The business applications of predictive analytics cannot be understated. Learning from the past is so critical, lest the same mistakes from that time be repeated. As a result, it is necessary to come up with methods of analyzing data obtained from the past using its unique qualities and determining its future outcomes through the systemic use of data. Predictive analytics analyzes data to find patterns and thereby identify future patterns from the wealth of past data. In this paper, the application of predictive analytics is embarked on looking at the benefits of its application in modern-day business.
Predictive analytics is specifically unique in that it offers the business the unique opportunity to look into its future based on historical data (Farooq, 2015). On the other hand, different other big data analytics methods such as prescriptive analysis look into data, showing the organization its challenges and how to remedy them. Descriptive analytics, on the contrary, offers the management of the organization a full picture of what is currently happening. Predictive analytics is especially important for organizations where big money is involved. This is because the lack of strategy or a mistake in strategy can cost the organization to the tune of millions, both in revenue and operational costs. As a result, forecasting is necessary to avoid such losses.
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Consider the case of an investment company looking to invest in long-term options. The management of company is faced with several investment options, each attached with certain risk and rewards at the maturity date of the investments. In such a scenario, predictive analytics come in handy to empower the management of the company to make the right choices. The absence of such a choice could result in gross inefficiency within the management of the company, leading to abounding losses.
An important aspect of organizational leadership today is the ability to make strategic choices within management. Consider the innovation of a new product by a company. The product having performed in the market under certain conditions for a time provides the business manager with a feel of what performance can be like. To materialize this ‘feeling’, data analytics come into place cementing the feeling with actual statistical data to either support or reject the manager’s feeling. In other words, predictive analytics can be used in evaluating the past performance of a product to come up with expected future performance levels of the same.
Additionally, it licenses other mechanisms within the organization to find out the one that produces most results. Where a company has multiple marketing strategies, predictive analytics obtain performance for each marketing strategy and determine the most effective method of marketing, thereby getting the most out of it. Moreover, where demographics for product sales are involved, it helps the company fine-tune its market strategy to exhaust the market for which the product largely appeals to. Again, an analysis of the company’s products and how it is performing so far can be used to determine the future market share of the product in a prescribed length of time. As a result, it would be possible to calculate revenue, operational costs and expansion within a certain timeframe where the factors are considered constant.
In conclusion, predictive data analytics is especially critical to business processes. Among other things, this application enables businesses to become more efficient, empowers the business to overcome future hurdles and provides the management with a feel of the future direction of the company or a product, among other things. As a result, the importance of such application is critical to the business.
References
Farooq, M. (2015). Applications of Predictive Analytics in various industries . Retrieved November 8, 2017, from Big Data Made Simple: http://bigdata-madesimple.com/applications-of-predictive-analytics-in-various-industries-2/
