Impact of Data-Driven Strategies on Global Business

Desklib provides solved assignments and past papers to help students succeed.

Trends in Global Business Environment
1

Table of Contents
Introduction......................................................................................................................................3
Data Driven Business......................................................................................................................3
Challenges Identified.......................................................................................................................4
New Trends......................................................................................................................................4
Performance Management...............................................................................................................5
Conclusions......................................................................................................................................6
References........................................................................................................................................7
2

Introduction
With the advent of the modern age technologies the business shaped itself with the competition
in the global business environment. The reshaping of the social, economic, structural,
technologies etc are such that shapes the current and emerging trends in the business. Today the
individual, community and the market is linked with a network of technology where the trends of
global business has laid its effects on. The case at hand is been studied and analyzed to
understand and direct the lifelong learning for the business for continuous developments. Hence
to manage the business has to compete globally where the bigger players are using the
technologies like data gathering and analysis for the best delivery and making the smaller players
to follow them and thus get the needful market competition.
Data Driven Business
Becoming data driven is the policy been adopted by various brands across the globe to manage
the needful data and analyze them to get the best out of the market in terms of performances. The
report on the Big Data 2019 and AI Executive survey has brought up some grave scenes from big
business of the day. It surveyed few large companies like American Express, General Electric,
Johnson & Johnson, Ford Motors etc to gather their data management culture in the business. It
shows that 72% of the business is yet to bring in data driven business culture and 69% of them
suggests they are yet to develop a data driven organization. 53% suggested that they don’t treat
the data as an asset for the business while 52% admitted that they are not competing on the data
driven analytics in the business processes (Bean and Davenport, 2019). Artificial Intelligence
and Data driven processes is accelerating I the businesses but they are yet to reach the point that
would suggest that the data is well identified and investments regarding it is well done for the
long term benefits. A greater urgency for the investment on big data is needed (Katavić, 2013).
Nevertheless, there is a 75% mass who cites the disruption as the main reason for the data based
operations and Artificial Intelligence integration with the business processes. The companies of
the day are taking a not and 68% of the businesses have Chief Data Officer as a position to aid
this process further. 77% of the staffs in the business however finds the adoption of Data and AI
in the processes as a major challenge while a whopping 93% thinks that the people and process
issues are the biggest obstacle in the data management and 24% of them cites the organizational
3

culture of resistance to change as the reason of not implementing big data and AI in the business
(Bean and Davenport, 2019).
Challenges Identified
The survey and the data therein shows the short term financial goals are the major challenger to
the long term adoption of data driven business processes. However, the people in the data
management part have shown the drive for the process adoption but they have cited the
organizational intent and support is needed to get the transformation on (Westney, 2011). A
number of data driven teams has been made by the businesses in the recent times to integrate the
Data Analytics with the objective of rapid Data integration for the drive and rapid results. The
survey results gave an analysis which wish to integrate data driven process in a manner that
suites a project or process to transform the organization and not looking in it as an overall Data
Driven transformation. Since the data and its objectives are to make a business work better so the
integration has to be such which is needful and helpful in the long run. Such process would make
the changes slowly but surely which would drive the business towards the data driven
transformation slowly but with efficiency. The agility of implementation is the key in such
projects which would move the process and the business to grow towards the data driven
transformation as needed that would deliver rapid improvements and thus give the firm the
needful data culture in the long run. The training and the skills of the people and the process
adoption has to be such that it gets the involvement of all with the least disruption of the
operations (Geslevich-Packin and Lev-Aretz, 2016).
The need for the Data analytics in the business is not going anywhere so a data driven
transformation is needed where the process adoption is key to its success. So the business has to
be serious in managing and collection of data so that the real analysis of the same can be done to
get the best out of the business where the human intervention like training, adoption and
implementation would generate the needful results (Alonso and Ocampo, 2017).
New Trends
The new trends in the market is driven by the data analysis which further aids the businesses to
decide upon what to do first and what is the priority for them. Data driven businesses has the
competency to perform well and challenge the competition based on the data analysis. The new
trends of the day has made the businesses to get in the newest of technologies like the online
4

