Elucidate Importance of Forecasting in an Organization

SOUTHEASTUNIVERSITY Assignment

On

Elucidate Importance ofForecasting in an

Organization

Submitted To:Dr. Matiur Rahman

Course Instructor

School of Business Studies

Southeast University

Submitted By:Students Name ID No. SignaturePapia Sakawat 2011210004018

Md. Monwar Azam 2011210004019Md. Shafiqur

Rahman2011210004021

Md. Omar Faruq 2011210004023

Letter of Transmittal

May 13, 2012

Dr. Matiur RahmanCourse InstructorSchool of Business studiesSoutheast UniversityDhaka, Bangladesh.

Subject: Submission of the Assignment.

Dear Sir,

We would like to submit the assignment which to as doneon “Elucidate Importance of Forecasting in an Organisation”. The assignment writing has given us the opportunity to combine our theoretical knowledge with practical experience. We would like to say that if thisassignment effect on any organization then we’ll be responsible for that and we don’t submit it anywhere.

Your valuable advice, suggestion and guidance have helped us to prepare the assignment. We will be very glad, if you kindly accept this assignment.

Sincerely yours,

Papia SakawatID-2011210004018

Md. Monwar AzamID-2011210004019Md. Shafiqur RahmanID-2011210004021Md. Omar FaruqID-2011210004023

ACKNOWLEDGEMENT

At first we want to express our gratitude to AlmightyAllah for giving us the strength and the composure tofinish the task within the scheduled time.

Our sincere gratitude goes to our honorable courseteacher, Dr. Matiur Rahman, Faculty of BusinessStudies, Southeast University. Without his support andencouragement this case would not possible such anendeavor to enhance my practical knowledge about thereal online marketing.

Thanks all from core of our heart.

Table of Contains

Contains Page noIntroduction

Meaning of ForecastingUsefulness of Forecasting

Tools of ForecastingConclusion

Definition of Forecasting:

Forecasting is the process by which companies ponderand prepare for the future. It involves predicting thefuture outcome of various business decisions. Thisincludes the future of the business as a whole, thefuture of an existing or proposed product or productline, and the future of the industry in which thebusiness operates, to name a few. Forecasting is usedto answer important questions, such as:

How much profit will the business make?

How much demand will there be for a product or service?

How much will it cost to produce the product or offer

the service?

How much money will the company need to borrow?

When and how will borrowed funds be repaid?

Businesses must understand and use forecasting in orderto answer these important questions. This helps thecompany prepare for the future. It also helps theorganization make plans that will lead to becoming a

financially successful business. This article willdiscuss the reasons financial forecasting is importantto an organization.

Usefulness of Forecasting:Financial forecasting is important for several reasons.First, it enables management to change operations atthe right time in order to reap the greatest benefit.It also helps the company prevent losses by making theproper decisions based on relevant information.Organizations that can create high quality and accurateforecasts are able to "see what interventions arerequired to meet their business performance targets"(Vadasz).

Forecasting is also important when it comes todeveloping new products or new product lines. It helpsmanagement decide whether the product or product linewill be successful. Forecasting prevents the companyfrom spending time and money developing, manufacturing,and marketing a product that will fail.

Stockholder expectations highlight another reasonbehind the importance of forecasting. Public companies

experience scrutiny and pressure for short-termperformance from investors. Operational results will beexamined by investors and investment analysts, andactual results that differ from forecasts will be badfor the company and its stock price. This is becauseboth meeting predictions and exceeding predictions willreduce investor confidence. This will cause investorsto believe that the company does not understand its ownbusiness model.

Tools of Forecasting:Assessment of a company's current technology shoulddrive the direction of the R&D planning process. Thereneeds to be a systematic process for assessing

technology. [2, 5] There are eight (non-TRIZ)forecasting methods to aid assessment:

1.Intuitive forecasts2.Consensus methods3.Delphi method4.Application of a statistical model5.Application of a causal model6.Analogy method7.Extrapolation8.Structural modeling

Intuitive Forecasting:Intuitive forecasting is a very popular and widelyapplied methodology. "Asking the expert" usuallyprovides the information for the forecast. It isassumed that the experts' base of experience andeducation is sufficient, in a particular field, topredict or forecast the vectors of expansion orevaluation. Records indicate the pronounced fallibilityof this forecasting method.

