The Application of Analytics to Business - Case Study Example

Predictive Modeling Name Institution Date Predictive Modeling Introduction Large corporations are increasingly facing different challenges that require major decisions to be made from time to time. Several factors are responsible for business pressure and hence the need for appropriate decision making techniques. Analyzing and solving a problem may take a lot of time and resources depending on the model that is used. This therefore requires a proper understanding of the modeling techniques. During the decision making process, different alternatives have to be selected. This is for the purposes of ensuring that the best alternative for solving the problem is selected. The increased competition in the market requires the large corporations and other businesses to develop a response and support for countering the competition. Business pressure response and support models are in place although it requires some form of expertise (Barton & Court, 2012). Technology has also been introduced in the analytical models for making decision and solving the problems associated with the business pressures. Some of the analytics technology commonly used for countering the business pressures includes predictive analytics, prescriptive analytics and reporting. The paper discuses the application of three analytics in relation to the case study. Predictive analytics Predictive analytics is one of the techniques that are used by the large corporations in response to the business pressures. This technique involves the use of a variety of modeling, data mining and machine learning for the analysis of current issues facing an organization in order to make predictions about the future. The predictive analytics mainly deals with the transactional data within the organization for identifying the possible risks and opportunities. The pressures in most cases usually result to the risks which may affect the competitiveness of the corporation. When using this technique, the business is able to obtain a predictive score for each individual aspect of the business which is related to the business pressure that the organization is facing (Larose, et al, 2015). The probability is usually used to determine the potential of the business units to overcome the pressure. The predictive score is usually provided for the customers, employees, product, organizational unit or machine. Some of the large corporations have used the predictive analysis for the purposes of fraud detection. This is considering that fraud has a lot of negative impacts on the growth and development of the organization. The manufacturing companies also use this model for analyzing and solving the problems in the manufacturing processes. The extraction of information from the available data is usually carried out when using this method in order to predict the trends and behaviors. Government agencies also use this technique for making predictions. The quality of assumptions as well as the levels of data analysis is an important determinant of accuracy when using the predictive analysis. Amazon is one of the largest and profitable corporations that are involved in the sale of goods and services through online methods. However, the company was facing a challenge in terms of delivering the products to customers on time. The shipping cost was also high when the products were only delivered as per the order of the customers. This had negative impacts on the ability of the company to satisfy the needs of the customers. However, the company employed the use of predictive technique for solving this problem. The company utilized the records, website traffic and geographical; relevance data (Lindsey, et al, 2014). This was for the purposes of predicting the trends with regards to the needs of the customers. As a result of the predictive analytics the company was able to develop a service called anticipatory shipping and it acquired a patent for the service. Through the use of this service, the company is able to ship products even before it is ordered by the customers. Through the use of anticipatory shipping, the company starts to ship products to different regions even before any order for the products is made. The shipping is usually carried out with the anticipation that the products will be required in the regions that it has been shipped. This process makes it easy for the products to be delivered to the customers in the particular region. The delays as well as increased shipping costs are reduced through the use of this service. The corporation is able to know that the products will be required in certain geographical areas as a result of predictive analytics. Amazon has customers from different parts of the world and the pressure to deliver the products on time was quite huge for the company. The company and the customers are therefore able to benefit from the predictive analytics. The company in some instances takes less than 24 hours to deliver products to the customers as opposed to the two day system that was in place. Cost effectiveness at the company has also been achieved and hence ensuring that the company is able to increase on its profits. The use of existing data to see into the future is an important aspect of predictive analytics. The predictive models are currently in use by most of the corporations. This model is useful in terms of enabling the organization to assess the likelihood of certain events (Waller, et al, 2010). This includes the performance of the organization operating in certain conditions. The effect that the processes will have on the customers is usually determined through the use of the model. The known performances as well as the attributes have to be considered during the process in order to come up with the most likely future predictions. However, the predictive analytics requires a lot of expertise as a lot of data analysis has to be carried out. It may also require a lot of resources due to the nature of expertise required. The probability of success when using this method is usually high although it is dependent on the situation facing the organization. Prescriptive analytics The prescriptive analytics is considered as the third and final phase of business analytics. This technique mainly synthesizes the big data and makes suggests options that can be used by an organization. The prescriptive analytics plays an important role in ensuring that the actions required for achieving the predicted actions are clearly specified. The benefits that the business is likely to experience as a result of the predictions are usually highlighted through the prescriptive analytics. The prescriptive analytics usually plays an important role in terms of answering the question of why a certain event will happen (Perugini & Perugini, 2014). This includes the risks that a corporation is likely to face as a result of the business pressure. The main advantage of using the prescriptive analytics is its ability to take in new data to re-prescribe. Some of the business situations may change from time to time and hence the importance of incorporating the new data. The level of accuracy is also improved when any new data with regards to the business situation is used. Other priorities are usually considered when using the concepts of prescriptive analytics. This is for the purposes of avoiding any contradictions that may impact negatively on the other business processes and operations. The structured as well as the unstructured data are usually incorporated when using the prescriptive analytics method. All the business rules are usually considered when using this technique and hence ensuring that it is efficient. This technique also requires a lot of expertise and an understanding of the business rules. The prescriptive analytic was developed in 2003 and it is therefore still new. Most of the companies are unable to use this technique for dealing with the business pressures. A lot of errors are still evident in most companies when using this technique