Business Analytics

Table of Contents

Introduction 3

Brief of Business under Study and Summary of Possible Business Analytics in the Multiple Scenarios 3

Business Analytics Implementation Plan 5

Benefits and Disadvantages of Business Analytics 5

How the Business Can Be Proactive in Addressing these Disadvantages 6

Challenges the Organization May Face Using Business Analytics 7

How the Organization Can Be Proactive in Addressing the Challenges 7

Proposal of 3 Business Analytic Techniques for the Organization and their Benefits and Disadvantages 8

Implementation Plan to Integrate Business Analytics in the Organization 10

Backup Proposal for the Organization’s Management 11

Conclusion 12

References 14

Business Analytics

Introduction

The increasing competitiveness in the world facing organizations requires that businesses are aware of what drives demand and how to lower cost of operation. Indeed, without having sufficient information about these factors, businesses are likely to make losses. Further, information is important in ensuring that firms are able to attract qualified personnel that help boost their performance. However, such information cannot be available without the management collecting data from different sources and analyzing it to get the different trends. Business analytics acts as a tool that supports organization to gather relevant data and carry out statistical analysis to help in decision-making (Park & Thambusamy, 2017). The approaches make it possible for companies to make decision pertaining to production, marketing and expansion. Indeed, it becomes relatively easy to make decisions through aid of analytical data collected over time from different sources. Business that are embracing business data analytics are able to prefect the changing dimensions in the market and therefore remain competitive. It is important that organizations use business analytics in their decision making to ensure they remain profitable. 

Brief of Business under Study and Summary of Possible Business Analytics in the Multiple Scenarios

A design company that utilizes technology in their daily activities but fails to embrace business analytics for analyzing their data is likely to remain uncompetitive. The business has significant amount of data it collects from its clients and its process, but rarely uses that data to make decisions. It is also evident that the company does not have working connected system that helps share data in the different departments within the firm. Actually, there are different databases in different departments and this makes it challenging to use entire data in the organization for decisions. Each segment of the business seems to carry its activities on its own and it takes relatively long if consultation takes place with the other departments. The limitation in available data and lack of business analytics also makes the business unable to make decision to expand its operations in a different locality. If it embraces business analytics, the company can get at a glance whether such a move is viable and how it helps support the strategic plans of the firm. 

Different business analytics approaches are relevant in providing a solution to the design company, empowering it to meet its objectives. Descriptive analytics is relevant to the company because it will help bring ideas of what happens in the organizations (Bayer et.al. 2017). Therefore, the management is able to understand how data from different departments come together to aid in decision-making. Actually, through approach, the management is able to identify the data similarities and how helps the company remain competitive. Further, another approach their company should use so diagnostic analytics that aid in identifying problems that influence the disintegration of data from different departments (Bayer et.al. 2017). The analysis would form a basis for combining data from the departments into a single location. Predictive analytics is necessary in supporting the company identifies the likelihood of the organization performing in the new market (Bayer et.al. 2017). The method uses information from diagnostics and descriptive analytics to predict trends in future and thus an important forecasting tool. Actually, using the analytic methods by the business makes it possible for the business to handle the multiple challenges it is currently facing in decision-making. 

Business Analytics Implementation Plan

Benefits and Disadvantages of Business Analytics

There are various benefits that business analytics offers to business such as management of big data (Bayer et.al. 2017). There are complex data that organizations rely with in order to make decisions. In fact, any organization has varying activities taking place and any process affects the progress of the other. A change in any of the processes can have significant change in terms of costs to the company thereby need business analytics to prevent such occurrences. An organization with business analytics is able to make faster decision even when presented with large data from various departments. Through business analytics big data is synthesized in real time and decision made by the management (Bayer et.al. 2017). Another benefit is ability of organizations to track their performances in different departments. The management is thus able to trace areas of the organizations that reduce profitability of the company thus carrying corrective actions. Further, business analytics allows easier visualization of data in an organization (Bayer et.al. 2017). Actually, through use of different applications, it is possible to present data in graphs that makes their interpretation relatively simple. 

However, business analytics present different challenges to organizations especially the concern of different people giving differing conclusion from single data (Bayer et.al. 2017). Business analytics helps bring big data and simplify it in form of graphs or statistics that makes it easier for people to handle. Despite this effort, the interpretation of such information is not consistent in different individuals. Therefore, availability of the analytic tool does not guarantee correct decision by some individuals in the organizations. There is possibility of making poor decision using the analytic data if the person who studies the information has bias. Another disadvantage of business analytics is its exposure to insecurity from cyber criminals (Bayer et.al. 2017). The technological advancement in the world poses a threat of hacking to organization data where such information is changed. Relying on data that hackers interfere with has potential to influence poor decisions. Further, business analytics suffer from changing regulations that govern is business intelligence (Bayer et.al. 2017). Organizations face legal sanctions if they breach some regulations especially on personal data. The legal suits could damage reputation of a business and further add to its operational costs through payment of fines. 

