Introduction
Among the goals that every business entity outlines during its establishment and operation include the development and success of all their endeavors. Besides identifying the needs of its clients and how the competitors operate, business analytics in every organization is essential especially in accomplishing the set goals. In consideration of the advancement and data within the body, use of analytics in resolving arising challenges is vital in operation and facilitating efficiency. As highlighted by Molly Galetto, business analytics is the critical study of the organization’s data and formulating predictive measures while applying optimized techniques whose results are later communicated to all concerned stakeholders (Patt, 2017) . Most of these involved stakeholders include business partners, customers, and investors among others. For purposes of formulating decision or coming up with predictions that are reliable, the business analysis must be conducted quantitatively with evidence-based methods. Furthermore, the primary reason for relying on the analytic solution is to handle massive data volumes and enhance decisions made.
Forms of Business Analysis
Currently, most business and organizations are focused ensuring that the decisions made in the firm meet their future demands while enhancing the productivity in their everyday activities. Through optimizing the supply chain, historical data must be put into consideration to analyze the incidences that might take place in the future. Moreover, the quest to stay relevant in the market is encouraging and a great course that supports organizations into being data-driven hence analytical. Despite the existence of analytic options that tend to be sophisticated and daunting, they can be used together to complement each other thus co-exist. Therefore, for purposes of the business to get a clear view of the market, its competition and identify strategies that will facilitate efficiency, the use of an advanced and robust analytic system or the environment. The three common forms of business analysis include descriptive, predictive and prescriptive analytics. As mentioned earlier, these kinds of analytics can be used incorporation of each other primarily to facilitate effectiveness.
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Descriptive Analytics
Just like the name denotes, descriptive analytics illustrates and elaborates the data summarized raw data to ease the ability to be interpreted by humans. Analytics in this form takes an insight into the past of the organization, and activities that were done in previous days, hours minutes or seconds. The importance of descriptive analytics in any team is to make sure that past events provide vital lessons that will be applied in operation and activities of the firm targeting the outcome and influence of the future. In most cases, descriptive analytics are used when the quest to understand the events of the organization and what is required in summary of the varieties of business aspects. It is under this category that most of the statistics in a group or business fall under with infinite ranges. Elements of the organization that rely on descriptive analytics include the sum of stock inventory, change in sales and money spent annually by customers, financials, sales, production, and operations among others.
Predictive Analytics
Under this form of analytics, the organization is in a position to understand the future of its operation, activities among other vital events. Under this type of analytics, the organization is not only in a position to predict the future but also can make decisions and actions that are insight-filled by the data. Moreover, the analytics in question ensures that future outcomes are estimated on a precise level even with the knowledge that predicted statistics cannot achieve 100% accuracy. Therefore, companies are aware that the predictions are based on probabilities hence use the statistics to outline future happenings. The process applied in the predictive analysis is making use of the available data and filling in suitable and relevant statistics. Most of the historical data used are got from ERP, POS, HR and CRM systems and are used to identify patterns that are later applied to models that help capture the relationships between sets of data. For organizations to figure out their future needs, they will have to ask and make use of the predictive analytics (Marshall, 2015) . Moreover, this kind of analytics is used for purposes of studying the behavior of customers regarding their trends in purchasing and activities of the sales. As a result, it is easy for the organization to outline inventory, the inputs of demand and the supply chain and all other operations. Predictive analytics are in most cases used by the agency to describe credit scores of their customers. Besides all available financial services, the credit score produced through predictive ratings, the organization is also in a position to determine the chances which customer with credit is in a place to make their payments. With close predictions of the credit scores made, the organization also is in a position to understand the sales and inventory variables. In summary, predictive analytics is used primarily to identify future needs or fill the missing data and information.
Prescriptive Analytics
As observed earlier, the events and progresses taking place within an organization are immense. They determine in most cases how and when some anticipated outcomes may be found. Prescriptive analytics is mostly used in deliberating possible solutions and advise on relevant outcomes required. The form of analytic in question is primarily used in quantifying future effects of the decisions and applied the advice. Therefore, predictive analytics outlines the events that will take place and the reasons why issuing a recommendation on the outcomes that make use of the predictions made. While the descriptive and predictive analytics provide elaboration and possible future outcomes, the prescriptive analytics goes to the extent of making recommendations on actions that are suitable to the consequences of the organization’s future. Based on the activities and operations taken by the company, it is easy for the management to prescribe the quantity of the decisions made analyzing the solution that is relevant and meet both present and future demands. For efficiency in prescriptive analytics, incorporated techniques, strategies and tools are used. Such methods include computerized procedures, business rules, machinery, and algorithms. The decisions made and the kind of impact experienced within an organization is determined by the proper implementation of the prescriptive analytics. The prescriptive analysis is mostly used by well-established companies in production optimization, planning, and inventory in the supply chain. The purposes of applying the prescriptive analytics in the mentioned areas are to ensure that customer preferences are produced and goods delivered on time and in good conditions.
Conclusion
Business analysis is one of the critical factors that contribute to the success of the organization. Through application and use of proper business analysis, interpreted information ensures that organization is in a position to understand the factors that are affecting its operations either positively or negatively. As a result, the interpreted data influences the decisions made and the outcomes expected. The forms of analytics used will depend on the preferences of the organization. In instances where the firm relies on the records and activities, it will be better to make use of the descriptive analytics. For future reference and outcome, predictive analytics is more relevant and geared towards identifying the anticipated goals. Prescriptive is more detailed than the two since it offers recommendations of the concerned underlying issues.
References
Marshall, A. (2015, May 26). Big Data & Analytic Hub . Retrieved November 17, 2017, from IBM: http://www.ibmbigdatahub.com/big-data-analytics-heroes/all
Patt, M. (2017, September 26). 7 keys to a successful business intelligence strategy . Retrieved November 17, 2017, from CIO: https://www.cio.com/article/2437838/business-intelligence/7-keys-to-a-successful-business-intelligence-strategy.html
