BUSN-278 Week 1 Discussion Question 2 – Forecasting Techniques

Week 1 DQ 2, Forecasting Techniques Discuss the difference between quantitative & qualitative forecasting. Does one provide a more accurate forecast than the other? The differences between qualitative & quantitative forecasting is that: with Qualitative forecasting, (1) educated guess or experts opinions are made. (2) It can be useful in formulating short-term forecast & can also supplement projection based on the use of any of its four models namely executive opinions, Delphi, Sales - force polling, & Consumer Surveys models. (3) Its forecast are quick & easy without statistical elaboration. Whereas with Quantitative forecasting: Forecast is based on historical (time series) data where: (1) naïve methods, moving average, exponential smoothing, trending analysis, & classical decomposition models are used. (2) Quantitative forecasting also use Associative (causal) forecast where simple regression, multiple regression, & econometric modeling are being used. According to our textbook, the quantitative forecasting is a technique that can be applied when information about the past is available, if that information can be quantified & if the pattern included in past information can be assumed to continue into the future. While forecasting techniques include qualitative methods such as seeking expert advice, the techniques suitable for market analysis require quantitative methods that deliver numerical forecasts suitable for an analytic approach. Effective mathematical forecasting looks at existing data & applies corrections or smoothing to predict future trends. The key inputs required for forecasting are the present situation, past data to determine past trends, selection of the sampling period for historical data & selection of the forecasting period. Week 1: Budgeting Process & Types of Budgets - Discussion Forecasting Techniques (graded) Discuss the difference between quantitative & qualitative forecasting. Does one provide a more accurate forecast than the other? First Question Professor Foor 8/22/2012 2:41:39 PM Class, describe the qualitative approach. What does it mean? RE: First Question Ddungu Wasswa 9/8/2012 12:44:25 AM The basic definition of the qualitative approach in forecasting is an estimating method which mainly relies on the expert human judgment in association with the rating scales irrespective of the presence of any kind of hard data. This technique comes into play when the suitable quantitative data is unavailable. This is simply based on judgment & institution. It involves following methods to qualitatively find he forecasting solutions. The first in list is the jury & executive opinion, the opinion from the expert are taken & ten combined & averaged. The opinion may be taken in individual or even may be a brain storming group decision. The next method is to have an opinion for the sales, being in close contact with the consumers the sales person has the liberty of freedom of estimating the market needs more accurately. The other method is the consumers’ expectations which are simply dependent on the market survey of analyzing the consumer targeted reach. Finally the Delphi method which is a method where the expert is provided a situation is asked to give his reviews & opinion on it, the expert writes the answers & they are brought to the panel for consideration. RE: First Question Marina Benz 9/7/2012 3:24:34 PM The qualitative approach, or also called judgmental approach is very useful in formulating short-term forecasts. It can also enhance projections based on the use of any of the quantitative methods. Qualitative forecasting is based on judgments about future revenue collection through observation of existing. There is a very small dependence on numbers & this technique does not provide harsh specification of underlying assumptions. The positive side is that they can identify systematic change more quickly. Also, it can better interpret a change’s effect on the future. The following is an example of judgmental forecasting: An individual or small group of people make assessments of likely future conditions. While sounding unplanned, the technique can produce very good estimates, especially when experienced persons are involved. Judgmental approaches tend to work best when background conditions are changing rapidly. The best known qualitative forecasting methods are executive opinions, the Delphi method, sales-force polling, & consumer surveys. (Shim 228) Shim, Jae K.. Budgeting Basics & Beyond, 3rd Edition. John Wiley & Sons (P&T). <vbk:6754#outline(14.2)>. Qualitative approach are forecasts based on judgment & opinion, according to our textbook. It is also referred to as the judgemental approach also. Qualitative approach is good when making short-term decisions. RE: First Question Jessica Samhan 9/4/2012 1:03:21 PM According to our lecture, qualitative approach is based off expert human judgement including four different methods to make a decision: • Executive opinions average the views of experts from various departments to generate a forecast of future sales. This forecasting method can be performed easily & quickly, without the use of elaborate statistics. However, this method is conducted in a group, which increases the risk of group pressure & stifles critical thinking. • The Delphi Method questions a panel of experts individually. An outside party summarizes the information obtained & returns it to the experts with further questions. The process continues until a consensus is reached. While the experts are not influenced by others participating in the forecasting, this method is often criticized for its low reliability & lack of consensus. • Sales force polling questions those salespeople closest to the customer. The information gathered in the poll is averaged to create a future forecast. This method is simple to use & understand, drawing on the knowledge of those closest to the customer. However, it may include overly optimistic or pessimistic predictions. • Consumer surveys regarding specific purchases may be conducted by a company. These surveys use personal interviews or questionnaires to collect data, which are compiled & analyzed to form assumptions regarding consumer behavior. Quantity are for fast easy budgets that need to made. Quality is for the long term. We can tell what companies are doing by measuring these quantity & quality metrics. The qualitative approach is a type of forecasting where judgement & opinion are used. In my opinion it is like an estimate of what to expect instead of an exact. The qualitative approach uses information provided by "executive opinions, consumer surveys, sales force polling & delphi technique". It is based on human judgement & opinion instead of facts. This may be a better approach depending on the type of business. RE: First Question Kayla Riley 9/5/2012 11:00:31 PM The Delphi Method kind of reminds me of a game show. There is a panel of experts who go through rounds of answering the same set of structured questions. Once an agreement has been made amongst the responses of the experts, the data is used as a forecasting tool. I think its pretty cool. An approach of quantitative forecasting is the time series method. The time series method bases its forecasting off of past data in order to predict future values. Examples of the times series method include the Dow Jones Industrial Average, gross domestic product, unemployment rate, & airline passenger loads. Reference: The qualitative approach