SOLUTION: Business Intelligence Application and Development

Coursework Brief 2020/21 Module name:Business Intelligence Application and DevelopmentModule code:Title of the Assignment:East Midlands Candy AssignmentThis coursework item is:SummativeThis summative coursework will be marked anonymouslyYesThe intended Learning Outcomes (LOs) that are assessed by this coursework are:LO1: Identify the required components of a BI system by systematic analysis of a perceived problem area, appraisal of available techniques and tools, and the critical evaluation of developed systems.LO2: Conceptual understanding of a range of predictive analysis techniques, critically evaluating current research and new insights.LO3: Design appropriate BI systems using appropriate BI approaches.This coursework is:IndividualThis coursework constitutes 100% to the overall module mark.Date Set:Date & Time Due: Tasks to be undertaken: See belowDeliverables to be submitted for assessment: See below.How the work will be marked: See Appendix 3Module leader/tutor name:Contact details: Case Study: East Midlands Candy East Midlands Candy (EMC) is a small local confectionary manufacturer founded in Leicester, UK in 1850. Over the years, the organisation has evolved to produce a range of sweet products, including chocolates, crisps and snacks, and a range of cakes supplied to sweet shops, vending machine companies, hotels, and cinemas. There is also a retail section which is offered through a network of branches found in towns, cities and in large suburbs throughout in the East Midlands. A new Chief executive has recently been appointed following the retirement of the previous CEO. The new senior management team is now keen to upgrade the organisations IT provision to become more market focused and efficient. As part of this initiative the management is considering setting up a new department of ‘Business Understanding’. The purpose of this department is to assist management to understand customers better and to make justified decisions on operational management. This department will undertake Business Intelligence related activities and in particular will be focused on using techniques in forecasting, and linear programming in relation to the company’s activities. Your task is to prepare a management report in which to illustrate to management how the techniques of forecasting and optimisation (linear programming), and Business Intelligence could be useful to the organisation. As management knows little of these techniques, you need to demonstrate how they will work in practice. For this purpose, data has been supplied for you to carry out some of the techniques. Requirements and Instructions The report should be broken down into three parts (Part 1 – 3). Your report should include your workings and/or spreadsheets for the practical exercises and a reference list. We will have access to your SAS BI work on the SAS server so you do not need to supply anything other than the screen shots of your SAS BI work within your report.It is expected that you will prepare and submit a comprehensive word-processed, structured, logical, technical report in the correct format.A typical report structure includes: Title page, contents, introduction, and main body of report, conclusions, recommendations, and appendix (where appropriate).Note: The title page should contain: Module code and your p-number (name optional), assignment title, deadline date, module tutor’s name. You should include your p-number in the footer of every page along with page numbers (there should be no page number displayed on the title page).Total word count: 3000 (±10%)The marking criteria are supplied Appendix 3. Part 1 Decision Making Techniques (50%) Forecasting As a consultant at East Midlands Candy, you are required to introduce and motivate for the use of Forecasting techniques by:Providing an overview of how forecasting techniques could be useful.Discussing the challenges and/or implications that East Midlands Candy could face in the application of forecasting approaches/processes?Discussing the four keys questions that management at East Midlands Candy should consider when measuring the success of their forecasting techniques. Use the following guidelines and instructions for the application of forecasting techniques:Review the data supplied in Appendix 1.Use this data to demonstrate how the different products (A, B & C) show different characteristics with regard to forecasting (Hint: identify and describe the pattern using a time seriesplot).Identify the most appropriate forecasting technique for each of the three products given and justify your choice.Give forecasts for Year 4, for each product.Critically evaluate your results highlighting whether you consider the forecasting model to be good or not (Hint: consider forecastaccuracy). (NB: Please use Microsoft Excel to support your calculations) (10 + 15 = 25 Marks) Linear Programming/LinearOptimisation Provide an overview of how optimisation and linear programming (LP) could be useful in supporting decision-making at East Midlands Candy.Discuss how optimisation mathematical modelling could be used in the area of the production/manufacturing of candy products (Hint: identify possible decision variables, results variables, and uncontrollablevariables/parameters)Use the following guidelines and instructions for the application of linear programming techniques.Review Problem Case 1 (Production) and Problem Case 2 (Staff