Introduction
In 2014, General Electric began its digital transformation journey by investing in its IT system. However, challenges stemming from the company’s massiveness led to the decision to use cloud services, an example of a shadow IT project. As a result, the firm chose Amazon Web Services (AWS) as its preferred choice of a cloud service provider to more than 2,000 apps and services (Matthews, 2019). The move has enabled the company's IT team to concentrate its resources on innovation, rather than on building and running data centers. While the project was beneficial in promoting employee effectiveness and efficiency, employees' anonymized usage of different cloud services has resulted in a significant rise in IT costs. For instance, employees in the company use approximately 50 different file-sharing services, potentially impeding collaboration between employees.
Proposed Information System
The firm can reduce issues related to shadow IT projects by standardizing enterprise license for a maximum of 3 services for every function. By implementing this type of information system, GE can promote collaboration among employees and reduce licensing costs arising (Zota & Fratila, 2014). Introducing standardization on cloud services across the organization will significantly enhance security and compliance among employees. Overall, the proposed information system will improve collaboration among employees, reduce licensing costs, enhance security, and promote compliance to organizational policy.
For the proposed IS to perform the mentioned functions, its architecture must be changed. Standardizing the file-sharing process at GE can lead to a change in the will to review the information being shared and uploaded in the cloud. As a result, only three applications will be chosen to facilitate file sharing across the firm, whereas other file sharing services will be blocked entirely (Zota & Fratila, 2014). Analytics application software will be used to find the three most popular cloud services for file sharing among the ones currently in use. Furthermore, the security application software will allow the IT department to prevent sensitive data such as employee health information and intellectual property (IP) from being shared in shadow IT file-sharing applications.
Figure 1. Standard steps for cloud services adoption (Zota & Fratila, 2014)
Functions Important to Business
File sharing is a crucial function in GE's business. Numerous users exchange information to facilitate business processes such as procurement, payments, employee compensation, and performance management. The current information systems involve the use of many cloud services to share files. Each user utilizes cloud services that work for them as long as their licenses are paid. As mentioned earlier, this impedes collaboration among users, security, compliance, and increases costs. Additionally, blocking some cloud services to avoid this problem led to users searching for lesser-known cloud services, making it harder for the firm to regulate cloud services. Standardizing the cloud services used for various services reduces the anonymous usage of cloud services paid by the company, thereby scaling down the use of shadow IT in file-sharing processes and other business functions.
Data Management
An autonomous database is considered a suitable choice of data management practice for GE. Autonomous databases are based in the cloud, but they utilize artificial intelligence and machine learning to automate tasks related to data management, including backing up databases, performing security checks, and performance tuning (Knauer, Nikiforow, & Wagener, 2020). Because of GE's massive size, the autonomous database will likely reduce complexity, probability of human error, higher reliability and security of the database, lower costs, and enhanced operational efficiency. Adopting an autonomous database will also facilitate flexibility according to business needs, such that the firm can scale down or up relatively fast and cost-effectively. Therefore, data will be reviewed for compliance before it can be shared, while backups will be done automatically at a specific time of the day.
Data Types
The proposed information system includes several types of data, including Big data, time-stamped data, real-time data, and structured data. Big data will include the overall data produced by the information system, that does fit into the standard database for analysis and processing (Knauer, Nikiforow, & Wagener, 2020). Structured data, on the other hand, will include information on products, customers, or connected assets across the firm. The system will also contain time-stamped data, which comprises behavioral data with time-ordering definitions of the sequence of its capture or collection. Real-time data will capture cloud services usage, thereby allowing the IT department to determine the popular applications and further standardization with the growth of popularity of one or two apps among the chosen three.
Storage Methods
Establishing the most suitable data storage methods is vital to the effectiveness of an information system. Public cloud remains the primary choice of data storage for data generated in the proposed information system. Nevertheless, it has several drawbacks, particularly the security of sensitive data due to the open nature of the public cloud environment (Hart et al., 2016). Therefore, a private cloud may be more appropriate for use with sensitive data only. The encryption protocols used in the virtualized data center offer the company far higher levels of security to the sensitive data. Thus, a multi-cloud system will be advocated for use with the proposed information system.
Data Quality
Data quality in the proposed information system will be defined by the accuracy, completeness, timeliness, and consistency in terms of fulfilling the organization’s needs, including operations, planning, and decision-making. The accuracy of data will be measured by determining the ratio of data to errors, which allows tracking known errors relative to the available data set (Knauer, Nikiforow, & Wagener, 2020). On the other hand, consistency will be ensured by verifying that there is no conflict between two or more data values retrieved from separate data sets. So, to ensure completeness, data will be evaluated by establishing whether the data entry is full or not. The timeliness of data will be measured by the data time-to-value metric, which assesses the availability and accessibility of information. As a result of using an autonomous database, the cost and maintenance of the database are set to improve data quality, given that AI and machine learning will perform the evaluations and provide feedback for further actions.
The transition of System Functions
As mentioned earlier, the current information system involves many unapproved cloud services to perform organizational functions. An example of file-sharing services was given, where users in the GE were found to use more than 50 cloud services for this function. Because of this, the security of sensitive corporate data is reduced, low compliance of cloud service usage is on the rise, and collaboration among employees is impeded. The new information system is set to lessen these problems by introducing the standardization of cloud services used for every specific function in the organization, including file sharing. Therefore, the transition of system functions to the new information system will primarily be a scale-down of shadow IT activities and is expected to improve the security of sensitive data and promote collaboration and compliance among employees.
Evidence of Feasibility
The limitation of cloud services to three per specific function, as a standardization strategy, has shown promising results in terms of cost. A majority of businesses rarely take time to determine which applications and cloud services work for them before migrating their data operations to a cloud provider. As a result, the firms end up paying for extensive cloud services that allow unapproved services to perform organizational works. Because of this, approximately 40% of total IT spending in a company goes to shadow IT activities (McAfee, 2020). Standardizing cloud services reduces the number of different services being used for a specific function, reducing its licensing costs and the overall spend on cloud services. Moreover, it results in consistent business processes and information in the long-term.
References
Hart, E., Barmby, P., LeBauer, D., Michonneau, F., Mount, S., & Mulrooney, P. et al. (2016). Ten Simple Rules for Digital Data Storage. PLOS Computational Biology, 12(10), e1005097. https://doi.org/10.1371/journal.pcbi.1005097
Knauer, T., Nikiforow, N., & Wagener, S. (2020). Determinants of information system quality and data quality in management accounting. Journal of Management Control, 31(1-2), 97-121. https://doi.org/10.1007/s00187-020-00296-y
Matthews, K. (2019). 6 Big Companies That Succeeded with Cloud Computing. Smart Data Collective. Retrieved from: https://www.smartdatacollective.com/6-big-companies-that-succeeded-with-cloud-computing/
McAfee. (2020). What is Shadow IT? McAfee. Retrieved from: https://www.skyhighnetworks.com/cloud-security-university/what-is-shadow-it/
Zota, R., & Fratila, L. (2014). Cloud Standardization: Consistent Business Processes and Information. Informatica Economica, 17(3/2013), 137-147. https://doi.org/10.12948/issn14531305/17.3.2013.12
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