is based on judgement & intuition. In my opinion it seems like preparing for the worst while hoping for the best when managing a budget. The qualitative approach is a forecasting method that is an approach to forecasting based on judgement & opinions. The qualitative approach means using someones judgement to prepare a forecast,such as conducting surveys or using the delphi method.The delphi method is used to ask experts individually what they believe about future events. Qualitative forecasting typically involves the use of experts who are capable of generating forecasts for a business. An advantage qualitative forecasting is that it can be used in situations where historical data is not available like when I brand new business is just beginning. Sometimes when historical data is attainable, changes in environmental conditions may make the historical data irrelevant & questionable when it comes to forecasting. Let's say that historical data on the sales of a restaurant are available for current use. If the government changes the taxes associated with the sales of liquor, changing how much money can be made off of every drink sold, this change would pose a question involving the accuracy of the restaurant sales forecast that was based on the past data that had been collected. Qualitative forecasting methods help create a way to project these forecasts in scenarios like this. The Delphi technique, scenario writing, & the subject approach are all types of methods that can be used generate qualitative forecasts for a business. For more information on this topic please visit: Forecasting Qualitative forecasting is an estimating method the relies on expert judgement as opposed to quantitive which uses cold hard facts & data to make a decision. I agree with you Cynthia. Qualitative uses judgment & quantitative uses data. I think I found a mistake in our study mate in the lecture, though. I think the second definition for "qualitative forecasting" (the one that comes after the definition for Delphi method) should read "quantitative forecasting" for being based on time series data. Time series is connected to the quantitative branches in Exhibit 14.2 in our book. Modified:9/9/2012 9:16 PM Qualitative approach focus on forecasts based from human judgment & opinion of qualitative methods such as Executive opinions, Delphi technique, Sales force polling, & Consumer surveys. This judgement method can be used when creating forecast for short term projects, & also can supply projections from any of the quantitative methods. Having a better advantage, this approach is a quick & easy way of forecasting. Shim, J. & Siegel, J. Budgeting Basics & Beyond. Retrieved from RE: First Question Angel Ketchum 9/3/2012 10:03:14 PM I found this on a web site & thought it explained it where I could understand it. I also wanted to find something that hadn't already been posted. Qualitative methods of sales forecasting rely less on data, & much more on the opinions & experiences of the people involved in the forecasting process. If qualitative forecasting is about obtaining opinions about the future, what are the main methods of getting those opinions? There are three common approaches: Delphi method Perhaps the best-known method for generating a forecast using “experts”. Rather than getting experts to meet face-to-face, the chosen experts are sent a survey or questionnaire (by post or email). Each expert completes the survey without reference to any other contributor. The replies to the survey are analysed, summarised & then returned back to the experts so that they can reconsider their responses & views after learning about the views of the other experts. This survey process may be repeated several times until a consensus is reached (or perhaps a narrower range of sales forecasts is arrived at). The obvious disadvantages of this approach are: - The time-consuming nature of the survey process (potentially costly as well) - The way in which the “experts” are chosen (who choses & why?) - Whether some experts are more expert than others! I.e. whose opinions should be given most weight (if anyone) Panel method This method of sales forecasting is a specialised form of focus group (remember that from consumer market research?) The panel’s members meet face-to-face & discuss openly their views on the forecasts required, with the aim of reaching a consensus. The disadvantages? - Some experts will shout louder than others, or be more forceful in expressing their opinions - The panel approach ncourages a quick resolution, rather than a more reflective approach (which might lead to a better quality sales forcast) Scenario planningThis method is popular where the sales forecast is subject to a lot of uncertainty. This is often true when a sales foecast is intended to cover a long time period (e.g 3+ years) or where there are inherent risks in the demand for the poduct or market being forecasted. Scenarios are not intnded to produce a consensus. Rather, it is about identifying the likely or possible scenarios for different sales outcomes, & then coming up with a plan for how the business would respond for the least desirable scenarios. Scenario planning is linked, therefore, to contingncy planning. Riley, J. (2009, May 31). Business Studies. Retrieved September 3, 2012, from Tutor2u: RE: First Question Diundra Satterfield 9/3/2012 5:08:11 PM The lecture states that the Qualitative approach is a method used for judgmental forecasting models. All of the qualitative models require an expert to provide information that we will actually use in our forecast. Quantitative method is primarily used for time series forecasting models. The best forecasting model will be one that has a strong correlation between the model & the actual performance of your company. The primary models are; Moving average, weighted moving average, & exponential smoothing. RE: First Question Kimberly Stevens 9/3/2012 1:38:37 AM ualitative Approach The qualitative (or judgmental) approach can be useful in formulating short-term forecasts & can also supplement the projections based on the use of any of the quantitative methods. our of the better-known qualitative forecasting methods are executive opinions, the Delphi method, sales-force polling, & consumer surveys. Shim, Jae K. (2012). Budgeting Basics & Beyond. VitalSource Bookshelf, p.231. Retrieved from ttp:// RE: First Question Professor Foor 9/4/2012 12:03:31 AM Great start class! Describe the quantitative approach. Can you provide an example? RE: First Question Kimberly Stevens 9/4/2012 12:41:12 AM Quantitative approach • a.Forecasts based on historical data o ▪Naive methods o ▪Moving average o ▪Exponential smoothing o ▪Trend analysis o ▪Decomposition of time series • b.Associative (causal) forecasts o ▪Simple regression o ▪Multiple regression o ▪Econometric modeling Quantitative models work superbly as long as little or no systematic change in the environment takes place. Shim, Jae K. (2012). Budgeting Basics & Beyond. VitalSource Bookshelf, pp.228-229. Retrieved from RE: First Question Charles Agnor 9/5/2012 6:26:53 PM The moving average method is a smoothing technique that is more sophisticated than naive methods. The naive method does not consider why the trends are occurring but it can consider trends. The formula to do this would be future data value = previous data value + (difference between previous data value & the data value previous to the previous). This is on page 234 in chapter 15. The moving average method updates averages daily as new