Assignment:
Introduction
Analytics refers to discovering, interpreting and communicating important patterns in collected data. Analytics has been used in organizations since exercises in managements were put into place by Frederick Winslow Taylor in the late 19th century.
Today, with the introduction of computers in day to day running of businesses, organizations and most of the institutions, the use of analytics has been brought to a whole new level. These consequential patterns can help in decision making in different scenarios.
Business analytics refers to the proficient use of technologies in continuously exploring and investigating past business performance so as to make inferences and help in business planning and decisions. Predictive modeling and statistical methods are extensively utilized to help the management in making this decision.
Business analytics are applicable in a wide range of business and organization scenarios to help in making management decisions. Business analytics has been changed the way businesses look at their key indicators of performance.
The business analyst has responsibilities in the following areas:
1. They help in identifying the technical actions that would address a certain situations, also supports in delivering the business strategies.
2. They help in defining procedures they will use in organizations.
3. They help in supporting the implementations and operations of strategic plans.
4. They refine the techniques once they have implemented in order to tolerate changes while ensuring continued alignment with the business strategy.
Business Description
The firm is involved in the design. Design firms make designs to clients to meet their (clients) needs.
The business analytics can use different methods analytical techniques. For example, the orders for particular graphic designs vary seasonally due to upcoming promotions and holiday season. The firm should use business analytics to know when in the past they experience different designing orders. The firm should use business analytics to analyze data so that it can be able to make informed decisions.
The organization possesses technological equipment's but they do have any integrated system. The business should use analytics to connect its databases for easy access and efficiency of information flow.
The firm should also use business analytics to predict how the business would perform in a new environment it wishes to venture into. It would analyse all the factors that would seemingly impact its operations and success in the new environment.
Benefits and disadvantages of Business Analytics
Benefits
Business analytics creates a better operational efficiency- A business that uses analytics has its important information in a manner that it can be readily available to aid in any upcoming operation. Through Business Analytics, the organization can be able to measure its performances in different departmental areas and give recommendations for improvement. Proper analytics help to create a rapid, fact-based culture to make decisions and thus reducing guesswork.
Better customer service- If business analytics are properly executed, they give a better response to customer needs and trends. They provide a better understanding of the customers' habits, especially buying and searching characteristics. Customers benefit as they receive better customer service which allows them to operate more efficiently and possibly gain a competitive advantage.
Profit optimization- Predictive modelling and statistical methods techniques help the business to make much more informed investment decisions which have a high profitability chance. Data collected gives the business an insight of what would happen if they choose to make one decision at the expense of the other, and analysing which investment decision would be more profitable.
Disadvantages
High initial investment- the business will have to incur high initial costs of laying out analytics system to help in their day to day operations. Setting up a business analytics personnel also means additional costs to the business. There would also be required to have the proper technological equipment, to analyze large amounts of data. This may force a business to halt some of its development operations to draw revenue toward installing and implementing business analytics.
The organization should have proper financing strategies to provide resources needed for the analytic system while ensuring that they do not neglect their development projects.
Losses of the investment do not pay off- If the business analytics does not pay off, the company stands to lose the high investment of resources and time. The possibility of the business analytics not paying off cannot be ignored.
Organizations should hire proficient business analytics to guide them on the appropriate analytic techniques usable in their organization.
There is also an issue of personnel needed to manage implementation and maintenance of this analytics. The systems also require regular maintenance procedures thus adding more costs to the business.
Organizations should emphasize the proper use of the systems to avoid regular breakdowns.
Challenges that the organization may face using business analytics
Even if there is provision of large quantities of data, to succeed in analytic process depends most on organization alignment and process for the chosen analytical technique.
There are challenges that the organization may face while using business analytics to aide in their decisions. Below are some of the challenges and how the organization can be proactive in addressing each of the challenges;
Strategic alignment- the organization may have some business analytics already in place. This might create difficulties in doing away with the old system of doing things and giving way for the new one. There would also be a problem with the staffs that have been conversant with the existing analytic to appreciate the new one.
The Proper Study of the already existing analytic would help to identify key operational areas that will have to be merged or replaced so that the new system operates effectively.
Promptness- the organization may face the challenge of quickly responding to an analytic request. There might be problems involved if the business analytics does not give a response to a decision problem quick enough to help in decision making. Taking too much time might lead to inefficiency.
