Target Compliance

a) Identify the scenarios that require the use of forecasts

b) Analyze the different forecasting methods of qualitative models, time series models and causal models.

Introduction

In Topic 1: Forecasting and Decision Making in Module 3, the importance of using forecasting methods as part of decision making under uncertainty was discussed. In this work the student will a real modeling scenario for the sales of a supermarket. It will apply the use of the steps to follow in decision making and the use of forecasting methods.

Instructions:

Using the six steps to follow in decision making, model a problem that requires the use of decision making related to the application of the use of a sales forecast for a supermarket. Make the forecast with the data in the Table below. Data is in thousands of dollars. The student will assume that these data come from the company.

Board. Supermarket Sales Data

Months	2018	2019	2020	2021
January	2165	2046.6	2075.3	2032.3
February	2213.5	2109.2	2097.7	2107.4
March	2103.1	1956.7	2021	2012.8
April	2133.6	2016.7	2082.8	2029.1
May	1966	1849.5	1906.9	1826
June	1937.5	1818.3	1950.3	1795
July	1856.8	1791.9	1817.8	1762.3
August	1758.4	1629	1738.3	1629.4
September	1864.3	1720.2	1993.4	1814.5

October	1889.7	1814.3	1895.8	1793.3
November	2032.8	1897.4	2009.1	1890.7
December	2014.5	1961.1	1990.3	1938.3

Board. Supermarket Sales Data

1. Using your creativity, you are going to give a name and location to the Supermarket. 2. You must explain each step using the Table: Modeling in a Real Scenario that is included later, the closest to a real situation. 3. Make the forecast using at least four projection methods discussed in class and compare your results. Include their interpretation. For the estimation you will use the Excel QM tools. 4. The methods that will be used are the following: To estimate these criteria, you will use the Excel tool QM or QM for Windows. a. Trend for 4 years (scatter plot) (You can use regular Excel) b. Weighted moving average (for the year 2020 and 2021 (separate) c. Exponential smoothing with adjusting trend (year 2021 only, alpha and beta is 0.5) d. Trend regression (year 2021 only) e. Multiplicative decomposition method (year 2021 only; 4 series)

Table: Modeling of a Real Scenario

Modeling in a Real Stage (Name of the company)
Step	Description
Definition of the problem
Development of a Model
Data collection
Development of a solution
Proof of solution
Analysis of the results
Implementation
Note: Next to this Table, attach results of the Excel Qm or QM for Windows programs that served as a support tool in the decision-making of the modeling of a real scenario.