Allocation) in Appendix 2.Formulate a Linear Programming model for:Problem Case 1 (Production)Problem Case 2 (Staff Allocation) NB: There is no requirement to solve this problem or make calculations. A model is only required, which includes decision variables, a result variable, objective, and uncontrollable variable. (5 + 5 + 15 = 25 Marks) Part 2 Business Intelligence Systems (30%) The owners of EMC have asked you to develop a Business Intelligence application for the Sales department. The Sales Department is currently split into three groups, each of which has responsibility for one customer area (retail, wholesale and grocery). The members of each team are to be provided with an Information Delivery Portal (IDP) page. The information displayed is to be relevant to each sales group i.e. it is to be filtered to display the customer group they have a responsibility for. All users can be considered low level IT users. In Section 1 of the IDP page a web report is to be displayed showing the sales history for each product group (a tab page for each year) in table form. This table should show as a minimum the sales totals for each product group for that sales group. You may choose to add additional measures. Be aware that as the designer you need to find an appropriate balance of detail for the user. In Section 2 of the IDP page, a web report is to be displayed in a graphical format. This should show sales to all customers in a selected product group. Refer to the data sets provided to identify these groups. The user should be prompted as to which product group and year they are interested in. Remember they should only see sales for their customer group. The graph format is your choice (pie chart, bar chart etc.). In section 3 of the IDP page produce a dashboard showing total sales of each product group for the current year which is 2003. Set the range based on:- Above target being +10% on 2002 sales On Target being between 90% and 110% of 2002 sales Below target being less than 90% of 2002 sales. Again the choice of gauge is yours; remember to limit the data to that sales group’s customers. You will need to manually calculate the value to enter for each range. There is no way for SAS to calculate this requirement. The data is already registered in metadata within the SAS BI suite, within the shared folder. The files you will need include – Candy_Customer, Candy_Products, Candy_Sales_History, Candy_Time_Periods and Candy_Sales_Summary. You will need to create information maps, filters and prompts as necessary to complete the tasks. To achieve a pass you will need to demonstrate an understanding of SAS techniques as we have covered in labs. To achieve a distinction level pass you will need to demonstrate your ability to produce an application tailored to non-technical user needs. Refer to the marking sheet for more detail on the marking. Include samples of your work in your report and an evaluation of your system, identifying any areas where this system could be improved – for example highlight shortcomings in the software. Part 3: Compliance (legal), Ethics, and Privacy Issues in Business Intelligence (10%) Compile a brief overview of compliance, ethics, and privacy issues that may affect East Midlands Candy and the proposed business intelligence systems. Support your overview with possible examples that apply to EMC, and the nature of its business. Report format and structure (10%) There are 10% of the marks allocated for the correct report structure and clarity of the supporting material, including layout, clarity, grammar, spelling, referencing and appropriate depth of coverage. Submit your structured word processed report. Your report should include your workings and/or spreadsheets for the practical exercises and a reference list. These could include hand written and scanned LP formulations, excel spreadsheets and a list of references used. Refer to the marking grid provided in Appendix 3 for more details. Appendix 1 Sales figures for three (3) products Sales of three (3) products have been selected for a trial of forecasting methods. Sales of the three products (in 000s) are shown in the tables below Product A: Chocolate bar YearWinterSpringSummerAutumn19.59.39.49.629.89.79.810.539.99.79.69.6 Product B: Children’s treats YearWinterSpringSummerAutumn114.231.833.06.8215.434.836.27.4314.838.241.47.6 Product C: Adult Mint bar YearWinterSpringSummerAutumn111.412.613.012.8213.814.014.815.2315.615.816.216.6 Appendix 2 Problem case 1: Production EMC produces two types of popcorn (standard and deluxe). The supply of sugar is limited to 40,000 kg a week. The standard popcorn uses 300g of sugar whereas the deluxe version uses 400g of sugar per kg. EMC also has a commitment to supply 1,000 kg of the standard popcorn to a local cinema. A final constraint on production is that EMC only has 48 litres of colouring. The standard product requires 8 millilitres per kg and the deluxe product requires 15 millilitres per kilo. EMC sells popcorn to its customers at a profit of 50p per kg of standard and 80p per kg of the deluxe. Formulate a linear programming model to maximise profit from the production/sales of popcorn. Do not attempt to solve the problem. Problem case 2: Staff Allocation The main factory at EMC operates 24 hours a day, with staff working 9-hour shifts. Not all production lines operate 24 hours. Some only operate for 9 hours and others for 18 hours each day. The demand for staff during each 3-hour period