Your Will Select A Big Data Analytics Project That Is Introduced To An Organization Of Your Choice
Running head: BIG DATA ANALYTICS 1
BIG DATA ANALYTICS 2
Big Data Analytics
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Background Information
Starbucks Corporation is company that is leading in the roasting, retailing and marketing of specialty coffee in the world. It was established in 1971 as a small store and has now developed into a gourmet coffee giant of the 21st century (Voigt, Buliga & Michl, 2017). It operates in most countries of the world with the distinguishing factor being the different coffee flavors it gives to its customers. This company has made coffee to become more than just a beverage but rather it is a way of life. There are at least 7,300 coffee kiosks in the United States only. The company operates in other countries such as Japan, Australia, New Zealand, and China. Apart from the coffee kiosks, the company also sells its products through mail-order and online (Garthwaite et al., 2017). Therefore, it is a supplier to restaurants, businesses as well as institutions. Starbucks though the partnership with Kraft Foods Inc. has been able to sell whole bean coffee into the clubs and merchandise stores.
Problems/Opportunities of Data Analytics
Starbucks is a company that has mounds of data that must be well analyzed and leveraged to improve customer satisfaction. The company also has about 90 million transactions every week and over 25,000 stores worldwide (Snell et al., 2017). This leads to problems such as ineffective decision making, inefficient resource allocation and problems with establishment of the kiosks at the right and strategic positions. As such, effective data analysis helps to improve the performance of the company. Some of the opportunities presented by data analytics adoption include;
Personalized Customer Attention
Starbucks uses available data to make important decisions such as the location of the stores. However, to maintain the competitive advantage in the industry, it is important that the company uses real time data to identify the changes in customer requirements and make changes accordingly (Bradlow et al., 2017). Programs such as the loyalty card help to identify what needs to be changed to suit the needs of the people depending on the region. Such, this is an opportunity to maximize on the profits.
Optimization of Menu Design
The data obtained from all the stores all over the world is important in helping Starbucksalign the product line with the consumer preferences. For example, the development of new product lines such as the bottled beverages and k-cups, data from the stores and the customer market is important in making the decision on which product should be created(Bradlow et al., 2017). Depending with the characteristics that the customers show from the data collected, Starbucks was able to develop the k-cups which have unsweetened tea because from the data most customers do not sweeten their tea. Through data analytics, Starbucks has also the opportunity to develop digital menu boards and hence be able to increase its sales (Sanders, 2016). This is because these menu boards are able to feature different products depending with the weather.
Impact of the Problem
Lack of effective analysis and proper decision making has been costing the company financial losses. This is because without use of data, the decisions made are less effective. This has led to closure of some of the stores as the company was unable to meet the obligations in certain areas due to declining profits. This led to some of the stores making losses and hence inefficiency in internationalization of the firm. However, using big data analytics, the company can be able to introduce new services in the industry. This involves introducing the products different from those that the customers use (Tian, 2017). As such, it will be able to improve its revenues as well as overall position in the industry.
Performance Metrics
Key performance indicators are the measurable values that show how effective a company is able to achieve its business objectives. Therefore, they work in hand with set goals or strategies. Key performance indicators are the signs which show whether the business is moving to the right direction or not. There are various indicators which Starbucks will use. First of all is the economic performance indicator (Heo, 2017). This is an indicator which shows the performance of the company as compared to others in the industry. One of them is the profit and loss. Secondly is the environmental performance indicator. It shows how well the company is in managing the environment while at the same time making maximum benefits. One exampleisdetermination of the percentage of materials used and recycled. The third indicator is the labor practices and decent work performance(Heo, 2017). This is related to the benefits of the employees. Salary considerations as well as providing a good environment for the employees to work will be some of the measures to be considered.
Big Data Tool
Apache Hadoop a tool that is capable of handling large amounts of data as well as having a high capability of large scale data processing. It is a framework that is able to run on any existing data center. It is also capable of running on a cloud infrastructure(Iqbal&Soomro, 2015). This is a tool that consists of Hadoop Distributed File System which is a distributed file compatible with a very high scale bandwidth (Iqbal&Soomro, 2015). The second characteristic is MapReduce which is a programming model for processing big data. Yarn is a platform that is used for managing and scheduling the resources in the Hadoop infrastructure. The last feature is the libraries which are used to help other modules and enable them work with Hadoop.