information is received. All data is given equal weight (add values & divide by number of values added), so the manager can give greater weight to newer data by using less data values. This is on page 237 of Chapter 15. Exponential smoothing gives more weight to more recent data, but is more complex. RE: First Question Charles Agnor 9/6/2012 3:57:49 PM p.s. the quantitative models forecasting spreadsheet from the link in our lecture was very helpful in understanding how to do the problems in the homework. Without it I would have been lost. The MAD confused me. I now know that it is the mean absolute deviation & to compute it you sum up all of the absolute values of differences between actual versus forecast data & put that sum in the numerator. In the denominator you have the number of occurrences that you had taken the sum for. The formula for exponential smoothing also made more sense to me to see it in excel than in the book. RE: First Question Brandon Rader 9/4/2012 7:49:02 AM The quantitative approach involves using statistics & measurable historical data to estimate future performance. This approach is how baseball uses sabermetrics to estimate future player performance. RE: First Question Cynthia Sprinkle 9/5/2012 5:05:44 PM The quantitative approach helps narrow a large number of possibilities & help predict which ones will be the most successfully. This approach can used in any business setting to help increase profits, you just have to take the time & have the knowledge to analyze the data properly. In my industry, HVAC, we can use this to determine which brand and/or model is our most popular & what price we should be offering this product at. This can also be used to analyze our cliental base as far as most profitable areas. There are many ways to analyze data & utilize your research to make more money. RE: First Question Professor Foor 9/6/2012 12:08:14 AM Of the three quantitative forecasting techniques (moving average, weighted moving average, & exponential smoothing), which do you think provides the most accurate forecast & why? The forecasting method that is chosen depends heavily on the type of situation it is being used to forecast. A simple moving average simply collects an average of specified number of periods for a business. This is relatively simple to do, & can yield a decent forecast that is somewhat primitive. For example, et's say your business did $1,000 in sales for period 1, $2,000 for eriod 2, & $2,500 in sales for period 3, all you would do to find he sales forecast for period 4 is add these numbers together & ivide by 3. This will give you a sales forecast of $1833.33. Will his be very accurate? Probably not. A weighted moving average is similar to the simple moving average, but each period of historical data is weighted differently & can forecast for longer projections. Exponential smoothing can be best utilized when a orecasting situation arises where there is not any trends in the previously collected data. Periods that have occurred more ecently receive greater weight in demand than periods that have ot occurred as recently in retrospect. For this reason exponential moothing can account for the most variations in demand & can reate the most accurate forecasts for the future depending on how the business may be growing accordingly. For more information on this topic please visit: Professor, This seems to be a trick question but if I had to choose the most accurate forecast I would choose moving average. Its simple & easy to understand. Moving averages are averages that are updated as new information is received. With the moving average, a manager simply employs the most recent observations to calculate an average, which is used as the forecast for the next period. Shim, Jae K.. Budgeting Basics & Beyond, 3rd Edition. John Wiley & Sons (P&T). <vbk:6754#outline(15.2.1)>. Based on what our textbook says, exponential smoothing provides the most accuracy. It gives more weight to the most recent information. The moving average & weighted moving average techniques apparently have disadvantages because all the data is weighted equally & it requires a large amount of data to be kept. In my opinion I would say that the moving averages would be more accurate just for the fact that you do keep a large amount of data. You may be in an industry that has seasonal fluctuations & you would need to be able to look at the last peak season to make an accurate forecast. For example, I work for an HVAC company, our busiest season is of course the hotter months. If it were February I could not look back at the last six months & get a good idea of what the future held because that time period would be considered off season. So even though using the moving averages techniques would require more work & more space for data it would be the only accurate way for my company to get an accurate forecast of the future. It seems the moving average would be best. Even thought it takes a lot of data it is updated as new information comes in & it is the easiest to understand. Moving Averages Moving averages are averages that are updated as new information is received. With the moving average, a manager simply employs the most recent observations to calculate an average, which is used as the forecast for the next period. (Shim 235) Exponential Smoothing Exponential smoothing is a popular technique for short-run forecasting by managers. It uses a weighted average of past data as the basis for a forecast. The procedure gives heaviest weight to more recent information & smaller weight to observations in the more distant past. The reason is that the future is more dependent on the recent past than on the distant past. (Shim 236) Shim, Jae K.(2012). Budgeting Basics & Beyond, 3rd Edition, pp.235-236. John Wiley & Sons (P&T). <vbk:6754#outline(15.2.1)>. I'm not sure I can answer your question, Professor. First off, I'm not sure if I found 'weighted average' in the book. All I could find is that exponential smoothing & weighted average work together. Second, are you asking about their formula calculations? I know on page 235 moving averages is stated to be the simplest equation form. I don't understand exponential smoothing's formula, or how to plug things into it. But I will take a guess that it gives the more accurate calculation because it's so detailed & complex. If only one could be chosen, I would say the exponential smoothing would be the most accurate. However, it seems that all forecasting methods have some measure of success or they would have been thrown away a long time ago. Likewise, I would think there isn't one method that works the best all the time, or the other ones would be tossed away in preference of the one that works the best. So to be perfectly accurate, I would say that each of them works depending on the amount of data available, the accuracy of that data, & a few other factors such as anything that would boost or shrink the economy that was currently going on. I would think the changing of the economic conditions in the society would affect the forecast accuracy negatively, especially if the conditions from the past are held to be as equally important as any current data. For example, if a depression or recession were going on, & very little current data was involved, then the predictions could be way off the mark because of a greater amount of past data influencing the forecast for a more positive result. RE: First Question Ronald Moore 9/9/2012 9:46:02 PM I would think that the weighted moving average would be the