of the day is given below. Formulate a linear programming model to determine the minimum number of staff required in each 24 hour period. Do not attempt to solve the problem. Time PeriodNumber of Staff Required9:00-12:003212:00-15:002415:00-18:002018:00-21:002821:00-24:00120:00-3:0043:00-6:0026:00-9:0010 Appendix 3 Marking Scheme 0-39 Fail40-49- Fail50-59 Pass60-69 Pass Merit70-79Pass Distinction80 + DistinctionForecasting Techniques (15%)No attempt Or incorrect approach usedAn attempt to evaluate the given data. Inappropriate methodoloAppropriate evaluation of time series Appropriate methodology Forecasts produced Some minor errorsGood evaluation of time series Good methodology Forecasts produced Possibly a minor errorGood evaluation of time series Good methodology Correct Forecasts producedExcellent evaluation of time series Excellent methodology Forecasts produced at a professional levelgy used.Possibly some wholly incorrect techniques used in placesForecasting Evaluation (10%)No attempt or incorrectAn Attempt made but incorrect in several places or no application to the case study.Evaluation showing an understanding of the area of forecasting. Some errors of understanding or minimal application to the case studyGood evaluation showing a good understanding of the area of forecasting. Possibly a few errors of understanding or minimal application to the case studyGood evaluation Showing real insight into the technique applied to the case study throughoutAs before but at a professional level. Difficult to faultLinear programming Techniques (15%)No attempt Or incorrect approach usedAn attempt to evaluate the given problems. Inappropriate methodology used Possibly some wholly incorrect techniques used in placesAppropriate methodology Optimisation models created produced Some minor errorsGood methodology Optimisation models produced Possibly a minor errorGood methodology Correct LP models produced. Very minor error in formulationExcellent methodology LP models produced difficult to faultLinear Programming Evaluation (10%)No attempt or incorrectAn Attempt made but incorrect in several places or no application to the case study.Evaluation showing an understanding of the area of LP. Some errors of understanding or minimal application to the case studyGood evaluation showing a good understanding of the area of LP. Possibly a few errors of understanding or minimal application to the case studyGood evaluation Showing real insight into the technique applied to the case study throughoutAs before but at a professional level. Difficult to faultInformation Maps and Filters (5%)Not attempted or demonstrates noAttempt made to create information maps butAppropriate Information maps or Filters createdAppropriate Information maps created with sensible filters but with minorExcellent Information maps with useful fully functioning filters that are appropriate.Information maps produced to a professional levelunderstanding of thepossibly no filters oromissionsinformationineffectivemaps purposeinformationmapsWeb reports (5%)Not attempted or wholly inadequateAttempted but with major flawsReports produced with one possibly not meeting the spec or with obviousAppropriate reports produced but possibly with minor problemsExcellent reports meeting user requirements at a very high levelReports produced to a professional level demonstrating adeficiencies. This could include overlysound understanding of user needscomplexDashboards (5%)Not attempted or wholly inadequateAttempted but with major flawsDashboard produced possibly not fully meeting the spec or with obvious deficienciesAppropriate Dashboard produced but with possible minor problems. Static targetsExcellent Dashboard meeting user requirements at a very high level. Dynamic targetsDashboards produced to a professional level demonstrating a sound understanding of user needs Development of IDP (5%)Not attemptedAttempted but not correctCompleted but requires more attention to detail in layout and headings etc. May not understand different user group needs.Completed but possible minor issues in appearanceGood attention to detail in creating the pageExcellent attention to detail- extras added to make it more user friendlyEvaluation of System (10%)Not attemptedAttempt made but too superficial or shows no understanding of BI systemsA reasonable attempt made to evaluate the system and software. One area is either missing or superficialA good attempt made to evaluate the system and software. Evaluation of some areas vague or brief but most covered adequately.An excellent attempt made to evaluate the system and softwareAn excellent attempt made to evaluate the system and software. Shows evidence of an in depth understanding of the issuesCompliance (10%)Not AttemptedAttempt made but many compliance issues omittedSeveral compliance issues identified but not completeMajor issues identified and key factors highlighted in report maybe not fully applied to the case studyMajor compliance issues identified and applied to the case studyAs before but shows a level of understanding not usually expected from students at this levelReport Format and Referencing (10%)Very Poorly attemptPoorly written, unstructure d, no illustration( s), none or entirely inappropri ate referencin gUnderstandable, little structure, no contents list and not spell checked, no or questionable illustration(s), adequate coverage of sources, lacking sufficient detail in referencingReasonably written, adequate structure, contents