Holmes Institute HC3031: Global Business Literature Review Report

This report presents a literature review focused on the trends in global business, specifically examining the adoption of data-driven strategies by organizations. It analyzes the challenges companies face in becoming data-driven, including cultural resistance and the failure to achieve transformational results from data initiatives. The review explores the importance of a data-driven culture, the reasons for failures in data initiatives, and the practical application of big data across different departments. It also discusses the usefulness of various data-driven business strategies, emphasizing the need for companies to adopt data-driven approaches to enhance decision-making, improve customer understanding, and drive business growth. The report references several articles and surveys to support its findings, and concludes with recommendations for companies to effectively implement data-driven strategies and foster a data-oriented culture.

STUDENT DETAILS:
TRENDS IN GLOBAL
BUSINESS

LITERATURE REVIEW 1
Contents
Introduction.........................................................................................................................................2
Literature review................................................................................................................................2
1. Why the companies should have data driven culture?.................................................2
2. What are the reasons of a failure to get transformational results from the data
initiatives?.......................................................................................................................................3
3. How to use big data by all departments in operations?................................................3
4. What the data driven business strategies can be useful?............................................3
Conclusion..........................................................................................................................................4
References..........................................................................................................................................5

LITERATURE REVIEW 2
Introduction
In a competition to win the clients and market shares, the data-driven companies are
enhancing the space between them and their not-informed nobles. The values of having
the data-driven organizations are that there is reliability and uniformity over the period. Big
data is very useful to know the clients and their attitude, and their choices. The
corporations are intense to increase the traditional data set with social media data,
browser log and texts analytic and instrument data to achieve the whole picture of the
clients (Akhtar, et. al, 2016). The transactional data is incredibly significant for the
business. The reason is that the data helps them to uncover inconsistency and enhance
the operation for the high quality outcomes. In the following report, the article ‘Companies
are failing in their efforts to become data-driven’ is analysed. This report also states the
reasons of failures to become data-driven organisations and the data driven strategies.
Literature review
The data-driven culture is very important in developing the effectiveness of business and
the efficiency of operations. There are numerous big corporations, which are not
succeeding in creating the data-driven culture in the organisations. It is required by these
organisations to know the causes of being failure in getting data analytics, to know the
significance of big data as well as data-driven culture in the organisation and to adopt the
different data-driven business approaches to create data-oriented culture in organisation
(Sutherland, et. al, 2018). By analysing this article, following four questions can be raised-
1. Why the companies should have data driven culture?
The data has become the key part of a business of company. The data-driven culture
means to overcome the data-resistant viewpoint, which impedes the corporations from
implementing the data-driven approaches. In twenty first century, the business has been
trending to applying the approaches to advance the corporate culture. These innovations
have not only enhanced the efficiency among the team members; however, they have
increased successful employees on embarking the procedures and enhanced corporation
branding wholly. It is a key target of organisations to establish the data driven culture in
organisations (Business premium collection, 2013b).
The firms are still discovering the manners to benefits from the collective intellect in a
procedure of decision-making. For achieving this aim, the organisations have made efforts
to consider the data as significant assets, to advance the culture in more data-oriented
directions and to make adjustments of the approaches to give emphasis to data and
analytics. The culture of organisation has become the devoted organisation for recognising
if the businesses are well. The other phase to applying the organisational culture in the
productivity is becoming the data-driven culture. The development to the data-oriented
objectives was embarrassingly slow; however, the conditions now seem poorer. The top
organisations appear to be failing in the determinations to become data-driven
organisations (Gupta and George, 2016).

LITERATURE REVIEW 3
2. What are the reasons of a failure to get transformational results from the data
initiatives?
As per the 2019 Big Data and AI Executive Survey, it is found that the big corporations
including Johnson & Johnson, American Express, and General Motors have been failed to
achieve transformational outcomes from data initiatives. It is stated by seventy two per
cent survey report that corporations have to create data-driven culture in the organisations
(Business premium collection, 2013a). The sixty nine percent-survey report says that the
corporations do not have developed the data-oriented organizations. Further, fifty-three
per cent survey report provides results that these organisations do not considered the data
as the assets of business of organisations. Furthermore, fifty-two per cent survey report
states that these big organisations do not compete on data as well as analytics. However,
it can also see that this proportion of the organisations recognising themselves as big
data-driven has reduced in every three years (Shank, 2018).
There are various reasons of being failure to attain the transformational results from data
analytic. Obviously, the complexities of cultural changes have been noticeably
underestimated in the big corporations. Certain corporations are being failure because of
the absence of recognition of organizational arrangements and certain organisations are
being failure due to cultural confrontation as top elements contributing to absence of
business’s acceptance (Nickel, et. al, 2016). Additionally, there are several of other cases
for failure of big organisations to get the aim of data-oriented organizations. Maybe the
search of short-run financial aims pushes long-term targets such as the data-oriented
culture to back burner. It can also be that the failure of certain high-profile digital
transformation has led managers of entity to be cautious of transformational initiative
(Mouritsen, et. al, 2016).
3. How to use big data by all departments in operations?
Whatever the causes for the failure to get the transformational outcomes from data
initiatives, the amounts of data continue to take place in businesses and societies.
Analytical decisions and actions continue to be normally greater to those based on
perceptions, understanding, and knowledge. The corporations in the survey are making
investment greatly in big data and data analytic. In brief, it can see that the requirement for
data-driven firms and data-oriented culture is not going away. It is essential to use the big
data effectively by all the departments in operations because it helps in giving the useful
data for taking the best and proper decisions related to business. The corporations may
advance the approaches by taking into the consideration viewpoints of the customers. The
big data analytics helps operation related to business in very effective manner to become
very productive. It is helpful in increasing the advantages of the each department of the
company. In the addition of this, the insights given by the big data analytics devices assist
in considering the client’s needs in best way. It assists in establishing the new and best
product. The advanced service and good with new standpoints may be helpful for the
company extremely. It can help the customers too as they achieve best offerings satisfying
the requirements in effective and proper way (Bean and Davenport, 2019).
4. What the data driven business strategies can be useful?
It is required by the organisations to get the tough look at why these initiatives are not
succeeding to achieve the business tractions. In the addition of this, the organisations
should know that what steps should be made to decrease the cultural barriers to business

