Global Management Competencies Report
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This report examines the implementation of Business Intelligence (BI) and Data Analytics solutions at John Lewis Partnership PLC. It begins by providing background information on the company, highlighting its size and the challenges posed by managing large volumes of data using traditional methods. The report then critically appraises the project management and planning required to implement a big data and data analytics solution, detailing the benefits (error identification, new strategy development, fraud detection, cost savings, and understanding consumer trends) and drawbacks (noise, privacy concerns, and security risks). The necessary systems for data analysts within John Lewis to effectively utilize the BI/DA system are outlined. Finally, the report concludes with recommendations for successful implementation, emphasizing a consumer-centric approach, the need for technical expertise, strategic planning, and the development of a robust business case.
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Running head: GLOBAL MANAGEMENT COMPETENCIES
Developing Global Management Competencies 2 (Dgmc2) - Bi Strand: John Lewis Partnership
PLC
Name of the student:
Name of the university:
Developing Global Management Competencies 2 (Dgmc2) - Bi Strand: John Lewis Partnership
PLC
Name of the student:
Name of the university:
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1GLOBAL MANAGEMENT COMPETENCIES
1. Introduction
This report depicts the importance of implementation of Business Intelligence solution
and Data Analytics solution in a business organization. Both the functional and operational
excellence of a business organization gets enhanced after the adoption this kind of business
solution. For this particular report the selected organization is John Lewis Partnership. From
wide research of the business industry it has been defined that, in order to engage consumers
to the company it is very much necessary to apply proper tools and technologies (Williams,
Ferdinand & Croft, 2014). After representing the background of the company, a critical appraisal
of project management and planning needed to be implemented by the organization to gain
competitive advantages from the competitive market.
Different managerial tools and technologies are there those are generally used by the
business industries to gain competitive advantages and measurable revenue as well. However,
the data management capability of John Lewis Partnership is not enough efficient. Thus, in
order to manage data properly without any error it is necessary to implement big data
technology and data analytics as a managerial tool. The advantages and disadvantages of big
data tool and the way through which the operational and functional excellence of big data and
data analytics can improve the existing situation of the company is also elaborated n this report.
Not only this but also, the potential business values and even the organizational key challenges
could overcome with the help of big data analytics tool and data analytics tool.
1.1 Background of the business organization
For understanding the role of big data and data analytics tool, the selected business
organization is named as John Lewis Partnership. From the background research of the
company, the details are identified. It implies that, John Lewis Partnership PLC a British
company based Retail Company which operates John Lewis department stores, in waitrose
supermarket (Assunçao et al., 2015). This retail company is localized in Oxford Street, London
in the year of 1929. Behalf of its owners and partners as well the company generally operates
by Trust. The annual and financial turnover of the company is quite high and keeps on
increasing every year. The products served by the company include clothing, watches,
jewelleries, furniture, bedding, food. Computing and photography services as well. The revenue
of the company is calculated to be 11 Billion in the year of 2015. In the year of 2012 and 2013
the net income of the retail company is measured as 409.6 Million. The total numbers of
employees working for the company is 88,900. However, due to good service and productivity
1. Introduction
This report depicts the importance of implementation of Business Intelligence solution
and Data Analytics solution in a business organization. Both the functional and operational
excellence of a business organization gets enhanced after the adoption this kind of business
solution. For this particular report the selected organization is John Lewis Partnership. From
wide research of the business industry it has been defined that, in order to engage consumers
to the company it is very much necessary to apply proper tools and technologies (Williams,
Ferdinand & Croft, 2014). After representing the background of the company, a critical appraisal
of project management and planning needed to be implemented by the organization to gain
competitive advantages from the competitive market.
Different managerial tools and technologies are there those are generally used by the
business industries to gain competitive advantages and measurable revenue as well. However,
the data management capability of John Lewis Partnership is not enough efficient. Thus, in
order to manage data properly without any error it is necessary to implement big data
technology and data analytics as a managerial tool. The advantages and disadvantages of big
data tool and the way through which the operational and functional excellence of big data and
data analytics can improve the existing situation of the company is also elaborated n this report.
Not only this but also, the potential business values and even the organizational key challenges
could overcome with the help of big data analytics tool and data analytics tool.
1.1 Background of the business organization
For understanding the role of big data and data analytics tool, the selected business
organization is named as John Lewis Partnership. From the background research of the
company, the details are identified. It implies that, John Lewis Partnership PLC a British
company based Retail Company which operates John Lewis department stores, in waitrose
supermarket (Assunçao et al., 2015). This retail company is localized in Oxford Street, London
in the year of 1929. Behalf of its owners and partners as well the company generally operates
by Trust. The annual and financial turnover of the company is quite high and keeps on
increasing every year. The products served by the company include clothing, watches,
jewelleries, furniture, bedding, food. Computing and photography services as well. The revenue
of the company is calculated to be 11 Billion in the year of 2015. In the year of 2012 and 2013
the net income of the retail company is measured as 409.6 Million. The total numbers of
employees working for the company is 88,900. However, due to good service and productivity

2GLOBAL MANAGEMENT COMPETENCIES
the number of consumers of the company is keep on increasing and in order to manage the
details information about the employees and consumers the traditional data management
techniques stood less efficient (Fan & Bifet, 2013). In order to increase the efficiency for
managing the business operational data and other confidential information, implementation of
big data tools and data analytics tool is very much important. With the help of these tools the
managerial level issues will get minimized.
2. Critical appraisal of project management and planning required
implementing and deploying by John Lewis Partnership
2.1 Implementation of big data and data analytics solution
Big data analytics tool can help the business organizations to increase the existing
situation of the business organization. Most of the companies are currently adopting big data
trending practice tool for enhancing their operation and functional excellence. After getting
proper information about the landscape then only an organization should jump their operation
from the existing one to the big data analytics (Diamantoulakis, Kapinas & Karagiannidis, 2015).
This analytical process helps to gain competitive advantages and new revenue with improved
operational efficiency over the business rivals of John Lewis Partnership PLC. Different types of
analytical tools are there such as descriptive analytics, perspective analytics etc. With the help
of descriptive analytics the performance of the organizations including the performance served
by every individual employees as well historical data and the root causes for different
operational and functional issues can also be identified with the help if the big data tool.
Whereas, with the help of perspectives analytics anticipate entrepreneurial opportunities
can be developed and eve the business owners of John Lewis Partnership PLC will be able to
take effective decision to gain measurable success and competitive advantages from the
marketplace (George, Haas & Pentland, 2014). Improper data management might affect the
profit of areas and like targeting market campaigns by reducing the consumer churn and
avoidance of equipment failure. The demands for advanced analytics application have
completely limited the bi data applications. However massive volume of data could be managed
well with the help of big data toll within a big data platform.
the number of consumers of the company is keep on increasing and in order to manage the
details information about the employees and consumers the traditional data management
techniques stood less efficient (Fan & Bifet, 2013). In order to increase the efficiency for
managing the business operational data and other confidential information, implementation of
big data tools and data analytics tool is very much important. With the help of these tools the
managerial level issues will get minimized.
2. Critical appraisal of project management and planning required
implementing and deploying by John Lewis Partnership
2.1 Implementation of big data and data analytics solution
Big data analytics tool can help the business organizations to increase the existing
situation of the business organization. Most of the companies are currently adopting big data
trending practice tool for enhancing their operation and functional excellence. After getting
proper information about the landscape then only an organization should jump their operation
from the existing one to the big data analytics (Diamantoulakis, Kapinas & Karagiannidis, 2015).
This analytical process helps to gain competitive advantages and new revenue with improved
operational efficiency over the business rivals of John Lewis Partnership PLC. Different types of
analytical tools are there such as descriptive analytics, perspective analytics etc. With the help
of descriptive analytics the performance of the organizations including the performance served
by every individual employees as well historical data and the root causes for different
operational and functional issues can also be identified with the help if the big data tool.
Whereas, with the help of perspectives analytics anticipate entrepreneurial opportunities
can be developed and eve the business owners of John Lewis Partnership PLC will be able to
take effective decision to gain measurable success and competitive advantages from the
marketplace (George, Haas & Pentland, 2014). Improper data management might affect the
profit of areas and like targeting market campaigns by reducing the consumer churn and
avoidance of equipment failure. The demands for advanced analytics application have
completely limited the bi data applications. However massive volume of data could be managed
well with the help of big data toll within a big data platform.

3GLOBAL MANAGEMENT COMPETENCIES
Figure 1: market revenue of John Lewis Partnership
(Source: Johnlewispartnership, 2017)
After analyzing the current environment of John Lewis Partnership PLC it is found that in
order to scale up the business efficiency the data should be managed well both in terms of
access and entry (Chen & Zhang, 2014). Again, security is another important aspect that is
served by big data analytics tool. In order to store information regarding the employees and
consumers big data provides framework, for utilizing the mining technique for analyzing the
data, patter discovery and analytical model proposal for recognizing the performance of John
Lewis Partnership PLC in terms of operational application and business process (Williams,.
Ferdinand & Croft, 2014). Currently in every industry for decision making and managing large
set of data, big data analytical tools are widely used. Within the geographic region, massive
amount of shipping delivery data, traffic data streaming and vendor performance data could be
analyzed well with the help of big data tool (Wamba et al., 2015). Even wider variety of data
types such as structured data, semi structured data, and unstructured data can be ingested with
big data tool.
Figure 1: market revenue of John Lewis Partnership
(Source: Johnlewispartnership, 2017)
After analyzing the current environment of John Lewis Partnership PLC it is found that in
order to scale up the business efficiency the data should be managed well both in terms of
access and entry (Chen & Zhang, 2014). Again, security is another important aspect that is
served by big data analytics tool. In order to store information regarding the employees and
consumers big data provides framework, for utilizing the mining technique for analyzing the
data, patter discovery and analytical model proposal for recognizing the performance of John
Lewis Partnership PLC in terms of operational application and business process (Williams,.
Ferdinand & Croft, 2014). Currently in every industry for decision making and managing large
set of data, big data analytical tools are widely used. Within the geographic region, massive
amount of shipping delivery data, traffic data streaming and vendor performance data could be
analyzed well with the help of big data tool (Wamba et al., 2015). Even wider variety of data
types such as structured data, semi structured data, and unstructured data can be ingested with
big data tool.
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4GLOBAL MANAGEMENT COMPETENCIES
2.2 Benefits of business intelligence
Error identification: The operational and functional issues occurring in John Lewis
Partnership PLC can be known instantly with the help of big data analytics. From the real time
insight into the errors helps John Lewis Partnership PLC to react fast for mitigating the effect of
the operational problems (Schoenherr & Speier‐Pero, 2015). It will help the organization to
avoid major hardware, software or even functional failure that might reduce the number of
consumers.
New strategy development: In order to reduce the rate of errors and number of
consumer’s reduction it is very much necessary to notice the competition level immediately.
With the help of big data analytics John Lewis Partnership PLC can stay one step ahead the
competition level (Provost & Fawcett, 2013). With the changing business strategies it will be
able to grab new customer and also able to engage the old consumers.
Fraud detection: Intra organizational and inter organizational frauds can be detected
when it will took place. Through proper measurement the damage can be limited. Big data can
generate real time safeguard system for those who are suffering from data hijacking. As John
Lewis Partnership PLC has been following traditional manual data management system and the
company has just currently implemented the new advanced data managerial technology thus
they fails to maintain every security aspects (Kim, Trimi & Chung, 2014). In order to detect both
the internal and external error big data toll is very much helpful.
Cost saving: Though implementation of real time big data analytics tool is expensive
but still, it eventually helps to save money, for the business leaders there is no such waiting time
but it helps to reduce the work burden, from the company’s IT application (Halperin et al., 2014).
Understanding of the consumer’s trend: The big data analytics help to understand the
competitive offerings and promotion for the consumers and also helps to identify the current
consumer trend. Proper decision could be undertaken with the help of big data analytical tool.
2.2 Benefits of business intelligence
Error identification: The operational and functional issues occurring in John Lewis
Partnership PLC can be known instantly with the help of big data analytics. From the real time
insight into the errors helps John Lewis Partnership PLC to react fast for mitigating the effect of
the operational problems (Schoenherr & Speier‐Pero, 2015). It will help the organization to
avoid major hardware, software or even functional failure that might reduce the number of
consumers.
New strategy development: In order to reduce the rate of errors and number of
consumer’s reduction it is very much necessary to notice the competition level immediately.
With the help of big data analytics John Lewis Partnership PLC can stay one step ahead the
competition level (Provost & Fawcett, 2013). With the changing business strategies it will be
able to grab new customer and also able to engage the old consumers.
Fraud detection: Intra organizational and inter organizational frauds can be detected
when it will took place. Through proper measurement the damage can be limited. Big data can
generate real time safeguard system for those who are suffering from data hijacking. As John
Lewis Partnership PLC has been following traditional manual data management system and the
company has just currently implemented the new advanced data managerial technology thus
they fails to maintain every security aspects (Kim, Trimi & Chung, 2014). In order to detect both
the internal and external error big data toll is very much helpful.
Cost saving: Though implementation of real time big data analytics tool is expensive
but still, it eventually helps to save money, for the business leaders there is no such waiting time
but it helps to reduce the work burden, from the company’s IT application (Halperin et al., 2014).
Understanding of the consumer’s trend: The big data analytics help to understand the
competitive offerings and promotion for the consumers and also helps to identify the current
consumer trend. Proper decision could be undertaken with the help of big data analytical tool.

5GLOBAL MANAGEMENT COMPETENCIES
2.3 Disadvantages of business intelligence
Big noise: In most of the time big data hold s big noise. It means that due to presence
of huge amount of unwanted data points disorder might occur (George, Haas & Pentland,
2014). In order to mitigate this issue, the employees of John Lewis Partnership PLC are
required to work hard separating the unwanted data points and required data points.
Privacy error: Security or privacy is another factor that affects the server where the
employee’s information is stored. Due to lack of security, the network and data storage might be
hijacked or misused by the external attackers.
Lower security: Due to lower level of security, the on house data warehouse of John
Lewis Partnership PLC can be accessed by the external attackers easily (Halperin et al., 2014).
3. Critical appraisal of systems needed by a data analyst within John
Lewis Partnership to make effective and efficient usage of Business
Intelligence (BI) to Data Analytics (DA) system implemented
For successful implementation of big data analytics in the operation of John Lewis
Partnership PLC, the necessary steps those should be followed by the data analysts are as
follows:
1. The data analyst should work with executives, data owners to create data
management strategies considering the process requirement and operational
goal of John Lewis Partnership PLC (Williams, Ferdinand & Croft, 2014).
2. To support and co ordinate with all the data analyst
3. To perform data analysis and facility for delivering all the end users
4. To supervise the issues of the clients to facilitate data deliverable (Provost &
Fawcett, 2013)
5. To monitor and organize all the clients feedback to provide the metrics of the
company
2.3 Disadvantages of business intelligence
Big noise: In most of the time big data hold s big noise. It means that due to presence
of huge amount of unwanted data points disorder might occur (George, Haas & Pentland,
2014). In order to mitigate this issue, the employees of John Lewis Partnership PLC are
required to work hard separating the unwanted data points and required data points.
Privacy error: Security or privacy is another factor that affects the server where the
employee’s information is stored. Due to lack of security, the network and data storage might be
hijacked or misused by the external attackers.
Lower security: Due to lower level of security, the on house data warehouse of John
Lewis Partnership PLC can be accessed by the external attackers easily (Halperin et al., 2014).
3. Critical appraisal of systems needed by a data analyst within John
Lewis Partnership to make effective and efficient usage of Business
Intelligence (BI) to Data Analytics (DA) system implemented
For successful implementation of big data analytics in the operation of John Lewis
Partnership PLC, the necessary steps those should be followed by the data analysts are as
follows:
1. The data analyst should work with executives, data owners to create data
management strategies considering the process requirement and operational
goal of John Lewis Partnership PLC (Williams, Ferdinand & Croft, 2014).
2. To support and co ordinate with all the data analyst
3. To perform data analysis and facility for delivering all the end users
4. To supervise the issues of the clients to facilitate data deliverable (Provost &
Fawcett, 2013)
5. To monitor and organize all the clients feedback to provide the metrics of the
company

6GLOBAL MANAGEMENT COMPETENCIES
4. Conclusion and recommendation
4.1 Conclusion
From the overall discussion it can be concluded that implementation of big data and data
analytics is very much helpful for any business organization to increase the management
efficiency of the business organization. John Lewis Partnership PLC should also utilize these
tools and technologies for enhancing their operational ability. With the application of newly
invented technologies like social media and mobile devices the actionable data keep on
generating continuously. For providing improved consumers experiences John Lewis
Partnership PLC is required to harness the confidential information. In order to optimize the
supply chain oriented issues and for managing the sales price it is necessary for the company to
have the ability of use purchase an inventory data accurately. The continuously rising
competitive bar is the main reason for which the company is required to use proper tool and
technologies. The benefits and disadvantages of big data and data analytics tools are
elaborated in this report and from overall analysis it is defined that, different challenges are
associated to John Lewis Partnership PLC. In order to gain competitive advantages and
measurable revenue from the market it is necessary to implement big data and data analytics
tool. After analyzing the operational tools and technologies of John Lewis Partnership PLC, the
data analyst of the company has implemented big data tool in their business organization.
Though, different benefits are associated to big data tool but still certain disadvantages are
might rise with this approach. In order to mitigate these risks it is necessary to identify certain
risk management processes. The recommendations for the system are elaborated in the below
section.
4.2 Recommendations
In order to resolve the issues associated to big data told t is necessary to follow the
recommendations instructed below:
Start up with consumer centric outcome: The Company is required to frame their
business in such a way so that the service and productivity could meet the requirement of the
consumers with perfection. The means starting of analytics strategy with customer analytics
provides the consumers a much better service for better consumer retention.
Technical expert: In order to implement the big data tool in the business organization it
is very much necessary to hire technical experts I the business organization. By hiring the
4. Conclusion and recommendation
4.1 Conclusion
From the overall discussion it can be concluded that implementation of big data and data
analytics is very much helpful for any business organization to increase the management
efficiency of the business organization. John Lewis Partnership PLC should also utilize these
tools and technologies for enhancing their operational ability. With the application of newly
invented technologies like social media and mobile devices the actionable data keep on
generating continuously. For providing improved consumers experiences John Lewis
Partnership PLC is required to harness the confidential information. In order to optimize the
supply chain oriented issues and for managing the sales price it is necessary for the company to
have the ability of use purchase an inventory data accurately. The continuously rising
competitive bar is the main reason for which the company is required to use proper tool and
technologies. The benefits and disadvantages of big data and data analytics tools are
elaborated in this report and from overall analysis it is defined that, different challenges are
associated to John Lewis Partnership PLC. In order to gain competitive advantages and
measurable revenue from the market it is necessary to implement big data and data analytics
tool. After analyzing the operational tools and technologies of John Lewis Partnership PLC, the
data analyst of the company has implemented big data tool in their business organization.
Though, different benefits are associated to big data tool but still certain disadvantages are
might rise with this approach. In order to mitigate these risks it is necessary to identify certain
risk management processes. The recommendations for the system are elaborated in the below
section.
4.2 Recommendations
In order to resolve the issues associated to big data told t is necessary to follow the
recommendations instructed below:
Start up with consumer centric outcome: The Company is required to frame their
business in such a way so that the service and productivity could meet the requirement of the
consumers with perfection. The means starting of analytics strategy with customer analytics
provides the consumers a much better service for better consumer retention.
Technical expert: In order to implement the big data tool in the business organization it
is very much necessary to hire technical experts I the business organization. By hiring the
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7GLOBAL MANAGEMENT COMPETENCIES
technical experts in the organizations it can be expected that the business will be able to serve
desired outcome to the consumers.
Strategy development: Both the operational and functional business strategies are
needed to be adopted by the business organizations so that it can bit the operational excellence
of other organizations. In order to implement proper strategy he business owners should
identify the business priorities and based on those priorities strategies are needed to be
deployed by the business organization.
Development of business case: Proper business cases are needed to be developed
by the management authority so that the expected business outcome of the organization can be
measured by the company owners.
technical experts in the organizations it can be expected that the business will be able to serve
desired outcome to the consumers.
Strategy development: Both the operational and functional business strategies are
needed to be adopted by the business organizations so that it can bit the operational excellence
of other organizations. In order to implement proper strategy he business owners should
identify the business priorities and based on those priorities strategies are needed to be
deployed by the business organization.
Development of business case: Proper business cases are needed to be developed
by the management authority so that the expected business outcome of the organization can be
measured by the company owners.

8GLOBAL MANAGEMENT COMPETENCIES
References
Assunçao, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2015). Big Data
computing and clouds: Trends and future directions. Journal of Parallel and Distributed
Computing, 79, 3-15.
Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and
technologies: A survey on Big Data. Information Sciences, 275, 314-347.
Demirkan, H., & Delen, D. (2013). Leveraging the capabilities of service-oriented decision
support systems: Putting analytics and big data in cloud. Decision Support
Systems, 55(1), 412-421.
Diamantoulakis, P. D., Kapinas, V. M., & Karagiannidis, G. K. (2015). Big data analytics for
dynamic energy management in smart grids. Big Data Research, 2(3), 94-101.
Fan, W., & Bifet, A. (2013). Mining big data: current status, and forecast to the future. ACM
sIGKDD Explorations Newsletter, 14(2), 1-5.
George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of
Management Journal, 57(2), 321-326.
Halperin, D., Teixeira de Almeida, V., Choo, L. L., Chu, S., Koutris, P., Moritz, D., ... & Xu, S.
(2014, June). Demonstration of the Myria big data management service. In Proceedings
of the 2014 ACM SIGMOD international conference on Management of data (pp. 881-
884). ACM.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise
of “big data” on cloud computing: Review and open research issues. Information
Systems, 47, 98-115.
Hu, H., Wen, Y., Chua, T. S., & Li, X. (2014). Toward scalable systems for big data analytics: A
technology tutorial. IEEE access, 2, 652-687.
johnlewispartnership (2017). john lewis partnership. [online] john lewis partnership. Available at:
https://www.johnlewispartnership.co.uk/ [Accessed 10 Sep. 2017].
References
Assunçao, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2015). Big Data
computing and clouds: Trends and future directions. Journal of Parallel and Distributed
Computing, 79, 3-15.
Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and
technologies: A survey on Big Data. Information Sciences, 275, 314-347.
Demirkan, H., & Delen, D. (2013). Leveraging the capabilities of service-oriented decision
support systems: Putting analytics and big data in cloud. Decision Support
Systems, 55(1), 412-421.
Diamantoulakis, P. D., Kapinas, V. M., & Karagiannidis, G. K. (2015). Big data analytics for
dynamic energy management in smart grids. Big Data Research, 2(3), 94-101.
Fan, W., & Bifet, A. (2013). Mining big data: current status, and forecast to the future. ACM
sIGKDD Explorations Newsletter, 14(2), 1-5.
George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of
Management Journal, 57(2), 321-326.
Halperin, D., Teixeira de Almeida, V., Choo, L. L., Chu, S., Koutris, P., Moritz, D., ... & Xu, S.
(2014, June). Demonstration of the Myria big data management service. In Proceedings
of the 2014 ACM SIGMOD international conference on Management of data (pp. 881-
884). ACM.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise
of “big data” on cloud computing: Review and open research issues. Information
Systems, 47, 98-115.
Hu, H., Wen, Y., Chua, T. S., & Li, X. (2014). Toward scalable systems for big data analytics: A
technology tutorial. IEEE access, 2, 652-687.
johnlewispartnership (2017). john lewis partnership. [online] john lewis partnership. Available at:
https://www.johnlewispartnership.co.uk/ [Accessed 10 Sep. 2017].

9GLOBAL MANAGEMENT COMPETENCIES
Kim, G. H., Trimi, S., & Chung, J. H. (2014). Big-data applications in the government
sector. Communications of the ACM, 57(3), 78-85.
Merelli, I., Pérez-Sánchez, H., Gesing, S., & D’Agostino, D. (2014). Managing, analysing, and
integrating big data in medical bioinformatics: open problems and future
perspectives. BioMed research international, 2014.
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven
decision making. Big Data, 1(1), 51-59.Sagiroglu, S., & Sinanc, D. (2013, May). Big data:
A review. In Collaboration Technologies and Systems (CTS), 2013 International
Conference on (pp. 42-47). IEEE.
Schoenherr, T., & Speier‐Pero, C. (2015). Data science, predictive analytics, and big data in
supply chain management: Current state and future potential. Journal of Business
Logistics, 36(1), 120-132.
Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can
make big impact: Findings from a systematic review and a longitudinal case
study. International Journal of Production Economics, 165, 234-246.
Williams, N., P. Ferdinand, N., & Croft, R. (2014). Project management maturity in the age of big
data. International Journal of Managing Projects in Business, 7(2), 311-317.
Kim, G. H., Trimi, S., & Chung, J. H. (2014). Big-data applications in the government
sector. Communications of the ACM, 57(3), 78-85.
Merelli, I., Pérez-Sánchez, H., Gesing, S., & D’Agostino, D. (2014). Managing, analysing, and
integrating big data in medical bioinformatics: open problems and future
perspectives. BioMed research international, 2014.
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven
decision making. Big Data, 1(1), 51-59.Sagiroglu, S., & Sinanc, D. (2013, May). Big data:
A review. In Collaboration Technologies and Systems (CTS), 2013 International
Conference on (pp. 42-47). IEEE.
Schoenherr, T., & Speier‐Pero, C. (2015). Data science, predictive analytics, and big data in
supply chain management: Current state and future potential. Journal of Business
Logistics, 36(1), 120-132.
Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can
make big impact: Findings from a systematic review and a longitudinal case
study. International Journal of Production Economics, 165, 234-246.
Williams, N., P. Ferdinand, N., & Croft, R. (2014). Project management maturity in the age of big
data. International Journal of Managing Projects in Business, 7(2), 311-317.
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10GLOBAL MANAGEMENT COMPETENCIES
Appendices
Appendix: 1
Appendix: 2
Appendices
Appendix: 1
Appendix: 2

11GLOBAL MANAGEMENT COMPETENCIES
Appendix: 3
Appendix: 3
1 out of 12
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