list or spell checked, some illustration(s), adequate coverage of sources, lacking sufficient detail in referencingWell written, good structure, contents list and spell checked, appropriate illustration(s), Appendices through coverage of sources with sufficient detail in referencingVery well written, excellent structure, contents list and spell checked, informative illustration(s) with comprehensive, informative and relevant referencing Tasks to be undertaken: See belowDeliverables to be submitted for assessment: See below.How the work will be marked: See Appendix 3Module leader/tutor name:Contact details: Case Study: East Midlands Candy East Midlands Candy (EMC) is a small local confectionary manufacturer founded in Leicester, UK in 1850. Over the years, the organisation has evolved to produce a range of sweet products, including chocolates, crisps and snacks, and a range of cakes supplied to sweet shops, vending machine companies, hotels, and cinemas. There is also a retail section which is offered through a network of branches found in towns, cities and in large suburbs throughout in the East Midlands. A new Chief executive has recently been appointed following the retirement of the previous CEO. The new senior management team is now keen to upgrade the organisations IT provision to become more market focused and efficient. As part of this initiative the management is considering setting up a new department of ‘Business Understanding’. The purpose of this department is to assist management to understand customers better and to make justified decisions on operational management. This department will undertake Business Intelligence related activities and in particular will be focused on using techniques in forecasting, and linear programming in relation to the company’s activities. Your task is to prepare a management report in which to illustrate to management how the techniques of forecasting and optimisation (linear programming), and Business Intelligence could be useful to the organisation. As management knows little of these techniques, you need to demonstrate how they will work in practice. For this purpose, data has been supplied for you to carry out some of the techniques. Requirements and Instructions The report should be broken down into three parts (Part 1 – 3). Your report should include your workings and/or spreadsheets for the practical exercises and a reference list. We will have access to your SAS BI work on the SAS server so you do not need to supply anything other than the screen shots of your SAS BI work within your report.It is expected that you will prepare and submit a comprehensive word-processed, structured, logical, technical report in the correct format.A typical report structure includes: Title page, contents, introduction, and main body of report, conclusions, recommendations, and appendix (where appropriate).Note: The title page should contain: Module code and your p-number (name optional), assignment title, deadline date, module tutor’s name. You should include your p-number in the footer of every page along with page numbers (there should be no page number displayed on the title page).Total word count: 3000 (±10%)The marking criteria are supplied Appendix 3. Part 1 Decision Making Techniques (50%) Forecasting As a consultant at East Midlands Candy, you are required to introduce and motivate for the use of Forecasting techniques by:Providing an overview of how forecasting techniques could be useful.Discussing the challenges and/or implications that East Midlands Candy could face in the application of forecasting approaches/processes?Discussing the four keys questions that management at East Midlands Candy should consider when measuring the success of their forecasting techniques. Use the following guidelines and instructions for the application of forecasting techniques:Review the data supplied in Appendix 1.Use this data to demonstrate how the different products (A, B & C) show different characteristics with regard to forecasting (Hint: identify and describe the pattern using a time seriesplot).Identify the most appropriate forecasting technique for each of the three products given and justify your choice.Give forecasts for Year 4, for each product.Critically evaluate your results highlighting whether you consider the forecasting model to be good or not (Hint: consider forecastaccuracy). (NB: Please use Microsoft Excel to support your calculations) (10 + 15 = 25 Marks) Linear Programming/LinearOptimisation Provide an overview of how optimisation and linear programming (LP) could be useful in supporting decision-making at East Midlands Candy.Discuss how optimisation mathematical modelling could be used in the area of the production/manufacturing of candy products (Hint: identify possible decision variables, results variables, and uncontrollablevariables/parameters)Use the following guidelines and instructions for the application of linear programming techniques.Review Problem Case 1 (Production) and Problem Case 2 (Staff Allocation) in Appendix 2.Formulate a Linear Programming model for:Problem Case 1 (Production)Problem Case 2 (Staff Allocation) NB: There is no requirement to solve this problem or make calculations. A model is only required, which includes decision variables, a result variable, objective, and uncontrollable variable. (5 + 5 + 15 = 25 Marks) Part 2 Business Intelligence Systems (30%) The owners of EMC have asked you to develop a Business Intelligence