LITERATURE REVIEW 4
implementation (Business premium collection, 2017). There are various companies, who
have made investment heavily in the technologies as the primary step to becoming the
data-driven; however, this alone clearly is not sufficient. The organisations should become
much more severe and imaginative in respect of stating the human side of data if they
actually expect to arise significant business advantages. The company should use the
data-driven approaches to make proper decisions based on data analysis and
interpretations. The data-driven strategies make able the corporations to assess and
identify the data with an objective of best serving the clients (Mayo, 2016).
To make best data-driven strategy, the company should commit to a plan. The changes
may be complex, no matter how bigger or lesser a company can be; integrating the data-
driven plan is no exclusion. However, incapacitating antipathy of the individuals to change
needs more than the devices and data. For making changes how the companies take
decision and become data-oriented companies, it is required to consider regarding how to
drive changes and reward staff for taking best data-oriented decision. Through the
utilisation of data to drive the action, the company may contextualise and personalise the
texting to the prospects and clients for the more client-oriented strategies (Huang, et. al,
2019).
Conclusion
As per the above analysis, it can be concluded that generally, the use of big data
proclaimers various incredible requests for a world of business. The use of big data not
only helps to put together the ideal teams, however this would also assist the business to
launch modern product with accurate amount of speed to generate the good quality. No
wonder big data is over the growth to alter the business landscape, as people know this
(Adrian, et. al, 2018). In this way, as per the above findings it can say that the
organisations have fear to make investment of the hard-earned cash because of the higher
rate of failure practised by other organisations in the marketplace. Corporations have
making investment only of the small part of the money in keeping and handling the portion
of big data. Therefore, the company should take the time to make sure that they are
employing the correct and skilled people to handle the intelligence functions of businesses
within the companies. It is recommended to follow the appropriate and effective data
driven approaches (Business premium collection, 2010).

LITERATURE REVIEW 5
References
Adrian, C., Abdullah, R., Atan, R. and Jusoh, Y.Y. (2018) March. Expert Review on Big
Data Analytics Implementation Model in Data-driven Decision-Making. In 2018 Fourth
International Conference on Information Retrieval and Knowledge Management
(CAMP) (pp. 1-5). IEEE.
Akhtar, P., Tse, Y.K., Khan, Z. and Rao-Nicholson, R. (2016) Data-driven and adaptive
leadership contributing to sustainability: Global agri-food supply chains connected with
emerging markets. International Journal of Production Economics, 181, pp.392-401.
Bean, R. and Davenport, T. H. (2019) Companies are failing in their efforts to become
data-driven. Available at: https://hbr.org/2019/02/companies-are-failing-in-their-efforts-to-
become-data-driven [Access on 1/05/2019]
Business premium collection (2010) Creating the Data-Driven Culture. Available at:
https://search.proquest.com/businesspremium/docview/2208635952/A2AB7275FCFB4B2
1PQ/3?accountid=30552 [Access on 01/05/2019]
Business premium collection (2013) Capturing Big Data in Social and Detection Systems:
Market Opportunities and Challenges 2013 – 2019. Available at:
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PQ/2?accountid=30552 [Access on 01/05/2019]
Business premium collection (2013) Research and Markets: Big Data in Pharma
Marketing. Available at:
http://www.researchandmarkets.com/research/xmztbj/hitbig_data_in. [Access on
01/05/2019]
Business premium collection (2017) Leadership Styles in a Data Driven Culture. Available
at:
https://search.proquest.com/businesspremium/docview/1980087214/A2AB7275FCFB4B2
1PQ/1?accountid=30552 [Access on 01/05/2019]
Gupta, M. and George, J.F. (2016) Toward the development of a big data analytics
capability. Information & Management, 53(8), pp.1049-1064.
Huang, Y., Zang, H., Cheng, X., Wu, H. and Li, J. (2019) Data-driven soft sensor for
animal cell suspension culture process based on DRVM. Applied Soft Computing, 77,
pp.34-40.
Mayo, C.S., Deasy, J.O., Chera, B.S., Freymann, J., Kirby, J.S. and Hardenberg, P.H.
(2016) How can we effect culture change toward data-driven medicine?. International
Journal of Radiation Oncology• Biology• Physics, 95(3), pp.916-921.
Mouritsen, O.G., Edwards-Stuart, R., Ahn, Y.Y. and Ahnert, S.E. (2017) Data-driven
Methods for the study of Food Perception, Preparation, consumption, and
culture. Frontiers in ICT, 4, p.15.
Nickel, C., Farr, L., Wood, A., Bergman, S. and Cunningham, C.J. (2017) Making it stick:
The secret to developing a data-driven culture.

LITERATURE REVIEW 6
Shanks, J.N. (2018) Establishing a Data Culture Using a Data-Driven Instructional System
for School Improvement. In Data Leadership for K-12 Schools in a Time of
Accountability (pp. 39-53). IGI Global.
Sutherland, C.A., Liu, X., Zhang, L., Chu, Y., Oldmeadow, J.A. and Young, A.W. (2018)
Facial first impressions across culture: Data-driven modeling of Chinese and British
perceivers’ unconstrained facial impressions. Personality and Social Psychology
Bulletin, 44(4), pp.521-537.