British author and inventor Arthur C. Clarke describedsome false predictions based on the "expert" intuitiveforecasting by unquestioned authorities in hisbook, Profiles of the Future, including, for example, that in1956 the Royal British Astronomical Society predictedthat "space travel is utter bilge."

Consensus Method:A simple method of overcoming some of the disadvantageof intuitive forecasting is the use of a "panel ofexperts." The presumption is that many experts are morelikely to be accurate than one. The U.S. Department ofDefense has used this method successfully on projectsincluding the Strategic Defense Initiative program(more commonly known as "Star Wars" as well as numerousweapon systems and vehicle platforms. The U.S. AirForces Project Forecast was an effort in the mid-1980sto characterize high-leverage future militarytechnologies and is an example of a large andsuccessful application of the consensus method. Ofcourse, the shortcomings of the intuitive method can becompounded during the application of the consensusmethod (the possibility of a hidden bias being canceledby a hidden counter-bias may not materialize).

Delphi Method;To improve on the intuitive and consensus methods, theRand Corporation developed the "Delphi Procedure" in

which a panel of experts (like the consensus method)arrive at a consensus but eliminate the regulating ofcommittee bias by employing a series of questionnaires.The first phase asks for the panel's forecasts. Thereplies are compounded. The second phase requestscomments on the Phase I compound forecast. Phase III isa derivative of Phase I based on the results of PhaseII. A typical process includes five or six phases. Thegoal of this multi-phase process is a forecastconvergence. Figure 1 shows the convergence of ahypothetical date for a certain even based on a multi-phase Delphi process.

 Figure 1: Delphi Forecasting Convergence Example (A, B, C, E, F, G and H represent panel members. The data converges as the panel of experts forecast phase-by-phase.)

Application of a Statistical Model:A statistical model is based on a series ofobservations of the phenomenon and it delineates thepattern of the association between the various factors(or variables) of the phenomenon that are of interest.Descriptive models used in forecasting are oftenquantitative, but qualitative ones are used as well.Many events, such as descriptive phenomenon, are singleoccasion events and as such they are a difficultphenomenon to model. Therefore, the application of astatistical model necessitates a thorough understanding– lengthening the forecasting process.

 Figure 2: The Method of Prediction Based on a Descriptive Model

Application of a Causal Model:A causal model is similar to a statistical model as italso describes (through research) the development of aphenomenon to be predicted. It is an improvement on thestatistical model as it also provides the causativeagent(s) for the occurrence of the phenomenon to bepredicted. An understanding of the invariance of thephenomenon gives the forecaster good grounds forforecasting as this invariance is believed to remainvalid into the future. A causal model is normally basedon a population and is therefore valid only in thatcontext. A causal model limitation is the necessity toassume uniformitarianism (invariance as a function oftime).

A famous example of a large causal model was fabricatedby the Club of Rome and published in the 1972book, Limits to Growth. It consists of dozens of variables,including world population, birth rate, industrial andagricultural production, non-renewable resources andpollution. In the model, the levels, or physical

quantities that can be measured directly, are indicatedwith rectangles, rates that influence those levels withvalves and auxiliary variables that influence the rateequations with circles. Time delays are indicated bysections within rectangles. Real flows of people,goods, money, etc. are shown by solid arrows and causalrelationships with broken arrows. Clouds representsources or "sinks" (exits of material) that are notimportant to the model behavior.

The Club of Rome think tank started building their"World Model" by first constructing five sub-models.These concentrated on the five "basic quantities":population, capital, food, non-renewable resourcesremaining (measured as remaining fractions of the 1900reserves) and pollution. One of the sub-systemsincluded the causal relations and feedback loopsbetween population, capital, agriculture and pollution.Finally, the researchers combined all the five sub-models and created the final World Model, part of whichis illustrated in Figure 3.

