MSc Management Data Driven Decisions for Business Assignment Sample

MSc Management Data Driven Decisions for Business Assignment Sample

Introduction

Data analytics is the process of extracting insights from raw facts that also includes the collection, organizing, and storage of data. It simply comprises the techniques, tools, and processes to analyse the company or business data.

With the help of data analytics, companies can simply transform their businesses and can become more advanced and innovative, and develop forward-thinking while decision-making (Olabode et. al. 2022). http://MSc Management Data Driven Decisions for Business Assignment SampleThis report is based on the case study of two companies such as BIJ and WFTT.

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WFTT is a company that provides consultancy services to other companies related to the business. So, this report discusses the data analysis service provided by WFTT to BIJ to help BIJ in analysing its market data and information and also helps BIJ to improve its business decisions as well. The market evaluated by WFTT is Japan, the US, and the UK from 2018-2020.

MSc Management Data Driven Decisions for Business Assignment Sample
Figure 1: Data Analytics Workflow.

(ICARUS, 2019).

Context

With the help of data analytics companies across the world, can examine a range of data and information to evaluate hidden patterns, correlations, and other insights.

Thus, in the current business scenario, data analytics have proven to be an effective tool for analysing and solving complex data, allowing companies to make better business decisions (Xing et. al. 2022). http://MSc Management Data Driven Decisions for Business Assignment SampleSo, WFTT with the help of data analytics tools can collect and analyse the market and sales data of BIJ from different markets such as the US, Japan, and the UK for the years 2018-2020. In addition to that, WFTT with the assist of statistical analytics gathers records, examines, and measures the outcome of records to solve BIJ’s business problems.

BIJ operates in the United Kingdom, and on the behalf of BIJ, WFTT collects the UK market data from the years 2018 to 2020 and also analyses the sales record of Bangles Company. The sales values and income volumes of Bangles for the year 2018 are £1,933,006 and 2303.

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Additionally, the income values and income volumes for of the 12 months 2019 are £1,794,417 and 2247, and, sooner or later, the income values and sales volumes of the BIJ for the yr 2020 are £2,259,426 and 13974 respectively. The marketplace facts gathered by Wood from the Trees for the three consecutive years can also be presented in the table beneath.

MSc Management Data Driven Decisions for Business Assignment Sample

Table 1: Market data Analysis of the UK.

Thus, the data collected by WFTT on behalf of BIJ can help BIJ to make proper business decisions and determine and examine the current as well as future market trends, and can even determine the profitability ratios of the business.

Data related to sales values and sales volumes collected by WFTT can also be present in the form of charts as shown beneath.

MSc Management Data Driven Decisions for Business Assignment Sample
MSc Management Data Driven Decisions for Business Assignment Sample

It can be assessed from above charts that a huge market trend can be identified within the sales of Bangles Company in the UK markets. In addition to that, Bangles International Jewellery has been successful in 2020 as the company has managed to enhance its sales values and sales volume in the same year.

However, it may additionally be analysed that one of the principal functions at the back of the excessive sales within the 12 months of 2020 turned into the growing popularity of e-commerce shopping developments in the country because of Covid-19.

Also, another reason identified was that BIJ has effectively organized marketing campaigns in the UK and has been able to influence people. Thus, this has helped the company to gain more sales within the country. On the other hand, BIJ Company in the year 2019 suffered a huge decline in sales due to the pandemic.

Plan

Various tools of project management are utilized by numerous businesses across the globe to complete their projects correctly. In the same manner, Wood from the Trees used a project management tool to gather and analyse data and information for BIJ Company.

The project management tool used by WTFF helps the company to make effective use of data analytics and manage the project effectively. Project management tools can be categorized into three different categories such as agile, PRINCE2, and waterfall model (Gregory et. al. 2022). http://MSc Management Data Driven Decisions for Business Assignment SampleWFTT adopted the agile project management model to analyse the data of Bangles to execute the project.

WFTT used the agile project management model to collect and analyse the market data of BIJ to allow the company to come up with better business decisions and improve its sales as well across different markets.

The agile model has allowed WFTT to collect BIJ’s market data from different such as the US, Japan, and the UK for 3 consecutive years from 2018 to 2020 to provide business solutions. WFTT needs to follow 5 different project management phases to execute and complete the project effectively. These five different phases act as a roadmap for WFTT to execute the project.

On the other hand, the agile model offers flexibility to the company so that it makes required adjustments during the project (Sharma et. al. 2022).http://MSc Management Data Driven Decisions for Business Assignment Sample Thus, it will allow the company to make improvements regularly, and this can enhance the project results or outcomes and allow BIJ to improve its business decisions as well.

By following all the phases effectively, WFTT with the help of the agile model can generate accurate results and can make valid business decisions, and even can determine and measure market changes and trends.

MSc Management Data Driven Decisions for Business Assignment Sample
Figure 2: Agile Model.

(Source: JavaTpoint, 2022).

BIJ’s Key performance indicators

GMROI (Gross Margin Return on Investment): GMROI is a type of KPI that tells BIJ Company how much profit the company has made against the company that has invested in the inventory stock.

