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Abstract

Big data is being used in most industries to fuel their operations, increase returns as well as improve their decision making. As such the need for decision making expertise is decreasing due to availability of the required information from the big data, more personalized products and promotions are being made to customers and a revolution in business management taking place over being fueled by big data technologies. Big challenges are however being faced both the leaders in terms of their roles being taken over and unavailability of adequate data scientists.

Introduction

Many businesses are in the middle of having a management system that is data driven getting data from the social media, customers browsing trends, how they use their mobile phones as well as their sentiments since analysis of such data is promising to give a whole positive turnaround to the management’s decision making process (Tambe, 2014). Big data refers to data that is too vast to be processed using the traditional technologies and hence require new technology systems for processing (McAfee et al., 2012). Many firms that rely on big data to stay competitive includes firms in industries such as transportation, insurance, banking, health care as well as other in the education sector (Tambe, 2014). Big data has come to help in adding the value of firms as well as revolutionize management. This paper thus looks at what is big data, how big data has affected the value of a firm, benefits associated with use of big data as well as challenges faced in implementation of the same and how to tackle such challenges, steps that can be used by organizations to implement big data and finally gives a conclusion to big data and its usage.

Big data

Tambe (2014) considers big data technologies to be used for data mining, as well as other activities involving data science in order to come up with data driven decision making as shown in the figure below. It maybe inform of pictures, messages, updates of social media, readings gotten from sensors, Global Position Systems gotten from cell phones and more (McAfee et al., 2012). Big data can be structured, semi-structured or unstructured. With structured data being well formatted in databases, unstructured being the data mostly stored in traditional technologies while the semi-structured is a combination of both. However, most of the big data available is unstructured (McAfee et al., 2012). Big data requires tools such as Hadoop and NoSQL for analysis.  Hadoop is a tool that is helps to store any kind of data that would have otherwise been discarded (Alfouzan, 2015).   

Fig: data driven technologies

Big data is also used in to boost a firm’s productivity growth with a single standard deviation of big data use bringing about 1-3% productivity growth as compared to an average firm and with a single standard deviation less big data utilization being associated 1-3% less productivity. This hence makes a very big difference in terms of productivity for two firms at the extreme ends (Alfouzan, 2015). As McAfee et al., (2012) explains, just like analytics, big data seeks to gather important acumen from data and convert it into a business gain.

Characteristics of operational big data

According Tambe (2014), the following are the features of effective big data;

1. Ability to integrate, the data must be capable of being mixed and combined effortlessly with other data sets.
2. Economical: the data must be of low cost such that the returns achieved from the use of such data is lower as compared to the cost of acquiring and hiring of technical skills to make such data usable.
3. Flexible: the data must be of less complexity in a way that it can accommodate other requirements such as aligning it for the required user.
4. Stable: the data must have stability since it is huge and has to be used by a large number of users with all getting the same information without distortion.

In order to increase the performance of big data on businesses, it is important to get the required components such as;

1. Data sources: these should be well functioning systems
2. Data platforms which can help capture data including data warehouses which can help manage such data and give consumer insights as well as help act on such information.
3. Analytical tools of big data; these should be capable to being used by the analytics including giving the required insights to the executives and management for effective decision making.

Effects of big data on firms

Integration of present big data insights with Hadoop as well as the inclusion of environmental analytics may help enrich a business with business insights (Alfouzan, 2015). Firms that are able to acquire experts in big data information technology are able to acquire firm value than firms who find it difficult to acquire such expertise (Tambe, 2014). Additionally, Tambe (2014) explains that firms acquiring new IT-innovations faster are able to reap benefits from the investments of other firms which relate faster and whose adoption of such innovations are low. McAfee et al., (2012) extrapolates that as more as companies term themselves as big data drive, the more they showed better results of management.

In the near future, big data will become essential in business operations and every firm must set a foundation for such technologies though some forward thinking firms have already reached that level (Tambe, 2014). However, Tambe, (2014). if the other firms continue to lag behind in their adoption of these data intensive technologies, firms operating in big data intensively will continue experiencing larger productivity rate and growth than others.  The more tools and ideas of big data continue to spread; the more they will change the ideas firms have concerning experience, expertise and how management is practices and leaders who are keen will begin to see big data as a revolution that has come for management. (McAfee et al., 2012). McAfee et al., (2012)      add by explaining that as more firms join in to use big data, other sources of information cropping up will be readily available and new tools will become more cost effective as they usher in a new era of digitization in which big data will be virtually available on basically any topic that businesses maybe interested in.

