Module 2 Week 2 Negotiation

Q4) Define the following concepts with example. Market Potential Sales Potential Market Share

Q1. Does Livestock Wealth use "inside-out" or "outside-in"?

Q-4: Define and briefly explain the following methods of demand estimation with examples from the real world? a) Consumer Surveys b) Consumer Clinics c) Market Experiments

1 Given the data below. Find the forecast value from June to December Month Actual Demand Forecast January February 380 420 March 375 April May 285 325 June July August Sept October November December ?? ?? ?? ?? ?? ?? ??

Please do not give solution in image formate thanku.

NEED HELP WITH THE EXCEL:  DECISION VARIBLES OBJECTIVE FUNCTION CONTRAINSTS

Month Actual Sales Naive Forecast- Absolute Value of (# of Product X) Sales Errors (# of Product X) Jan/19 Feb/19 Mar/19 Apr/19 May/19 Jun/19 Jul/19 Aug/19 Sep/19 Oct/19 Nov/19 Dec/19 Jan/20 1,860 2,033 3,556 4,211 6,250 7,990 10,250 9,850 9,980 9,990 7,895 5,353 - Explain the calculation method for the Naive Forecast model. the faln

Question Using a suitable moving average method, find the trend values.

(b) Demand history of five different products of a company is shown below. Products 2012 2013 2014 2015 2016 2017 2018 2019 2020 A 37 40 41 45 49 26 34 30 26 23 33 28 32 C 58 55 32 38 45 56 62 70 77 86 95 83 88 81 92 85 i. Name the methods that is suitable to forecast the demand of the above five products? ii. Forecast demand of the product B or D with error for the year 2021. If you need a value of a then consider it 0.7.

Requirement: Show your calculation

. Trucks: develop causal regression forecast model and analyze

Q1 Given the Supply chain cost for a service is PKR 195 and the customer value is PKR 225. Determine supply chain surplus and consumer surplus. Q2  PizzaHut is a franchise based model which serves customers a variety of pizzas and related products. The service is purely customized. Identify whether the model is push-based supply chain or pull based supply chain. Can we a have push-pull boundary in PizzaHut case? How?  Q3 Discuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods. Discuss Delphi forecasting method and its challenge.

New Accounts New Accounts Period 200 232 11 214 248 12 211 250 13 228 253 14 5 235 10 267 15 Using linear regression, what is your forecast for period 16? Less than 300 Between 301 and 308 Between 309 and 350 Period 1 2 3 4 O Higher than 350 Period 6 7 8 9 New Accounts 281 275 280 288 310

(4) The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per season (quarter) during the past five years. Orders (1,000s) Year 1 Year 2 Year 3 Year 4 Year 5 Winter (Q 1) Spring (Q 2) Summer (Q 3) 18.6 18.1 22.4 23.2 24.5 23.5 24.7 28.8 27.6 31.0 20.4 19.5 21.0 24.4 23.7 Fall (Q 4) Total 41.9 46.3 45.5 47.1 52.8 104.4 108.6 117.7 122.3 132.0 Develop a seasonally adjusted forecast model for these order data. Forecast demand for each quarter for year 6, using the annual trend line as given: Y(t) = 96.33 + 6.89t (a) Find seasonal index for each quarter (b) Find seasonally adjusted demand forecast for each quarter for year 6 (c) Find MAD for seasonally adjusted forecasting for year 1 through 5.

Question 1 Q1) The monthly sales of a retailer company were as follow: Month -Sales February-- March- 1000 1800 April- -2100 May- -1000 June- July-- 2048 2600 August As a planner, you are required to calculate the Demand Forecast for August using the Naive approach Add your answer

A forecast for the first six months of the year revealed a tendency to underpredict the actual demand for the revitalized Hubig’s Pies plant in the Marigny.   Month Actual Forecast January 675 600 February 720 700 March 640 620 April 510 495 May 480 410 June 565 535   What is the MAD of this forecast?   a. 38.33   b. 64.11   c. 55.79   d. 71.89

Q-5: A firm A tries to estimate the relationship between demand for its product and income of the consumers. By estimating the relationship, it has been found that B= -0.85. Interpret such a relationship. (4)

OQ16

Required: Create a Competitive Analysis for Hersheys Company Noted: details in the photo attached