best because financial costs usually have trends. By using the weighted moving average you can adjust somewhat to a recent trend. If you used exponential smoothing, then you would take into account all prior data & those numbers are like to be different. In my opinion I believe the weighted moving average provides the most accurate forecast. I think it is easier to understand & can be updated easier. The manager can choose what periods to use & how to weight it depending on the information used & needed. The one disadvantage is the need to retain more data however, I like to have more details that not enough to do my job. In most cases you will need to have some type of paper and/or electronic trail to complete most tasks. I would say that exponential smoothing would provide a more accurate forecast because it uses most recent data. The data throughout different periods isn't equal. The old data has less value to forecasting & most recent data is looked at more. I think this helps because most forecasting & budgeting is based on most recent data. The old data is still taken into consideration but the new data will hold more value to not just inside managers but for outsiders as well. Quantitative forecasting is a technique that can be applied when information about the past is available, if that information can be quantified & if the pattern included in past information can be assumed to continue into the future. I think quantitative forecasting can be applied to our economy & its future. When using the quantitative approach, existing trends will be heavily relied upon so you have to expect some shortcomings every once in a while. You also hope that no unexpected systematic changes occur because your projects will be worth a lot less than what you originally expected. At my Credit Union, our loan goals are based upon our historical trends over time as well as other market concerns such as the economy, consumer confidence etc. Every once in a while we fall way short of our loan goal & therefore are forced to work even harder so that we don't end the year in such a bad position goal-wise. As we all know sometimes qualitative methods tend to get mixed in as well, like executive opinions that can end up setting the bar very high performance-wise . The quantitative approach is a forecasting method based on historical data. Quantitative data is usually numerical to obtain statistics. With the quantitative approach, a person is able to collect data & make a forecast based on that data. For example, a researcher could speak with 200 people in an emergency room waiting area & ask how long of a wait time they each had throughout a period. based on those answers, the researcher may be able to establish what the average waiting time is for that hospitals' waiting room. RE: First Question Ddungu Wasswa 9/8/2012 9:23:53 PM The quantitative forecasting method is simply the one that is based on the numerical representation. The numerical data is very useful in analyzing this kind of forecasting. Except this the quantitative forecasting method is required to estimate the future demands to be used as a function for the analysis of the past data. It is only appropriate when the past data is available. This method of quantitative forecasting is used only in short intermediate range decisions. The simple examples of the quantitative forecasting are the last period demands, simple & eighted moving averages, multiplicative seasonal expenses & exponential smoothing. The quantitative forecastng method also involves two main methods namely the ime series method which is concerned with the past events often industry & analyzing the future demands of the markt. The smoothing processes are used when the time series ethod fails to fulfill the forecasting needs. The other metho is trend projection method & uses the long term trend of the time series data for future values. The other methods in th list are seasonal method, & casual methods. RE: Forecasting Techniques Chanel Thorpe 9/2/2012 11:56:24 PM Modified:9/3/2012 12:14 AM According to the class ook, differences between quantitative & qualitative forecasting is that quantitative approach focus on forecasts based on historical data such as aive methods, Moving average, Exponential smoothing, Trend analysis, & Decomposition of time series. While qualitative focus on foecasts based on judgment & opinion of Executive opinions, Delphi technque, Sales force polling, & Consumer surveys. Shim, J. & Siegel, J. Budgeting Basics & Beyond. 3rd Edition. Retrieved from Quantitative & Qualitative Angela Warner 9/3/2012 4:08:45 PM Qualitative & Quantitative are both forecasting techniques. According to the text book, qualitive forecasts provides a more accurate forecast because it can identify systematic change more quickly & interpret better the effect of such change on the future. The qualitative approach forecasts based on judgement & opinion, such as, executive opinions, delphi technique, sales force polling, & consumer surveys. The quantitative approach forecasts based on historical data, such as, naive methods, moving average, exponential smoothing, trend analysis, & decomposition of time series. In addition to that quantitative approach forecasts based on associative (casual) forecasts, such as, simple regression, multiple regression, & economic modeling. Quantitative models work superbly as long as little or no systematic change in the environment takes place. The advantage, however, is that they can identify systematic change more quickly & interpret better the effect of such change on the future. Qualitative approach can be useful in formulating short-term forecasts & can also supplement the projections based on the use of any of the quantitative methods. Diundra I agree with you. The quantitative models is objectives that need to be supported with laws & measures the assumption of forecast. Qualitative is subjective & used to conduct social paradigms as well as calculates the accuracy in forecast. Quantitative & qualitative models can both be used in the medical field, social life, & in science to measure forecast or to conduct surveys. Forecasting Techniques Dianna Gilmore 9/3/2012 10:57:40 PM Qualitative forecasting is based on human judgement & opinion. Human judgement is important & can recognize change faster but so because qualitative is based on human judgement there are some flaws. Whereas Quantitative is based on historical data & Associative forecasts. The quantitative model works as long as there is no change in the environment then it becomes less useful. Class, select a current (not older than one month) event article from a newspaper, periodical or internet site. Make sure that you have summarized the article & NOT copied. State the name of the periodical, date, author, link, & title. Discuss its relevance for this week’s material. Why did you choose your article? By Marisela Burgos 7:13 p.m. EDT, August 11, 2011 There is expected to be about a $40 million budget shortball for 2012. According to Mayor Ballard, in order to balance the budget, he is looking at $20 million cuts in non-public safety, including 'reducing' 200 jobs through attrition. He said Public Safety & Criminal Justice Agencies will be spared of budget cuts. I found this to be a very interesting article because of the economy we're in. Many people in this city jobs are going to be effected & that's an issue for all of us that live here. I have a problem with how the Mayor is spending the money for this city because people are in