Assignment Overview

Developing a business forecasting provides management with strategic and operational insight leading to improve business performance. It is the basis of budgeting and provides the information that allows managers to manage. Without a business forecast a business has limited capacity to maximize future opportunities or minimize potential risk. The purpose of this project is to give you an opportunity to make use of time series forecasting methods to inference about future performance.

Assignment Scenario

Pam Golding Properties is recognised locally and internationally as Southern Africa's leading independent real estate group and the South African's most awarded real estate company. Offering a full spectrum of property services, Pam Golding Properties boasts a network of over $300$ offices in sub$-$Saharan Africa as well as offices in the UK$,$ Germany, Mauritius and Seychelles. The Group also facilitates property sales and residency in Spain and Portugal and property sales in the USA.

The Pam Golding Property group forms part of a strategic alliance with one of the world's largest property groups, Savills plc$,$ gaining access to its prestigious network of over $600$ offices worldwide. Through this partnership and other associations, including Homecoming Revolution and Southern Africa Luxury Association, their estate agents are uniquely equipped to provide prospective buyers and sellers with a comprehensive range of professional property services.

The group has concluded that to plan for the growth of the Pam Golding Property in the northern suburbs, the sales director, Mrs Carmen Samuels needs to develop a system that will enable her to forecast property sales by quarter for up to one year in advance. The number of houses sold quarterly by Pam Golding Property in the northem suburbs is recorded for the $16$ quarters from $2020$ to $2023,$ as shown in Table $1.$

Table $1.$ Quarterly house sales by Pam Golding $(2020-2023)$

$\backslash$table$[[$Year$,$Season$],[$Quarter $1,$Quarter $2,$Quarter $3,$Quarter $4],[2020,54,58,94,70],[2021,55,61,87,66],[2022,49,55,95,74],[2023,60,64,99,80]]$

Management Question $1$

Refer to the quarterly house sales data in Table $1.$ The sales director has requested a trend analysis of this sales data to determine the general direction of future quarterly housing sales, and an estimate of house sales for the fifth year.

$[32$ marks$]$

Page $2$ of $3$

Management Question $2$

Refer to the quarterly house sales data in Table $1.$ Mrs Samuels would like to identify the impact of quarterly seasonal influences on house sales. Calculate the quarterly seasonal indexes for the house sales data and interpret the results for the sales director of Pam Golding Property in the northern suburbs.

$[20$ marks$]$

Management Question $3$

Refer to the quarterly house sales data in Table $1.$ The sales director would like to use the exponential smoothing time series model with smoothing constants of $0\mathrm{.}1$ and $0\mathrm{.}5.$ Which smoothing constant appear to provide the better forecasts? Determine an estimate of house sales for the first quarter of $2024$ using the best smoothing constant.

$[48$ marks$]$

Total: $100$ marks $=100\%$

Weights: $20\%$