Networks "Enterprise Glue": Information Mobilization the Core Essay

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networks "enterprise glue": information mobilization the core case module involves careful assessment sources strategic enterprise information. But ' ready tackle, speed underlying issues dynamics.

Information networks as "enterprise glue": information mobilization

To what degree should organizations depend on the analysis of large data and other IT resources to formulate basic strategy?

The business agents of the modern day society are faced with countless challenges from both within and outside their environments. For instance, competition intensifies, the customers become more demanding, the stakeholders pose more pressures and the employees play an increasingly important role. In such a setting, firms across the globe strive to develop and implement novel strategies that help them create competitive advantages.

A powerful example in this sense is represented by the integration of technology within the business decision making process. Companies as such purchase and utilize technologic applications at a wide array of company levels, such as staffing, employee compensation, inventory management or customer relationship management. This massive utilization of data is possible due to the commoditization of large data storage devices, and the trend appears to be maintained in the future.

Given this setting, a question is being posed relative to the means in which the economic agents should employ large data analysis and other IT tools in their decision making process and their search for competitive strategies. This project assesses that the degree of IT utilization should be increased, but it also presents some counter arguments in this direction.

2. In favor of large data and IT utilization

The utilization of large data analysis and other tools of Information Technology is gradually becoming critical in the dynamic and competitive sectors of today. Firms which do not integrate technologic innovations in their strategic decision making processes would not be able to respond to the challenges of the continually changing society.

The support for the integration of IT and specifically large data analysis in the internal business processes is supported by various authors, both academic researchers, as well as practitioners. For instance, Carmen Nobel (2010) argues that the integration of IT solutions within business contexts shapes the overall decision making process at various levels, such as the ones listed below:

The integration of decision making as a wider business activity; for instance, Nobel argues that information bases systems push decisions to be made at a lower organizational level, whereas communication systems push decisions to be made at the top level

The usage of technologies "facilitates the dissemination of information throughout a large company, enabling detailed coordination among various operating units" (Nobel, 2010)

The usage of large data analysis solutions increases the company wide access to information and subsequently leads to the decentralization of the decision making process.

In the specific case of large data analysis utilization within the firms, a solid point-of-view is presented by Steve LaValle, Eric Lesser, Rebecca Shockley, Michael S. Hopkins and Nina Kruschwitz (2010). These researchers have participated in an extensive study of almost 3,000 managers, executives and analysts, across 30 industries in 100 countries. Their findings, which come in support of large data analysis, are as such highly substantiated, especially when the study was conducted in a partnership between the MIT Sloan Management Review and the IBM Institute for Business.

The study divided the participating companies into top performances and lower performers. The top performers were understood as companies which performed well within their industry and which outpaced and outperformed their competitors. The lower performance companies were institutions that performed less well than their competitors. The study found that the top performers were characterized by high levels of IT integration, with increased emphasis on large data analysis.

"Top performers approach business operations differently than their peers do. Specifically, they put analytics to use in the widest possible range of decisions, large and small. They were twice as likely to use analytics to guide future strategies, and twice as likely to use insights to guide day-to-day operations.

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(See "The Analytics Habits of Top Performers.") They make decisions based on rigorous analysis at more than double the rate of lower performers" (LaValle, Lesser, Shockley, Hopkins and Kruschwitz, 2010).

Overall, the top performing companies had relied on IT support at all levels of business decision making and strategic development and they were able to capitalize on this utilization in terms of competitive advantage creation, growth, efficiency and differentiation (LaValle, Lesser, Shockley, Hopkins and Kruschwitz, 2010).

3. Against large data and IT utilization

The benefits of large data analysis for the creation of strategic advantages within the firms are often recognized within the literature, yet it has to be recognized that the topic is relatively novel and has yet to be exhaustively discussed. And what is even more so notable is that, despite the proposed benefits of IT utilization, some authors also pin point to some specific problems.

One example in this sense is represented by Carmen Nobel (2010) who, while supporting the IT integration within firms as a means of decentralizing decision making, she also argues that the simple implementation of large data analysis and other IT tools is insufficient to ensure high quality organizational strategies and decision making. At this level, she then argues that the success of IT integration can only be guaranteed in a context in which the organizational management enforces a corporate culture based on trust and empowerment.

Aside from Nobel, other authors also raise some concerns related to large data analysis and IT integration benefits within the internal context of the economic agents. R.

A. Hayles (2007) for instance points out that the integration and utilization of Information Technology at various organizational departments and in an isolated manner can create more shortages than advantages. The ultimate implication then is that the firms have to couple their technologic utilization with the managerial function of planning

"Planning ensures that technology efforts are business driven, aligned with business strategies, and coordinated across the company as opposed to being done in silos (each business unit acting in a compartmentalized manner)" (Hayles, 2007).

In the specific context of big data, Edd Dumbill (2012) states that the usage of the large size databases reduces the flexibility of data manipulation and processing within the firm. In other words, the integration of large size databases requires constant upgrading of the information, and this might be complicated to attain; this trait is given by the static nature of the schemes used in the large size databases.

"Even where there's not a radical data type mismatch, a disadvantage of the relational database is the static nature of its schemas. In an agile, exploratory environment, the results of computations will evolve with the detection and extraction of more signals. Semi-structured NoSQL databases meet this need for flexibility: they provide enough structure to organize data, but do not require the exact schema of the data before storing it" (Dumbill, 2012).

Finally, the last set of disadvantages of big data is represented by the novel feature of the elements. Specifically, since the field is only in its inception stages, as it grows, it will soon be confronted with several shortages. For instance, there will not exist sufficient staffs specialized in the field and able to operate big data applications. Then, the legal background is not prepared to rule the new domain at levels such as privacy, intellectual property or security. And there will also be the constant need to integrate more and more data, from multiple sources (Manyika, Chui, Brown, Burghin, Dobbs, Roxburgh and Byers, 2011).

4. Conclusions

At the level of the shortages pegged to the integration and utilization of large data analysis and other tools of Information Technology, the main focus falls on the fact that these mechanisms are not self standing, and that their overall success depends on the organizational ability to combine them with.....

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