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MIS771 Descriptive Statistics And Visualisation

tag 0 Download 8 Pages / 1,943 Words tag 22-11-2020
  • Course Code: MIS771
  • University: Deakin Business School
    icon is not sponsored or endorsed by this college or university

  • Country: Australia


Case Study (Background to AusPaper) 

AusPaper, a subsidery of Pinnon Paper Industries, is an Australian company with a long history in local manufacturing of paper products. In 2013 only, AusPaper produced 619,000 tonnes of paper products, and sold more than 690,000 tonnes of products to local and overseas markets. They export their products to over 75 countries in Asia, USA, Europe, Middle East, the Indian subcontinent, Latin America and Africa.

AusPaper sells paper products to two market segments: the newspaper industy (e.g. Australian Finacial Review, Herald Sun etc.) and the magazine industry (e.g. Mens’ Style Magazine, Homes and Gardens etc.). Also these products are sold to these market segments either directly to the customer or indirectly through a broker.

Despite their successful operations and solid financial turn-overs over the last two decade, AusPaper is forecasting a major shift in business climate within the next seven years. This is a result of a change in end-consumers preferences (i.e., readers’ preference to access newspapers, magazines online or via e- readers, and social media). Now more than ever, AusPaper management feels the need to ensure a strong customer base and ideally a strong strategic alliance with their clients in newspaper and magazine industry. In addition, they are planning to put in place a formal procedure to be able to project future financial turnovers using historical data.

Consequently, AusPaper has approached ANALYTICS7 (a Market Research Company) and asked them to conduct a large-scale survey of their clients to better understand the characteristics of AusPaper customers, their perceptions of the company, and the likelihood of customers building long-term strategic alliance with AusPaper.

Data Collection Process (Conducted by ANALYTICS7) 

To address AusPaper concerns, ANALYTICS7 has contacted purchasing managers of firms buying from Auspaper and encouraged them to participate in an online survey. The collected data are then supplemented by other information compiled and stored in AusPaper’s data warehouse and accessible through its decision support system.

Primary Database 

The primary databse consists of 200 observations on 18 separate variables. Two types of information are accessible in this database. The first type of information is perceptions of AusPaper’s performance on 13 attributes. Purchasing managers of firms buying from AusPaper were asked to rate the company on each of these 13 attributes using a 0 – 10 scale, with 10 being “Excellent” and 0 is being “Poor”. The second type of information relates to purchase outcomes and business relationships (e.g., satisfaction with AusPaper and whether the purchasing firm would consider strategic alliance / partnership with AusPaper). A third type of information is available from AusPaper’s data warehouse and includes information such as size of customer and length of purchase relationship, as well as quarterly turnover of AusPaper operations. A complete listing of variables, their definitions, and an explanation of their coding are provided in file.

Your Role as an ANALYTICS7 Data Analyst Intern 

You are a master of business analytics student doing an interenship at ANALYTICS7. The research team manager (Hugo Barra, with PhD in Data Science and a Master Degree in Digital Marketing) has asked you to lead the data analysis process for AusPaper project and directly report the results to him. You and Hugo just finished a meeting wherein he briefed you on key purposes of AusPaper research project.

Hugo explained that an important prerequisite in building a strategic alliance in a B2B environment is “customer satisfaction” with a firm’s operations. Therefore, the first goal is to identify key factors that predict customer satisfaction with past purchases from AusPaper. He is also interested in gaining deeper insights into factors that predict the “likelihood of AusPaper customers building strategic alliance” with the firm. The final analytics goal is constructing a forecasting model to predict AusPaper’s turnover in the upcoming three quarters of 2017. From these understandings, Hugo and consequently AusPaper will be in a good position to develop plans for the next financial year.

In addition to briefing you about key research questions, Hugo also allocated relevant research tasks and explained his expectations from your analysis. Minutes of this meeting are available on the next page.

Now, your job is to review and complete the allocated tasks as per this document.

Task 1

Providing an overall summary of two outcome (dependent) variables of interest: One variable captures the extent of satisfaction with previous purchases from AusPaper. The other one indicates whether a client perceives his/her firm would engage in strategic alliance or partnership with AusPaper.

Task 2.1

Identifying 15 factors (from AusPaper_Data) that may influence customer satisfaction with

An appropriate statistical technique could be used here to identify a list of predictors that could be included in the regression model.

Task 2.2

Building and finalising a model (Model building process) to predict customer satisfaction with

Task 2.3

Hugo has done a separate analysis and found that the depth and breadth of AusPaper ‘product line’ is a significant predictor of ‘customer satisfaction’. In line with his findings, prior research shows that the strength of this relationship may vary according to ‘customer location’. That is, customers from global markets have needs that are more diverse compared to those from a specific region such as ANz.

Thus, the relationship between ‘product line’ diversification and ‘customer satisfaction’ should be more prominent for customers in global markets (i.e. outside ANZ region). Your task here is to test Hugo’s assumption by modelling an interaction effect between the above-mentioned independent variables and ‘customer satisfaction’.

Task 3.1

Building and finalising a model (through a model building process) to predict the “likelihood of customers developing strategic alliance/partnership” with AusPaper.Hugo has already done an initial analysis for this task. Based on his analysis, Hugo has narrowed down the key predictors of “customers likelihood to build a strategic alliance/partnership” to the following:

Product Quality, Product Line, Personnel Image, Price Flexibility, and Competitive Pricing

Your job now is to continue his work by finalising a predictive model of key factors that influence the “likelihood of building a strategic alliance/partnership”.Hugo would like to gain a deeper understanding of customers’ likelihood for building strategic alliance/partnership with AusPaper. He is specifically interested in understanding the probability of having strategic alliance with AusPaper for customers who meet the following criteria:

a. Feel neutral (i.e. score of 5 on the relevant scales) towards AusPapers’ image and its product
b. Varying levels of perception towards product quality (i.e., scores from 1 to 10) and price flexibility (scores of 0, 5, and 10).

Hugo believes that ‘price flexibility’ and ‘product quality’ would define AusPaper’s success in building strategic alliance with its customers. Therefore, it is important for AusPaper to know how flexible its sales representatives should be in negotiating prices on the one hand, and how much effort should be put in improving perceptions of product quality in order to increase the probability of building strategic alliance.

Accordingly, your job is to visualise the predicted probability of building strategic alliance with AusPaper for customers with varying levels of ‘product quality’, and ‘product flexibility’ perceptions and fixed perception towards ‘product line’ diversity and personnel ‘image’.

Task 4

Developing a time-series model to forecast AusPaper financial turnover in the next 3

It is your job to decide which time-series model is most appropriate in this scenario.

Task 5

Produce a written report detailing ALL aspects of your analysis. Your report should be as detailed as possible and should describe ALL key outputs of your analysis.
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