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Must follow instructions to perform the report and the graphs requested. Additionally, must keep graphs in excel and put a copy on the word document of the report with each analysis for each graph. *** Dont do the line items that say dont highlighted in yellow.Midterm Project Assignment: Elizabeth Burke wants to develop a model to more effectively plan production for the next year. Currently, PLE has a planned capacity of producing 9,100 mowers each month, which is approximately the average monthly demand over the previous year. However, looking at the unit sales figures for the previous year, she observed that the demand for mowers has a seasonal fluctuation, so with this “level” production strategy, there is overproduction in some months, resulting in excess inventory buildup, and underproduction in others, which may result in lost sales during peak demand periods. . Ms. Burke explained that she could change the production rate by using planned overtime or undertime (producing more or less than the average monthly demand), but this incurs additional costs, although it may offset the cost of lost sales or of maintaining excess inventory. Consequently, she believes that the company can save a significant amount of money by optimizing the production plan. . Ms. Burke saw a presentation at a conference about a similar model that another company used but didn’t fully understand the approach. The PowerPoint notes didn’t have all the details, but they did explain the variables and the types of constraints used in the model. She thought they would be helpful to you in implementing an optimization model. Here are the highlights from the presentation: Variables: . Xt=plannedXt=planned production in period t . It=inventoryIt=inventory held at the end of period t . Lt=numberLt=number of lost sales incurred in period t . Ot=amountOt=amount of overtime scheduled in period t . Ut=amountUt=amount of undertime scheduled in period t . Rt=increaseRt=increase in production rate from period t−1t−1 to period t . Dt=decreaseDt=decrease in production rate from period t−1t−1 to period t . Material balance constraint: . Xt+It−1−It+Lt=demand in month tXt+It−1−It+Lt=demand in month t . Overtime/undertime constraint: . Ot−Ut=Xt−normalOt−Ut=Xt−normal production capacity . Production rate-change constraint: Xt−Xt−1=Rt−DtXt−Xt−1=Rt−Dt . Ms. Burke also provided the following data and estimates for the next year: unit production cost=$70.00;cost=$70.00; inventory-holding cost=$1.40cost=$1.40 per unit per month; lost sales cost=$200 per unit;cost=$200 per unit; overtime cost=$6.50 per unit;cost=$6.50 per unit; undertim e cost=$3.00 per unit;cost=$3.00 per unit; and production-rate- change cost=$5.00 per unit,cost=$5.00 per unit, which applies to any increase or decrease in the production rate from the previous month. Initially, 900 units are expected to be in inventory at the beginning of January, and the production rate for the past December was 9,100 units. She believes that monthly demand will not change substantially from last year, so the mower unit sales figures for the last year in the Performance Lawn Equipment Database should be used for the monthly demand forecasts. Analytics Team Case Analysis Consulting Report Performance Lawn Equipment Attention: Ms. Elizabeth Burke Supporting Documents for this Learning Assignment • Structure of a Data Analysis Report PDF Document • Consulting Is More Than Giving Advice https://hbr.org/1982/09/consulting-is-more-than-giving-advice • Data Analysis Steps https://www.r-bloggers.com/data-analysis-steps/ • The Difference Between Reporting and Analysis and Why it Matters https://datahero.com/blog/2017/08/14/data-reporting-and-analysis/ • How to Write a Data Report https://smallbusiness.chron.com/write-data-report-61330.html • The Seven Key Steps of Data Analysis https://rizkashifs.wordpress.com/2015/09/03/the-seven-key-steps-of-data-analysis/ Table of Contents 1. Executive Summary ( don’t do) 2. Overview Case Analysis – What’s this case analysis about? ( don’t do) 3. Scope of Consulting Work and Report – • Detailed List of Assignments this case analysis is requesting. ( don’t do) 4. Introduction ( don’t do) 5. Analysis and Findings ( don’t do) For EVERY Case Analysis ASSIGNMENT • 5.1 Assignment(s) 1 – Statement o Identify Business Problem - “Define Problem statement [aka Case Analysis Assignment]” o Analytics Tools and Models used and results o Interpretation, Discussion, and Analysis of Findings and Results – Interpretation, Discussion, and Analysis of outcomes and results of Analytics Tools and Models used § Tip: Support your Interpretation, Discussion, and Analysis of Results with the numbers you developed in your: • Analytics Tools and Models used results • Business Analytics Case Analysis EXCEL model(s) and outcomes and results o Recommendations • 5.2 Assignment(s) 2 – Statement o Identify Business Problem - “Define Problem statement [aka Case Analysis Assignment]” o Analytics Tools and Models used and results o Interpretation, Discussion, and Analysis of Findings and Results – Interpretation, Discussion, and Analysis of outcomes and results of Analytics Tools and Models used § Tip: Support your Interpretation, Discussion, and Analysis of Results with the numbers you developed in your: • Analytics Tools and Models used results • Business Analytics Case Analysis EXCEL model(s) and outcomes and results o Recommendations • 5.n Assignment(s) n – Statement o Identify Business Problem - “Define Problem statement [aka Case Analysis Assignment]” o Analytics Tools and Models used and results o Interpretation, Discussion, and Analysis of Findings and Results – Interpretation, Discussion, and Analysis of outcomes and results of Analytics Tools and Models used § Tip: Support your Interpretation, Discussion, and Analysis of Results with the numbers you developed in your: • Analytics Tools and Models used results • Business Analytics Case Analysis EXCEL model(s) and outcomes and results o RecommenCase Analysis Background 33 The case scenario was based on Gateway Estate Lawn Equipment Co. Case Study, used for the 1997 Malcolm Baldrige National Quality Award Examiner Training course. This material is in the public domain. The database, however, was developed by the author. PLE, headquartered in St. Louis, Missouri, is a privately owned designer and producer of traditional lawn mowers used by homeowners. In the past ten years, PLE has added another key product, a medium-size diesel power lawn tractor with front and rear power takeoffs, Class I three-point hitches, four-wheel drive, power steering, and full hydraulics. This equipment is built primarily for a niche market consisting of large estates, including golf and country clubs, resorts, private estates, city parks, large commercial complexes, lawn care service providers, private homeowners with five or more acres, and government (federal, state, and local) parks, building complexes, and military bases. PLE provides most of the products to dealerships, which, in turn, sell directly to end users. PLE employs 1,660 people worldwide. About half the workforce is based in St. Louis; the remainder is split among their manufacturing plants. In the United States, the focus of sales is on the eastern seaboard, California, the Southeast, and the south central states, which have the greatest concentration of customers. Outside the United States, PLE’s sales include a European market, a growing South American market, and developing markets in the Pacific Rim and China. Both end users and dealers have been established as important