with only 3% of the companies using it. Road accidents are one of the major problems in the world and it accounts for thousands of deaths every year. Human error contributes to the accidents but the mechanical errors are also a contributing factor. Google is one of the innovative companies that have utilized the prescriptive analytics to develop self-driving cars (Chen, 2011). This is for the purposes of solving the problems associated with road accidents as well as eliminating the need for the mandatory driving licenses for all drivers. The cars have to make decisions based on predictions and future outcomes. The self-driving cars have to anticipate what is coming for the purposes of avoiding accidents. This is therefore set to reduce the number of fatalities and damages as a result of road accidents in different parts of the world. However, the cars are not yet on the roads as more tests are still being carried. It is set to be in use in the near future in most parts of the world. The prescriptive analytic is therefore useful in terms of improving on the quality of the products as well as the business processes. It can therefore be used for the purposes of benefiting the customers as well as the organization. The prescriptive analytics has the potential of impacting hugely on the businesses. The decisions making process within an organization is also impacted by the prescriptive analytics. The effectiveness and efficiency of the organization can also be improved through the use of prescriptive analytics. Prescriptive analytics has also been used by some companies for the purposes of optimizing scheduling, production, inventory as well as the supply chain. The delivery of right products in the right quantity to the customers can also be achieved through the use of prescriptive analytics (Goodnight, 2011). This is beneficial to the customers and the organization. The understanding of the business processes is also made easier when the prescriptive analytics is used. This is beneficial to the people running the business as well as the customers. The companies with big data can also benefit from using the prescriptive analytics. However, only a few companies have big data and hence limiting the use of prescriptive analytics. Ayata is one of the companies that are well known for big data. The company is currently using the prescriptive analytics for the purposes of carrying out its operations. The management of the company through the use of the technique has been effective as compared to the previous years when it was not using the technique. IBM is one of the technological companies that have also endorsed the use of prescriptive analytics. It has described it as the final phase of business analytics. Reporting Reporting is one of the structures that are used for the purposes of measuring and monitoring the business performance. It is also considered as a method of converting data into information. The information can be used by the organization for the purposes of responding to business pressure. The information that is obtained through reporting can be used for making decisions that are aimed at promoting effectiveness and efficiency. The reports are used in most of the corporation for supplying answers with regards to what happened and when (Sharda , et al, 2013). This could be in terms of the operations that are affecting the organization. Predetermined queries are mainly associated with the reports. This is considering that the reports are supposed to highlight the likely solutions for the business pressure. Analyzing the information provided in the report can be useful in terms of obtaining a better understanding of the problems facing the organization. This can also be used to identify the most probable solution to the problem facing the organization. However, may not be conclusive as it only addresses specific problems facing the organization. As compared to business analytics, the method is only aimed at addressing specific problems within the organization. Siemens is one of the major manufacturers of electronic gadgets. Its mobile phone was once dominant in the market as a result of its high quality and features. Currently the company uses different methods to determine its productivity and efficiency. Reporting is one of the techniques that the organization utilizes for various purposes. The reports are used for decision making process within the organization when responding to the business pressures. Corporate performance within the organization is usually gauged through the use of reports. The reports are usually prepared with a lot of expertise within the organization. In case of any challenges facing the company, a report is usually prepared to determine the likely cause of the problems and why the company is facing the challenges at the particular moment (Goodnight, 2011). High levels of accuracy are usually maintained for the purposes of ensuring that the report meets the needs of the organization. The business metrics are usually established at the organization through the use of reports. KPMG which is one of the famous audit firms in the world supports the use of reporting. This is in terms of promoting efficiency within the organization and hence meeting the performance goals and objectives. The financial performance of the organization can also be enhanced through the use of reporting. This is because it enhances the operations of the organization in terms of promoting accountability and efficiency. Multiple data sources can also be brought together for the purposes of developing the reports. However, it is also important to note that the reporting tools in some instances tend to provide static results for the managers. This has the potential of making it difficult for the business managers to respond to the business pressures (McAfee & Brynjolfsson, 2012). Reporting is however commonly used by most of the organizations as it is simple as compared to the other analytics techniques. However a lot of manual work has to be carried out when reporting is used. As a result of the manual work, it may be less flexible and difficult to maintain. More than one data sources are usually used when the reporting technique is utilized. Most of the logistics companies also use the reporting method for the purposes of ensuring that it improves on its operations. The performance of the logistics company in terms of the supply chain can be obtained through reporting. How much of a product can be sold can also be determined through the use of reporting and hence the development of competit8ive strategies. Conclusion It is evident that the business analytics and reporting is useful in terms of responding to the business pressures. The different techniques have been used by different companies for the purposes of ensuring that it is able to maintain enhance its operations. Amazon is one of the companies that use predictive analytics for the purposes of enhancing its supply of products and meeting the needs of the customers. Google has used the prescriptive technique for the development of a self-driven car. This is for the purposes of reducing the high rates of road accidents which in most cases are fatal. It is evident that the future of an organization can be enhanced through the use of prescriptive and predictive analytics. Reporting technique is also commonly used by most of the organizations due to its simplicity. Siemens is one of the large companies that utilize the use of reporting. References Larose, D. et al. (2015). Data Mining and predictive analytics. London: John Wiley and Sons. Waller, M. et al. (2010). Data Science, Predictive Analytics and Big Data: A Revolution That Will Transform Supply Chain Design and Management. Journal of Business Logistics, Volume 34, Issue 2. Pp 77-84. Lindsey, C. et al. (2014). Predictive Analytics to Improve Pricing and Sourcing in Third-Party Logistics Operations. Journal of the Transportation Research Board, Volume 2410 Issue 14. Barton, D. & Court, D. 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