Read the case study provided and answer ALL the questions.

FORECASTING AT AFROS CAFE

With the growth of Afros Cafe$$from one pub in Bloemfontein in $1988$ to more than $145$ restaurants in $60$ countries

today$$came a corporatewide demand for better forecasting. Afros Cafe uses long$-$range forecasting in setting a

capacity plan and intermediate$-$term forecasting for locking in contracts for leather goods $($used in jackets$)$ and for

such food items as beef, chicken, and turkey. Its short$-$term sales forecasts are conducted each month, by cafe, and

then aggregated for a headquarters view. The heart of the sales forecasting system is the point$-$of$-$sale $($POS$)$ system,

which, in effect, captures transaction data on nearly every person who walks through a cafe$$s door. The sale of each

entr$$e represents one customer$$ the entr$$e sales data are transmitted daily to the Orlando corporate headquarters$$

database. There, the financial team, headed by Todd Lindsey, begins the forecast process. Lindsey forecasts monthly

guest counts, retail sales, banquet sales, and concert sales $($if applicable$)$ at each cafe. The general managers of

individual cafes tap into the same database to prepare a daily forecast for their sites. A cafe manager pulls up prior

years$$ sales for that day, adding information from the local Chamber of Commerce or Tourist Board on upcoming

events such as a major convention, sporting event, or concert in the city where the cafe is located. The daily forecast

is further broken into hourly sales, which drives employee scheduling. An hourly forecast of R$5,500$ in sales translates

into $19$ workstations, which are further broken down into a specific number of waitstaff, hosts, bartenders, and kitchen

staff. Computerized scheduling software plugs in people based on their availability. Variances between forecast and

actual sales are then examined to see why errors occurred.

Afros Cafe doesn$$t limit its use of forecasting tools to sales. To evaluate managers and set bonuses, a $3-$year weighted

moving average is applied to cafe sales. If cafe general managers exceed their targets, a bonus is computed. Todd

Lindsey, at corporate headquarters, applies weights of $40\%$ to the most recent year$$s sales, $40\%$ to the year before,

and $20\%$ to sales $2$ years ago in reaching his moving average. An even more sophisticated application of statistics is

found in Afros Caf$$s menu planning. Using multiple regression, managers can compute the impact on demand of

other menu items if the price of one item is changed. For example, if the price of a cheeseburger increases from R$7\mathrm{.}99$

to R$8\mathrm{.}99,$ Afros Cafe can predict the effect this will have on sales of chicken sandwiches, vegetarian sandwiches, and

salads. Managers do the same analysis on menu placement, with the center section driving higher sales volumes.

When an item such as a hamburger is moved off the center to one of the side flaps, the corresponding effect on

related items, say french fries, is determined.

Extracted from: Heizer and Render, $2018$

QUESTION $1[30$ MARKS$]$

$1\mathrm{.}1$ Considering the case study presented, advise Afro$$s Caf$$ planners regarding the factors they should consider

when establishing sales projections for their individual caf$$s$.$ Incorporate relevant examples from the context.

$(15)$

$1\mathrm{.}2$

Within the framework of Afros Caf$,$ critically discuss the importance of forecasting and propose the primary

forecasting methodologies that should be utilised. Support your discussion with pertinent examples. And also give examples of each. Make references