Performance Management and Business Analytics Model- myassignmenthelp

Question: Discuss about thePerformance Management and Business Analytics Model. Answer: Introduction The technological advancement in business analysis for intelligence management has resulted in the strong tool for better performance management. The business analytics modal like data mining along with strong support system as well as expert system that also offers different base for algorithms to work in complex function to draw some meaningful results from the data that specifically manage the performance. In the current time, tools in business analytics also helps in providing some crucial and needed support to manage the performance of the workforce in the company (Sharda et al., 2014). But the overload of data is usually faced by the decision maker who ever wanted to process all the data to manage the performance in right manner. The issue of data overload has further deepened with the growth of many data storage alternatives which are also very comprehensive by nature. Thus, right kind of integration of business analytics is very crucial part to overcome the issue. A lot of da ta available for the organizations to use for answering the issues related to organizational challenges and issues. Discussion A performance management system consist of multiple layers while managing the performance in right manner that are based on inputs, processing, outputs and results. Business analytics can be applied with the right consideration of such layers. There is also absence of the right kind of approach that helps in providing incorporation of all components in a more comprehensive manner. Thus, existence of the different approach helps the manager to recognize different kind of analytics and must be used in performance management (Akter et al., 2016). Such kind of approach can also help in improving the decision-making procedure to sustain the efficiency of performance management. Management also use different layer of approach which must carefully notice the input, output, procedure and many results to make important decisions. Such layers consist of internal as well as external points, recognizing performance based drivers and also integrating the performance based drivers with management work and performance as well as control mechanism. Following is the detailed discussion: - Internal and external features: internal as well as external features are present in the business culture of the company. Such factors are right part while applying the model of business (Rausch et al., 2013). Thus, information related to such factors are integral part of analytics of business. Such kind of data is important for getting important and useful data which draws meaningful solutions to effective decisions about the environment of organization through business analytics. The environment of company is also very dynamic by nature and complicated and business analytics plays a crucial role in data processing about internal and external culture. environmental scanning helps in providing ample amount of information about varied internal and external components. Identification of performance based drivers: performance based drivers holds a important position in performance management. The drivers of performance also make sure that the workforce and the company can meet the expected level of performance. Business based analytics process crucial data on processing, input and output and results. This kind of processing outcomes in identifying of the crucial performance drivers. Performance drivers can also recognize from already executed performance management system or the standards. Such kind of performance bench-mark can be tangible as well as intangible by nature. The standards are present and how a company can grow their own set of standards for the sake of performance management (Laursen, et al., 2016). The process of business analytics, operations and job description as well as specification of the workforce to test the performance standards. Thus, business analytics is important for integrating the process of performance management and growing the standards of performance that are crucial to test the performance. Integration of performance drivers with performance: after recognizing the performance drivers via business analytics, it is also important to link them with the real performance. Business analytics and associated analyses like linkage through cause and effect relationship. Once, the connection is set, it is also important to verify or evaluate the performance on specific performance indicator. After recognizing of the performance drivers, it become crucial to form a link with performance also. The link further is not developed and performance cannot be calculated. Business analytics also plays a key role as well as provide data associated with cause and effect relationship through using the raw data and converting it into used data. Business analytics ensures that performance based driver properly calculate the performance and they are right to test whether the performance is measured in right manner or not. Business analytics also take the performance based data and performance bas ed drivers that are tested under the actual performance of the workforce. Another disadvantage is lacking the integration is based of exertion of work in completely wrong direction (Chae et al., 2014). However, the workforce performs as per the performance drivers, but they are less integrated with the outcome of performance. Management action along with control system: management based actions as well as control system is crucial to manage the performance. Once the cause and effect relationship exist between the performance drivers and the real performance is settled, management control further verified whether the actual performance standards are being met or not. Business analytics recognizes the management based actions along with control for performance measurement. Business analytic principles and standards There are three crucial factors that have been addressed here and that promotes the need for applying of business analytics. These kinds of factors are based on excessive data, organizational interdependencies and requirement for the complete and holistic approach to execute business analytics. Such factors have emerged because of the individualization process along with globalization in the current business environment. This, consideration of such factors is crucial because of the execution of business analytics (Chae et al, 2014). Excessive data: large amount of data give rise to the issues based on data overload. Management usually is restricted to data processing abilities. There are so many factors that are internal as well as external environment of the company based needs to be evaluated for impactful decision-making process. This, the issue further intensified and required for business analytics to filer important data and integrate with performance management is