There are different industry standards for most of the niche markets, thus making this metric a tangible way to see if the company is hitting set benchmarks (Tableau, 2022).http://MSc Management Data Driven Decisions for Business Assignment Sample Besides, it also provided information to the company on which items or products are giving the most value and which product categories need to be replaced or switched out.

It can be calculated by the formula: Average Sales / Average Inventory Cost x Gross Margin.

Sell-through Rate: It is another KPI used by BIJ Company to evaluate the performance of the company in different markets that the company is operating. It is the percentage or rate of units sold by the company compared to the number of units that are available to be sold in the market (Okunev, 2022). http://MSc Management Data Driven Decisions for Business Assignment Sample

Sell-through is considered the most effective KPI, as it helps the company to understand how quickly a product is sold in the market, how often an item needs to be re-ordered, and which item the company can promote over others.

It can be calculated by the formula: Number of units sold / Original Inventory x 100.

Data issues and remedies

During the data analysis, WFTT encountered some issues, and it has caused some hindrances to the company to execute its project effectively. On the other hand, the tool adopted by WFTT to analyse the market data of Bangles Company for three consecutive years in the US, Japan, and the UK is MS Excel.

WFTT compiled the data in the form of columns and rows to determine sales values, sales volumes, and monthly, and year-to-year sales (Chen et. al. 2022).http://MSc Management Data Driven Decisions for Business Assignment Sample Some of the issues encountered by WFTT are that while analysing the data, for example, the USA markets were spelled as the US and the USA both, creating confusion for users, and this made the analysis of the data quite difficult.

Another issue encountered by WFTT is that the company has to collect the market data for three consecutive years, that too from three different markets such as the US, Japan, and the UK. This made the collection of data more complex and hectic for analysts and made data organizing and compiling of data more complex for WFTT.

WFTT developed an effective solution to deal with issues related to data analysis. WFTT used a filter option in the spreadsheet to filter the data and get or retrieve particular data from a particular market and a particular country.

So, the filter option made the analytics job quite easier for the company (Perdana et. al. 2022).http://MSc Management Data Driven Decisions for Business Assignment Sample For instance, the company made use of a filter option to analyse market data of the US for the year 2019 by picking the data from a specific market (Japanese market) and a definite year (2019).http://MSc Management Data Driven Decisions for Business Assignment Sample

Data analysis and Commentary

WFTT collected and analysed the marketing data record of BIJ within the UK markets from the years 2018 to 2020. In addition to that, WFTT also gathered and analysed the market data from the other two countries, the US and Japan, for three consecutive years, 2018-2020 by using a filter option.

Based on the market analysis done by WFTT, it can be said that the sales values and volumes of Bangles Company in Japan for the year 2018 are £6,121,066 and 4168, and sales values and income volume for the year 2019 are £6,002,612 and 4085. Similarly, the sales values and income volume for the yr 2020 are £4,132,431 and 27825.

Thus, it can be said that Bangles has faced a drop in the sale values and income volume in the year 2019 in Japan. The major reason identified is the pandemic. Due to the pandemic, all the retail companies across the world suffered a loss. Due to the pandemic, customers shifted their preferences to online shopping, and this resulted in the growing popularity of online shopping trends which can be another reason for the decline in sales in the UK and the US.

Also, BIJ shifted its focus towards the US and the UK markets completely in 2019, and this can also be another reason for the decline in sales of BIJ in 2019 in the Japanese markets. Table 2 below describes the market analysis of BIJ in the US, Japan, and the UK.

MSc Management Data Driven Decisions for Business Assignment Sample

Table 2: UK, US, and Japan market data analysis.

Similarly, WFTT also analysed the product sales information of Bangles Company in different markets. Based on the product analysis, it can be said that Bangles is offering numerous product categories to its customers in different markets. WFTT analysed the product categories of Bangles to determine the success rate of the company.

On the other hand, this type of analysis has helped BIJ in determining the most profitable product category of the company and the least profitable product category. Moreover, the sale done by Bangles Company across various markets reflects the organisational objective as well as business goals.

So, it can be said that the sale of the goods is directly proportional to the growth of an organisation. Table below gives the proper insights of product categories of BIJ Company.

MSc Management Data Driven Decisions for Business Assignment Sample

Table 3: Analysis of BIJ’s product categories.

Data Charting and Commentary

The income values and volumes of BIJ are re-presented by Wood from the Trees in the form of diagrams  due to effective analysis of Bangles Company’s product categories in addition to sub-merchandise.

WFTT analysed and presented the data in graphical form so that readers can develop a proper understanding of sales values and sales volumes of BIJ Company.

MSc Management Data Driven Decisions for Business Assignment Sample

Figure 3: Sales Value Chart.

MSc Management Data Driven Decisions for Business Assignment Sample

Figure 4: Sales Volume Chart.

