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Factors to Take Into Account When Upgrading the Company S IsResearch Paper

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The company wishes to upgrade its information systems, which is natural given the rapid pace of change in information technology. There are two overarching objectives for this upgrade: improve cybersecurity and enhance managerial decision-making. These two goals are completely different, but they are not mutually exclusive. There are several different areas that have been targeted for these improvements: hardware, software, networks and telecommunications, decision support systems and data gathering. This report will outline the latest information about these issues, and offer up guidance with respect to the proposed information systems upgrade.


Hardware is a critical underpinning for information systems. Hardware includes computers, servers, smartphones and routers. With respect to security, a general rule of thumb is that the mode modern the equipment, the better it will be with respect to security. Most security breaches, however, do not occur at the hardware level. It is recommended, however, that the company builds redundancy with respect to critical information and data into its systems, in the event of system failure.

Where hardware is critical is for improving the data collection and decision-support systems. Modern big data analytics requires the automated gathering of vast amounts of data. Decision-support systems require that this data is gathered, stored, and then available for recall quickly. Not all hardware is capable of handling the workloads demanded by big data analytics, however. High performance servers and hard drives are critical to handling the data loads required of modern analytics. While it is possible that traditional low-power embedded processors can handle this load, our purchasing specs must be carefully conceived with big data in mind -- anticipating exponential growth in our data gathering and usage as we build out these upgrades (Malik & Homayoun, 2015).

We will also need to do a full review of cloud computing, and the role that it can play in big data analytics going forward. The new system architecture should be scalable over the course of the next few years. Cloud storage and retrieval can play a role, and is particularly valuable with respect to the use of mobile technology and enabling the company to have decision-support systems that are available at all work sites, and even remote for managers and sales staff who are on the road (Agrawal, Das & Abbadi, 2011). It will be essential, however, to ensure that the latest security measures are put into place with respect to cloud computing, and that a training program is developed to ensure that our people are knowledgeable about security best practices when utilizing cloud computing and mobile technology.


As with hardware, the more modern the software application, the better its security. However, there are many software packages that can be utilized to improve our security. It is recommended that the company has a specific security software vendor that is capable of offering a comprehensive security suite, along with the ability to work with us to ensure that our security is up-to-date. Off-the-shelf solutions are not recommended for this company, as they can be dated, and more importantly they might not address all the security weaknesses that are specific to our organization. The company should have a full-time cybersecurity officer, if it does not already have one, not only because of the high risk of attacks, but the potential damage that such attacks can cause.

One of the things that big data has revolutionized is managerial decision-support systems. It is recommended that the company moves immediately to data-driven decision-making. First, we need to identify the data that we need to gather, and that will guide the search for specific software that we require to gather and process data, then subsequently assist with decision-making. Cloud-based decision-support systems are relatively new, and it is worth exploring this for the company, specifically as a means of understanding the transactions we conduct, and how to make better decisions based on hard information (Demirkan & Delen, 2013).

Networks and Telecommunications

If the company has not yet embraced the move to mobile, it needs to. Mobile, combined with the cloud, allows for the gathering of movement of information anytime, anywhere. There are requirements technologically, however. The company would need to make decisions about supplying devices, for example. This can be a costly hardware purchase, and the benefits of this would need to be weighed carefully.

Security is a significant issue with networks, because if somebody gains access through one portal, they can often gain access to all or most of the information that is contained within the network. While modern hardware and software will certainly improve security, it is not necessarily enough. Clouds can also be susceptible to cybersecurity risks. There are a number of companies that provide security solutions with respect to both networks and clouds, and it is recommended that the company work with a vendor for this (Shin & Gu, 2012). It is important to remember that physical devices are often used to breach network security and download data, so there will need to be specific detection of physical devices required as part of our security protocols (Pierson & DeHaan, 2015).

The biggest decision facing the company at present is the degree to which cloud networks should be implemented. This will be based largely on business need. Cloud networks pose unique risks compared with traditional networks and therefore a cost-benefit analysis will need to be undertake with respect to the implementation of cloud networks. In addition, it is recommended that the company reviews its telecommunications provider, to ensure that our provider has not only the technological capability to support our program going forward but that it has the security that we need as well.

Decision Support Systems

Decision support systems are used to provide real-time support for people making decision within the organization. The objective is to reduce uncertainty and risk with respect to decision-making. Ultimately, this can be done through gathering data and ensuring that decisions are made on the basis of evidence and the best available information. A decision-support system, therefore, is a garbage in, garbage out system. While there are a number of different systems available, it is important first to define the decisions that need to be supported, the types of information that will help people to make those decisions better, and to set up the means by which that information can be gathered. Thus, the system needs to be conceptualized fully before it is implemented.

One of the things most often stated in the literature about decision-support systems is that a high degree of training is typically required for these systems to be valuable. Professionals who are accustomed to making decisions a certain way are hesitant to modify their decision-making methodologies quickly. Rather, they often resist change. Training programs to illustrate the value, and ensure that non-IT staff can understand how the system works and why it is superior, will be important (Shibi, Lawley & Debuse, 2013).


While the different components of the information systems are discussed on their own in this report, it is important to remember that all of these elements -- hardware, software, DSS and networks -- all work together. Thus, the system upgrades should be conceived as a whole, and then decisions made about each individual component based on the overall strategy and objectives that have been determined.

The most important takeaways from this analysis are the importance of maintaining up-to-date systems, both in terms of hardware, software and networks, for security, and having a dedicated IT security officer to ensure that cybersecurity risks are minimized. Another important takeaway is that the company needs to look at big data and cloud computing as options for modernizing the information systems. Big data in particular is important, because it can give the company competitive advantage, allowing managers to make better decisions based on the data that has been gathered. The system upgrades should ensure that the company can gather the information it needs and that this information can be processed and subsequently implemented into decision-support systems for managers. Cloud can be investigated, though its value to the business will depend on the nature of the business, how much remote work is done, and other factors that are firm-specific. These upgrades should not be done to do business as usual, but better; they should be designed to overhaul how the company does business. Our company is at a crossroads with respect to data-driven decision-making, and the IT upgrades should reflect a decision to pursue data-driven decision-making with vigor.


Agrawal, D., Das, S. & Abbadi, A. (2011). Big data and cloudy computing: Current state and future opportunities. EDBT 2011. Retrieved March 31, 2016 from http://www.users.csbsju.edu/~rdissanayaka/courses/f14/csci312/p530-agrawal.pdf

Demirkan, H. & Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems. Vol. 55 (2013) 412-421.

Malik, M. & Homayoun, H. (2015). Big data on low power cores. 33rd IEEE International Conference on Computer Design (ICCD). Retrieved March 31, 2016 from https://ece.gmu.edu/~hhomayou/files/ICCD15-1.pdf

Pierson, G. & DeHaan, J. (2015).… [END OF PREVIEW]

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