Big Data Case Study: Strategic Planning For RTR Company

Question

Task:
In this assessment you will have to research a small case study and you will need to apply your knowledge to identify the main issues, prioritise, provide insights and to discuss alternatives. You must write a Big Data Case Study Report about your company discussing the strategic plan of an organization. To present a case study based on the selected organization’s current analytics strategy and your recommended strategy. Identify a key business initiative for your organization, something the business is trying to accomplish over the next 9 to 12 months. It might be something like improve customer retention, optimize customer acquisition, reduce customer churn, optimize predictive maintenance, reduce revenue theft, and so on.

Brainstorm and write down what (1) customer, (2) product, and (3) operational insights your organization would like to uncover in order to support the targeted business initiative. Start by capturing the different types of descriptive, predictive, and prescriptive questions you'd like to answer about the targeted business initiative. Tip: Don't worry about whether or not you have the data sources you need to derive the insights you want (yet).

Write down data sources that might be useful in uncovering those key insights. Look both internally and externally for interesting data sources that might be useful. Tip: Think outside the box and imagine that you could access any data source in the world. Be analytical within your report and examine key terms and theoretical relationships in depth.

Answer

Introduction to Big Data Case Study
Data is one of the most crucial assets associated with the business firms in the present era. This is because of the increase in the use of the digital systems and applications. These systems use and process increased amount of the data sets. Many of the business decision are based on these data sets with execution of the data-related operations. The organizations that lag the data handling and management capabilities are suffering due to such limitations and may experience significant concerns in the years to come. The organizations shall innovate and implement the improved data analytics and management capabilities to efficiently manage the information set [1].

Data analytics is a brand of data science that deals with the management and analysis of huge chunks of data to identify the specific patterns and trends. Big Data technology is used to analyse the huge data sets and is combined with Business Intelligence (BI) concepts for effective analytics.

The report is developed for RTR Company to determine the Big Data usage and potential by the business firm.

RTR Company – Organization Overview
Rent the Runway, RTR is the company selected to develop the case study report. The organization is a fashion company that was incepted in 2009 and rents designer clothes and accessories to women and girls. The organization was co-founded by Jennifer Hyman and Jennifer Fleiss and now has direct partnership with the designers [2]. If the customer likes specific designer wear but cannot afford it then RTR is a good choice to wear the clothes and accessories on rent. As recorded in 2018, the company had nine million members and had over $100 Million in revenue. The organization has its stores both offline and on the online portals [3].

Problems and Issues
RTR Company is looking to develop the customer profiles based on the concept of perfect dress. The idea is to understand the customer preferences and demands for the dresses that they opt to determine the specific factors considered. These factors decide the rent or don’t-rent decision for the customers. The perfect dress profiles will enable the customers to use the feature of try and buy and they will be able to view their preferred products online.

The issue is that the organization offers more than 500 designer brands to the unlimited customers and around 350 brands to the update members. The choices and preferences of these customers vary [4]. It is not possible to manually interact and understand the requirements of the customers. The advanced analytics tools are useful in making sure that the customer demands are identified to determine the concept of a perfect dress. It will be useful in the promotion of sales and returns for the organization.

Business Insights
Whenever a new strategy is adopted or launched by a business organization, there are several aspects associated with the concept. The customer preferences and demands need to be determined and understood. It is also necessary that the product details are effectively analysed. The analysis from the operations aspect is also crucial. The combination of all the three can be useful in obtaining business insights.

Customer Insights
Jennifer Hymen, one of the co-founders of the RTR Company believes that the organization can achieve $100 Billion in revenues in the next five years [5]. One of the most critical aspects to achieve the same is to understand the demands and preferences of the customers. The idea of coming up with perfect dress profiles can be successful only when the concept of perfect dress is analysed and understood from the customers’ perspective. The following questions shall be asked from the customer to determine the customer’s viewpoint and preferences. These questions shall be asked from women and girls to gain insights to their idea of a perfect dress.

Product Insights
The product in this case is the customer profiles to be developed based on the idea of a perfect dress. The customers will access their online accounts and will be presented with the customized options based on the perfect dress criteria. These will be developed based on the measurements, preferences, and choices provided by the customer along with the ongoing fashion trends [7]. The implementation of such an idea will be performed by the technology experts. The insights shall be obtained on the product to determine the feasibility of the implementation.

Operational Insights
Operational insights shall be obtained on the business idea to make sure that it has the operational feasibility attached with it.

Analysing the Issues
Big Data analytics is being used by the RTR Company in many of the business operations and activities. However, there are a few issues that may be associated with the use of the technology in the proposed business idea. Also, the idea of a perfect dress includes numerous variables that may increase the complexity levels.

There are numerous customers associated with the business firms. These customers vary in terms of the age group, work profile, standard of living, etc. These factors can have major influences in the customer purchase power and preferences. There are over 500 brands that the RTR Company is associated with. With these many choices, it is certain that the choices of the customers will vary [10].

The use of the Big Data technologies can be ineffective and inadequate with the insufficient data sets. The large volumes of data will be necessary so that the preferences and patterns can be identified accordingly. The large-scale analysis will be effective with the involvement of massive data pieces [11].

Possible Alternatives
The issues illustrated above can be resolved by considering and including the response of the customers along with obtaining the product insights and operational insights. These will enable the RTR Company to understand the use and validity of the business idea. The business insights will also be obtained based on the collective information gathering and analysis [12].