Interpretation

  • It is interpreted that the income values and income volumes records gathered by means of Wood from the Trees by combining market records of 3 distinct markets such as the US, Japan, and the UK for three different years such as 2018, 2019, and 2020. So, this represents the sales data of Bangles Company across all of its product categories.
  • It can also be interpreted from figures 3 and 4 that those bracelets are the products of Bangles Company that has resulted in a huge profits for Bangles out of all of its product categories. Moreover, bracelets have allowed the company to enhance its sales volumes and sales values.
  • From the above two charts, it can also be interpreted that the entire product categories of Bangles Company have made an effective contribution in increasing the sales volumes and income values of Bangles. It can also be assessed that there is very few difference between the income volumes and values of Bangle’s overall product categories.

The UK, the US, and Japanese marketing campaigns – Comparisons

MSc Management Data Driven Decisions for Business Assignment Sample

Figure 5: UK marketing campaign impact.

MSc Management Data Driven Decisions for Business Assignment Sample

Figure 6: Japan marketing campaign impact.

MSc Management Data Driven Decisions for Business Assignment Sample

Figure 7: USA marketing campaign impact.

Interpretation

  • It is interpreted from above figures (5-7) that the US is the only country where marketing campaigns have proved to be the most influential to people. It can be assessed that more than 91% of the US people get impacted by advertisemnts. In this case, it will be quite easy for Bangles to attract and influence the US people.
  • It can also be interpreted from charts 5, 6, and 7 that in the UK 77% of the UK public gets imapcted by advertisements, but this percentage is fourteen percent less in comparison to the US. In this case, BIJ has to make minimum efforts to attract people from the UK to its products through marketing campaigns.
  • It can also be interpreted that Japan is the country that has been least affected by marketing campaigns. In this case, BIJ may have to face some difficulties in attracting Japanese people to its products.

Conclusion and Recommendations

It can be concluded that data analytics can prove to be an effective tool to analyse and measure data results and can help businesses to make better business decisions.

Data analytics can also help BIJ Company to access, analyse, and measure the current and future business trends, thus can solve business problems as well. It can also be concluded that the bracelets product category has enhanced the sales of the company due to the pandemic, there has been a drop in the income value and volume of Bangles.

The present report also concludes that with effective use of data analytics, the company can enhance its business sale over the time.

Recommendations

  • It is recommended to that board that the firm should use advanced data analytics tools to analyse sales volumes and values (Jiwat and Zhang, 2022). This can help the company to improve its business.
  • The board can also make use of the advanced techhnologies such as sales tracking system to track various types of sales records in different markets.
  • In additon to that, the board must prepare proper and aggressive advertisement strategies and tools to attract Japanese people. This can be done by using social media marketing tools.

Possible actions

To augment the income values and volumes, Bangles can use econometric analysis. As per the situation, econometric analysis can probe to an effective tool to analyse and monitor business data and information (Lv and Li, 2021). Moreover, econometric analysis can allow BIJ to analyse data directly and can improve the decision-making process of the company.

Advantages: Can permit the business enterprise to analyse raw records without delay without using any form of filter alternatives. It can prove a time saver for the company.

Disadvantages: It can prove costly for the company besides, the company needs to follow a series of steps to execute the project. This can enhance the complexity and error-making chances as well.

 

 

References

Chen, C., Choi, H. S., and Ractham, P. (2022). Data, attitudinal and organizational determinants of big data analytics systems use. Cogent Business and Management9(1), 2043535.

Jiwat, R., and Zhang, Z. L. (2022). Adopting big data analytics (BDA) in business-to-business (B2B) organizations–Development of a model of needs. Journal of Engineering and Technology Management63, 101676.

Lv, Z., and Li, S. (2021). How financial development affects CO2 emissions: a spatial econometric analysis. Journal of Environmental Management277, 111397.

Okunev, R. (2022). Putting It All Together: An Email Campaign. In Analytics for Retail (pp. 115-133). Apress, Berkeley, CA.

Olabode, O. E., Boso, N., Hultman, M., and Leonidou, C. N. (2022). Big data analytics capability and market performance: The roles of disruptive business models and competitive intensity. Journal of Business Research139, 1218-1230.

Perdana, A., Lee, H. H., Koh, S., and Arisandi, D. (2022). Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance. International Journal of Accounting Information Systems44, 100547.

Sharma, M., Luthra, S., Joshi, S., and Joshi, H. (2022). Challenges to agile project management during COVID-19 pandemic: an emerging economy perspective. Operations Management Research, 1-14.

Xing, Y., Wang, X., Qiu, C., Li, Y., and He, W. (2022). Research on opinion polarization by big data analytics capabilities in online social networks. Technology in Society68, 101902.
Gregory, P., Strode, D. E., Sharp, H., and Barroca, L. (2022). An onboarding model for integrating newcomers into agile project teams. Information and Software Technology143, 106792.

ICARUS. (2019). Aviation Data Analytics Perspectives in ICARUS. [Online]. Available Through: <https://www.icarus2020.aero/aviation-data-analytics-perspectives-in-icarus/>.

JavaTpoint. (2022). Agile Model. [Online]. Available Through: <https://www.javatpoint.com/software-engineering-agile-model>.

Tableau. (2022). 8 Important Metrics for Retail Industry KPIs. [Online]. Available Through: <https://www.tableau.com/learn/articles/retail-industry-metrics-kpis>.

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