Please reply to the discussion below in 250 words.
The business world has changed immensely following the introduction of big data. Managers understand their business operations and have established big data can improve business operations through better decision-making. Conventional business models have become increasingly unreliable as it has become difficult for them to make strategic decisions based on predictions made using algorithms. This explains why organizations such as Amazon have closed down most of their physical stores. Big data has paved the way for business executives to attain goals that they only imagined in the past (Janssen, van der Voort & Wahyudi, 2017). The big data trend has become increasingly popular and has led to smarter and improved predictions. The discussion offers a detailed evaluation of the article titled, Big Data, The Management Revolution.
Challenges to the implementation of big data
While big data stands to benefit businesses in a wide range of ways, it is difficult for organizations to attain the benefits if they fail to manage change accordingly. For big data to be successful within organizations, the management should develop clear goals and outline what a successful plan should look like. Big data works in cohesion with human reasoning and should be applied to establish opportunity and support strategic decisions. The second challenge that companies face is coming up with individuals to implement big data management (Janssen, van der Voort & Wahyudi, 2017). It follows that businesses need highly qualified individuals that can work with vast amounts of data to achieve business goals and objectives.
It follows that effective decision-making is a critical issue that affects businesses that apply big data. Businesses may fail to establish structures that allow flexible decision-making in light of big data application. The article asserts that big data calls for applying the latest technology, and businesses that fail at this do not succeed in its implementation (Janssen, van der Voort & Wahyudi, 2017). The final challenge that influences the application of big data is the company culture. This refers to the attitude that the organization holds towards big data. If the mood is negative, the implementation of big information is likely to fail.
New Decision-Making Model
Businesses face technical challenges in applying big data and a wide range of managerial challenges. The role of the senior executive management team becomes more complex (McAfee & Brynjolfsson, 2012). One of the essential facets of big data is the influence on how decisions are made. In instances where data is expensive and scarce, decision-making should be left to the experts as they are conversant with the business trends and patterns. This form of decision-making has been applied in organizations over the years and is termed intuition.
When considering critical decisions, expensive experts are hired or senior individuals in the organization required to make the final verdict. Notably, crucial business choices are made by the highest-paid person’s opinion that is abbreviated as HiPPO (McAfee & Brynjolfsson, 2012). The article has demonstrated that companies in the present times rely excessively on intuition and experience instead of depending on the possibilities that are given by big data. Research has shown that most organizations have failed to implement big data to full capacity, which has continued to impact their competitiveness and business performance adversely.
Business executives that are interested in making data transitions should plan for the strategy. They should start by preparing the implementation of two basic techniques (McAfee & Brynjolfsson, 2012). The first step is through the consideration of big data while making decisions on diverse issues. This means that they should reconsider the origin and application of big data. The second step asserts that the management should not allow the organization to be domineered by big data.
When considering the challenges that can be addressed using big data, it is evident that domain expertise is imperative (McAfee & Brynjolfsson, 2012). Conventional domain experts are those that have gained competence in a given area. In other words, they have knowledge on the areas where the biggest challenges and opportunities can be found. Businesses should acknowledge that as significant data advances, the part that is played by domain experts shifts. An evaluation of the article clarifies that big data should be applied together with conventional approaches to achieve success.
Advantages of Big Data
Executives have questioned the benefits of implementing big data in their organizations. It follows that there are organizations that have been skeptical regarding its application as they view it as an approach that disrupts companies’ operations (McAfee & Brynjolfsson, 2012). The first advantage of implementing big data is that it can be applied to process and make sense of high data volumes. It follows that businesses handle a high volume of data that can be used to make critical business decisions. It has emerged that decisions made using big data are better than those made relying on traditional methods.
Businesses that rely on big data benefit from a high velocity in data analysis, which increased the quality of decisions that executives make. It has been found that the business space has become increasingly competitive, and this improves the significance of real-time decision-making. Organizations need to be aware of business trends, and they can make changes that can result in profitability (McAfee & Brynjolfsson, 2012). As seen in the diverse format that company data is available in, the information world has become increasingly diverse. Accordingly, big data promotes the evaluation of the different types of data, and this facilitates decision-making.