need of jobs, homes, & so forth & he's taking the money & using it for the improvement for Downtown especially since the Super Bowl was held here this year. The Mayor says in 2014 there's going to be an increase in property taxes. As a homeowner that definitely doesn't sit well with me. While this article is from last year its still an issue that needs to be looked at . RE: Current Event Diundra Satterfield 9/7/2012 8:18:22 PM I found a more recent article for this year & it talks about how the state government is sitting on cash reserves of $2.15 billion following a year of continued budget cuts & improved tax collections. Unlike my previous articles there are some good things that have come out of this budget situation. There were some mistakes that were uncovered in the Governor's administration. Because of these mistakes being uncovered there's money that was able to be sent to the state teacher's pension fund. Author: Associated Press July 12, 2012 Title: Indiana closes year with $2.1B in cash reserves RE: Current Event Ricky Ontiberos 9/7/2012 11:13:24 PM (9/7/2012) Noel Randewich & Nicola Leske: This articles explains why Intel cut its revenue estimate for the third quarter down to $13.2 billion from previous forecast of about $13.8 - $14.8 billion. Not only are consumers demanding less PCs but weak enterprise sales to businesses & governments are also expected which will slow the demand for their products which ultimately forced them to lower the expectations for analysts & investors when they report the earnings in October. Their revenue outlook is looking so bad that they had to even withdraw their full-year forecast. This shows how important it is for companies to accurately forecast their sales & financial performance by making accurate predictions based on the current market environment & trends. If they were to stay with their initial forecast & their revenue estimates would have been way off, it might have rattled investors a whole lot more in October when the earnings are officially released. I chose this article because I really enjoy reading finance headlines regarding company earnings & values. It is so interesting to see how critical analysts & investors can be when forecasts & estimates are a little off. Name/Author: Congressional Budget Office Date: August 22, 2012 Link: Title: An Update to the Budget & Economic Outlook: Fiscal Years 2012 to 2022 Discuss its relevance for this week’s material & why you choose your article? The Congressional Budget Office has been around since 1974 & has provided articles stating information about the deficit, unemployment, & several other key issues of government officials. The particular article I chose gives relevant past & current, & future “budgeting & forecasting information. The government needs to budget & forecast as well to determine where the country stands financially, how money will be spent, & where money is actually going. This particular article gives forecasts for the years 2012 – 2022, as well as previous year information. In Colonie, New York there is a dispute over the town's budget & a deficit in its highway fund that was discovered by the comptroller's office. The 2012 budget for Colonie did not contain actual revenues & expenses, & this has raised eyebrows about a lack of transparency from the town's hierarchy. Colonie has had financial trouble in the recent past & the comptroller's report warns of the dangers involved with maintaining their budgeting practices. I chose this article because it was a recent news story about budgeting & it is relevant because cities across America are in poor financial condition due to similar budgeting practices. O'Brian, T. (2012, September 4). One gap filled, one still yawns. Times Union. Retrieved from RE: Current Event Daniel Smith 9/5/2012 2:53:02 PM As most people these days know, our federal government is in debt. This debt is so huge that most people can barely fathom it. The article that I came across talks about the the federal debt being at 16.2 trillion dollars by the end of the current fiscal year, & goes on to say that the debt could not only continue to grow, but could surge to over 25 trillion dollars if the current proposed budget by the president goes forward. This analysis by the opposing party may very well be wrong, but it could also be right. The article goes on to say that of every dollar spent, forty cents is borrowed. Needless to say, the simple fact is that the financial debt & lack of successful planning or budgeting in the federal government has amounted to a huge problem & the article states that the president's failure to outline a "serious plan" regarding this country's financial future will wreck us all. It goes on to say that certain things are needed in the government such as a restoration of discipline to the government, & an economic renewal. I'd like to stay away from the politics of the article, but it definitely applies to this weeks material as there has been much planning, but little true successful budgeting or following a budget, for the debt to be reduced & eventually removed. Halper, D. (2012, Septermber 4). $16,015,769,788,215.80, $5.4 trillion added under Obama. The Weekly Standard. Retrieved from RE: Current Event Sarah Preble 9/8/2012 9:46:56 PM It is sad & it is also depressing & because of the the race for presidency & the campaigns have become just rotten & dirty. I will keep my political opinions out of this discussion, but we all need someone to blame, right? Anyway, I live in California & the economy here, just like everywhere else is horrible. So many cities around me are filing bankruptcy. City workers continue to be laid off because the city cannot pay them. There is no money anywhere & now taxes are increasing on many businesses that weren't charging tax before. Quantitative & Qualiative Forecasting Jessica Dais 9/4/2012 8:54:03 PM Quantitative forecasting mostly pertains to numbers or figures, such as sales forecasts, budget forecasts, figure projections or econometrics. It is usually based on the history of a company’s figures & takes into account the industry’s history as well. In quantitative forecasting, the two most basic techniques are the time series technique wherein one looks into the future based on what happened in the past & the relational technique which operates on the idea that the future depends on a number of different factors which may affect it presently. Based more on expert opinion & judgment, qualitative forecasting usually doesn’t rely on history. It can be used to determine a company’s strengths, weaknesses, opportunities & threats, as well as to predict performance. One common qualitative technique is the Delphi technique, wherein trends & effects of decisions are predicted. This particular technique does not necessarily require very high expertise. In the Delphi technique, results are mostly obtained through mailed surveys where participants are paid for their participation. These results are then analyzed based on the average of the group’s opinion. Whereas quantitative forecasting looks more into statistics & past trends to make predictions, qualitative analysis relies more on managerial or judgmental opinion. Qualitative analysis is also often used when quantitative data is absent. forecasting Wilma Balmonte 9/4/2012 8:59:50 PM Qualitive forecasting is a prediction that is made based on someone's judgement or thoughts of what will come about of a situation. An example of gathering useful data would be to conduct a survey or poll with