InfoTech Importance in Strategic Planning
InfoTech Importance in Strategic Planning
Introduction
Information technology (IT) plays a central role in any business, mainly given today’s ever-increasing business uncertainties, swiftly changing tools, funding issues, and completing priories. As such, having a practical IT roadmap will help to lead the business in the right direction. In essence, a sound IT strategic planning framework would result in increased returns on business investments. It also ensures the prioritization of scare resources to guarantee the success of projects and initiatives. Besides, the process followed when creating an IT strategic plan remains as vital as the plan itself. Such a process ensures that all stakeholders have a part to play in an organization’s operational activities. Moreover, because IT often accounts for nearly 15-20 percent of a firm’s annual budget, undertaking an efficient IT strategic planning becomes pertinent for organizational success. Equally, such planning is paramount in supporting as well as sustaining a business’ strategy, controlling risks, reducing costs, and clarifying the gains that business initiatives or projects provide to the company and end-users. This paper looks to looks at different areas of IT strategic planning, including data warehouse architecture, big data, and green computing in informing a firm’s decisions.
Data Warehouse Architecture
Data warehousing refers to the process of gathering and controlling data from various sources to generate significant business insights. It usually serves the purpose of connecting as well as measuring data from diverse sources. Pearlson, Saunders, and Galletta (2019) assert that data warehouse stands at the core of any business information system, which helps to analyze and report vital facts that drive success. It blends technologies and components that assist the tactical utilization of information. According to Dymek, Komnata, and Szwed (2015), data warehouses provide companies great sources of clean, precise, timely, and unified information for reporting, analyzing, and policymaking. They argue that these warehouses often integrate information from varied sources and warrant efficient access to synchronized data. They also say that these data warehouses include systems that have different characteristics, mainly concerning their makeup and architecture.
According to Pearlson, Saunders, and Galletta (2019), a successful data warehouse has five central components, including data sources, software tools, data-driven environment, as well as a skilled workforce. With data sources, a warehouse has data streams and repositories that allow information collection, storage, and analysis. Software tools help in extracting information from data sources by a process known as data mining. This process also plays a vital role in exploring data warehouses and other data sources to facilitate decision-making. In turn, this analysis helps to identify trends, habits, features, and other improvements. This evaluation might allow firms to better comprehend their customers by addressing several customer-business related questions.
With a data-driven environment, it helps to provide a setting or culture that supports data analytics. Pearlson, Saunders, and Galletta (2019) state that the value of a data-driven culture lies in its ability to support a business’s success. In other words, they affirm that it is a leading success factor for any given transaction. Given this environment, a company requires to along its business information system plan and organizational strategy with its business strategy. Workers can also use information streams to analyze and make amendments as necessary as possible continually. In this sense, an organization must ensure alignment of its corporate culture, incentive systems, and performance metrics to achieve a productive data-driven environment. While different firms have analytical tools in place, they often fail to use them for mainstream decision generation. Thus, companies that gain competitive edges from analytics frequently utilize these capacities as fundamental aspects of their operations. Furthermore, many of these companies usually expect data-driven choices and have created robust analytics in their teams to increase the use of data in every business decision-making process.
A skilled workforce also builds a successful data warehouse. While data analytics and technologies play integral parts, experts help in pointing areas with anomalies. Moreover, even with the most complicated tools and techniques, people fill a special place in every aspect of such data analytic capacities. In this regard, managers have to leverage the knowledge and skills of workers to enhance decision-making processes. It means that leaders must set examples for others to follow. Perhaps the most significant role for leaders is leading companies in achieving useful data warehouses.
Data warehousing also continues to evolve, with several trends emerging every time. For instance, over the past years, cloud innovations have changed from traditional servers to new things. Data warehousing has developed and continues to revolutionize cloud capacities in today’s turbulent environment. Companies such as Amazon and Azure have become significant leaders in using data warehousing services. Some of the main trends facilitating the application of data warehousing include the desire for self-service and data visualization, among others.
Big Data
Big data has transformed how businesses operate. It has also changed the way people manage, evaluate, and leverage information for business success. It has a great deal for any business in the world today. The onslaught of the internet and other related tools has also curved a profound uptick in the level of information companies gather, control, as well as examine. Along with the big data concept comes the possibility to unravel significant insights for every sector, industry, and market. Today’s utilization of big data opens up numerous prospects and avenues to capture ideas that propel novelty. From more precise business forecasting to high operating competences and better customer understanding, increased big data drive capacities that could change the world, transforming people’s lives, advancing businesses, and protecting various activities from real and perceived exposures. Indeed, the notion of big data has thrived for years. Schmarzo (2013) argued that most firms today know that if they excellently capture all the information needed from diverse streams into their dealings, they can use them to their gain.
One of the sectors that have pointedly benefited from big data is the healthcare industry. In this area, data analytics pose a significant advantage in reducing the costs of medicine, treatment, and operational expenses. It can also help to healthcare facilities to predict disease outbreaks, avert avoidable conditions, and enhance care quality. I have seen what it means to use big data in the healthcare industry. For a long time, I have followed several developments and advances in this sector. Its application has countless benefits across the industry, including increasing care outcomes. Now that people live longer, treatment frameworks have transformed, and most of these changes have resulted from this concept. Doctors can now know about their patients as earlier as possible. They can also collect several signs of serious illnesses that might arise, enabling early interventions and treatments. Hospitals can also make predictions for improving staffing and patient engagement. In my view, big data places demands on firms as well as data management technologies by requiring putting in place the right people, appropriate policies, and suitable techniques to guarantee security, precision, and quality.
Green Computing
According to Saha (2014), green computing denotes the practice of utilizing computing assets and capacities in an environmentally friendly manner while upholding the overall computing trajectory. He also says that green computing involves IT solutions that benefit both people and the environment, mainly with the use of sustainability principles. As such, the goal of this notion includes reducing the utilization of poisonous materials, reducing climate change, and optimizing energy use efficiency. Several companies have made headlines in adopting and using IT green computing strategies today. One such organization is Dell Inc., which has successfully used this concept across its operations. The company holds the highest levels of standards and has always sought to maintain high corporate environmental responsibility. It has also promoted a multi-stakeholder team in designing its electronics to ensure ecological protection. The firm’s Electronics Products Environmental Assessment Tool, also known as EPEAT, has given Dell an advantage in aligning its production activities with sustainability efforts. For instance, all Dell products are bought through the EPEAT criteria to ensure that the organization stays in line with its objectives. It has also banned any export of its electronic wastes to developing countries. Besides, Dell also has an effective trade-in initiative for its equipment. It usually focuses on every way that can make its products as environmentally friendly as possible.
References
Dymek, D., Komnata, W., & Szwed, P. (2015). Proposal of a new data warehouse architecture -reference model. In International Conference: Beyond Databases, Architectures, and Structures (pp. 210-221). Springer, Cham.
Pearlson, K. E., Saunders, C. S., & Galletta, D. F. (2019). Managing and using information systems: A strategic approach. John Wiley & Sons.
Saha, B. (2014). Green computing. International Journal of Computer Trends and Technology (IJCTT), 14(2), 46-50.
Schmarzo, B. (2013). Big Data: Understanding how data powers big business. John Wiley & Sons.