The organization should liberate its analytical capabilities; they should pool together analysts who possess high analytic skills into one department. This would enable much quicker insights into demanding data insights
Availability of data- Analytic processes depends on bulky of relevant data data. Past data on organization's performance should be readily available for analysis and interpretation of its patterns. Analysts collect large volumes of data and then break down to more meaningful ones that will be analyzed to give results that can help in making decisions.
The organization should an assessment of its information systems. Sources of data should be identified and quality measured for both transactional and aggregated information.
Business Analytic Techniques That the organization Can Use
The firm can use time series, regression modeling and analysis, and cluster analysis. In the use of using the regression, the expert will create a model which will look at the different variables (Sedddon et al., 2012). This involves several calculation before the conclusion can be arrived at. For example, taking organization's scenario, the analyst may look and analyse the customers' buying habits during different seasons. Helpful fact about this model is that, it is very appealing, it also uses sets of calculation and this mean it uses the numerical data provided. One shortcoming of this technique is that it takes a lot of time doing calculations. The second limitation is that professionals are required to carry out this analysis.
Time-series forecasting is the second method. This technique allow us to predict future events using past data in mainly collected in intervals of time. Usually graphical representations are used in forecasting the future independence with how the graph looks like (Liebowitz, 2013. It has two main variables. Its advantage is that variables can be predicted at different intervals of time. This method consumes less time.
Thirdly, we can use cluster analysis. Cluster analysis involves dividing the provided data into small clusters. There should be similarity within individual clusters.One advantage of this technique is that it can be used in a wide range of variables. This technique is also easier to use. There could be difficulties to interpreting this clusters.
The Implementation Plan
It would be more advisable to use the regression model in our case. If managers adopt the laid plan. Various steps should be followed for an analytic system. Firstly, the staffing process should be in such a way that the necessary staffs implement to operate the systems are acquired. The firm having decided to use the business analytic technique, it is important that the management equips the firm with the necessary personnel that can handle the technology. The firm should make sure that the staffs needed to effectively operate the system are enough. The staffing step should take a maximum of three weeks. After the staffing process and the staff have been adequately oriented, the next phase in the implementation begins. The next task is the familiarization of the staff and the business analytic technique. The phase will involve training from training organizations hired by the organization. The process should take a maximum of two-three weeks. The implementation plan will first have some trials. After the staff has been trained, they will now go into the records of the organization and fish out information on past activities and performances of the organization.
The obtained data will be put together and analyzed to bring meaningful information. The variables can be divided into dependent and independent. The relationship between the two can be established, and then a graph is utilized to interpret the information, after which it is presented to the management. The next stage is the validity phase. The management scrutinizes the recommendations given for the use of business analytics and decides if it is worth the risk of investment or not. The next process is dependent upon the approval of the recommendations above. If approved, statistical methods are used in decision making
How these decisions affect firms determines the viability of the BA technique. The implementation plan takes a maximum of six to eight months.
Backup plan
If the stated plan does not succeed at any of the phases, several stages could be changed. First of all, the technique used will be changes. Other techniques suggested can still fit in our organization. Time series technique would be used. Our designs clients vary with time in many cases. This technique is relevantly cheaper than regression. Since the backup plan should not be more costly than the first one, there would be significant reductions in expenses. The amount of time for training of the staff will have to be reduced to one week. Due to unsuccessful implementation of the first proposal, the backup plan will have to take a maximum of three to four months.
Conclusion
Using past events iteratively, business analytics can help so as to predict future outcomes. The business analytic system is effective and usable by both the customers and the organization to make decisions. Cluster analysis, time series, and regression model are some of the analytical techniques used. Backup plan should be less costly than the first proposal.
References
1. Chen, H., Chiang, R. H., & Storey, V. C. (2012) : Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.
2. LaValle, S., Hopkins, M., Lesser, E., Shockley, R., & Kruschwitz, N. (2010). Analytics: The New Path To Value. IBM Institute For Business Value." October.
3. Liebowitz, J. (Ed.). (2013): Big Data And Business Analytics. CRC Press.
4. Seddon, P. B.Constantinidis, D., & Dod, H. (2012). How Does Business Analytics Contribute To Business Value?