Conduct an ABC analysis on the following twelve items. SKU $ Value/Unit Annual Use (units) B 60 580 D 52 620 36 720 K 20 600 38 300 40 250 25 360 16 280 G 480 10 320 12 240 22 120

» 95 A cosmetics manufacturer's marketing department has developed a linear trend equation that can be used to predict annual sales of its popular Hand & Foot Cream. Ft = 80 + 25t where Ft = Annual sales (000 bottles), t is in years. Predict annual sales for year 6? 170 230 10 % 6 52 min 42 secs

Definition and Comparison Questions: For each question, provide an explanation of the marketing terms, compare and contrast them  and provide examples of how they are used in marketing. Q 1.2: Primary data and Secondary Data:

Day 2 Time of day Morning Afternoon Evening Morning Afternoon Evening Morning Afternoon Evening Demand (in thousands) 42 75 125 35 88 110 52 65 155 What is the seasonal index for evening?

06 A B xfx 64000 C D E F G Roll up the individual product forecasts and compare them with the family data. Use the family forecasts to revise the individual forecasts (both dollars & units). PART A Product Family Forecast Family $ Rolled-Up $ Rolled-Down $ Family Forecast Forecast Sales Goal 1 50,000 46.000 60,000 2 50,000 64.000 50,000 3 75,000 65,000 90,000 Total 175,000 175,000 200,000 , Use the FAMILY forecast to revise the individual item forecasts (in both dollars & units) 1 2 ROLL UP Unit 3 Product Forecast Dollars/Unit Dollar Forecast (goal) ROLL DOWN Dollar Forecast Unit Forecast (goal) A 10 $ 1,000.00 $ 10,000.00 5 B 15 $ 1,200.00 $ 18,000.00 6 C 20 $ 900.00 $ 18,000.00 17 TOTAL $ 46,000.00 18 5 $ 5,000.00 $ 25,000.00 19 E 3 $ 7,000.00 $ 21,000.00 20 F 2 $ 9,000.00 $ 18,000.00 xxXX XXXX 21 TOTAL $ 64,000.00 22 G 100 $ 250.00 $ 25,000.00 xxxxxXXXXXXXXXXXXXXXX 23 H 24 I 180 $ 220 $ 100.00 $ 18,000.00 xx 100.00 $ 22,000.00 25 TOTAL XXXXXXXXXXXX XXXXXXXXXXXX XXXX XXXXXXXXXXXX $…

Q1: Compare and contrast between SECI vs Wiig knowledge mangamnt models. Justify your answer by explaining how are they complementary? Are they complete – would you add any components from those models that you did not select? What are some of the obstacles you would expect to encounter and how would you overcome them to implement each of them?

I could use a hand with this

Month Demand Forecast Error Abs Error alpha 1 20 2 18 3 21 4 25 5 24 6 27 7 22 8 30 9 23 10 20 11 29 12 22 Mean Bias MAD (mean error) Problem 6: Maverick Jeans' demand manager decided to evaluate exponential smoothing. To maintain com- parability, she used the data from problem 6, copied below. 1 Month 2 3 Demand 20 18 21 25 4 5 24 6 7 8 9 10 11 12 27 22 30 23 20 29 22 Develop forecasts for months 5-12. Calculate the Bias and MAD. Use a starting forecast of 20 for month 4 and an alpha value of 0.2. (Note: Adjust all cell values to two decimal points.)

Regression line. A large midwestern retailer has developed a graph that summarizes the effect of  advertising expenditures on sales volume. Using the graph, determine an equation of the form y = a + bx that describes this relationship.

Q 21 What are the two (2) most important times when a marketer wants possible customers to think about their products? Group of answer choices When talking with their neighbor about the local baseball team. When the customer encounters a problem which your product would solve. When shopping in a store which carries your product. When helping their children with their homework. All the time — we need customers to continually have our products in their minds.

The K&R Camera shop sells all the latest cameras and accessories. To meet customer demand, the manager must forecast demand for items she sells. Lately the XR-42S zoom lens has been very popular. Recent monthly demand for this item has been as shown: Number of Lenses Month Sold 1 12 17 2 3 4 15 20 18 23 6.

Calculate the mean square error, mean absolute deviation and the Period Year Call Volume forecast Error 1 1 30 45 -15 2 2 25 15 10 3 2 55 65 -10 4 3 15 20 -5 Your answer?