Business analytics: PESTLE, CATWOE, SWOT

Junior (College 3rd year) ・Business ・APA ・7 Sources

Business analytics is the wide use of data, statistical and quantitative analysis, management based on facts, and models for prediction and explanation (Liebowitz, 2014). The usage of management information systems (MIS) helps organizations streamline their financial and logistical processes while digitizing company resources. The program serves as a business intelligence tool that maintains accurate financial records and extrapolates possible business scenarios based on historical data. Today, organizations access more data at their disposal than ever before. Using a variety of big data efforts, the harnessing and exploring of volumes of data repositories to get business insights help firms to create a niche position for themselves in the market. It is imperative for organizations to make good use of ubiquitous connectivity and pervasive digitization to enhance customer satisfaction as well as create additional value. In the design industry, many firms are extensively offering the same products and services. This shows that the business processes have become essential in the creation of differentiation. For this reason, the firm ought to identify the business processes, which create unique capability and apply far-reaching data and analysis in support of these operations. Companies need capacity and tools to not only consolidate and understand the data but create valuable insights out of it. This, in turn, empowers decision making that support the unique capabilities and thus improves the business functions.

This paper focuses on the implementation plan, the MIS, techniques, and tools to use and an analysis of the value that MIS adds to the organization. Business analytics provide solutions for the business dynamics today through the application of efficient technology that increases performance and output drastically while reducing the operational challenges. Business analytics integrates the human resource, financial transactions and stock controls in one system enabling the business owners to analyze the progress at a click of a button.

Implementation Plan

Installation and commissioning of business analytics into a business is not an easy venture because it requires proper prior planning and procedure guiding the whole process. The readiness concerns include the IT, business, technology and data (Developing a Business Analytics Roadmap, 2013). On IT readiness, the business owner should acquire the right technical team that has the required expertise for the firm analytics. The experts should be enlightened on the latest technology and procure the right equipment and gadgetry for the analytics. The IT team should provide leadership on the entire issue of the analytics and identify obsolete applications of IT. Well-designed data models are recommended for secure computation and interpretation by downstream systems. The technicians need to provide guidance on the best IT solutions for the particular business with an aim to attain long-term goals of the firm. The next feasibility check is business readiness. The management of the enterprise documents the needs of the firm and in this case the limitations data analysis. Professional analysts will give direction on the areas to improve in the company. Technology readiness means identifying the correct tools and techniques. The tools to use depend on the objectives and roles that prompted the technology. Compatibility of the tools with what is presently in use by the organization is a crucial factor to consider. Infrastructure and security cannot be ignored when installing the analytics technology. A computer system, data storage, backup and sophisticated safety is of the essence. The business manager should then identify the important implementation partners who include consultants and IT service providers. Finally, data readiness guarantees the success of business analytics. The source systems need to be reliable and flexible to avoid potential failures when there is an influx of data. The IT technicians have to make sure there is adequate data coverage. The data quality risks should be addressed before they show up. The steps of the implementation plan include organization structure, mapping business objectives, data understanding, and analysis.

Organization Structure

This step entails the determination of the number of resources required for a fruitful business analytics implementation scheme. While the number of resources differs from one project to another, the rule of thumb is that the primary project team should comprise of an analyst, statistical modeler and the developer (Abdelhafez, 2014). A fully functioning team will as well comprise of a project leader or manager, evaluators and business analysts. The firm should ensure that the right staffing is in place and are adequately oriented. It is worth noting that experts with mathematical background are difficult to find and the finding of the key skill set is vital for the successful implementation of business analytics. The next step concerns the familiarization of the project team with the firm analytics technique, which is the regression model procedure as well as the general acquaintance with the framework and guidelines to be used. It will entail the training of the staff and clarify on various issues.

Mapping Business Objectives

The mapping of business objectives is one of the underpinnings in the effective implementation of the firm analytics. This phase questions what is intended to be solved. Whereas this step is usually perceived to be a simple issue, it often has recurring problems. It is essential to spell out how the company can use the predictive analytics instead of outlining the concerns that they are pursuing an elucidation. This means that first thing to consider during the implementation of the business analytics is to have a business understanding of the issues (Duan & Xiong, 2015). Analytics is based on an explicit knowledge of the business knowledge and mathematics, with the former being precise in the solving of specific problems. As the leader of the analytics implementation team, the best practices should be followed, and this entails the mapping out of business aims to the precise inquiries of the analytics solutions.&

The optimization of the enterprise with the business analytics begins with strategy. As a company that is defined by data-driven strategies, the application of quantitative outcomes to the prospective business decision is recommended. Since the organization wants to improve marketing return on investment, the platforms shall be connected to the web-based application as a service database to offer real-time monitoring as well as metric measurement of activities. This is in consideration of the importance of the point of reference performance that reflects the sustainability and profitability of the enterprise into the future. The metrics selected should be in line with the process and turn be able to measure the strategic business operations return on investment.