application for the Sales department. The Sales Department is currently split into three groups, each of which has responsibility for one customer area (retail, wholesale and grocery). The members of each team are to be provided with an Information Delivery Portal (IDP) page. The information displayed is to be relevant to each sales group i.e. it is to be filtered to display the customer group they have a responsibility for. All users can be considered low level IT users. In Section 1 of the IDP page a web report is to be displayed showing the sales history for each product group (a tab page for each year) in table form. This table should show as a minimum the sales totals for each product group for that sales group. You may choose to add additional measures. Be aware that as the designer you need to find an appropriate balance of detail for the user. In Section 2 of the IDP page, a web report is to be displayed in a graphical format. This should show sales to all customers in a selected product group. Refer to the data sets provided to identify these groups. The user should be prompted as to which product group and year they are interested in. Remember they should only see sales for their customer group. The graph format is your choice (pie chart, bar chart etc.). In section 3 of the IDP page produce a dashboard showing total sales of each product group for the current year which is 2003. Set the range based on:- Above target being +10% on 2002 sales On Target being between 90% and 110% of 2002 sales Below target being less than 90% of 2002 sales. Again the choice of gauge is yours; remember to limit the data to that sales group’s customers. You will need to manually calculate the value to enter for each range. There is no way for SAS to calculate this requirement. The data is already registered in metadata within the SAS BI suite, within the shared folder. The files you will need include – Candy_Customer, Candy_Products, Candy_Sales_History, Candy_Time_Periods and Candy_Sales_Summary. You will need to create information maps, filters and prompts as necessary to complete the tasks. To achieve a pass you will need to demonstrate an understanding of SAS techniques as we have covered in labs. To achieve a distinction level pass you will need to demonstrate your ability to produce an application tailored to non-technical user needs. Refer to the marking sheet for more detail on the marking. Include samples of your work in your report and an evaluation of your system, identifying any areas where this system could be improved – for example highlight shortcomings in the software. Part 3: Compliance (legal), Ethics, and Privacy Issues in Business Intelligence (10%) Compile a brief overview of compliance, ethics, and privacy issues that may affect East Midlands Candy and the proposed business intelligence systems. Support your overview with possible examples that apply to EMC, and the nature of its business. Report format and structure (10%) There are 10% of the marks allocated for the correct report structure and clarity of the supporting material, including layout, clarity, grammar, spelling, referencing and appropriate depth of coverage. Submit your structured word processed report. Your report should include your workings and/or spreadsheets for the practical exercises and a reference list. These could include hand written and scanned LP formulations, excel spreadsheets and a list of references used. Refer to the marking grid provided in Appendix 3 for more details. Appendix 1 Sales figures for three (3) products Sales of three (3) products have been selected for a trial of forecasting methods. Sales of the three products (in 000s) are shown in the tables below Product A: Chocolate bar YearWinterSpringSummerAutumn19.59.39.49.629.89.79.810.539.99.79.69.6 Product B: Children’s treats YearWinterSpringSummerAutumn114.231.833.06.8215.434.836.27.4314.838.241.47.6 Product C: Adult Mint bar YearWinterSpringSummerAutumn111.412.613.012.8213.814.014.815.2315.615.816.216.6 Appendix 2 Problem case 1: Production EMC produces two types of popcorn (standard and deluxe). The supply of sugar is limited to 40,000 kg a week. The standard popcorn uses 300g of sugar whereas the deluxe version uses 400g of sugar per kg. EMC also has a commitment to supply 1,000 kg of the standard popcorn to a local cinema. A final constraint on production is that EMC only has 48 litres of colouring. The standard product requires 8 millilitres per kg and the deluxe product requires 15 millilitres per kilo. EMC sells popcorn to its customers at a profit of 50p per kg of standard and 80p per kg of the deluxe. Formulate a linear programming model to maximise profit from the production/sales of popcorn. Do not attempt to solve the problem. Problem case 2: Staff Allocation The main factory at EMC operates 24 hours a day, with staff working 9-hour shifts. Not all production lines operate 24 hours. Some only operate for 9 hours and others for 18 hours each day. The demand for staff during each 3-hour period of the day is given below. Formulate a linear programming model to determine the minimum number of staff required in each 24 hour period. Do not attempt to solve the problem. Time PeriodNumber of Staff Required9:00-12:003212:00-15:002415:00-18:002018:00-21:002821:00-24:00120:00-3:0043:00-6:0026:00-9:0010 Appendix 3 Marking Scheme 0-39 Fail40-49- Fail50-59 Pass60-69 Pass Merit70-79Pass Distinction80 + DistinctionForecasting Techniques (15%)No