 How the Business Can Be Proactive in Addressing these Disadvantages

Despite the disadvantages, the benefits of business analytics is relatively higher and therefore organization should embrace ways to handle the disadvantages. The management of organizations needs to conducts training on its employees to enhance their analytic data interpretation in their company (Sharda et.al. 2013). The training ensures that the perception and understanding of information from business analytics does not vary significantly. Further, the business needs to engage different individuals to interpret data and develop a consensus on what decision to make as a group. The incidence reduces issues of bias decisions. Ina addition, organization requires investing in cyber security procedures such as installation of antiviruses (Sharda et.al. 2013). Further, the business requires encrypting its website to ensure that hacking does not take place. Forecasting is also necessary to ensure that the firm is aware of changing regulations in the industry to avoid legal suits. Further, when using any data especially from external sources, the business needs to understand the regulations such information (Sharda et.al. 2013). The move makes it possible for an organization to have relatively few legal battles as it relies on business analytics. 

Challenges the Organization May Face Using Business Analytics

Some of the challenges that face implementation of business analytics include inadequate support from the software providers (Sharda et.al. 2013). When the providers fail to engage with the employees, they find it challenging to use the tool in analyzing data in the organization. The situation results to underutilization of the analytic tool. Therefore, an organization is likely to suffer from low return on investment due to minimal utilization of the tool. Another challenge is poor reception the analytics by the employees. It is common to find employees who are unwilling to embrace any changes in their company. Some find it cumbersome to collect big data and bring it together to enable make decisions. Another challenge is inflexibility of some business analytics software that is only useable in computers (Sharda et.al. 2013). Actually, some of the software is able to analyze data when installed in computers. Indeed, it is common to find the software providers putting such tools in company computers. Therefore, the analytics is only accessible within the business premises.

 How the Organization Can Be Proactive in Addressing the Challenges 

Organizations require carrying background check when engaging business analytics provider to identify their reliability (Sharda et.al. 2013). Further, it is important to ensure that the business engages the providers through contractual terms to ensure they provide the service for a given period. Indeed, the approach makes the provider work with the organization to ensure that it gets value for such an investment. Business also requires engaging their employees before deciding to introduce data analytics in their organizations (Sharda et.al. 2013). Actually, training is necessary to ensure that the employees are aware of the importance of business analytics and its support on their work. Further, the management requires gathering any concerns or recommendation from the employees before business analytic introduction. The procedure enhances teamwork and ensures there is significant support of the system when introduced into the company. Businesses also need to ensure that they embrace business analytics that are compatible with mobile devices (Sharda et.al. 2013). The situation makes it possible for the employees to access such data using their mobile phones. Therefore, sales persons can share data with the organization management even when they are outside the company conducting marketing activities. 

Proposal of 3 Business Analytic Techniques for the Organization and their Benefits and Disadvantages 

The design organization needs to embrace different analytic techniques to enable it to match the demands in the market. Descriptive analytics is necessary for their company because it helps in bringing together large data and forms simple data from it (Mujawar & Joshi, 2015). Therefore, it is necessary in helping the company to summarize different finding into a single place. The techniques allow organizations to present raw data in organization in understandable methods for managers, shareholders and investors. Indeed, the stakeholders are able to understand areas where the organization has strengths and weaknesses thus able to develop mechanisms to collect any limitations. Descriptive analytics major benefits include ability to present detailed data that helps understand behavior, attitudes and feelings (Mujawar & Joshi, 2015). Further, the method further gives details of why people or customers behave in a particular manner (Mujawar & Joshi, 2015). Therefore, the method is effective in bringing together different departments in a common platform of responding to consumer’s needs. However, the methods limitations such as overreliance on generalization of huge data through percentages may result to erroneous decisions (Mujawar & Joshi, 2015). Further, the method suffers from inability to carry systematic comparisons especially where subjective information is gathered (Mujawar & Joshi, 2015). 

Diagnostic analytic is also necessary for the business because it helps in finding reasons why things happen in a certain meaner. In the organization, there is poor coordination of data in different departments. Therefore, the tool is necessary in identifying what influences such an approach. Further, it brings in ideas on whether any interpretation of data in the organization took place in the past and why it failed. The method thus ensures that the organization gets viable solutions to present and past problems that threaten its performance (Mujawar & Joshi, 2015). The method has benefits such as allowing the management to understand why sales are high or low in certain market segments (Mujawar & Joshi, 2015). Such information helps in planning how to respond to needs of such markets. The method is also beneficial because it helps establish causal relationships while focusing on past trends (Mujawar & Joshi, 2015). Despite the benefit, the method has limitations such as some past data being obsolete (Mujawar & Joshi, 2015). The environment where organization is operating is changing and relying on past data for decision-making could be erroneous. Further, the method may fail to provide adequate data from experiences limiting the options of decision making by the organization (Mujawar & Joshi, 2015). 

