Forecasting Project

Introduction:

The GEA supported entertainment events trend in Jeddah is an almost new trend that was introduced around mid 2017 and took off at around December 2017. The trend is ruled by different factors. The most important factor is the time of year. The season of these type of entertainment events is estimated to be from November – June, which are the dates that the weather is bearable in Jeddah. The 2017/2018 season anticipated very high demand. The demand peeked around January – February.

Objective:

The 2018/2019 season of entertainment events is soon to start. The purpose of this project is to forecast demand of events this upcoming season. Multiple factors have changed by the previous year, Factors include:

1. Possibility of trend decline

2. Introduction of new trends

3. Cinema opening

4. Saudi innovation

5. Increase of supply and variety

Company selected:

The forecast will be done on levels company, which is a local entertainment events company in Jeddah. Event chosen is “Enchanted”, which will be the company’s 3rd event so far. Launching at the 14th of November, the event will be kicking off the 2018/2019 season by hosting the first large event.

Data:

The forecast will be using data from large successful events of the previous year. The data looked into will be most importantly the number of attendance, the number of events on the same day, the number of events of the week before and after, and also entertainment alternatives other than events, comparing them with this year.

Event	Attendance	Ticket Price	Other Events the same day	Events The previous week
Vintage	6800	150	0	0
Glow	4000	100	2	1
Rise Up	7500	100	1	0
Takya	6500	80	1	1

Forecast:

The forecast will using the above data as a reference including changing factors for this upcoming, which we seek to find:

1. Demand forecast for the upcoming event.

2. Demand forecast for the upcoming year.

Post event:

By the end of November 2018, data about event “enchanted” will be acquired, data collected from that event will be an accuracy reference to how well the forecast was made. If data collected can relate to the forecast, we can build a tangible hypothesis about the upcoming season and maybe about the trend and its direction.