Essay Sample on Influence of Big Data and Analytics on Management Control Systems

Published: 2022-11-16 05:17:09
Essay Sample on Influence of Big Data and Analytics on Management Control Systems
Type of paper:  Dissertation
Categories: Management Statistics
Pages: 7
Wordcount: 1754 words
15 min read
143 views

Big data involves the use of more advanced methods of data analysis to come up with technical means of coming up with an understanding of abroad spectrum in a manner that would have otherwise not been assessable through the use of conventional methods. The use of Big Data continues to be a common trend among business organisations in the modern context. The relevance of Big Data today may vary from that of the future mostly because the methods and tools to be used in the latter case may be advanced from the former. Unlike the traditional age, stakeholders of an organisation can now be able to capture relevant information from an operational environment through faster and more effective means. Organisations have opted to make use of such systems owing to its universality which allows for an organisation to benefit from interacting with other organisations. In recent decades, the capability of IT applications has since increased as a result of attributable information technologies. For this study, the researcher made use of semi-structured interviews as the primary data collection tool. The tool was essential as it allowed the researcher to actively interact with the study's respondents in the Big Data industry. It also allowed them to share insights about the dynamics in the sector. This study used semi-structured interviews as the primary data collection tool. For this study, a qualitative data analysis method was used.

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The modern corporate world is characterized by the availability of an enormous amount of data. A considerable sum of this data may be directly or indirectly linked with elements including decision-making and policy formulation in fields such as supply chains, industrial enterprises, service and manufacturing processes. The availability of such data may be used in customer management, macroeconomic development, and in the generation of commodity markets. As such, a majority of business activities in the modern world are being undertaken in a big data environmental perspective. The sole introduction of big data in the business world has played a significant role in the sole survival of a majority of companies operating today. Big data may therefore be defined as the use of computational methods to analyse large quantities of data in an effort to identify the associations, trends, and patterns of distinct human interactions and behaviour. Big data allows organizations to explore available information in an attempt to enable the management to effectively enhance its performance growth. Big Data analytics allows for faster analysis of complex data from a variety of sources with the aim of enabling an organisation to gain a competitive advantage in the highly flooded economic markets.

In the current context, a majority of researchers have only been able to pursue the theoretical bit of the topic on Big Data. As time advances, the need for a different type of information may increase or merely depreciate depending on its usefulness to the operations of the company. Accompanied with other IT advancements such as cloud computing, the introduction of the internet, and development of gadgets such as smartphones and computers, the generation and accumulation of data has become an easy task among business operators in the modern context. Big Data and analytics also allow key decision makers in an organisation to be in a position where they are likely to take advantage of the various positives resulting from the availability of previous and current data from customer behaviour, processes of production, and the supply chain of goods and services produced (Lee 2014, 5). Although this s the case, a majority of organisations today tend to focus on the analysis of data affecting the internal environment of a business. These include inventory, shipment, sales among many more data types. Since the introduction of Big Data, organisations can now be able to also analyse external data such as those involving customer behaviour and the trends in the supply chain of the business.

The introduction section of the study covers vital areas including the definition of the research problem, the identification of the objective of the research, the specification of the research question, clarification of the environment where the study was conducted, and the determination of the organisation of the overall study. Today, alternative data such as purchase data may be analysed together with other data type hence making it to become richer and of increased relevance to a given organization unlike the use of traditional data analysis methods. These issues are discussed in the consequent section.

Problem Statement

Changes in the Information Technology (IT) field have eased how modern business operations may be carried out among various entrepreneurs. The advancements in the information technology would have allowed for the introduction of efficient computer systems which are heavily depended upon in the modern corporate world. A majority of businesses today often rely on the use of computerised systems in carrying out key operations owing to its high level of convenience and flexibility. Additionally, organisations have opted to make use of such systems due to its universality which allows for an organisation to benefit from interacting with other organisations.

Regardless of the advancements that have taken place along the years, most companies have often found it difficult to effectively make use of data that is in its exposure. The reason for this has mainly been as a result of the fact that as most organizations continue to operate, the resultant data also tends to increase as well. In such a scenario, organizations in question lack necessary means of exploiting historical information in the day-to-day running of the organization. When companies continue to store piles of data, chances are high that they may lack relevant means of utilizing it in the future. The reason behind this is because most organizational setups lack the expertise and adequate technology to enable them to sort and characterise the data at their disposal so as to enhance overall means of enhancing overall performance in an organization.

Conventional methods of data analysis such as the use of excel sheets have been used for ages now. Although such a method has proven to be of great significance in the past, it is essential to note that such a method continues to lack relevance with the advancement of time. The reason for this has mainly resulted from the fact that such computer software lack relevant tools and functions that are likely to analyse huge loads of data (Choi 2017, 87). As stated earlier, most organizations tend to hoard data dating back since their inception. In such a case, the management of such a company may find it particularly difficult to effectively analyse such data through the use of mere conventional computer software. In such a case, the organization in question may be required to come up with relevant means of ensuring that it is able to fully explore the available data to its fullest potential as doing so may enable it to enjoy benefits such as gaining a greater competitive edge amongst its peers, better decision making procedures and better understanding of consumer behaviour which in turn may lead to the growth of a business.

Although numerous advancements have been made in the information technology sector, Big Data is arguably one of the most recent improvement to revolutionize the business world. A significant portion of businesses across the world has since seen the need to adopt its use today. It is quite reasonable to come across its (Big Data) use in firms in the modern age (Choi 2017, 89). Most business operators have opted to incorporate the use of Big Data into their organisations mainly as a result of the fact that it is likely to provide user-generated information as it may also be utilised in providing insights for critical stakeholders such as the government, businesses, social initiatives, and education sector.

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