The shirt-term goals defined for the organization is the determination of the customer preferences and characteristics associated with the idea of a perfect dress. Based on these factors, the profiles and the sales strategy of the organization will be developed. The advanced data analytics will provide the ability to recognize the patterns and trends. The involvement of insufficient data will result in the inaccurate analytics and the inferences made will also be inaccurate.

There are various sources of data that can be used and targeted by the business firms. Social media platforms are significant data sources that shall be used to gather the data sets. The existing customers and the potential customers of the organization are active on the social media platforms. These platforms can provide the organization will elaborate understanding of the customer preferences, fashion trends, and the customer demands [13].

Resources and Timeframe
Big Data tools, such as Hadoop will be necessary to manage the huge volumes of information and for the advanced analytics of the data sets. The information will be gathered from a variety of sources and all of these varied data sets will be included in the Big Data tools for analysis. The human resources will also be involved in the project. The Data Engineers and Data Scientists along with the Data Analysts will be involved in the process of gathering, analysis, and extraction of the data [14].

The overall duration for the project will be 8 months. Monitoring and review procedures will be essential to achieve the successful outcomes. These shall include the security and privacy checks and compliance verifications. These will be necessary to ensure the misuse of the data gathered is prevented. The actual and estimated values will also be mapped in the monitoring processes to make sure that there are no gaps.

Recommendations & Conclusion
RTR Company shall consider and follow the recommendations listed below.

• The collective analysis from the customer insights, product insights, and operational insights shall be used so that the adequate business decisions are made
• Compliance checks and verifications shall focus on the legal compliance, security compliance, and ethical compliance. Any of the gaps or loopholes shall be reported immediately
• Trainings on the Big Data tools and platforms shall be enabled and provided to the resources engaged in the RTR project. Skill-assessment of the resources shall be performed before allocating the responsibilities to the resources.

Data analytics is being used by the business firms all across the globe. There are numerous benefits provided by Big Data and the analytical tools to the business firms. RTR Company shall also make use of the Big Data tools to carry out the advanced data analysis. The business idea of identifying a perfect dress for the customers can be successful only when the detailed insights to the customer requirements and viewpoints are obtained. The other aspects, such as product insights and operations insights will also be crucial to make the business decisions. The determination of the preferences and trends will be possible only when the organization succeeded in collecting adequate information and applied advanced analytics to recognize the associated patterns.

References
[1] C. Catlett and R. Ghani, “Big Data for Social Good,” Big Data, vol. 3, no. 1, pp. 1–2, Mar. 2015, doi: 10.1089/big.2015.1530.

[2] Y. Du, “Data Analytics and Applications in the Fashion Industry: Six Innovative Cases,” 2019. Accessed: Jul. 01, 2020. [Online]. Available: https://digitalcommons.uri.edu/cgi/viewcontent.cgi?article=1007&context=tmd_major_papers.

[3] T. Hartung, “Making Big Sense From Big Data,” Frontiers in Big Data, vol. 1, Oct. 2018, doi: 10.3389/fdata.2018.00005.

[4]C. L. Remondino, “Fashion Industry as a Big Data Enterprise for Sustainability,” Current Trends in Fashion Technology & Textile Engineering, vol. 3, no. 4, Mar. 2018, doi: 10.19080/ctftte.2018.03.555616.

[5]S. S. Kim and Y. S. Kim, “Study on Recognitions of Luxury Brands by Using Social Big Data,” Fashion & Textile Research Journal, vol. 18, no. 1, pp. 1–14, Feb. 2016, doi: 10.5805/sfti.2016.18.1.1.

[6]J.-Y. DAI, “The Application of Big Data in the Fashion Industry,” DEStech Transactions on Social Science, Education and Human Science, no. esem, Jun. 2018, doi: 10.12783/dtssehs/esem2018/23880.

[7]V. Quevedo, “Fashion is Big Business,” Journal of Textile Science & Fashion Technology, vol. 4, no. 4, Feb. 2020, doi: 10.33552/jtsft.2020.04.000595.

[8]M. DuBreuil and S. Lu, “Traditional vs. big-data fashion trend forecasting: an examination using WGSN and EDITED,” International Journal of Fashion Design, Technology and Education, vol. 13, no. 1, pp. 68–77, Jan. 2020, doi: 10.1080/17543266.2020.1732482.

[9]T. Hartung, “Making Big Sense From Big Data,” Frontiers in Big Data, vol. 1, Oct. 2018, doi: 10.3389/fdata.2018.00005.

[10]N. Verma, D. Malhotra, and J. Singh, “Big data analytics for retail industry using MapReduce-Apriori framework,” Journal of Management Analytics, pp. 1–19, Feb. 2020, doi: 10.1080/23270012.2020.1728403.

[11]A. Hussain and A. Roy, “The emerging era of Big Data Analytics,” Big Data Analytics, vol. 1, no. 1, Jul. 2016, doi: 10.1186/s41044-016-0004-2.

[12]S. S. Kumar and Ms. V. Kirthika, “Big Data Analytics Architecture and Challenges, Issues of Big Data Analytics,” International Journal of Trend in Scientific Research and Development, vol. Volume-1, no. Issue-6, pp. 669–673, Oct. 2017, doi: 10.31142/ijtsrd4673.