2 What is Forecasting? Forecasting is the art and science of predicting It may involve takinghistorical data andprojecting it into thefuture by means of amathematical model.It may also be anintuitive prediction.It may also be amathematical modeladjusted by goodjudgement.Forecastingis the artand scienceof predictingfuture events.
3 Forecasting is Data Mining Too ! Data mining is the process of extractingpatterns or correlations among dozensof fields in large relational data bases.With the amount of data doubling everythree years, it is becoming increasinglyimportant for transforming data into in-formation, which in turn, can be used toincrease revenues, cut costs, or both.Data mining uses simple and multi-variate linear, and non-linear regressionmodels as well as hypothesis testing.
4 Simple Linear Regression Data Mining Exampleone or moreSimple Linear RegressionmodelsA grocery chain analyzed local buyingpatterns.They discovered that when men boughtdiapers on Thursdays and Saturdays,they also tended to buy beer.
5 Data Mining Example Further analysis showed that these men A Multiple RegressionModelFurther analysis showed that these menusually did their weekly grocery shoppingon Saturdays. On Thursdays, however,they only bought a few items.
6 Data Mining Example The retailer concluded that the men purchased beer to have it available for the upcoming weekend.The grocery chain could use this newly discoveredinformation in various ways to increase revenue.For example, they could move the beer display closerto the diaper display. And, they could make sure thatbeer and diapers were sold at full price on Thursdays!INFORMATION to KNOWLEDGE to DECISION !
7 A Word of Advice… There is seldom a single superior forecasting method. One firm may find exponentialsmoothing to be effective. Another firm mayuse several models, and a third firm may combineboth quantitative and subjective methods.Whatever approach works best should be used.
8 Forecasting Time Horizons 1. Short-range forecast : Time span of up to 1 year but generallyless than 3 months. It is used for planning purchasing, jobscheduling, workforce levels, job assignments, and product-ion levels.2. Medium-range forecast : Time span of 3 months generally to3 years. It is useful in sales planning, production planning /budgeting, cash budgeting, and analysis of various operatingplans.3. Long-range forecast : Generally 3 years or more in time span.It is used in planning for new products, capital expenditures,facility location or expansion, and research and development.
9 The Strategic Importance of Forecasting Good forecasts are of critical importance in allaspects of a business.The forecast is the only estimate of demanduntil actual demand becomes known.Forecasts of demand therefore, drive thedecisions in many areas.
10 Forecast Impacts Human Resources Hiring, training, and terminating workers all dependon anticipated demand. If the HR department musthire additional workers without warning, the amountof training declines and the quality of the workforcesuffers.
11 Forecast Impacts Capacity the resulting shortages When capacity is inadequate,the resulting shortagescan mean undependabledelivery, loss of customers,and loss of market share.When capacity is in excess,costs can skyrocket.
12 Forecast Impact Supply Chain Management In the global marketplace, where expensiveparts for Boeing 787 jets are manufacturedin dozens of countries, coordination drivenby forecasts is critical.Scheduling transportation to Seattle for finalassembly at the lowest possible cost meansno last-minute surprises that can harm alreadylow profit margins.
13 Product Life Cycle Influence Products and even services, do not sell at a constant levelthroughout their lives. Most successful products passthrough four stages : introduction, growth, maturity, anddecline.
14 Product Life Cycle Influence Products in the first two stagesof the life cycle need longerforecasts than those in thematurity and decline stages.Forecasts that reflect life cycleare useful in projecting differentstaffing levels, inventory levels,and factory capacity as theproduct passes from the firstto the last stage.
15 Forecasting Caveats Forecasts are seldom perfect. Outside factors we cannot predict or control often impact the forecast.Most forecasting techniques assume that there issome underlying stability in the system.Product family and aggregated forecasts are moreaccurate than individual product forecasts.This approach helps balance the over and underpredictions of each.
16 Service Sector Forecasting Barber ShopsExpect peak flows on Fridays and Saturdays.Many call in extra help on the above days.Most are closed on Sunday and Monday.
17 Service Sector Forecasting Flower ShopsWhen Valentine’s Day falls on a weekend, flowers cannot bedelivered to offices, and customers are likely to celebratewith outings rather than flowers ( low sales ) .When Valentine’s Day falls on a Monday, some celebrationwill have taken place on the weekend ( reduced sales ) .When Valentine’s Day falls in midweek, busy midweek workschedules make flowers the optimal way to celebrate( higher sales ).
18 Service Sector Forecasting Fast Food RestaurantsUse point-of-sale computers that track salesevery 15 minutes.May use the moving average technique tominimize the error of the 15-minute forecasts.The forecasts are used to schedule staff, whobegin in 15-minute increments, not the 1-hourblocks as in other industries.
19 Hourly Sales at a Fast-Food Restaurant 20%15%10%5%Percent of Sales by Hour of Day( Lunchtime )( Dinnertime )
20 Monday Calls at a FedEx Call Center 12%11%10%9%8%7%6%5%4%3%2%1%0%A.M P.M.
21 Service Sector Forecasting Federal Expressmakes 1-year and 5-year models to predict number of servicecalls, average handle time, and staffing needs.breaks the forecasts into weekday, Saturday, and Sunday,and then uses the Delphi Method and time-series analysis.tactical forecasts are monthly, and use 8 years of historicaldaily data. They predict caller volume by month, day of theweek, and day of the month.the operational forecast uses a weighted moving average and6 weeks of data to project the number of calls on a 30-minutebasis.
22 Service Sector Forecasting Federal ExpressFed Ex’s forecasts are consistentlyaccurate to within 1% to 2% of actualcall volumes.This means that coverage needs aremet, service levels are maintained, andcosts are controlled.
24 Weighted Moving Average, Exponential Smoothing, Time-Series ModelsPredict the future by using historical data.Assume that what happens in the future isa function of what has happened in the past.Moving Average,Weighted Moving Average,Exponential Smoothing,Trend Projection
25 Ice cream sales, for example, might depend on the season, Causal ModelsIncorporate variables or factors thatmight influence the quantity beingforecasted into the forecasting model.The most common causal model isregression analysis.Ice cream sales, for example,might depend on the season,average temperature,day of the week, and so on.
26 Qualitative Models Incorporate judgmental or subjective factors into the forecasting model.Opinions by experts, individual experiences,and other factors are expected to be veryimportant.Used when accurate quantitative data aredifficult to obtain.EXAMPLES ARETHE DELPHI METHOD,SALES FORCE COMPOSITE,ANDCONSUMER MARKETSURVEY
27 1. The Delphi Method Three types of participants: decision makers, staff personnel, and respondents.The decision makers make the actual forecast.The staff personnel prepare, distribute, collect,and summarize a series of questionnaires andsurvey results.The respondents are those whose judgementsand values are being sought. They provide in-put to the decision makers before the forecastis made.
29 2. Sales Force Composite Each salesperson estimates what sales will be in his or her region.These forecasts are reviewed to ensurethat they are realistic.These forecasts are combined at thedistrict and national levels to reach anoverall forecast.
30 3. Consumer Market Survey This method solicits input from customersor potential customers regarding their futurepurchasing plans.It can help not only in preparing a forecastbut also in improving product design andplanning for new products.