Data Understanding

Data availability and quality are two of the main issues that impact on the outcome of business analytics. As the best practice about dealing with the problem of data quality, they are considered before the undertaking of the project implementation proceeds. While the data does not need to be perfect to realize a successful analytics project, the managers ought to understand the limitations that face the project (Liebowitz, 2014). Furthermore, various statistical techniques can be deployed to enhance the outcomes as well as minimize the issues relating to the quality of data. This can be achieved through the segmentation of the projected outcomes or those with a great likelihood of data-quality concerns for assessment results. Concerning the availability of data, it is more complicated for the reason that results can be extrapolated even without the availability of data.

The internal enterprise systems that are connected to the various databases enhance data collection. This is in addition to the metric tools that are set up for analytic reporting as well as the various electronic invoicing points. Owing to the numerous activities that the design company undertakes, the business analytics reporting will help the firm in the measurement of the current performance, productivity as well as give projections regarding performance. The team will dig into the records of the enterprise as well as find any relevant information on the past activities that were undertaken.


The outcome of the business analytics is dependent on the application of understandings in relative testing. The implementation of the business decisions has to be founded on actual findings with the comparison of the references on the aggregate sector performance indices (Liebowitz, 2014). This means that the team has to scrutinize the collected data to bring out any meaning accurately. To ensure this, trials ought to be conducted first before proceeding, which uses various variables grouped into independent and dependent variables. The existing relationship can be established and graphically presented. The visualization of the analytics results can be achieved through different ways such as the dashboards. This will provide a way for the decision makers within the design firm to quickly grasp and understand the meaning of the resulting analytics. Some of the key policy makers should advise of how they want the information obtained from the business analytics to be presented. Of course, this should happen before embarking on the firm analytics project implementation. Even so, the latest advances in visualization techniques shall be used in the planning of the dashboard, which would encompass the deployment of 3-D graphs that integrates predictive analytics, dollar value, and statistical control process evaluation. This will ensure that the analytics can as well be used in operational and strategic areas. The results will further be presented to the management. The last phase depends on the approval of the recommendations by the Directorate. However, the firm can address the various challenges proactively by putting measures in place to mitigate against their occurrence. First, the right staffing is essential to not only implement business analytics function but also to run and work with it. Even so, having the personnel with the right skills and knowledge about business analytics system is essential. Not all the employees have the skills and competence required; hence it is the organization to source for the right personnel. Secondly, because the cost factor used in the implementation along with the maintenance is high, the company should raise enough capital to fund the whole system before the start of its implementation. Because of the complexity of the application of business analytics, and the period it takes to get the system in place, there will be a need for step by step implementation of the to enhance the efficiency and success of the project.

Management Information Systems

Management Information System (MIS) is the use of computer technology to record, process, analyze and store data to manage and run an organization. The system involves transactions, bio data of staff, executive information, inventory, E-commerce, and informatics. The MIS replaced manual labor that was prone to errors and limited to exhaustion. The system has components that require a command in a click of an icon and others which operate automatically by the default or modified settings. Security surveillance and camera are also connected to the MIS system to enhance safety in the premises of the business.

The firm can apply various business analytics scenarios in its daily business operations in multiple situations. With the right kind of analytics, the design firm can obtain richer insights by drawing chunks of data from different connected databases to uncover hidden patterns as well as relationships concerning its products and clients. Through prescriptive analytics, the firm will be able to understand the right actions to be taken in the future. This is the most valuable sort of analysis and often results in recommendations for the next steps to be taken. In predictive analytics, forecasts are made on the probable scenarios that might happen. Even so, with descriptive analysis, the design firm shall be in a position to understand the on-time happenings based on the incoming data. Also, the company can apply diagnostic analysis to provide insights of the past scenarios and why they happened as such. The outcome of the analysis can be presented on an analytic dashboard.