people. A quantitive forecasting is a prediction derived from physical data & figures from a previous year or multiple years. It can be done through data analysis or averaging numbers to come up with. Data for quantitive forecasting can also come from similar situations, companies, & what have you. Quantitive data would provide a more accurate forecast because it is made from actual data provided. There is more back up to the forecast instead of just being an opinion of a person or a group of people. Forecasting Michelle Jones 9/5/2012 11:29:03 AM Quantitative forecasting mostly pertains to numbers or figures, such as sales forecasts, budget forecasts, figure projections or econometrics. It is usually based on the history of a company’s figures & takes into account the industry’s history as well. In quantitative forecasting, the two most basic techniques are the time series technique wherein one looks into the future based on what happened in the past & the relational technique which operates on the idea that the future depends on a number of different factors which may affect it presently Based more on expert opinion & judgment, qualitative forecasting usually doesn’t rely on history. It can be used to determine a company’s strengths, weaknesses, opportunities & threats, as well as to predict performance. One common qualitative technique is the Delphi technique, wherein trends & effects of decisions are predicted. This particular technique does not necessarily require very high expertise. In the Delphi technique, results are mostly obtained through mailed surveys where participants are paid for their participation. These results are then analyzed based on the average of the group’s opinion. • Whereas quantitative forecasting looks more into statistics & past trends to make predictions, qualitative analysis relies more on managerial or judgmental opinion. Qualitative analysis is also often used when quantitative data is absent. Forecasting Professor Foor 9/5/2012 11:54:37 AM Discuss the mean absolute deviation (MAD) & the mean square error (MSE). Which do you think is a better indicator of the accuracy of a forecasting method & why? RE: Forecasting Latoya Shands 9/5/2012 2:22:37 PM The mean absolute deviation is a measurement of an amount that is widely spread in data sets. The mean square error is a quantity used to measure all the possible outcomes of the forecast error. I think the mean square error is a better indicator because the mean square error gives a more accurate estimation on the forecasts observations & does not depend solely on quantities. The mean square error provides accurate values to all the possibilities of close forecasts. This website provides examples of the mean square error & mean absolute deviation: Mean absolute deviation is average of absolute differences (differences expressed without plus or minus sign) between each value in a set of values, & the average of all values of that set. Mean square error is a risk function, corresponding to the expected value of the squared error loss or quadratic loss. I think the better indicator of a forecasting method would be MAD because it does not penalize large errors as much as MSE does. Good work Jessica & Latoya. Class, please discuss the mean absolute deviation (MAD). How is it calculated? Do you have an example? RE: Forecasting Sarah Preble 9/9/2012 9:37:33 PM Mean absolute deviation is based on the median, which can provide a measure of the core data without being affected by a few extreme data points. I was a little confused by our book so I found this link that broke it down in lamest terms. Read more: How to calculate median absolute deviation | eH RE: Forecasting Dianna Gilmore 9/6/2012 11:40:31 PM MAD 99+55+88/3=80.7 99-80.7= 18.3 55-80.7= -25.7 88-80.7= 7.3 18.3+25.7+7.3/3= 17.1 MAD RE: Forecasting Professor Foor 9/7/2012 1:06:05 AM Excellent work. Here's another example to help you out. I'm aware the text does not have the proper information. This should help in completing the ES assignment. Mean Absolute Deviation Mean absolute deviation (MAD) is used to improve upon the range as a dispersion indicator, or how variant the set is. The formula to calculate MAD is as follows: MAD = ((x1 - m) + (x2 - m) ..... (x10 - m)) / n x1, x2 ... x10 = set m = mean n = number of observations An example of how to calculate MAD is as follows: Number set (4,12,5,8,13,7,9,10,9,8) First you have to find the mean of the number set: (4+12+5+8+13+7+9+10+9+8)/10 = mean 85/10 = mean 8.5 = mean Now you can calculate the MAD: 4-8.5= -4.5 12-8.5= 3.5 5-8.5= -3.5 8-8.5= -.5 13-8.5= 4.5 7-8.5= -1.5 9-8.5= .5 10-8.5= 1.5 9-8.5= .5 8-8.5= -.5 (4.5+3.5+3.5+.5+4.5+1.5+.5+1.5+.5+.5)/10 = MAD 21/10 = MAD MAD = 2.1 This is a lot easier than what I was doing to get the answers. I was making it a lot more complicated than it needed to be. Thank you! RE: Forecasting Denise Mate 9/8/2012 8:47:08 PM Thank you so much for posting this Professor. I was really lost when trying to complete the homework. Now I have what was missing to figure it out. Thanks again this makes sense now. RE: Forecasting Ronald Moore 9/8/2012 11:49:59 PM Thank you for the post. This really helped me to grasp the MAD forcasting technique. This technique seems like it would be more useful with the more data you have. For a situation where less data is availabe it would be nearly useless. RE: Forecasting Jessica Dais 9/6/2012 6:12:07 PM Consider the data (1, 1, 2, 2, 4, 6, 9). It has a median value of 2. The absolute deviations about 2 are (1, 1, 0, 0, 2, 4, 7) which in turn have a median value of 1 (because the sorted absolute deviations are (0, 0, 1, 1, 2, 4, 7)). So the median absolute deviation for this data is 1. RE: Forecasting Angel Ketchum 9/6/2012 7:06:37 PM The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The Mean Absolute Deviation is calculated in three simple steps. 1) Determine the Mean: Add all numbers & divide by the count example: the weights of the following three people, denoted by letters are A - 56 Kgs B - 78 Kgs C - 90 Kgs Mean = (56+78+90)/3 = 74.6 2) Determine deviation of each variable from the Mean i.e 56-74.6 = -18.67 78-74.6= 3.33 90-74.6 =15.33 3) Make the deviation 'absolute' by squaring & determining the roots i.e eliminate the negative aspect Thus the Mean Absolute Deviation is (18.67 +3.33+15.33)/3 =12.44 Alternatively , you can use the excel formula =AVEDEV(56,78,90) to obtain the result. Read more: RE: Forecasting Jessica Samhan 9/6/2012 11:27:10 AM It is the standard deviation without squaring it. Basically it tells you how spread out from the mean your group of numbers is. Here's how to do it: Step 1: find the mean (add all numbers together, divide by how many numbers there are) Step 2: subtract each number in the list from this mean Step 3: take the absolute value of each number (so they are all positive numbers) Step 4: find the mean of these new numbers That's the Mean Absolute Deviation! RE: Forecasting Michelle Jones 9/7/2012 8:01:34 AM Mean absolute deviation is based on the median, which can provide a measure of the core data without being affected by a few extreme data points. According to "Business Statistics" by Naval Bajpai, the median absolute deviation (MAD) provides an absolute measure of dispersion not affected by extreme outliers that can throw off statistical analysis based on means & standard deviations. The mean square error (MSE) is the average of the squared errors between actual & estimated readings in a data sample. Squaring the difference removes the possibility