Improved Performance in airlines and businesses at large
Time is believed to be one of the most important resources for companies in the present times. Minutes count as they can lead to profitability and losses in companies if not well utilized. Most digital companies such as Amazon rely on sales and use big data to study consumer behavior and predict future trends (McAfee & Brynjolfsson, 2012). The airline business relies on accurate information on flights to come up with critical decisions. Take off times and landing times are essential considerations for airline staff to minimize waiting times, driving operational costs. Airlines rely on big data to increase accuracy in calculating the time that is a critical factor in business operations.
A prevalent practice used in airlines and the travel industry is the ETA (Expected Time of Arrival). It means that companies merely relied on estimates, resulting in increased costs and delays in decision-making. There was a shift in the airline sector as it began seeking decision support from PASSUR Aerospace to get accurate arrival times (McAfee & Brynjolfsson, 2012). It became clear that big data was transforming industries and business leaders continued investing heavily in the concept to realize improved business operations.
The need for talent management
There has been a growing demand for individuals that are skilled in data management. Consequently, there has been an increase in demand in the number of qualified individuals in data management and analysts. Most businesses operate in the online space as they realize the potential in this space (McAfee & Brynjolfsson, 2012). It can be noted that statistics is a valuable area of study that applies in big data but, it has been disregarded in the past. There are useful skills in statistics that apply to big data that should be considered in the present times when dealing with the management of enormous data volumes.
Companies should hire individuals experienced in big data management to support strategic decisions and improve business operations. On the other hand, businesses should improve employees’ competence in decision-making (McAfee & Brynjolfsson, 2012). Organizations should work towards ensuring all individuals understand big data and determine how it shapes business operations. This means that organizations should invest in skills that are associated with big data.
Big data does not move away from conventional best practices in business. Instead, it advocates for the application of effective practices specifically in leadership. It has been found that companies that have succeeded in big data have visionary leadership that questions methods and defines clear goals and objectives (McAfee & Brynjolfsson, 2012). Businesses should not apply big data simply because it is a trend. They should work towards understanding it and how it will benefit it. Additionally, business leaders should understand how the market works and think of creative ways to conduct business using big data.
The future demands leadership that will be flexible and will make decisions based on the market. In the present times, big data appears to be one of the best trends that will lead to increased business success and efficiency. Leaders’ attitude towards big data will influence that of the followers and teams within the business. Consequently, leaders should have a positive attitude towards the implementation of big data.
The successful implementation of big data is dependent on the culture applied by organizations. Companies and individuals in the organization should evaluate the knowledge they have about big data (McAfee & Brynjolfsson, 2012). A critical observation that has been made on companies is that they pretend to be more data-driven when they are not. Therefore, companies applying the practice should make sure that they understand what big data is before implementing it (Sun et al., 2018). Executives have often made decisions using traditional approaches and made it appears as if they used big data.
Organizations have been fast-moving towards big data owing to the fact that it has led to improved outcomes in decision-making (McAfee & Brynjolfsson, 2012). Companies that have cultivated a culture that combines data science with domain expertise have stood out in their respective sectors and set them apart from their competitors. As a result, the culture adopted by businesses impacts the successful implementation of big data.
One of the most important lessons that I have learned from the article is that organizations should embrace change. This is because the introduction of big data has resulted in an increased demand for new technology (McAfee & Brynjolfsson, 2012). While the technology required to implement new data is expensive, it has been found that most of the software can be accessed by all users. Businesses should consider investing in new technology as it will improve their big data application, resulting in a performance improvement.
Big data is likely to lead to the emergence of new roles that did not exist in the past. Concerning this, there has been an increase in demand for data analysts. The management should develop these skills in organizations through training the workforce and hiring the employees that have gained competence in these skills. The lessons learned from the article should be implemented in organizations applying big data in the present times.
Janssen, M., van der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision- making quality. Journal of Business Research, 70, 338-34
McAfee, A., & Brynjolfsson, E. (2012, October 1). Big Data: The Management Revolution. Harvard Business Review. Retrieved from https://hbr.org/2012/10/big-data-the- management-revolution
Sun, S., Cegielski, C. G., Jia, L., & Hall, D. J. (2018). Understanding the factors affecting the organizational adoption of big data. Journal of Computer Information Systems, 58(3), 193-203.