Analyze the effectiveness of statistical regression to manage data

Analyze the effectiveness of statistical regression to manage data

Statistical regression allows the data manager to essentially crunch numbers to help the user make decisions for the business. The regression will help in making decisions that will affect the business both currently and in the future. Data in many organizations and marketing are used to show how the market is carried out daily and know the kind of progress that they are supposed to expect in the future (Bryman,2017). The regression helps in predicting sales in the near and long term future. The numbers help in understanding the supply and demand of goods in the organization; thus, the business able to make rational decisions on the type of steps they should employ for better operations.

Statistical regression helps companies to analyze the data so that they can have a prediction on how sales will look like in the next six to twelve months. The effective of the regression has a significant impact on making new moves on the marketing sector since numbers never lie in statistics. Similarly, it has enabled companies to determine if they can choose one marketing promotion over the other. Additionally, regression on data has expanded ways on how to determine if a business can create a new market for products. Therefore, statistical regression of data is a crucial virtue for establishing statements and having guidelines based on the numbers and results that are obtained in later research (McCusker at el 2015).

Design the management decision strategy of forecasting

Identification of the problem is the first step that is taken when a decision has to be made. When a setback has been identified, it is easier to know how to tackle the problem. Similarly, the root of the effect is known, then another process can be followed without much difficulty. Analysis of the problem the second step that should be taken so that the management can see the weight of the problem and the impact it will cause to the organization. The analysis stage is where decisions are partially drawn to fill the gap that is affecting the organization.

Development of alternative solutions is the third step that an organization takes so that if the first decision does not suit the problem, they can apply the second one as a backup plan. When many choices have been drawn, there is a selection of the best option that will be able to suit the problem that is at hand. Moreover, in this stage, a lot of scrutiny over the repercussions of decision making are weighed so that they can be able to settle at a working forum.

When decisions are made, it is ethical to convert them into actions. Implementation of choices is the main idea that will help in ensuring things that have been discussed are put into action (Stage at el 2015). All decisions have to be made in one core assurance that they are implementable to suit the system. Following the implementation is a crucial factor at the end of decision making since that is the point where results of the decisions that were made have to be upheld. The diagram below shows the management decision strategy of forecasting.

Reference

Bryman, A. (2017). Quantitative and qualitative research: further reflections on their integration.                     In Mixing methods: Qualitative and quantitative research (pp. 57-78). Routledge.

McCusker, K., & Gunaydin, S. (2015). Research using qualitative, quantitative, or mixed methods and choices based on the study. Perfusion, 30(7), 537-542.

Stage, F. K., & Manning, K. (Eds.). (2015). Research in the college context: Approaches and methods. Routledge.