This report provides performance analysis of merchandisemade by Newcastle United Football Club (NUFC) with different products. As NUFCneeds to have sustainable business and growth prospect, it is important toanalyze its performance in terms of revenue generation. Dolles and Soderman(2012) explored the need for having a framework to analyze and gain competitiveadvantage in terms of promoting football club.
Ularu et al. (2012) stated thatdata analytics can help in improving understanding of the business and improveit further. Data analytics provides necessary intelligence to make gooddecisions.
Vamplew et al. (n.d) explored the usage of football grounds andpromoting the game besides revenues. Merchandise is an important activity ofNUFC with respect to different sport products. Sapana, Padro and Turmo (2007)studied football organizations and promoting business by performing datamining. Data mining can help in extracting business trends or patterns that canlead to leveraging of sustainable business. This report provides data analyticsand the insights related to business intelligence (BI) that can help in makingexpert decisions by NUFC. Excel is the spreadsheet software used to analyze thedata of merchandise of different products promoted by NUFC.
The data analyticspertaining to merchandise data is used to have strategic decision making.Forpreparing the Dashboard,I had to collect the data of the merchandise for thelast three years(ie.,2014-2016).I collected data and shortlisted it,which isrelevent to the products,channels and years.After the collection of data,I hadchoosen different charts which could be best to represent my dataeffectively.For representing the data on Dashboard,I have used different chartslike Area charts,Bar charts,Line charts and column charts.
The followingsections provide more information on the business intelligence and criticalevaluation of the BI extracted using data analytics in Excel ans SAS. Theoreticalframework is important to have systematic approach in completing a project.Framework provides building blocks that can be used to provide better possiblesolution.
Youssef (2014) explored a framework that can be used to haveframework that can help in data analytics in making good decisions. Usefulinsights can be obtained using data analytics. Augustine (2014) studied andprovided the advantages of data analytics. Data analytics are thus used toanalyze merchandise data of NUFC inorder to gain business intelligence. it is evident that the data theory andconceptual model are explored to make a formal model.
The tools and prototypesthat can help in making empirical data are used and then data analytics areexplored in order to have research findings. Koop (2005) studied the analysis ofeconomic data. Economic data needs to be analyzed in order to have correlationshidden data. In this report, data analyticswith merchandise data of NUFC is made and the business intelligence is studiedfor making recommendations. The data is analyzed in terms of revenues, theimportance of location, gender, product and loyalty points. The data issubjected to data analytics in Excel.
Excel is one of the spreadsheet softwarethat can be used to store data in tabular format and analyze it in order to havetrends in the data. The rationale behind the usage of Excel is its simplicityin the data storage and analysis. The columns of input data are type, product,price, quantity, discount, sales and loyalty points. Different types ofproducts are used for data analysis. The quantity of sales, discounts andlocation of sales besides the year of sales are considered for analysis.Loyalty points mean the points are given to regular customers. For example, theperson purchased products multiple times the points are given to customers.Functions are used in excel to solve the problems relating data analytics.
The concept of pivot table andsliceres are used in order to have better data analysis. Pivot table providesthe summary of data that can help in making useful information in the form ofgraphs. The graphical representation of data can help in understanding thedynamics of NUFC performance in terms of merchandising football products. Theproducts are selling by the NUFC in different sources like Amazon,Sportsdirect, Sportsdirect, Website and Store. To getting the most revenues andleast revenues through the products first we are finding the total revenues bythe each product. For that actually we are using the functions to calculate thetotal revenues of each product.
Critical Analysis andJustification of Data Analytics and BI:Data collection and data analyticsare very useful with Excel software. As explored by Barga et al. (n.d) manyproblems can be solved using spreadsheet. There are different ways of gettingdata analytics from Excel file. Berhe et al. (2007) opined that regressionanalysis is widely used in data analytics. Standard software programs likeExcel are used in order to have data analysis.
Multivariate and singlevariateanalysis can help in making data analysis and obtain business intelligence.Phillips-Wren et al. (2015) specified the data and its importance as it can beused to derive business intelligence. That is the reason, the merchandise dataof NUFC is analyzed and BI is achieved in this report.
Revenue in different locations:From the figure 1, It is evidentthat the revenues related to football products are more in England. The resultsreveal the trends in the sales of different products in different locations.The least performance and highest performance are observed.As shown in thefigure revenue gradually decreases from 2014 to 2016 in all locations except inEngland.The most of the revenue is generated only through the shoes andfootball products in all locations.
Finally,from the SAS and Excel reportsrevenue(sales) comes from the products footballs and shoes.In the same fashion,year wise quantity of sales of different products is shown in Figure 2.Year wise sales through differentchannels:As shown in Figure 2, it isevident that different channels are used to sell products. The EBay channel isable to perform well in selling products.