Predictive analytics is also relevant to the organization especially concerning starting new operation in a new environment. The method allows the management to forecast on the possible responses of the customers (Mujawar & Joshi, 2015). Therefore, the business is able to have an idea on the possible demand of its products before rolling out its operations. The impact is reduction in time used to start the business in a new environment. The method has benefits such ability of an organization planning adequately before penetrating new markets. Therefore, there is proper understanding of factors such as competition and its effect on performance. The method further helps a business to prepare for challenges that aid may encounter in the new segments (Mujawar & Joshi, 2015). Therefore, upon starting of operation, the company is able to run without interferences of uncertainties that could occur if the tool is not used. However, the tool has limitations such as inaccurate prediction that pose possible lose to the organization (Mujawar & Joshi, 2015). When organizations are over ambitious, they are likely to predict wrongly about the possible reception in the market. Another limitation is reliance on opinions through different media such as social media that maybe misleading (Mujawar & Joshi, 2015). Therefore, the method may influence a firm to take actions that are not viable in penetrating to a new market in future. 

Implementation Plan to Integrate Business Analytics in the Organization 

When implementing the business analytics, the first step is to ensure that the databases in the organization are accurate (Halaweh & Massry, 2015). The procedure involves removing any irrelevant files and records gradually. Further, the step involves choosing the source of data to be relied in the company. Internal sources make the significant reliable data source for an organization. In addition, there is need to establish a uniform process of data entry in the organization to enhance consistency of information. The other steps involve building a road map of long-term business analytic that is comprehensive and has timelines (Halaweh & Massry, 2015). The stage helps management to carry analysis of existing condition analyzing what processes to keep and what to avoid. Additionally, the stage allows choice of necessary technological infrastructure to support the analytics. 

The next step involves empowerment of employees in the organization to embrace data driven and reduces possible resistance of the intended changes (Halaweh & Massry, 2015). The process involves offering training to the employees to make them conversant with the analytics and understand their role in supporting its success. Through the training the employees becomes enthusiastic and are willing to support implementation of business analytics. The stage that follows is consideration of possible integration options tonsure that the business analytics fit in existing information technology systems (Halaweh & Massry, 2015). Management need to ensure that the software is able to extract data from different modules within the company such as from human resource, marketing and finance departments. Interconnectivity of the system improves the efficiency of business analytics. The last step involves monitoring and evaluation of the data systems (Halaweh & Massry, 2015). The management requires monitoring the software to ensure they are utilizing it maximum. The procedure further enables organizations identify any limitation of the analytics and ways to improve it. The impact is a working business analytics that supports the objectives of the organization. 

Backup Proposal for the Organization’s Management 

A different proposal that the management of the organization need to consider is use of prescriptive analytics that suggest outcomes on basis of course of actions. The method is different from the initial proposal because it offers businesses an opportunity to consider different action and connects them to possible outcomes (Mujawar & Joshi, 2015). Therefore, management has adequate information in making decision about use of business analytics. Another difference from previous proposal is; ability to use strong feedback mechanism that connects outcome and actions (Mujawar & Joshi, 2015). The situation makes it possible for organization to change their outlook when some set of data fails to give required results. Indeed, it boosts flexibility of decisions by organizations as they rely on data to boost their performance.  The prescriptive model further allows organization to use optimization methods in accurately determining performance of a business (Mujawar & Joshi, 2015). Therefore, before decision to expand its operations, the business can be conversant of accurate scenario in the market and probable performance. Through simulation approaches, the method allows management to place different metrics on key performance areas and choose the best combination. 

Conclusion

Business analytics are important in enhancing the ability of organization to make decision pertaining to their production or marketing activities. Further, it provides a platform for business to understand possible scenarios in new market segment where they can expand their operations. A design company with disconnected information system is likely to suffer from slowed and inaccurate decision-making. However, through use of business analytics, the business is able to have accurate data that supports all decisions it makes regarding profit maximization or cost reduction. There are different business analytics approaches that are available for their business such as descriptive, predictive and diagnostic methods. Understanding how they work and providing solution to their specific challenges make them an important tool to business performance. However, following an implementation procedure through various steps ensure that the analytic tools are effective. It is also important for the business to consider use of prescriptive analytics that offers accurate relation between results and actions that influence such outcomes. 

References

Bayer, H., Aksogan, M. Celik, E. & Kondiloglu. (2017). Big Data Mining And Business Intelligence Trends. Journal of Asian Business Strategy, 7(1), 23-33. 

Halaweh, M. & Massry, A. E. (2015). Conceptual Model for Successful Implementation of Big Data in Organizations. Journal of International Technology and Information Management, 24(2), 21-34. 

Mujawar, S. & Joshi, A. (2015). Data Analytics Types, Tools and their Comparison. International Journal of Advanced Research in Computer and Communication Engineering, 4(2), 488-491. 

Parks, R. F. & Thambusamy, R. (2017). Understanding Business Analytics Success and Impact: A Qualitative Study. Information Systems Education Journal, 15(6), 43-55

Sharda, R., Asamoah, D. A. & Ponna, N. (2013). Research and Pedagogy in Business Analytics: Opportunities and Illustrative Examples. Journal of Computing and Information Technology, 21(3), 171-183