crucial for the varied decision makers to recognize important performance indicators as well as success factors. Right amount of data is crucial to make important conclusion about the issues under the investigation but the excessive amount of data further develop numerous discrepancies that must be removed through proper filtering of data and retaining only crucial information. The business analytics also perform the task as well as retain valuable information and discard unimportant information. This the affective decision making is only possib le with the usage of the business analytics. Proper management of data and its implementation is also possible. But the right amount of fata is also required and is worth the importance to manage excess flow of data (Wang et al., 2016). Here inadequacy is an issue, with excessive data is also unimportant for the decision making. The balanced approach is important to take effective decisions in the company. Organization interdependencies: complicated organization culture and interconnection that exist between many practices in company needs a holistic approach to recognize performance. When there is lack of holistic approach which makes the data of performance completely worthless until it can be translated in some meaningful manner. Thus, holistic approach of data analyses with business analytics helps in contributing for more objective kind of decision for creation of performance by linking it with business analytics. It is important to understand that companies do not work in isolation. It is a process and function are interconnected with one another (Handfield et al., 2015). Thus, it is also important to adopt with the holistic approach to collect important data that is required to be tested simultaneously. Decision making is also based on specific factors that do not provide the complete picture of the problem. Thus, it is important all the interdependencies of the company must be properly evacuated. This is done in right manner and with the help of business analytics. Business analytics also provides a holistic approach to consider all the company interdependencies and give a rationale and effective decisions. There are cases when such issues come up from inadequate picture of the case which is going to be part of the management. This is the accountability of people that are engaged in decision making to consider all kind of factors of it. Need for holistic approach to execute the process of business analytics: the process of business analytics is implemented on the business intelligence in company and they often executed on part that are majorly in the planning phase. Thus, one of the main factors behind any kind of failure of the current strategic management decision is issues during the execution stage. The present research also lacks in providing the right clue for the execution business analytics. Decisions that are based on target of specific aspect of company further provides improper fata for decision making. For example, when the performance of employees is declining, it is important to aim on organizational and individual level of factors. Ignorance of any factors could lead to the ineffective evaluation of work for decision making. Thus, it is important to aim on the complete approach to execute the business analytics in the company (Wamba et al., 2017). Judgement The managers usually face many challenged to accomplish the competitive advantage and effective usage of business analytics further improves the strategic level decision for managers that can manage performance to accomplish the competitive advantage. Business analytics further helps in understanding of varied dynamics of business for so many business managers. It is further helpful to recognize shifts in varied business trends and modify in internal as well as external culture. This is crucial to evaluate the strategic level of decision making (Ji-fan et al., 2017). Thus, they are in a place to recognize whether these strategic decisions are producing the needed performance or not. They are in a place to change the strategy or make minor changes in the current strategy and bring back to perform at desire level. Operational level of effectiveness can further be improved by the process of business analytics. The process of business analytics also recognizes the more effective ways to process and operate in term of cost as well as time. Thus, the risk of time schedule and resources needed can be removed in effective manner. In addition, business analytics make it possible to further learn about the market and customer approach. Customer, market and transactional based data further provide important kind of insight related to varied business trends. Prediction of sales, seasonal level of peaks and demand can be recognised with the help of analysis of trend. The management also take the ideal decision at the right time. This is also done through adop ting effective business analytics. Another crucial advantage related with goal based decision making is authenticity. Objective level of decision making authentically deal the performance level and its execution in the company. Recommendations or solutions Important of business analytics can be realized by the practitioner as well as the scholars and it is further discussed that business analytics is usually related with affective decision making and better performance management. Properly integrating the performance management with business analytics further provides the basis for effective decision making for the management (Chae et al., 2013). It is a crucial aspect to accomplish the competitive advantage. Lower level of perfuming companies can achieve advantage from different analytics. Thus, recommendation for integration of analytics with performance management make the manager clear about the importance of performance management. The overall role of information technology and its application along with business analytics and management accounting based application along with integration is significant for the performance of the business. The important concern related to failure as well as inadequacy of business level analytics a lso lacks such kind of integration. There are majority of organizations that faces varied dilemma and they further regard performance management as performance indicators. There is a lot of need to gain clarity on the way business information can be processed from data to make effective solutions. Only then, advantages of business analytics can be properly reaped. In addition, it is also important that right culture must present in the company that helps the execution of business analytics (Vera-Baquero et al., 2013). Organization culture along with acceptance of stakeholder as well as the role of top management is important. When the organization culture is not very supportive and does not provide support for business level analytics, it cannot be executed with complete integration. 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