The least performance is recordedwith web site. With respect to the price of the products, the price of theproducts sold in stores is more. Similarly,from the SAS and Excel the sales aremore in the Ebay compare to the other channels in all the threeyears(2014-2016).
In the same way the price of the products in differentchannels is shown in Figure 3.Price of products throughdifferent means:From the Figure 3,it is clear thatdifferent channels have different prices for the products.Prices are high instore and are low on website for all the products.
The Amazon and Ebay showssimilar trends in pricing the products.Consequently,SAS and Excel reports alsoshows the similar pricing for the products in different channels.Also thediscounts given by various channels for diffrerent years are shwon in theFigure 4.Discount of products in differentchannels of revenue generation:It is evident that there are morediscounts given to the channel web site. The products that are offered at leastand highest discounts are presented. This can help in understanding the BI andthe correlation among the least performing products in different locations andmaking well informed decisions.Loyality points through differentchannels:Figure 5,shows the loyality pointsgiven to the both male and female by different channels from 2014 to 2016.
Thehighest loyality points was received by the male than the female from all thechannels.Overall,Website stays top by providing the highest loyality points forboth gendre in all the years.Where as,Amazon stays at the bottom for the Femaleand sportsdirect for the Male.As well as, the Excel and SAS reports alsodepicts the same trend for the different channels. Dataanalysis is made on merchandise data of NUFC. The data analytics are made forhaving comprehensive business intelligence. A dashboard is made in order tohave the information of business performance.
The dashboard can help inunderstanding the performance just by a glance. The information thus obtainedfrom business analysis can help in making correct business decisions. There aremany aspects of business data that is used to have analysis. The dataconsidered include revenues, products, promotions, locations, revenuegeneration channels, price and discounts. Revenue in different locations isanalyzed and understood that the revenue at different locations is differentfor different products. Loyalty points are also considered at differentlocations and years for different channels of making revenues. There was yearwise quantity of sales through different channels of making sales.
There isanalysis of price of different channels as well. The price of stores is morefor different products. The sales of products are more with e-Commerceapplications. The results of analysis reveal that more sales are made andrevenues are generated through e-Commerce applications. The rationale behindthis might be the time and geographical convenience and the reduced pricing. SAS Report Analysis:With the use of relevant raw-dataavailable from the dashboard,SAS reports represent the mean,median and the keyperformance Indicators of the sales,prices,channels and quantity of theproducts.
It also depicts the mininmum value,maximum value,and the standard meanof each of the performance indicators.From the Figure 1,it clearly shows the sales are highin the Northern Island compared to the other locations.In the Figure 2,thesales of the shoes are higher compared to the other products in allchannels.The Figure 3,represents the Loyalty points given by channels are highin website during the three year period.In the line of issues identifiedabove,SAS report provides the graphical representation of the sales of the NUFCMerchandise in different channels for the last three years(2014-2016).
This brings us to theunderstanding of the most of the revenue is generated from England from all thechannels and also depicts shoes and football products were the highest soldproducts in all the three years. NUFC has getting the revenuesthrough different sports products related to football. They used differentresources to sell the products. The resources are Amazon,Ebay, Sportsdirect,Website and Store. The products names are Bags/Hold alls, Football, Gloves,Headwear and Shoes. From this conceptual framework we analyzed and provided inthe report. The data is synthesized in order to solve business analytics on thedata.
Excel is used to store data in tabular format. The data set helped tofind the objectives. The objectives are finding most revenue through theproducts and find the least revenue through the products. The results ofanalysis reveal the performance of NUFC in terms of getting revenues throughthe selling of products.
From the dataset we are getting the values of eachproduct selling in the different sources like Amazon,Ebay, Sportsdirect,Websiteand Store. From these values we are getting more revenue selling shoes and lessrevenue getting by selling of headwear. The most revenue i.e.
485850 is gettingby NUFC to selling the product shoes. And the least revenue i.e.
2500 isgetting by NUFC to selling the product Headwear. From that most and least revenues in the dataanalytics problem the following are taken as recommendations.1. Focus on Bags/Hold alls whichare getting most revenue to selling to compare the others. From this productNUFC getting more revenue in future.2. At the same time to follow thesame standards to continue the revenues through the selling of the productshoes as performing best as of now.
3. Take measures to improve theother products as well. The product of Headwear getting less revenue to comparethe others as of now. So that put the most efforts and concentration to improvethe revenues.4. From this way we find thesolutions for data analytics problems.
5. It is better to promote salesby identifying the locations at which sales are low and the customer loyaltyneeds to be considered for the same.