Benefits of using big data

1. Tambe (2014) explains that Labour markets are able to have return on investments early through use of big data technologies.
2. Big data enables organization to think big in terms of investment, innovations as well as inventions. This as McAfee et al., (2012) explains, big data can be used to create new business by firms.
3. It helps in cost saving which may even grow bigger with time and as firms’ grow. This is because of the reducing costs of computer storage and memory fees, as well as bandwidth and processing. Cost saving could also be seen in form of not engaging outsourced expertise to come and help in decision making since all information needed for such decisions are gotten from the data base and are evidence based (McAfee et al., 2012).
4. It enhances operations across the business due to availability of the needed information.
5. Improved decision making: According to McAfee et al., (2012) it helps the management measure and know with certainty about their business and use that knowledge to improve decision making and business performance. Data driven decisions are quite better and informed as they help the management make decision on basis of facts as opposed to perception and has the ability to see a revolution in management.
6. Better advertising: through being able to track what customers bought, what they showed interest in, the sites they also searched, etc., online businesses are able to make more informed personalized promotions and recommendations to customers which mostly lead to sales as opposed to what traditional systems could help them achieve (McAfee et al., 2012)
7. Creation of sales
8. Increase of returns; through analysis of the customer, suppliers and competitors interactions, big data technologies will enable a firm to increase its returns as it improves the depth of insight gotten (Tambe, 2014)

Challenges faced in implementation of big data

Tambe (2014) notes that one big challenge faced in the implementation of big data by firms is lack of the required technical skills to be able to support the tools required for big data citing that the more big data technologies grows the more problems associated with finding the required skills increase. Advanced analysis requires people with the required skills including the required privacy law, data science as well as a good understanding of the business and know how value is gotten, companies also will require to employ scientists who have the ability of finding patters in data and convert them into information that can be used by the businesses (Tambe, 2015; McAfee et al., 2012)). Additionally, as McAfee et al., (2012) states, management challenges will come in inform of decisions being fact-based as well the whole organization having to change their mind-set on what they consider as “judgement”.

Huge and perplexing data range included in the big data technologies as well as their sellers make it very difficult to find the correct answer from the data (Tambe, 2014). Moreover, as organizations engage in big data intensively, it may require more or less of leadership a thing that may be more challenging for leaders (McAfee et al., 2012). Tambe (2014) extrapolates by citing that poor integration of big data may lead to poor results as 80% of the value obtained from big data is as a result of integration, further to acquiring the required skills, he notes that the scholar notes that data changes, and governance, practices of management as well as the response speed to information may pose additional challenges.

Ways of overcoming challenges

Leaders can be given new roles of being informants through giving them the required data and also asking the right questions, as such people are more likely to adopt information faster when it comes from the executives hence the conflict in leadership will be contained, additionally, big data does not remove the need for human acumen and as such there will still be need for leader (McAfee et al., (2012). McAfee et al., (2012) puts an insight that with most firms becoming digitized, most young people are finding data science as an attractive job and expertise will increase in these field and developing cheaper and more effective analysis tools, this will eliminate both the lack of expertise as well as the difficulty associated with getting the correct answers from the data, moreover, these incoming expertise will come in with skills that will be able to handle analytical tools like Hadoop and others to integrate data effectively in order to get best results. Tambe (2014) also notes that technologies of big data are maturing and ways of getting the needed skills are being expanded through the universities.

Implementing big data in firms

McAfee et al., (2012) states that to start using big data, firms do not need to make huge investments in Information Technology instead the following are some basic steps for stating off with big data ;

1. Choose a business unit which will be used as attest ground a and back it up with a leader and data scientist
2. Identify five key business opportunities which are based on big data and which can be tested in five weeks through prototyping by a of five or less people.
3. Implement an innovation process through use of these steps; experiment, measure, share and replicate.
4. Share your data sets and analytics challenges across the world through the internet.

Conclusion

Big data is quickly sweeping over through most of the industries and soon most businesses will have to join in and use big data in their management and decisions making.

As  Tambe (2014) explains, managers will eventually have to weigh the competitive advantages of using big data technologies against the costs involved in getting the required skills and which are expected to reduce with time since management is going through a revolution by use of big data technologies. Moreover, a firm’s value is added by use of big data through informed decision making, cost savings, opening of new business opportunities, better operations, result oriented advertisement and many more.

It is also important to note that firms that do not engage in big data while their related firms do become competitively disadvantaged as their related firms who use big data end up gaining more from their investments hence their value increasing. McAfee et al., 2012 concludes their paper by pointing out that a revolution on management which is inevitable will come in inform of big data usage almost across all industries, It is therefore evident that any firm still using the traditional data systems should invest in big data systems in order to reap ultimate benefits of better management and improved value.

References

[1] Tambe, P. (2014). Big data investment, skills, and firm value. Management Science, 60(6), 1452-1469.

[2] Alfouzan, H. I. (2015). Big Data In Business. International Journal of Scientific & Engineering Research, 6(5), 1351.

[3] McAfee, Andrew, Erik Brynjolfsson, Thomas H. Davenport, D. J. Patil, and Dominic Barton. “Big data: the management revolution.” Harvard business review 90, no. 10 (2012): 60-68.