attempt Or incorrect approach usedAn attempt to evaluate the given data. Inappropriate methodoloAppropriate evaluation of time series Appropriate methodology Forecasts produced Some minor errorsGood evaluation of time series Good methodology Forecasts produced Possibly a minor errorGood evaluation of time series Good methodology Correct Forecasts producedExcellent evaluation of time series Excellent methodology Forecasts produced at a professional levelgy used.Possibly some wholly incorrect techniques used in placesForecasting Evaluation (10%)No attempt or incorrectAn Attempt made but incorrect in several places or no application to the case study.Evaluation showing an understanding of the area of forecasting. Some errors of understanding or minimal application to the case studyGood evaluation showing a good understanding of the area of forecasting. Possibly a few errors of understanding or minimal application to the case studyGood evaluation Showing real insight into the technique applied to the case study throughoutAs before but at a professional level. Difficult to faultLinear programming Techniques (15%)No attempt Or incorrect approach usedAn attempt to evaluate the given problems. Inappropriate methodology used Possibly some wholly incorrect techniques used in placesAppropriate methodology Optimisation models created produced Some minor errorsGood methodology Optimisation models produced Possibly a minor errorGood methodology Correct LP models produced. Very minor error in formulationExcellent methodology LP models produced difficult to faultLinear Programming Evaluation (10%)No attempt or incorrectAn Attempt made but incorrect in several places or no application to the case study.Evaluation showing an understanding of the area of LP. Some errors of understanding or minimal application to the case studyGood evaluation showing a good understanding of the area of LP. Possibly a few errors of understanding or minimal application to the case studyGood evaluation Showing real insight into the technique applied to the case study throughoutAs before but at a professional level. Difficult to faultInformation Maps and Filters (5%)Not attempted or demonstrates noAttempt made to create information maps butAppropriate Information maps or Filters createdAppropriate Information maps created with sensible filters but with minorExcellent Information maps with useful fully functioning filters that are appropriate.Information maps produced to a professional levelunderstanding of thepossibly no filters oromissionsinformationineffectivemaps purposeinformationmapsWeb reports (5%)Not attempted or wholly inadequateAttempted but with major flawsReports produced with one possibly not meeting the spec or with obviousAppropriate reports produced but possibly with minor problemsExcellent reports meeting user requirements at a very high levelReports produced to a professional level demonstrating adeficiencies. This could include overlysound understanding of user needscomplexDashboards (5%)Not attempted or wholly inadequateAttempted but with major flawsDashboard produced possibly not fully meeting the spec or with obvious deficienciesAppropriate Dashboard produced but with possible minor problems. Static targetsExcellent Dashboard meeting user requirements at a very high level. Dynamic targetsDashboards produced to a professional level demonstrating a sound understanding of user needs Development of IDP (5%)Not attemptedAttempted but not correctCompleted but requires more attention to detail in layout and headings etc. May not understand different user group needs.Completed but possible minor issues in appearanceGood attention to detail in creating the pageExcellent attention to detail- extras added to make it more user friendlyEvaluation of System (10%)Not attemptedAttempt made but too superficial or shows no understanding of BI systemsA reasonable attempt made to evaluate the system and software. One area is either missing or superficialA good attempt made to evaluate the system and software. Evaluation of some areas vague or brief but most covered adequately.An excellent attempt made to evaluate the system and softwareAn excellent attempt made to evaluate the system and software. Shows evidence of an in depth understanding of the issuesCompliance (10%)Not AttemptedAttempt made but many compliance issues omittedSeveral compliance issues identified but not completeMajor issues identified and key factors highlighted in report maybe not fully applied to the case studyMajor compliance issues identified and applied to the case studyAs before but shows a level of understanding not usually expected from students at this levelReport Format and Referencing (10%)Very Poorly attemptPoorly written, unstructure d, no illustration( s), none or entirely inappropri ate referencin gUnderstandable, little structure, no contents list and not spell checked, no or questionable illustration(s), adequate coverage of sources, lacking sufficient detail in referencingReasonably written, adequate structure, contents list or spell checked, some illustration(s), adequate coverage of sources, lacking sufficient detail in referencingWell written, good structure, contents list and spell checked, appropriate illustration(s), Appendices through coverage of sources with sufficient detail in referencingVery well written, excellent structure, contents list and spell checked, informative illustration(s) with comprehensive, informative and relevant referencing