payments, booking, product search etc which has made the business the edge to reach a wider
audience with the most recent services that aids their business processes. The companies are
lacking behind as the data survey shows to align their efforts with the process adaptation. The
people to people connections has been made very easy in the markets where the internet is
working well. This has enhanced the business capabilities to gather the needful data and analyze
them to suite the business needs. The generation of the data of the people searching for a
product, the trends on the internet about an offer or the trends of the business in the competitive
environment are all answered with data and the results received from therein. The data would
help a business to gather the needful momentum by analyzing the most effective or ineffective of
schemes that can be replaced with a better one if one is not working. This can be best done
online with technology where the information reaches all stakeholders in real time. New trends
of sustainability can be brought in, the losses can be stopped in a project if the real time data
shows loss in such. So the adoption of data science would help the business take the needful
steps in real time without much of changes in the operations (Alonso and Ocampo, 2017).
Further, the same can be communicated via online media to all the needful stakeholders in real
time. So the decision making as well as the changes and its implementations are been made with
the data analysis where the technologies helps the business to mend its ways in real time that
helps in curbing the losses in real time (Geslevich-Packin and Lev-Aretz, 2016).
Performance Management
The performance of a business idea or the functioning of a business asset like machines or people
can be determined in real time if the data is well managed. The performance of the business can
be enhanced if the managers takes in the data and utilize them to get to a conclusion which
would make or break their business processes. For an example, the decision makes can make a
decision of making a product more if the demands forecasting is high for it while keeping the
product of least demand aside for the moment. The manpower, the machineries or the skills can
be used to make the challenges disappear once it’s noted. Such can only be done by the decision
makes in the real time. Offers for the products that are not fast moving can be generated for the
period of their low sales based on the data gathered on the product sales or its search on the
internet. The losses made due to an offer can be modified if the trends sows the same is
generating no profit as desired (Hritzuk, 2018).
5

Manpower likewise can be utilized where the person is needed from a place or scope of business
where the manpower is not well utilized. Further the feedback of the people can be gathered and
placed to further improve the data based performance mapping. Such helps the business in all
fronts. Hence the performances of the business is monitored in real time which makes the
business make changes fast to counter a loss or be ahead in the Competitive markets (Westney,
2011). The logistics like the stakeholders scope and management too is aided which can be
tracked in real time with the modern day technologies and data generated results.
Conclusions
The modern day technologies has made the businesses adopt the trends of the market that is
Global in scope and has the ability to keep the business competent in the market. This helps the
business to generate the needful pace and competence to be valued in the competitive market
environments. Nevertheless, the data driven processes has to be adopted by the businesses along
with new innovations which helps the business to have a better relationship with the stakeholders
and gives the clients the best of services with efficiency.
6

References
Alonso, J. and Ocampo, J. (2017). Global governance and rules for the post 2015 era. 2nd ed.
Bean, R. and Davenport, T. (2019). COMPANIES ARE FAILING IN THEIR EFFORTS TO
BECOME DATA-DRIVEN. ALEJANDRO ESTEVE/GETTY IMAGES.
Geslevich-Packin, N. and Lev-Aretz, Y. (2016). Big data and social netbanks. ACM SIGCAS
Computers and Society, 46(1), pp.36-40.
Hritzuk, N. (2018). Why Companies Risk Losing Customers By Not Reciprocating on Shared
Data. Journal of Advertising Research, 58(4), pp.394-398.
Katavić, I. (2013). International Business In Changing Global Environment. SSRN Electronic
Journal.
Westney, D. (2011). Global strategy and global business environment: changing models of the
global business environment. Global Strategy Journal, 1(3-4), pp.377-381.
7