Developing Global Management Competencies - Literature review Example

Developing Global Management Competencies

Introduction

The Business Intelligence (BI) critical success factors include Finance, IT, Marketing, Human resource, Procurement, Production, and Logistic, Sales, Service. Business intelligence plays a pivotal role in enhancing project planning. It streamlines the strategic decisions made towards achieving the corporate goals. Additionally, it enhances the tactical and operational decisions made. Data analysis is enhanced by the application of the business intelligence. Statistical analysis software enhances the analysis of data subject to business intelligence requirements. BI helps in the reduction of various risks facing the projects. It also enhances objective project governance.

Data analyst Skills Essential in Business Intelligence

The main success factor of concern is the budgetary process for the M&S clothing business delivery system. In this case the application of SAS will enhance a sound budgetary process, which will enhance the delivery of the organization’s products. In this case, the software will be used to streamline the delivery system of the business. SAS will be applied in the analysis and evaluation of the past and present budgetary and delivery figures to harmonize the information in achieving efficiency.

Figure: SAS application in delivery system

Data analysis is important and indispensable in BI. It entails the collection, evaluation, and analysis of all information relating to a business entity. It is an important process because it requires accuracy and precision. Business intelligence is manifest in the use of statistical analysis software in the process of data analysis (Negash, 2004). In this regard, charts, pie charts, tables and scatter diagrams are used to ensure that process of data analysis is fruitful. There are many skills in data analysis, which a data analysis needs to be applying in the implementation of business intelligence. These include the soft and technical skills. The technical skills required by the data analysis include a comprehensive knowledge of statistical analysis and the graphical user interface (Sherman, 2014). Additionally, the data analysis is required to have a thorough knowledge of Querying language. The Querying language includes SQL, Hive, and Pig. Additionally, they must be versed with the ascription language, which includes Matlab and Python.

The data analysis should be proficient in a statistical language like SPSS and SAS. The other technical skill the data analysis should have is the spreadsheet usage skills. The spreadsheet is basic in data analysis. The use of SAS is essential for a data analysis. In this regard, the expert is expected to create business intelligence for a business entity. According to Kudyba & Hoptroff (2001), the data analyst must be versed with the business analytics to enable him to create BI dashboards. The dashboards are created using the SAS software. Additionally, the data analysis is required to create information maps through the application of SAS. Business intelligence can be gainful for examining crude information. In any case, there is a need to guarantee that information is perfect, reliable and of good quality for the individuals who will utilize it. It is essential to keep up an aggressive edge, through the investigation of business information and better information administration (Aanderud, Hall & SAS Institute, 2012). This business intelligence instructional exercise covers information administration, information examination, business information utilization and business investigation.

The creation of stored processes is also a data analysis job; hence, a data analyst must possess ideal skills to create such processes. Additionally, the data analysis job requires the design, tuning, and maintenance of SAS OLAP cubes (Minelli, Chambers & Dhiraj, 2013). The data analyst must also be versed in the use of all consumer applications to enable him relate well with the clients. Additionally, it is incumbent upon the data analysis to develop various applications, which are relevant in the application of SAS software. The soft skills the data analysis job requires include the definition of the problems at hand. Business intelligence is a widely inclusive classification of utilizations and innovations for a social occasion. Business intelligence applications incorporate the exercises of choice-supportive networks question and reporting, online scientific handling, information administration, factual investigation, determining, information examination and information mining. Business Analytics manages the approaches utilized by associations to improve their business by settling on enhanced choices with the utilization of measurable strategies that may include information gathering and investigation.

The identification of a problem is vital because it provides a lead to the solution. In this regard, the data analysis must balance between the times available in the time the process of problem identification requires. According to Minelli, Chamber & Dhiraj (2013), the understanding of the audience is also important although it seems minor for some people. The understanding of the audience ensures that the data analysis understands the background of the applicability of the data being processed. Different heads require different data sets to enhance objectivity. For instance, a CEO requires data for strategizing as opposed to an operational manger. The business examination may require numerous intricate systems that need propelled measurements. Data can be extremely helpful in contriving new product offering with components that are prone to boost deals in a specific locale for an arrangement of target groups of onlookers (Miller, Bräutigam, & Gerlach, 2006). A legitimate investigation of information may likewise tell about things like repeating bolster client issues, and accordingly proactive strides can be taken before it becomes out of extent.

The audience knowledge enhances objectivity of the data analysis process. The selection of a sound predictive model is the onus of the data analyst, and this enables him to dispense his duties promptly hence managing time in the best way. The adoption of the advanced software of data analysis like SAS enhances efficiency and effectiveness of the entire process. In fact, the use of SAS enhances excellence in the handing off data with regard to business trends (Minelli, Chambers & Dhiraj, 2013). The process of data analysis also requires proficiency in the organization of unstructured data. Business Analytics is frequently utilized by advertising people as a part of foreseeing and dissecting buyer conduct, and this is finished by applying factual explanatory procedures on authentic information of client exchanges. Without amazing information and measurements, the business investigation can have practically zero intending to any association. Business examination utilizes measurable strategies and investigation on past business execution to grow new business experiences and drive business arranging.