 Figure 3: Example of Large Causal Model [3]

Analogy Method:This method utilizes analogies between the phenomenonto be forecast and some historical event, or popularphysical or biological process. To the extent that theanalogy is valid (all analogies become invalid at acertain level), the initial event or process can be

used to wake a prediction about future developments ofa technology. (See Figure 5.) The technologicalforecaster uses the analogy method consciously anddeliberately, examining the model situation and thesituation to be forecast in considerable detail todetermine the extent to which the analogy is valid. Anexample of this approach is delineated in the book TheRailroads and the Space Program: An Exploration in HistoricalAnalogy edited by Bruce Mazlish. The forecasters used19thcentury railroad development as an analogous systemto the U.S. space program. The utilization of growthcurves is used to predict the advance of sometechnologies (analogous to biological or physicalprocesses – the "'S" curve, see Figure 4).

 Figure 4: Growth Curves [4]

 Figure 5: Making Predictions (If a foreign system consisting of elements A, B and C produces elements D and E, an analogous system with elements A', B' and C' can be predicted to produce elements D' and E', where A', B', C', D' and E' are elements in the system to be predicted.)

Extrapolation Method:Trend extrapolation is one particular method of solvingthe prediction of the inflection problem associatedwith the "S" curve of the analogy method (when is thecurve going to change slope, B). Instead of focusing on

a single device and attempting to predict the futurecourse of development of that device, the trendextrapolation method considers a series of successivedevices while performing similar functions. These maybe considered individual representations of a broadarea of technology. (See Figure 6.) The extrapolatedtrend will eventually reach a physical limit and willlose its validity as the trend approaches this limit.

 Figure 6: ExtrapolationMethod [4]

 Figure 7: Approaching the Physical Limit (Dis measured between t = -1 and t = 0 so that dcan be applied to t = 1 to extrapolate the trend value at time t = 1. Thiscan be applied to t = any time as long as the trend value does not violate a physical limit. [3])

Structural Modeling:Structural modeling is an attempt to develop a mathematical or analytical model of a technology-generation process. As with mathematical models of any process, the purpose for model construction is to identify certain key elements, identify the functional aspects of those elements and express these functional aspects symbolically or mathematically. Structural models tend to be abstract and reductionist in their approach in removing what are denied to be non-essential functions. (See Figure 8.)

 Figure 8: Structural Model of the Technology-generation Process

 (Each block conceals a sub-model.)

Advantages and Disadvantages of ForecastingMethods of Production and Operations Management

Organizations use forecasting methods of production andoperations management to implement productionstrategies. Forecasting involves using severaldifferent methods of estimating to determine possiblefuture outcomes for the business. Planning for thesepossible outcomes is the job of operations management.Additionally, operations management involves themanaging of the processes required to manufacture anddistribute products. Important aspects of operationsmanagement include creating, developing, producing anddistributing products for the organization.

Advantages of Forecasting:An organization uses a variety of forecasting methodsto assess possible outcomes for the company. Themethods used by an individual organization will dependon the data available and the industry in which theorganization operates. The primary advantage offorecasting is that it provides the business withvaluable information that the business can use to makedecisions about the future of the organization. In many

cases forecasting uses qualitative data that depends onthe judgment of experts.

Disadvantages of Forecasting:It is not possible to accurately forecast the future. Because of the qualitative nature of forecasting, a business can come up with different scenarios dependingupon the interpretation of the data. For this reason, organizations should never rely 100 percent on any forecasting method. However, an organization can effectively use forecasting with other tools of analysis to give the organization the best possible information about the future. Making a decision on a bad forecast can result in financial ruin for the organization, so an organization should never base decisions solely on a forecast.

Conclusion:

The elements of doing business are constantly changing.Interest rates rise and fall, customer preferenceschange, suppliers go out of business, and the list goeson and on. As the factors that affect business change,the company forecasts must also change. In this time ofrapid change, accurate and timely forecasts have becomeeven more important. Recognizing this is the first stepin becoming a successful organization.