Business Intelligence System modeling - Essay Example

? Business intelligence Affiliation Business Intelligence System modeling For any business that intends to grow, theremust be a policy that promotes change. The contemporary business environment depends on how information system is applied. Business processing model is part of systems model that is useful in converting change management strategy proposals of a business into real applicability. The business model, which takes into account change processes in business environment, applies decision analysis, monte carlo simulation, data envelopment, exponential smoothing, and non linear programming. In order to remain relevant in a competitive business environment, an organization should have a strong change management strategy that must influence all departments within an organization. In this business model, management processes, supportive processes and operational processes are interlinked to avoid departmental miscommunication. Centralization of information and data is vital in ensuring appropriate decision making process and implementation of an organization’s policy (Tennet &Economic group, 2005). Exponential Smooth This system modeling technique is essential in making future projections that are essential for risk aversion and developing financial strategies that can withstand economi9c shocks. A business may be affected by fiscal and monetary factors that may lead to inflation. As such, it is important for any business to develop computer programs that can utilize present performance of a business to detect future trends. One of the essential concepts that need to be applied is triple exponential smoothing. This business modeling technique takes into account seasonal changes when projecting possible business performance. This technique analyses the present business trends and uses them to make future projections. It takes into account the time variable (t), sequence of best time estimate for seasonal change (b), seasonal correction factor sequence c1, and the expected proportion of the forecasted trend (c2) (Tennet &Economic group, 2005). Data envelopment Data envelopment enhances productivity. It is essential in management and cost accounting department of an organization. This technique is used to measure the productive efficiency of decision making units in the organization. Data envelopment utilizes the cost variable such as labor cost in searching for the lowest unit in any given cost output in order to promote an efficient frontier. Any organization that does not have an efficient frontier is considered as ineffective in a competitive business environment. Different variables that include quality of service, number of employees, and safety of the environment can be analyzed and compared with other companies in order to determine strategies that can enhance business performance. The advantage of this technique is that it has the ability of accommodating a multiplicity of outputs and inputs. It is also essential in calculating efficiency by allowing the analysis of output level and size in determining efficiency. Cost management is essential for any business because it maximizes profit and minimizes cost. Since one of the major factors of any business is to increase profit, data envelopment is useful because it promotes efficiency of costing techniques and developing managerial decision based on cost accounting data (Tennet &Economic group, 2005). Non linear programming This method uses mathematical optimization in solving non linear problems. It applies equalities and inequalities systems in determining long term business survival strategies. This technique is essential in forecasting an organization’s income statement to determine its profitability. In a typical non- convex problem, it can be used to optimize a specific expense among different forms of expenses to determine one that is economical. For instance, it can minimize transport cost by selecting a transport system that is economical. This technique is important in engineering or maintenance departments of an organization because of the complex and non- linear nature in determining cost effective measures of an organization.. Non linear programming uses multiple variables and theoretic models to determine the methodology and findings of a specific experiment. Although non- linear programming is not utilized in many businesses, it is essential in maintenance and departmental sections (Tennet &Economic group, 2005). Monte Carlo simulation Monte carlo simulation is a technique of business processing model that depend on random sampling to obtain numerical results. This technique is usually used in mathematical and physical problems to form closed-form expression. In businesses, it is used in mathematical finance and finance to analyze and value portfolios, financial instruments, and investments by simulating different sources of uncertainty that affect their average values against a range of total outcomes. An example of this technique is stochastic asset model that is commonly used in stock markets. The advantage of this technique in a business is that it easily determines the level of uncertainty of factors that affect organizations. In case of three or four state variable, this technique is the best solution .However, this model is not recommended for America option because it only estimates the option value by making assumption of a specific starting time and point, but since one of the main aim of a business is to grow, this technique is recommended for investment in other countries that an organization may wish to invest in (Tennet &Economic group, 2005). Decision analysis This is an important model in decision making processes of the organization. All strategies and business processing model techniques are aimed at assisting the management and support staff of an organization to reach an ardent decision for growth and survival. Decision analysis includes a myriad of processes, tools and methods that are aimed at identifying, presenting, and assessing essential aspects when making business and managerial decisions and developing recommendation for a course of action. One of the most appropriate decision analysis methods is stochastic dominance. This decision analysis technique utilizes probability distribution analysis in determining the growth prospects of a specified business activity within a given business environment. It determines whether there is a favorable or unfavorable business prospect. In this case, limited knowledge and risk aversion techniques are the major issue in making both business and managerial decision. However, this technique requires critical analysis and wisdom when analyzing the social, political and economic factors that influence growth of a business (Tennet &Economic group, 2005). In conclusion, it is recommendable for a business organization to utilize business processing model in enhancing its prospects of initiating change and maintaining growth in an ever- changing business environment. In order for a business to survive, the management needs to focus on change management strategies to enhance its performance in a competitive environment. References Tennent, J., Friend, G., & Economist Group. (2005). Guide to business modelling. London: Profile. Read More