Importance of MIS

MIS is an application of technology that is versatile compared to the human resource that is marred by fatigue. MIS minimizes bias and encourages impartiality. The system is efficient and an effective business strategy employed by visionary entrepreneurs. MIS generates data from statistical figures and information can be contrasted over time to predict future trends in business and plan accordingly.

Techniques and Tools Utilized with Illustrations

Business analytics use different technologies and tools to promote the performance of a firm. The techniques are highlighted in acronyms, and they include PESTLE, CATWOE, and SWOT (Business Analytics Techniques, 2013). PESTLE stands for Political, Economic, Sociological, Technological, Legal and Environmental. The six tools are external elements that influence a firm and its operations. The political factor affirms that the government of the day has a say on the business climate through the policies enforced. For example, if there is an exemption of some taxes and customs duty, then the business will experience a boom whereas the increase in taxation will affect entrepreneurs negatively. Economic influences refer to the impact of the global, regional and national economy depending on the scale of the business. For example, oil crisis is a thorn in the flesh of the international trade leading to increasing in production cost and subsequently inflation. Sociological factor sheds light on the role of a society in an organization considering culture and lifestyle of the populace. Technological examines the impact of the present and emerging technology in the business. Legal influences acknowledge the effect of the national and global legislation on the particular organizations and their brands. Finally, Environmental factor cites the impact of the local, national and even world environment.

CATWOE refers to Customers, Actors, Transformational process, and Worldview, Owner and Environmental constraints. This technique encourages critical thinking on the rationale and goals of the business. Customers judge a company by the benefits they derive from it. Actors are the people involved in the organization for production or providing solutions. Examples include the staff, technicians, auditors, clients, suppliers and business partners. The transformation process is gradual and continuous affecting the entire business system. Worldview is the image of the firm to the community. Environmental constraints are the business inhibitors to grapple with in the course of growth.

SWOT is the initials for Strength, Weakness, Opportunities and Threats. The power element assesses the achievements and competencies of the firm. Weaknesses tool evaluates the shortcomings of the organization. Opportunities factor emphasizes on seizing the possible chances of boosting the business, for example, identifying an unexplored market for a given commodity and stepping in before anyone else. Threats are hostile forces that pose risks to the firm and the entrepreneur ought to neutralize them.

Added Value to Organization

Business analytics has immense benefits to the organization if properly implemented and has provided many companies with a competitive edge for many years (Ghoshal, Larson, Subramanyam & Shaw, 2015). It makes an organization to be more competitive and ensures that fact-based decisions are made faster and better. By accessing valuable data, the firm is given more power to make accurate decisions, which could be used to leverage the business. The insights gathered help to automate and optimize business processes while also improving operational efficiencies. The most recent versions of business analytics take good care of the presentation of the data by the analytics team. The visual representations appeal visually and present the insights in an organized manner. Besides, with the capability to collect a vast volume of information in a fast way and its presentation in a visually appealing manner, the firm can be able to formulate strategies to realize stated objectives (Kowalczyk & Buxmann, 2015). This, in turn, encourages the organization to adopt a culture of effectiveness as well as a collaboration where employees can express understandings and share in the managerial course.


Business analytics feature as an advancement in business by use of technology. It is a current path to follow to combat the challenge of the business dynamics in the contemporary world. The implementation plan is first to step into embracing this inevitable change hence the actions highlighted give explicit details towards establishing analytics. MIS is a significant solution to many organizations, and it has many merits. Business analytics is implemented using various techniques and tools, which include PESTLE, CATWOE, and SWOT. Business analytics is value-adding to any organization where it is implemented. This is doing business the modern way.


Abdelhafez, H. (2014). Big Data Technologies and Analytics: International Journal Business Analytics, 1(2), 1-17. Retrieved from

Analytics Roadmap. (2013). Retrieved April 22, 2017, from

Duan, L., & Xiong, Y. (2015). Big data analytics and business analytics. Journal of Management Analytics, 2(1), 1-21. Retrieved from

Ghoshal, A., Larson, E., Subramanyam, R., & Shaw, M. (2015). The Impact of Business Analytics Strategies on Social, Mobile, and Cloud Computing Adoption. Academy ofManagement Proceedings, 2015(1), 17096-17096. Retrieved from

Kowalczyk, M., & Buxmann, P. (2015). An ambidextrous perspective on business intelligence and analytics support in the decision process: Insights from a multiple case study. Decision Support Systems, 80, 1-13. Retrieved from

Liebowitz, J. (2014). Business analytics (1st ed.). Boca Raton: CRC Press.Developing a Business

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