of dealing with negative numbers. It also gives bigger differences more weight than smaller differences in the result. Mean square error is widely used in signal processing applications, such as assessing signal quality, comparing competing signal processing methods & optimizing signal processing algorithms. RE: Forecasting Michelle Jones 9/6/2012 2:30:54 PM MAD is & average of the difference between the forecast & the actual demand · MSE is the average of the squared forecast errors & is sometimes used as a measure of forecast error. Forecast errors are typically normally distributed which results in the following relationship between MAD & the standard deviation of the distribution of error: 1MAD is about 0.8 stadard deviations. This enables us to establish statistical control limits for the tracking signal that corresponds to the more familiar normal distribution. · Statistical control charts are another method for monitoring forecast error. · For example, ±3 stadard deviation, control limits would reflect 99.7 percent of the forecast errors (assuming they are normally distributed). · Formula: Divide the Sum (Dt - Ft)^2 n-1 · This formula without the square root is the mean squared error (MSE). RE: Forecasting Angela Warner 9/8/2012 1:04:56 PM The mean absolute deviation (MAD) is the mean of the absolute deviations of a set of data about the data’s mean. The mean square error is the average squared error of the forecasts. An example of the mean absolute deviation is: Money taken in from donations were: $85, $100, $250, $250, $60, & $35 85+100+250+250+60+35 / 6 = 780 / 6 = 130 85 - 130= -45 100 - 130 = -30 250 - 130 = 120 250- 130 = 120 60-130 = -70 35- 130 = -95 45+30+120+120+70+95 = 480 480/6 = 80 (The mean absolute deviation) RE: Forecasting Marina Benz 9/9/2012 11:16:55 AM The accuracy of a forecast is very important when you have to decide between the different forecasting methods. The basis for accuracy lies in the historical error performance of a forecast. The difference between MAD & MSE is that MAD is the average absolute error & MSE is the average of squared errors. If you compare from a computational standpoint, the difference is that MAD weighs all errors evenly, & MSE weighs errors according to their squared values. If you are looking for an easy method, MAD is right for you. The downside is that it weighs errors linearly. MSE gives more weight to larger errors since it squares them. The downside is that it usually causes more problems. RE: Forecasting Brittany Whalen 9/9/2012 9:27:24 PM Modified:9/9/2012 9:27 PM Mean absolute deviation (MAD) is one of the simplest & most popular ways to conduct a forecast for a business. MAD is an average of the difference between the forecast & the actual demand of the business utilizing this method of forecasting. When it comes to MAD the smaller or lower value of MAD will yield the most accurate forecast result. One major benefit of MAD is the forecast's ability to compare the accuracy of several different forecasting techniques to each other to determine which forecast should be utilized. Mean square error (MSE) is the collective average of the squared forecast errors & is sometimes used as a way to measure forecast errors that may occur. An easy way to explain this concept is to use basic math. For example, 6 & 3 are only 3 numbers apart from one another. But if we square each number 6 becomes 36 & 3 becomes 9, making them 18 numbers apart from one another. This example shows how powerful the concept of squaring number can be. If you had a set of numbers you would do what I did above & add all the squared errors together & divide by the number of squared errors to obtain the average. MSE would yield a more accurate forecast than simply using MAD to generate a forecast based on the information I have uncovered. Quantitative & qualitative forecasting Marina Benz 9/5/2012 1:12:18 PM Forecasting is a procedure to predict something that will happen or come true in the future. However, it is not fortune telling. The basis for forecasting is solid evidence to predict future events. You can use it in many areas today; like predicting the future weather & the imminent economic climate. Quantitative forecasting is used to predict future figures & quantities such as sizes & lengths; it is based on measurements Qualitative forecasting is used to predict what something in the future will be like in terms of things other than set figures. For example, it could predict what color it will be, what the nature of it will be, etc. Qualitative forecasting is based on quality. Forecasting Techniques Steven Yoon 9/5/2012 2:28:35 PM Qualitative forecasting are forecasts based on judgment & opinion. Where quantitative forecasting are forecasts based on historical data. According to our book, "The qualitative (or judgmental) approach can be useful in formulating short-term forecasts & can also supplement the projections based on the use of any of the quantitative methods". Quantitative models work as long as there are no changes in the environment. When there is a change, then qualitative forecasting is more fit. Forcasting Techniques Marga Hodge 9/5/2012 2:38:46 PM 1. Qualitative approach—forecasts based on judgment & opinion ▪ Executive opinions ▪ Delphi technique ▪ Sales force polling ▪ Consumer surveys 2. Quantitative approach a. Forecasts based on historical data ▪ Naive methods ▪ Moving average ▪ Exponential smoothing ▪ Trend analysis ▪ Decomposition of time series b. Associative (causal) forecasts ▪ Simple regression ▪ Multiple regression ▪ Econometric modeling (Shim, 2009) Each way of forecasting has accurate outcomes. The way to determine which method to use is if it is needed short term or long term. Also, each company may use both types of forecasting, because each situation may require different things. Most companies do not use only one of these. Shim, J.K., Siegel, J.G. (2009). Budgeting Basics & Beyond. Third Edition. Retrieved from Forecasting Techniques Tamyra Scott 9/6/2012 9:09:47 AM There are basically two approaches to forecasting, qualitative & quantitative: 1. Qualitative approach- forecasts based on judgment & opinion: ▪ Executive opinions ▪ Delphi technique ▪ Sales force polling ▪ Consumer surveys 2. Quantitative approach a. Forecasts based on historical data ▪ Naive methods ▪ Moving average ▪ Exponential smoothing ▪ Trend analysis ▪ Decomposition of time series b. Associative (causal) forecasts ▪ Simple regression ▪ Multiple regression ▪ Econometric modeling I believe that qualitative forecasting provides a more accurate result seeing that it is forecast based on historical data versus what someone thinks or believes. Forecasting Techniques Ddungu Wasswa 9/6/2012 9:55:28 PM The qualitative & the quantitative forecasting differ in following ways. The first difference is In the approach, in the quantitative forecasting focuses on the matters related to sales forecast, budgets forecast, figure projection or econometrics, Whereas, on the other hand the qualitative forecasting is based on the expert opinion & judgment. The qualitative forecasting is not dependent on the history whereas the quantitative forecasting has the inclusion of the events that has happened in the history specifically the company’s figures abreast it also includes the events that has occurred in the history of industry. The quantitative forecasting is comprised of two techniques namely the time series technique & the relational technique. The time series technique is the one that focuses on the future