customers for PLE. Collection and analysis of end-user data showed that satisfaction with the products depends on high quality, easy attachment/dismount of implements, low maintenance, price value, and service. For dealers, key requirements are high quality, parts and feature availability, rapid restock, discounts, and timeliness of support. PLE has several key suppliers: Mitsitsiu, Inc., the sole source of all diesel engines; LANTO Axles, Inc., which provides tractor axles; Schorst Fabrication, which provides subassemblies; Cuberillo, Inc, supplier of transmissions; and Specialty Machining, Inc., a supplier of precision machine parts. To help manage the company, PLE managers have developed a “balanced scorecard” of measures. These data, which are summarized shortly, are stored in the form of a Microsoft Excel workbook (Performance Lawn Equipment) accompanying this book. The database contains various measures captured on a monthly or quarterly basis and is used by various managers to evaluate business performance. Data for each of the key measures are stored in a separate worksheet. A summary of these worksheets is given next: . Dealer Satisfaction, measured on a scale of 1–5 (1=poor, 2=less than average, 3=average, 4=above average, and 5=excellent).(1=poor, 2=less than average, 3=average, 4=above average, and 5=excellenDealer Satisfaction Dealer Satisfaction Survey Scale: 0 1 2 3 4 5 Sample North America Size 2014 1 0 2 14 22 11 50 2015 0 0 2 14 20 14 50 2016 1 1 1 8 34 15 60 2017 1 2 6 12 34 45 100 2018 2 3 5 15 44 56 125 South America 2014 0 0 0 2 6 2 10 2015 0 0 0 2 6 2 10 2016 0 0 1 4 11 14 30 2017 0 1 1 3 12 33 50 2018 1 1 2 4 22 60 90 Europe 2014 0 0 1 3 7 4 15 2015 0 0 1 2 8 4 15 2016 0 0 1 2 15 7 25 2017 0 0 1 2 21 6 30 2018 0 0 1 4 17 8 30 Pacific Rim 2014 0 0 1 2 2 0 5 2015 0 0 1 1 3 0 5 2016 0 0 1 1 3 1 6 2017 0 0 0 2 5 3 10 2018 0 0 1 2 7 2 12 China 2016 0 0 0 1 0 0 1 2017 0 0 1 4 2 0 7 2018 0 0 1 5 8 2 16 End-User Satisfaction End-User Satisfaction Sample Survey Scale: 0 1 2 3 4 5 Size North America 2014 1 3 6 15 37 38 100 2015 1 2 4 18 35 40 100 2016 1 2 5 17 34 41 100 2017 0 2 4 15 33 46 100 2018 0 2 3 15 31 49 100 South America 2014 1 2 5 18 36 38 100 2015 1 3 6 17 36 37 100 2016 0 2 6 19 37 36 100 2017 0 2 5 20 37 36 100 2018 0 2 5 19 37 37 100 Europe 2014 1 2 4 21 36 36 100 2015 1 2 5 21 34 37 100 2016 1 1 4 26 37 31 100 2017 1 1 3 17 41 37 100 2018 0 1 2 19 45 33 100 Pacific Rim 2014 2 3 5 15 41 34 100 2015 1 2 7 15 41 34 100 2016 1 2 5 16 40 36 100 2017 0 2 4 17 40 37 100 2018 0 1 3 19 42 35 100 China 2016 0 3 3 6 28 10 50 2017 1 2 2 4 30 11 50 2018 0 1 1 3 31 14 50 Customer Survey Customer Survey Region Quality Ease of Use Price Service NA 4 1 3 4 NA 4 4 4 5 NA 4 5 4 3 NA 5 4 4 4 NA 5 4 5 4 NA 5 5 3 5 NA 5 4 4 2 NA 5 5 4 5 NA 4 4 4 5 NA 4 5 4 5 NA 4 5 1 4 NA 5 5 4 4 NA 5 4 3 3 NA 4 5 4 4 NA 5 4 3 5 NA 5 5 2 5 NA 5 4 2 5 NA 5 4 2 5 NA 4 5 4 4 NA 4 4 5 4 NA 4 4 2 4 NA 4 3 3 4 NA 5 5 2 5 NA 5 3 4 3 NA 5 4 4 5 NA 5 5 2 5 NA 5 5 5 3 NA 4 4 5 4 NA 5 4 4 4 NA 5 1 5 5 NA 5 4 3 5 NA 4 5 1 4 NA 4 4 3 5 NA 5 3 4 4 NA 5 5 2 4 NA 5 4 4 4 NA 5 5 4 4 NA 5 5 4 5 NA 4 3 3 5 NA 5 4 4 3 NA 5 4 3 4 NA 5 5 1 5 NA 5 4 5 4 NA 3 4 3 4 NA 5 4 2 4 NA 5 5 4 5 NA 5 5 3 4 NA 5 4 4 4 NA 5 4 4 4 NA 5 4 4 5 NA 5 4 1 4 NA 5 4 5 5 NA 5 5 3 4 NA 5 4 4 5 NA 4 3 5 5 NA 5 4 4 4 NA 5 5 5 5 NA 5 5 4 5 NA 4 4 4 4 NA 5 4 5 5 NA 4 5 5 4 NA 5 5 5 4 NA 5 5 3 5 NA 5 4 4 4 NA 5 4 5 2 NA 4 4 5 5 NA 4 4 4 5 NA 5 4 4 4 NA 5 4 3 5 NA 5 4 5 4 NA 5 5 4 5 NA 5 4 4 4 NA 5 4 5 2 NA 5 3 4 5 NA 5 4 5 5 NA 5 4 1 5 NA 4 5 3 5 NA 3 5 2 5 NA 5 5 4 4 NA 4 4 3 5 NA 3 2 4 5 NA 1 4 3 4 NA 4 5 3 5 NA 5 5 4 4 NA 4 5 5 5 NA 5 5 4 5 NA 5 5 4 4 NA 4 2 4 5 NA 5 4 5 4 NA 5 4 5 4 NA 5 5 4 3 NA 5 5 5 5 NA 4 5 5 3 NA 5 5 4 5 NA 4 4 5 5 NA 5 5 3 4 NA 4 5 2 4 NA 5 5 5 4 NA 4 5 4 3 NA 4 5 5 4 SA 5 4 3 5 SA 5 4 2