ACC 202 Accounting Information Systems: Excel Solutions & Case Study

This document presents a solution to an accounting information systems assignment, featuring both practical Excel-based analysis and a research report on business intelligence. The Excel component calculates monthly employee payments, overtime, and total pay, highlighting employees with the most overtime. It also suggests incorporating functions for decision-making, such as considering employee tenure and forecasting demand for the upcoming quarter. The business intelligence section discusses features like location intelligence, executive dashboards, and interactive reports, emphasizing their role in enhancing business decision-making by providing real-time data, customizable interfaces, and analytical capabilities. The assignment concludes that these features are crucial for business organizations to thrive in the modern era.

Running head: ACCOUNTING INFORMATION SYSTEM
Accounting Information System
Name of the Student:
Name of the University:
Author’s Note:

1ACCOUNTING INFORMATION SYSTEM
Table of Contents
Answer to Question 1:.....................................................................................................................2
Requirement 2:.............................................................................................................................2
Requirement 3:.............................................................................................................................2
Answer to Question 2:.....................................................................................................................3
Introduction..................................................................................................................................3
Discussion....................................................................................................................................3
Conclusion...................................................................................................................................5
Reference List..................................................................................................................................6

2ACCOUNTING INFORMATION SYSTEM
Answer to Question 1:
Requirement 2:
MONTHLY PAYMENT TO EMPLOYEES:
Employee Name Hours Worked Regular Hours Overtime Hours Hourly Pay Base Amount Over-Time Total Pay
Jennifer Leepoz 41 36 5 $40.00 $1,440.00 $425.00 $1,865.00
Kath Hudson 52 36 16 $80.00 $2,880.00 $1,360.00 $4,240.00
Lara Bangle 40 36 4 $50.00 $1,800.00 $340.00 $2,140.00
Novak Djoker 37 36 1 $30.00 $1,080.00 $85.00 $1,165.00
Paris Holton 45 36 9 $70.00 $2,520.00 $765.00 $3,285.00
Rafael Nooderly 44 36 8 $60.00 $2,160.00 $680.00 $2,840.00
Ricky Mortini 52 36 16 $60.00 $2,160.00 $1,360.00 $3,520.00
Russell Creak 34 34 0 $80.00 $2,720.00 $0.00 $2,720.00
Selina Geemak 30 30 0 $40.00 $1,200.00 $0.00 $1,200.00
Willard Smith 39 36 3 $30.00 $1,080.00 $255.00 $1,335.00
TOTAL 414 352 62 $19,040.00 $5,270.00 $24,310.00
Maximum Overtime
Earned by: Kath Hudson Ricky Mortini
Requirement 3:
Several functions could be included within these situations so that assistance could be
provided to the decision-making process. Therefore, it could be observed that the employees
working for longer duration should be considered in the decision making process (Appelbaum et
al. 2017). This is because of the fact that the decisions pertaining to the staffs working for longer
duration have to be considered for increasing their motivation level, which, in turn, would
enhance the overall business productivity.
Another aspect considered is a model used so that demand could be estimated for the
upcoming quarter (Kimball et al. 2015). With the help of this estimation, ideas, policies and
plans could be obtained in relation to the production process for the upcoming quarter and these
would help in paving the path for the determination of effective operational activities.

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Answer to Question 2:
Introduction
In order to extract intelligence from business information, two business intelligence tools
are used commonly for aiding in decision making through modelling and analysis. In this
section, a brief description of the two tools used would be discussed for providing assistance in
the decision making process.
Discussion
The most significant aspect to be considered in this report is to describe the three features
inherent in the business intelligence tools widely used. It has been observed that there are various
characteristics associated with business intelligence tools and three significant features are
demonstrated as follows:
Location Intelligence
This tool possesses the capability of visualising and mapping data in various formats,
which have geographical nature (Larson and Chang 2016). The data visualisation and
exploration of the data sets based on spatial elements enables the organisations in gaining
understanding regarding their business operations from a fresh perspective. This is termed as
sales per region (Moro, Cortez and Rita 2015).
Executive Dashboards
These dashboards offer concise real time data that could be understood easily to the
business owners for assisting them in greater and effective decision making procedures by
minimising the response time to internal as well as external events (Sauter 2014). The executives
have control over the dashboards, which are personalised and this assists in easy understanding

4ACCOUNTING INFORMATION SYSTEM
of key performance indicators along with scheduled and regular information. In addition, the
method of exception reporting would have the ability of providing alerts to the executives
towards any sort of unprecedented situations and events requiring immediate actions (Trieu
2017). The customised data delivery denotes the ability of the executives in constructing quick
decisions without any sort of estimations and identifying irrelevant information for removing the
same.
Interactive Reports
These reports are beneficial for the users so that data could be transfigured into
knowledge. They allow the users to gain insight of the analyses within the reports and the
underlying information reliant on data for undertaking effective decisions (Wieder and Ossimitz
2015). Therefore, the users need to possess certain abilities, which are enumerated briefly as
follows:
Evaluating the different aspects of the reports thoroughly
Undertaking dice and slice related to the evaluation of OLAP
Incorporation of analysis such as regression and moving averages for dealing with the
data patterns
Using time series for scanning large sets of data so that anomalies could be understood
inherent in data
Use of conditional formatting for forming data alerts highlighting the data exceptions
(Wu, Chen and Olson 2014)

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Conclusion
It is evident from the above discussion that all the features of the widely used in business
intelligence tools are addressed so that better decisions could be undertaken for business
improvements. Moreover, it has been analysed that the features play a significant role and such
features are necessary for the business organisations to sustain in the current era.

6ACCOUNTING INFORMATION SYSTEM
Reference List
Appelbaum, D., Kogan, A., Vasarhelyi, M. and Yan, Z., 2017. Impact of business analytics and
enterprise systems on managerial accounting. International Journal of Accounting Information
Systems, 25, pp.29-44.
Kimball, R., Ross, M., Mundy, J. and Thornthwaite, W., 2015. The kimball group reader:
Relentlessly practical tools for data warehousing and business intelligence remastered
collection. John Wiley & Sons.
Larson, D. and Chang, V., 2016. A review and future direction of agile, business intelligence,
analytics and data science. International Journal of Information Management, 36(5), pp.700-
710.
Moro, S., Cortez, P. and Rita, P., 2015. Business intelligence in banking: A literature analysis
from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with
Applications, 42(3), pp.1314-1324.
Sauter, V.L., 2014. Decision support systems for business intelligence. John Wiley & Sons.
Trieu, V.H., 2017. Getting value from Business Intelligence systems: A review and research
agenda. Decision Support Systems, 93, pp.111-124.
Wieder, B. and Ossimitz, M.L., 2015. The impact of Business Intelligence on the quality of
decision making–a mediation model. Procedia Computer Science, 64, pp.1163-1171.
Wu, D.D., Chen, S.H. and Olson, D.L., 2014. Business intelligence in risk management: Some
recent progresses. Information Sciences, 256, pp.1-7.