based on the things that has happened in the past & the relational techniques related to the ideas the future of the organization depends on with several number of different factors that might affect it in present. The qualitative has only one major technique & that is the Delphi technique which is the common qualitative technique & is mostly gained from the mailed surveys & the participation is provided to the participants. Out of two according to me the quantitative technique is must better in contrast. Quantitive & Qualitative Jessica Samhan 9/7/2012 6:59:07 AM Quantitative forecasting tools are used to predict future figures & quantities such as sizes & lengths. Qualitative forecasting tools are used to predict what something in the future will be like in terms of things other than set figures. For instance, they could predict what type a future element will be; what color it will be; what the nature of it will be. Forecasting Techniques Brandon Rader 9/7/2012 7:31:03 AM Quantitative forecasting is based on historical data & numbers while qualitative forecasting is based on inference & observation. Both methods can prove to be accurate or inaccurate depending on how they are used. RE: Forecasting Techniques Tamyra Scott 9/8/2012 10:40:26 PM Quantitative forecasting- a statistical technique for making projections about the future which uses numerical facts & prior experience to predict upcoming events. The two main types of quantitative forecasting used by business analysts are the explanatory method that attempts to correlate two or more variables & the time series method that uses past trends to make forecasts. Read more: Example Professor Foor 9/8/2012 12:09:51 AM Imagine you are working in an office setting & needed to explain of all methods to forecast, the most effective to someone whom knows little about it. Which would you pick & how would you explain it? RE: Example Kayla Riley 9/8/2012 9:46:47 AM Professor Foor, that is a challenging question. I'm really not sure if one forecasting method is more effective than the next in general. In my opinion, it depends on the situation due to the fact there are a variety of methods but for different reasons. A company may be wanting a short-term forecast for up to six months, a mid-term forecast for up to two years or a long-term forecast for more than two years. You want to use the right forecasting method for the right term because what you use for one term may be inappropriate for the next. RE: Example Natasha Field 9/8/2012 8:27:27 PM The most effective in my opinion is the qualitative method. I would explain it as a method that does not need to use numbers to come to a forecast. It uses actual data to come to a trend. To get the actual data, you would conduct such things as customer surveys or using the judgement of experts in a particular field. The qualitative method allows for more in depth answers to give researchers more to work with. RE: Example Latoya Shands 9/8/2012 1:47:40 PM The most effective method of forecast I would explain to someone is tactical. Tactical forecast method is a short term goal the company establish to meet short term monthly quotas for the business. The tactical method of forecast meets the fulfillments of consumer demands through strategic planning that analysize the different methods that could safe the company money through inventory stocks, pricing, retail sales, & increasing revenue. Tactical forecast manages the business budget, & helps the company to know the ways to improve customer service as well as meeting customers demands. RE: Example Ricky Ontiberos 9/9/2012 12:10:54 AM I think the most effective method of forecasting to explain to someone who knows very little about it would be the quantitative approach because you could simply explain to them that you are forecasting based off of historical data & trends. I would explain to them that when making forecasts for the future sometimes you have to look at what happened in the past during similar conditions & that will give you a pretty good indication of what will happen, pending any unforeseen unsystematic surprises that may occur. As far as explaining the use of trends in forecasting I would explain to them that you have to look at any noticeable changes in business activities that are occurring either repeatedly or often. This can help you predict what may happen during certain periods of the year or when prices change. for example. RE: Example Steven Yoon 9/9/2012 9:16:38 PM I would explain the moving average. It is the most simplest & easiest to understand. I would make the person observe me calculating a forecast, using a three day moving average. By showing him how to use a 3 day moving average, the person can then apply that to any amount of days. RE: Example Wilma Balmonte 9/9/2012 10:13:22 PM I would choose the qualitive method. The qualitive method is done by gathering data through surveys, questionaires & etc. This can be easy for someone to do who knows nothing about forecasting. They will be able to collect data & locate a trend with the data collected. Lecture Professor Foor 9/9/2012 12:17:20 AM Class, from the lecture, here's the attached excel sheet. Please summarize from these three sheets in along with the TCO what the purpose of this excel program is for. Quantitative_Forecasting_M Weekly Summary Professor Foor 9/9/2012 12:17:57 AM Class, take the information from the TCO, lecture, assignments, text, & discussion boards to complete a weekly summary. Your thoughts? RE: Weekly Summary Kayla Riley 9/9/2012 11:27:11 PM Modified:9/9/2012 11:28 PM I thought this week was a pretty good week of learning new information. I learned what the exact meaning of a budget is, types of budgets, characteristics of an effective budget, & the budget processs. It was interesting reading other classmates' posts about their experiences with budgets whether personal or business. Although I did have a little trouble with a couple of the homework problems, it feels good to now know how to calculate different forecasting methods. I even found out how to do some of the calculations in excel, which can really save time, like for calculating exponential smoothing. RE: Weekly Summary Chanel Thorpe 9/9/2012 9:23:59 PM Modified:9/9/2012 9:27 PM During this week I learned of the budgeting process type process & the types of budgets used. I also learned why a budget is put in place from an organizational stand point, I've created personal budgeting pans, but never a plan for a business, or for that matter have I even thought of what it all consists of. Also, from this weeks lecture, I now know what is forecasting & it's difference from a budgeting plan. Within forecasting there are two approaches that we talked about, which are the quantitative & qualitative approach. & how the two approach differ when creating a forecast. quantitative & qualitative Monique Robertson 9/9/2012 10:36:53 PM Qualitative forecasting is based on the opinions of customers & executives whereas, quantitative forecasting uses the things that have happened in the past to predict what might happen in the furture.Quantitative uses numbers such as the moving average & techniques like the trend analysis. I don't think one provides more accurate information because with qualitative forecasting if things are not the same & consistent it can give inaccurate results & the same with the judgement & opinions of qualitative results however, when a company use qualitative forecasting you can take any change into better & faster consideration.