1 00:00:00,570 --> 00:00:10,380 Now, the next question we have to address is this who does forecasting and how it is used by entities 2 00:00:10,380 --> 00:00:16,890 forecasting is performed in nearly every organization that works with quantifiable data. 3 00:00:18,180 --> 00:00:22,910 For example, retail stores forecast sales. 4 00:00:24,150 --> 00:00:30,810 They use data of consumers past purchases and try to predict these sales forecasts for coming days. 5 00:00:31,890 --> 00:00:37,750 This can help them in managing the inventory level of different products, update pricing, et cetera. 6 00:00:41,070 --> 00:00:47,220 Similarly, energy companies forecast reserves, production, demand and prices. 7 00:00:48,690 --> 00:00:56,640 Forecasts of reserves are used to determine long term investment plans, whereas demand forecasts are 8 00:00:56,640 --> 00:01:00,810 used for short term production planning and competitive pricing. 9 00:01:04,020 --> 00:01:09,180 Government forecasts, tax receipts and spending every year. 10 00:01:09,270 --> 00:01:15,690 Governments produce the budget based on estimated values of tax, which will be collected in the coming 11 00:01:15,690 --> 00:01:15,970 year. 12 00:01:16,440 --> 00:01:19,290 And the plans for the expenditure accordingly. 13 00:01:22,440 --> 00:01:29,100 Banks and lending institutions forecast new home purchases, and venture capital firms forecast market 14 00:01:29,100 --> 00:01:34,560 potential to evaluate business plans and not just domestic banks. 15 00:01:35,640 --> 00:01:42,660 International financial organizations such as World Bank and International Monetary Fund forecast inflation 16 00:01:42,750 --> 00:01:43,860 and economic activity. 17 00:01:47,100 --> 00:01:52,170 In agriculture, various government organizations are involved in predicting the weather. 18 00:01:52,530 --> 00:01:53,850 Demand for several crops. 19 00:01:53,970 --> 00:01:55,700 Production of several crops, etc.. 20 00:01:57,310 --> 00:02:05,220 Now take a moment and think how other industries such as education, travel, stock market traders, 21 00:02:05,380 --> 00:02:08,010 etc, are using time to these forecasting. 22 00:02:09,690 --> 00:02:17,190 I guess you can also imagine how nearly every industry is trying to forecast some variable in the future 23 00:02:17,520 --> 00:02:18,870 to be better prepared today. 24 00:02:20,910 --> 00:02:23,430 Now let's see the process in all in forecasting.