Please respond with your thoughts/opinions and use examples to support your answer on the two separate posts in at least 100 words.
The question the two posts are answering is: Discuss the business uses of time series and forecasting. Use examples to support your answer.
In my industry of real estate there are many time series indexes that are used by brokers and managers. New housing starts, Average sales price, and Average 30-year mortgage rate are probably the most prevalent. Time series forecasting entails using known data gathered over time to predict the how the data for the same subject will respond in the future. Trends and trending are words we hear often as one can sometimes assume, correctly or not, that is a statistic is trending up or down then it will continue, at least in the near future. This can sometimes be problematic if too much emphasis is placed on one statistic over others to match a desired result.
Unfortunately, this is becoming a more and more common occurrence in my industry and in the American media. The National Association of Realtors will trumpet whichever stat looks the best in its monthly forecast. This usually is not the same stat each month. For instance, the New Housing Starts statistic will be shown to be up over last month and last year, while the Mortgage Application being down from last month and last year will only be found by digging into the statistics sheet. Next month it could be reversed and no one will mention that New Housing Starts are down this month.
The same thing happens in the media. If they want to make put the economy in a good light they will talk about how the quarterly statistic for those applying for unemployment was down from last quarter and not mentioning overall unemployment rising for the same period. I think the lesson really is to not focus on any one time series statistic when trying to forecast.
A time series is a set of data collected or obtained over a period of time. It could be hourly, daily, weekly, and monthly or yearly based on the need. Data obtained can be used in time series models to identify time series patters such as trends, seasonality and cycles. Time series models can be used in formal analysis and forecasting. Some of the main uses of this is economic and sales forecasting, budgetary and stock market analysis, quality control etc...
The line of work I work in these time series data analysis can be used and utilized in many ways. I could be used monthly in determining the budget allocations for each months ordering of supplies to forecasting annual or quarterly sales. Within the recent month my company went through a series of structural changes, starting from new owner to a new management. When each office is set with a production or a sales goal it is not just done randomly, if you look at the figures carefully each month would have a different sales or a production goal. How do they determine to set these goals, they can't go in blindly and give a random number and say, this is your target for the month. As I brought up this question to my management team, their answer was this we just evaluated the last 5 years of all sales and production figures and came to this conclusion based on the sales patterns we noticed. It was all about identifying the trends and seasonality based on the data gathered. This not only allowed them to determine an annual sales forecast but based on each individual monthly figure gave them the opportunity of forecasting a monthly goal.