The unstructured data can include production metrics and client figures. The data analysis enhances the predictive nature of information processed. Consequently, the managers can plan for the future. SAS helps in performing functions like business activity monitoring, trend analysis, and multi-dimensional analysis. Additionally, the software helps in the budgeting and competitive analysis. Consequently, an organization improves on the weak point discovered through such an analysis. According to Minelli, Chambers & Dhiraj (2013), the business activity monitoring ensures the provision of real-time data pertaining to the stage of operations and transactions within an organization. Business Analysis may utilize a blend of innovations, aptitudes, practices and applications in its persistent and iterative examinations. Business intelligence then again utilizes a steady arrangement of frameworks on the past information to gauge execution and drive the business arranging. BI can likewise utilize factual strategies. Business intelligence is a greater amount of reporting and questioning. Business intelligence can be utilized as a contribution for human choices, or it can completely computerize the basic leadership process.

Therefore, an organization can make an informed decision regarding total quality a manager and customer service. In a competitive analysis, the data analyst helps in the revelation of the progress of the rivals and benchmarking (Rud, 2009). Consequently, an entity develops competitive edge from the information provided by the SAS data analyst. Such information leads to a boost in a firm’s revenue. The analysis carried out on the competitions features both the strengths and weaknesses of the rival firms. Such an analysis helps a firm to ascertain whether a certain company is an actual competitor or a potential competitor. Business intelligence can answer what happened previously, in what numbers, the recurrence of occurrence, the area of the issue, and what remedial activities are required. It is conceivable, and turning out to be more mainstream, to create intuitive BI applications streamlined for cell phones, for example, tablets and advanced mobile phones, and for email (Sturdy, 2012). All around planned BI applications can give anybody in an organization the capacity to settle on better choices by rapidly understanding the different data resources in an association and how these connect with each other.

It is important to realize the significance of using statistical analysis software. When analysing the competitor in business, there are major aspects, which must be considered. The objectives of the competitor and the competitor’s resources are a vital source of information pertaining to the competitor threat (Minelli, Chambers & Dhiraj, 2013). Additionally, the competitor’s strategy is also vital because it helps in monitoring the moves of the rival in business. Additionally, the assumptions of the competitor are vital in analysing the rivalry of the competitor. The combination of the four aspects enables a firm to establish a competitive edge against the competitor. These benefits can incorporate client databases, network inventory data, workforce information, fabricating, item information, deals, and advertising movement, and whatever another wellspring of data basic to an operation. A vigorous BI application, which incorporates coordination and information purging capacities, can permit a man to incorporate these divergent information sources into a solitary intelligent structure for on-going reporting and examination by anybody in a comprehensive venture, clients, accomplices, workers, chiefs, and officials.

The SAS software is vital especially in the prediction of the financial aspect of the business. The prediction of the financial requirements of a business enhances objectivity and planning. The data analysis also must be versed with simulation skills. Such skills enhance the simulation of various outcomes upon applying a given strategy. In this regard, the sound decision can be made regarding the situation at hand. The process of data analysis also involves multidimensional analysis. The data analysis must be versed with the process to enhance objectivity (Wittemann & Project Management Institute, 2010). The freshness of insight business ventures can make achievement a troublesome metric to adequately quantify. The essential metric is a fundamental understanding that BI yields ought to positively affect the business. Conveying this impact ordinarily requires quick client selection A few studies have reported just a low reception rate toward the beginning of most business intelligence venture organizations. At the point when groups ought to dig into business knowledge, they are rather pushing for client appropriation which makes bottlenecks and can bring about venture slip-ups or disappointments, similar to the absence of execution or incorrect information.

The process entails the grouping of data into data dimension and measurements. For instance, data, which constitutes of information spanning many years is considered multidimensional. The analysis is vital for the data analyst because it helps him to analyse data objectively over a period of years. SAS reduces time spent in the statistical analysis of data, which improves every process in the strategic, tactical and operational levels of management (Minelli, Chambers & Dhiraj, 2013). The system is also relevant in a big organization, which has huge volumes of data for analysis. This notwithstanding, very business requires the SAS to objectively evaluate its operations. The data analysis is also charged with the responsibility of ensuring that data is economically utilized by investors and other stakeholders of an organization. The prevalence of the data analysis services is growing in almost every organization (Minelli, Chambers & Dhiraj, 2013). This is because of the benefits that the software accrues to the users. Data analysis is vital in the application of business intelligence in business because it provides insight into the entire business environment. Additionally, it enables a business manager to make accurate and reliable forecasts.

The application of the software underscores information management and total quality management. Performance management is also enabled by the application of the advanced statistical analysis software. The process entails the evaluation of the financial operations of an entity. The application of the SAS software allows an ideal combination of statistical and analytical skills to achieve the objectives of the business. The application of business intelligence helps in assuring eh going concern of the business. The application of business intelligent in an organization requires the incorporation of information systems. The application of the statistical analysis software accrues many benefits to the business (Hu & Cercone, 2004).

Conclusion

Business requires business intelligence in every aspect including the Finance, IT, Marketing, Human resource, procurement, production and logistic, sales service. A data analysis must process adequate skills to enable him successfully manage the application of business intelligence. These include technical and soft skills. The technical skills include knowledge of statistical analysis and the graphical user interface, thorough knowledge of Querying language, SPSS and SAS skills. The other technical skill the data analysis should have is the spreadsheet usage skills. There is a need to expand the application of the statistical tools because there are other vital statistical models besides SAS.