Data Requirements
Starbucks is a company that is constantly growing. Therefore, data to be collected include the information regarding the customers. This includes customer tastes as well as the distribution in various parts of the world. The second type of data that is required is information on location and resources. This will enable the organization to effectively manage all the operations. Data on financial performance is also important. This information is found from every day operations of the different stores. Therefore, the company needs to have the right form of record keeping for obtaining all the information. The online platforms such as customer response are also a good source of data. Data collection can be made from the customer royalty rewards, customer feedback as well as the online marketing analytics. Some of the data can be obtained from in-store traffic monitoring as well as transactional data. One of the methods that can be used to check the integrity of the large files of data is the hash tree (Liu et al., 2015). This is a method whereby a hash tree is made with different leaf nodes with each representing a hash value that is computed for each data block in a file. This uses the root node and the internal nodes. To verify the integrity, the data owner computes the root hash with data received and makes a comparison with the root hash stored. When there is equality in the two then data integrity is assured.
Gaps to Bridge
For effective implementation of big data analytics project in Starbucks, it is necessary to seek the help of the experts. Some of the vendors to work with in this project include those supplying the software for Hadoop. Secondly, information needs to be stored in the cloud and hence vendors are needed. It is also important to incorporate vendors in the supply of infrastructure such as the data center.
In this case, the best project management approach is hybrid. This is a model that is sequential in the initial stages and later on becomes iterative. This model is good for this project because it provides for the creation of a disciplined timeline for alignment of the client and gives time for iteration and refining (Conforto&Amaral, 2016). Hybrid project management allows for an independent management structure whereby work can be carried out in an independent space. Secondly, the project manager is capable to make decisions related to the project with the help of the other members in the team (Morozov, Kalnichenko&Liubyma, 2016). Hybrid project management also has the project manager cares about the front end of the project while the others are concerned about the backend of the project.
Conclusion
In conclusion, Starbucks is a company that has years of experience in coffee business. The company has been selling through stores and open kiosks all over the world. Starbucks has a log of data and information that when well organized can be used for the benefit of the company. This data can be obtained from the online data analytics, third party marketing and customer response. This data can be analyzed and used to develop new products which are not part of what is already in the market. This can be achieved using Apache Hadoop data analytics tool. Management processes on the other hand will be carried out using the hybrid management which allows for sequential and iterative aspects of a project.
References
Bradlow, E. T., Gangwar, M., Kopalle, P., &Voleti, S. (2017). The role of big data and predictive analytics in retailing. Journal of Retailing, 93(1), 79-95.
Conforto, E. C., &Amaral, D. C. (2016). Agile project management and stage-gate model—A hybrid framework for technology-based companies. Journal of Engineering and Technology Management, 40, 1-14.
Garthwaite, C., Busse, M., Brown, J., &Merkley, G. (2017). Starbucks: A story of growth. Kellogg School of Management Cases, 1-20.
Heo, C. Y. (2017). New performance indicators for restaurant revenue management: ProPASH and ProPASM. International Journal of Hospitality Management, 61, 1-3.
Iqbal, M. H., &Soomro, T. R. (2015). Big data analysis: Apache storm perspective. International journal of computer trends and technology, 19(1), 9-14.
Liu, C., Yang, C., Zhang, X., & Chen, J. (2015). External integrity verification for outsourced big data in cloud and IoT: A big picture. Future generation computer systems, 49, 58-67.
Morozov, V., Kalnichenko, O., &Liubyma, I. (2016, February). The models of procurement management and information technologies for hybrid project management. In 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET) (pp. 609-612).IEEE.
Sanders, N. R. (2016).How to use big data to drive your supply chain. California Management Review, 58(3), 26-48.
Snell, S. A., Lemley, A., Snell, S. A., & Yemen, G. (2017). Starbucks: Schultz Back in the Brew. Darden Business Publishing Cases, 1-18.
Tian, X. (2017). Big data and knowledge management: a case of déjà vu or back to the future?. Journal of Knowledge Management, 21(1), 113-131.
Voigt, K. I., Buliga, O., &Michl, K. (2017).Globalizing Coffee Culture: The Case of Starbucks. In Business Model Pioneers(pp. 41-53). Springer, Cham.