Chap: VIII

Q1: Multiplicative Seasonal Method

Actual Demand Forecast

 Year Q1 Q2 Q3 Q4 Av. Σ 2001 43 56 74 61 59 234 2002 56 102 115 111 96 384 2003 105 97 119 133 113 454 2004 136 140 - - 69 276

Seasonal Forecasting

Average Factor= 14.5*4 =58

 Year Q1 Q2 Q3 Q4 Av. 2001 0.74 0.97 1.28 1.05 1.01 2002 0.97 1.76 1.98 0.19 1.23 2003 1.81 1.67 2.05 2.29 1.96 2004 2.34 2.41 - - 1.77

Statistical Keys: Q = Quarter; Av. =Average, and Σ = Summation or Total

Average Seasonal Factor: Year 2001: 1.01(58) = 59

Year 2002: 1.23 (58) = 71

Year 2003: 1.96 (58) = 113

Year 2004: 1.77(58) = 102

Step 1: Take total flights data on annual basis and divide 4 (year Periods)

Step2: Divide the flights actual demand by average flights demand

Step3: Sum-up all seasonal factors then divide by the seasonal factor 58 i.e. 14.5*4

Step 4: Establish the projected monthly demand by considering average seasonal factor * forecasted future demand. Consider dividing by factor 12 to derive at the average demand on monthly basis (Verma & Boyer, 2009). As such on every month for a year period we anticipate the demand to stand at about 4.9 +5.9+11.08+8.5 = 7.6 flights (Refer to Memo Section for values 4.9. 5.9, 11.08 and 8.5 computations).

Q2: Memo Section

MEMO

To: Emergency services Department

Subject: Results Based Explanations

From: {Insert Name Here}

Date: March 20th, 2010

Results Based Explanations

The actual demands for the year 2001 to 2004 are computed by taking the average total value of all flights in quarterly basis. Each quarter indicates constitute of the projected demand based on both missed and actual flights falling under 14.5 days monthly consideration. The average factor considered is based on the average flights for actual monthly demand with 14.5 days as the base, and factor as the multiplier 4 for the projected quarterly demand (Hirschey, 2009). This illustrates that in every four quarters 14.5*3 = 43.5 days will either assume missed or actual flights demand.

Under this analysis, VHM emergency services can only be availed on 43.5 days in every quarter with each cruise covering between 230 and 50 miles. As such 3 Bell 222 UT will effectively cover a predicted demand at the rate of 59 flights in 2001, with 2002 having 71 flights , 113 flights in 2003 on annual demand and 102 in fiscal 2004. On monthly basis, we have predicted an increase with on average of 59/12 = 4.9 flights in 2001, where fiscal 2002 considerations gives about 71/12 = 5.9, 2003 monthly demand projections stands at 113/12 = 11.08 flights and finally 102/12 = 8.5

The reliability of this method is premised on two key assumptions. First, the actual demand of flights is based on real factor value 14.5 days considered on monthly basis. This indicates that if a normal emergency cruising service stands at 14.5*3= 43.5 days in every quarter, then assumed factor (monthly projected demand) will lie between the actual demands and average seasonal factor (Axsäter, 2006). Secondly, the variation in hours or days in flights coverage satisfies the use of multiplicative method in estimating actual monthly demand based on the idea that the resulting values indicates the adjusted effects on quarterly basis. Essentially, we only consider average considerations in flights on each quarterly demand, and multiply by seasonal factor as the basis of our multiplicative value.

Chap IX:

Q1: Basing the capacity requirements on average demand indicates/implies that, on seasonal periods the exceeding values on service facility will be ignored or even understated if hourly services coverage surpasses the estimated value in resources availed to clients. For example, if 80 beds consist of the actual supply in resources available to serve maternity services to all patients, then any eventuality that may alter the average demand on 9125 patients demand considerations on annual basis will act to influence the perceived need to meet the surpassing number of beds falling over 80 beds mark.

Q2: In developing an effective capacity plan VMH need to consider the seasonality of the services offered. For example, by considering the average patients in one year to be 9125, then in one month we have about 760 patients. If one patient stays for 3 days, then VHM maternity facility can only accommodate about 76 patients. Here we consider factor 10 as the divisor derived as number of days (30days a month) divide by the typical days-stay (3) to obtain 10.

Q3: The percentage utilization stands at 76/80*100 = 89.41%. Note that the projected patients demand as per bed capacity based on 9125 as the base annual demand is 76, but usually there 80 beds availed monthly for three-day stay and as such 76 is actual number of beds that ends-up being utilized. Thus the utilization percentage is derived by taking 80 beds as the base factor.

Q4: 15% capacity Cushion indicates that Lee has to have a steady supply of beds in excess of 15%*76 = 11 beds. The cushion capacity will stand at 11 beds based on the projected number of 76beds. The actual number of beds may be placed on about 87 beds (i.e. 76+11).

Q5: Lee ought to consider two key factors when planning for the expansion. First, Lee ought to ascertain the period in the month when seasonal demand peaks (Hirschey, 2009). Here she would consider the estimated capacity requirement and perhaps plan for the excess beds threshold based on estimated 87 beds. Secondly, she ought to consider the availability of resources or budgetary allocations for VMH resources planning and expansion programs. The amount availed should cover the estimated number of actual-beds' capacity plus the projected capacity cushion.

Source: Essay UK - http://turkiyegoz.com/free-essays/economics/multiplicative-seasonal-method.php

## Not what you're looking for?

### Search:

This Economics essay was submitted to us by a student in order to help you with your studies.

### Rating:

 Rating No ratings yet!

• Order a custom essay
• Search again

### Cite:

If you use part of this page in your own work, you need to provide a citation, as follows:

Essay UK, Multiplicative seasonal method. Available from: <http://turkiyegoz.com/free-essays/economics/multiplicative-seasonal-method.php> [11-12-18].