcher ascribed the “Yes” option as 1 and the “No” option as 2,

Table 2 Process of data Coding

At this stage, the descriptive statistics will be encoded as outlined in the following table:

Research variables	Mean	Standard deviation
Present status of productivity	2.63	.77
Effectiveness of concurrent business proposition	2.39	.66
Definition of productivity	3.65	.12
Emphasize over productivity	2.27	.38
Calculation of productivity	1.62	.67
Impact of CRM over business value	1.19	.56
Present status of CRM	2.22	.33
Effectiveness of customer relationship practices	2.37	.49
Core strength of CRM process	3.25	.32
Most severe CRM aspects	3.88	.35
Training of customer relationship management	3.54	.41
Provisions for measuring, monitoring and tracking progress	1.79	.56
Participation from customers	1.85	.73
Relationship between customer relationship management and organizational productivity	.19	.19
Relationship between operational customer relationship management program and organizational productivity	.22	.34
Relationship between collaborative customer relationship management and organizational productivity	.29	.106
Relationship between analytical customer relationship management and organizational productivity	.37	.24

Table 3: Descriptive statistics results

All insights resulting from the descriptive statistics offera greater understanding of the shared view among the sample respondents about diverse aspects of productivity at Syngenta AG and the impact of CRM over the same issue. As evidenced in the table above, the mean values provide knowledge about average opinion over the given facts and the standard deviation shows the scattered nature of the opinions among respondents. The results provide evidence that the concurrent status of productivity is at a moderate level and Syngenta AG’s prevailing business proposition is moderately effective when thought from the productivity dimensions. The concept of productivity is defined as having a reduced level of costs in the overall business processes of Syngenta AG. From the top level management, the extent of emphasize over the productivity concern of Syngenta AG is found at moderate level. Syngenta AG follows the functional practice for calculating the productivity measures that focus particularly over the organizational functions.

Syngenta AG’s core impact of CRM over business value so identified is the result of an optimized and increasingly effective management of data. Apart from this, the results provide evidence that the concurrent status of CRM is at a moderate level and Syngenta AG’s prevailing customer relationship practices is moderately effective when thought from the productivity dimensions. The core strength of Syngenta AG’s customer relationship management is identified as having exclusive customization opportunities. Poor involvement of the end users with the CRM processes is found as the most miserable aspect of Syngenta AG’s customer relationship management. The respondents highlighted the lack of adequate training on the CRM practices and the ineffectiveness of concurrent CRM practices in offering provisions for measuring, monitoring and tracking progress made in productivity. As per the respondents’ answers, there lies a reduced level of participation on all round participation from customers. Last but not least; the respondents favoured the fact that the all sorts of CRM practices have a relationship with Syngenta AG’s productivity level.

4.3 Hypothesis testing

This research paper’s hypothesis-testing part would enumerate testing the pre-mentioned hypotheses with a 5% level of significance. The so formed hypotheses were: