Case Study 1: Developing Personal Learning Environments

Case Study 1: Developing Personal Learning Environments to Build a “Smart Ecosystem”

Trish Gomez Ahern

BUS 4200 Enterprise Information Management Systems

Professor: Rodney Heisterberg

January 18, 2017

 

 

Problem Statement

Our world and business environments are changing at a rapid pace, and it is difficult to keep up with the fast-paced technological changes (Heisterberg & Verma, 2014).  Because of the social business evolution of the past decade, Web 2.0. has cultivated a culture of constant Internet connectivity, resulting in data-rich business environments.  Although the seemingly unlimited access to data can be very useful, the data is often siloed and therefore not understood or utilized.  This paper will exam how the use of Personal Learning Environments (PLEs) can be developed to create Smart Ecosystems for businesses in order to organize, utilize, and share their information in an efficient manner to gain a competitive advantage.

Challenges and Opportunities

In the past decade, the amount of information in existence has multiplied exponentially and has become abundantly accessible (Heisterberg & Verma, 2014).  The challenge no longer lies in accessing information, but it now lies in finding the best way to sort and use the excessive amounts of information.  Data growth has gone through a change in basic assumptions, from not much data that is mostly structured, to a lot of data that is mostly unstructured (Schneider, 2016).  An estimated 80% of the world’s data is unstructured, therefore the use of the data is limited.  Because so much data is unstructured, enterprises missing out on significant amounts of digital intelligence if they do not understand what is in their data.

As businesses, customers, and partners become increasingly interdependent on each other and technology, it has become ever more important for businesses to find their core competency, accelerate at this core competency, and collaborate with partners in such a way that leverages the mutual benefit for the partners.

Business Solution

As the digital revolution continues to evolve, businesses need to find a way to keep up at an ever-increasingly rapid pace in order to survive in the world of Big Data.  Gartner’s definition of an ecosystem as an “interdependent group of actors sharing standardized digital platforms to achieve a mutually beneficial purpose” implies that there is a blurred line between business and industry (Newman, 2016).  Digital ecosystems allow organizations to interact with customers, partners, adjacent industries, and even competitors (Sondergaard, 2017).  Figure 1 demonstrates the cross-enterprise collaboration within a virtual enterprise.

Figure 1: Data service centric collaboration

Top performing organizations use digital ecosystems to extend their reach, and avoiding participation in digital ecosystems is not an option (Sondergaard, 2017).  Because of digital ecosystems, industry models are changing from simple relationships to digital partnerships, and building a strong digital ecosystem is the solution to managing this change.  As demonstrated in figure 2, the digital ecosystem of any business consists of all the pertinent digital touch points, the people that cooperate with them, including the business processes and technological environment (Ohanian, 2014).

Figure 2: The digital ecosystem of any company

To allow for the adoption of new technologies and adaption to the things and people in the ecosystem, businesses must focus on closing skill gaps amongst employees (Newman, 216).  Therefore, it is imperative that employees are continually provided with proper training in order to know how to use and utilize technologies to their greatest capacity.  The challenge that comes with this is that different learners have different learning styles; therefore, a one-size fits all solution cannot satisfy all learner’s needs (Halimi, Seridi-Bouchelaghem, & Faron-Zucker, 2014, p. 2).  Because learning preferences have such a large effect on learning outcomes, the emergence of Personal Learning Environments (PLEs) has been more wide-spread over the last few years.  Through the connectivity of Web 2.0, PLEs allow for the learner to control their own learning environment and while promoting interactive learning in web environments (Jeremic, Jovanovic, & Gasevic, 2011, p. 2).  Figure 3 demonstrates the principles for the development of interactive PLEs.

Figure 3: Principles for the Development of Interactive PLEs

PLEs enable individuals the ability to access, configure and manage digital resources as they relate to present learning needs and interests, and allows for seamless communication and collaboration between individuals who are involved in the learning process (Halimi et al., 2014, p. 2). Due to the collaborative nature of PLEs, information can be recurrently created and shared (Malamed, 20016).  As seen in figure 4, learners can take advantage of the collaborative support, autonomy, and robust capability that is offered via the openness nature of Web 2.0 PLEs (Rahimi, Berg, & Veen, 2015, p. 783)

Figure 4: Mapping the core concepts of Web 2.0 into the student’s control model

According to Gartner, “a business intelligence competency center (BICC) develops the overall strategic plan and priorities for BI. It also defines requirements, such as data quality and governance and fulfills the role of promoting the use of BI.(Gartner, 2017).  Figure 5 demonstrates how companies that fail to use BI run into several problems, all which result from low-quality data.  Figure 6 then demonstrates that the result of a successful BI is empowered users, accurate reporting,increased sales, efficient operations, more customer satisfaction, better returns, and better forecasting.

Figure 5: Why BI?

Figure 6: What can be gained from deploying a successful BI

Lessons Learned/Business Case

Organizations today need to embrace digital ecosystems and take advantage of the potential opportunity that comes with this change. Daugherty (2015) cites the following examples of businesses that have taken notice the emerging global trends in technology:

Accenture’s annual outlook of global technology trends — Accenture Technology Vision 2015 — found that these visionary companies recognize that as every business becomes a digital business, together they can effect change on a much bigger stage, collaborating to shape experiences, and outcomes, in ways never before possible.  As a result, these leading enterprises are shaping a new economy — the “We Economy.”

This shift is highlighted best in the rapidly growing Industrial Internet of Things (IIoT) — i.e., the interconnection of embedded computing devices within the existing Internet infrastructure — as companies are using these connections to offer new services, reshape experiences and enter new markets through these digital ecosystems.

Home Depot, for example, is trying to shape the way people live through an emerging connected home market.  The retailer is working with manufacturers to ensure that the connected home products it sells are compatible with the Wink connected home system, thereby creating its own connected home ecosystem, with a wide range of services that are easy to install.

Philips is taking a similar approach with its healthcare practice teaming up with Salesforce to build a platform that they believe will reshape and optimize the way healthcare is delivered.  The envisioned platform will create an ecosystem of developers building healthcare applications to enable collaboration and workflow between doctors and patients across the entire spectrum of care, from self-care and prevention to diagnosis and treatment through recovery and wellness.

Within the automotive industry, Fiat is looking toward connected cars as the next growth opportunity — partnering with companies like TomTom, Reuters, Facebook and TuneIn to create its own Uconnect platform, which will be integrated with the Fiat-Chrysler Group’s vehicles to provide drivers with communication, entertainment and navigation features that can help drivers stay focused on driving.

Why I Care

There is no doubt that the volumes of data will only continue to grow (Marr,2016).  Considering the exponential growth expectancy of the number of devices and the Internet connectivity, we will continue to generate larger and larger volumes of data.  Many CIOs have indicated that they intend to double the number of ecosystem partners in two years (Sondergaard, 2017).  Research shows that 79% of the top performing digital organizations indicate participation in a digital ecosystem.  This is compared to 49% of average performers participating in digital ecosystems.  With this growth will come more ways to analyze and improve data, and more tools for analysis without the analyst.

In the short term, the information learned about PLEs and smart business ecosystems will serve me, along with the entire class, very well for our group project. The scope of the event along with the collaborative nature of the enterprises involved will require robust and interactive systems.

In the long term, this will serve me well in my professional career.  Regardless of the field you work business ecosystems are a large part of the present and will only continue to grow in the future.  Understanding the need for an effective business ecosystem that allows for collaboration and innovation is a driving factor in the success of an enterprise.

References

Daugherty, P. (2015, March 9). The Rise of Digital Ecosystems In The “We Economy”. Retrieved from http://www.forbes.com/sites/ciocentral/2015/03/09/the-rise-of-digital-ecosystems-in-the-we-economy/#56ad65095d94

Gartner (2017). Gartner IT Glossary. Retrieved from http://www.gartner.com/it-glossary/bicc-business-intelligence-competency-center/

Halimi, K., Seridi-Bouchelaghem, H., & Faron-Zucker, C. (2014). An enhanced personal learning environment using social semantic web technologies. Interactive Learning Environments, 22(2), 165-187.

Heisterberg, R., & Verma, A. (2014), Creating Business Agility:  How convergence of Cloud, Social, Mobile, Video, and Big Data Enables Competitive Advantage. John Wiley & Sons. ISBN 978-1-118-72456-9.

Jeremic, Z., Jovanovic, J., & Gasevic, D. (2011). Personal learning environments on the social semantic web. Personal learning environments on the social semantic web. Retrieved from http://www.semantic-web-journal.net/content/personal-learning-environments-social-semanticweb

Li, G., & Wei, M. (2014). Everything-as-a-service platform for on-demand virtual enterprises. Information Systems Frontiers, 16(3), 435-452.

Malamed, C. (2016). Models for Designing Your Personal Learning Environment. Retrieved from http://theelearningcoach.com/elearning2-0/designing-personal-learning-environment/

Marr,B. (2016, March 15). 17 Predictions About the Future Of Big Data Everyone Should Read. Retrieved from http://www.forbes.com/sites/bernardmarr/2016/03/15/17-predictions-about-the-future-of-big-data-everyone-should-read/#6262e3fb157c

Newman, D. (2016, December 20). Creating A Digital Ecosystem That Benefits Your Business. Retrieved from http://www.forbes.com/sites/danielnewman/2016/12/20/creating-a-digital-ecosystem-that-benefits-your-business/#1a0d90bc4de5

Ohanian, A. (2014, February 23). How to make a splash in social media. Retrieved from https://feeldigitallife.wordpress.com/tag/digital-ecosystem/

Rahimi, E., Berg, J. d., & Veen, W. (2015). A learning model for enhancing the student’s control in educational process using Web 2.0 personal learning environments. British Journal of Educational Technology, 46(4), 780-792.

Ramakrishan, P. (2009, October 24). Business Intelligence Banking. Retrieved from http://www.slideshare.net/PriyaRamakrishnan/business-intelligence-banking

Schneider, C. (2016, May 25). The biggest data challenges that you might not even know you have. Retrieved from https://www.ibm.com/blogs/watson/2016/05/biggest-data-challenges-might-not-even-know/

Sondergaard, P. (2017, January 13). Ecosystems are the future of digital. Retrieved from http://www.gartner.com/technology/topics/digital-ecosystems.jsp

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