Analyzing Macy's Use of Integrated Systems: ERP, OLAP, and EAM

This report examines the integration of Enterprise Resource Planning (ERP) systems, Online Analytical Processing (OLAP) servers, and Enterprise Asset Management (EAM) systems, focusing on Macy's as a case study. It identifies overlap points between these systems, highlighting their roles in business management, automation, and data analysis. The report details how Macy's uses big data to understand consumer patterns, personalize customer experiences, and optimize operations. It further explains how ERP, OLAP, and EAM systems can be leveraged to improve Macy's productivity, customer service, supply chain management, and asset availability, ultimately enhancing decision-making and competitive advantage. The report also provides a URL to a relevant online retail dataset from UCI Machine Learning Repository.

Running head: INTEGRATION OF ENTERPRISE SYSTEM
INTEGRATION OF ENTERPRISE SYSTEM
Name of Student
Name of University
Author’s Note

1INTEGRATION OF ENTERPRISE SYSTEM
Table of Contents
Overlap points......................................................................................................................2
New knowledge generated by Macy’s.................................................................................3
URL to the dataset...............................................................................................................6
References............................................................................................................................7

2INTEGRATION OF ENTERPRISE SYSTEM
Overlap points
The overlap points between the Enterprise Resource Planning Systems, Online Analytical
Processing Server and Enterprise Asset Management Systems or Asset Performance
Management Program are as follows
 They help the organization in using a particular system of integrated applications
which helps them to manage their business as well as automate various functions
that are related too technology, human resources and services and which are
carried out in back office of the organization (Lee, 2017).
 These systems focus on important business areas like HR, accounting, finance,
materials management, customer relationship management and production (Akter
& Wamba, 2016). Among the systems, organizations usually choose one on the
basis of their requirement of the business.
 The systems have a particular thing in common, they help the organization in
enabling the users to selectively and easily extract as well as query data for the
purpose of analyzing the data from various point of view.
 The systems help an organization in tracking as well as managing the physical
assets of the organization. The other systems are somewhat dependent on the asset
performance management program (Lima, Moura &Sabino, 2016). If the assets of
an organization are managed properly using various appropriate measures, the
enterprise resource planning system and the online analytical processing serer
would function properly and effective results can be obtained if asset performance
management program is utilized effectively.

3INTEGRATION OF ENTERPRISE SYSTEM
 All the systems aim in improving the overall performance of an organization by
helping it to obtain helpful results and as a result help in providing the
organization with a competitive advantage as compared to other organizations
working in the same field (Frizzo-Barker, Chow-White & Mozafari, 2016.
New knowledge generated by Macy’s
The company in the retail industry that uses big data for the purpose of uncovering new
consumer patters is Macy’s. It has been founded in 1858 by Rowland Hussy Macy. It is affiliated
with Bloomingdale’s department store. This organization has a good history on the excellent
customer service provided by them (Cohen, 2018). Macy’s make use of big data in order to
provide a smart computer experience. The organization analyzes various data points like price
promotions and stock levels, the findings are then combined with stock keeping unit data from a
specific product at a certain location along with customer data (Fan, Lau & Zhao, 2015). This
particular data ensures that the chosen products suit various buying habits of the customers who
are situated in the location. Along with this, the organization also collects various data related to
customers ranging from visit frequency and their style preferences. This data is used by the
organization in order to personalize their customer experience, offering incentives at a point of
sales along with promotion and loyalty rewards. They also send targeted direct mails to their
customers for boosting conversations.
The new knowledge that has been generated by the company includes the collection of
data related to the preferences of the customers. This assignment describes ways in which the
three systems mentioned above would help the company in using these data. The ways are as
follows

4INTEGRATION OF ENTERPRISE SYSTEM
 The ERP system would help the organization in delivering products as well as
services to customers in time along with improving their productivity. It would
also help them in implementing inventory control. The communication between
customers and organizational representatives is improved with the help of reliable
lead, quote tracking and opportunity (Laudon & Traver, 2016). Some more
benefits provided by the systems to the organization include streamlining shipping
operations, strengthening relationship with their suppliers and automating various
manual processes.
 The systems would help the organization in matching their supply with customer
demands. This is done by connecting sales order management to their fulfillment
management. Users would be allowed to set service levels along with assigning
inventory to various customer sales orders (Gunasekaran, Papadopoulos &
Dubey, 2017). On the basis of customer needs, the users would be able to assign
their priority scores for the customers, service level rules and supply locations.
After the settings are defined for groups or individuals, the systems would be able
to automate the fulfillment on the basis of their preferences that have already been
assigned.
 The usage of these systems would help the organization in getting better service
because they would be provided with a holistic view regarding customers
including the customer history (Cohen, 2018). This data would allow the business
for prioritizing best customers as well as automate discounts for their long-term
customers. The systems can be connected to warehouse with a specific user

5INTEGRATION OF ENTERPRISE SYSTEM
friendly ordering system so that the customers are allowed to place orders on the
basis of their preferences and choices.
 The systems including OLAP can be utilized in order to save the time dedicated
by the organization in analyzing their data; it also helps in analyzing the data
quickly as well as easily including big data. The systems would also provide the
organization with better insights and improve their financial results (Akter &
Wamba, 2016). The system can be utilized in order to correct mistakes in their
business process, this as a result improves their ability to take decisions and keep
customers happy.
 The program like Asset Performance Management can be utilized in order to
improve the availability of assets. Availability of assets would help the
organization in performing other functions like maintaining their productivity and
keeping up the customer satisfaction. Suppose if sufficient assets are available
within the organization, the operations can be performed with precision (Lee,
2017). This system would also help the organization to collect data regarding the
availability of the assets. In case an asset is exhausted or utilized completely, it
can be tracked by the system and ensure that it is available again. This system can
be used by the Assets manager as well as Assets investment manager to run
various predictions, perform models on data and run projections.
 Using these systems the organization can have mid as well as long planning for
asset investment, better investment in necessary assets would help them in
improving the quality of services provided to customers by investing on collecting
data related to the priorities of the customers.

6INTEGRATION OF ENTERPRISE SYSTEM
Dataset
This particular example dataset represents the transactions that had occurred within the
organization between the time period of 01/08/2016 to 08/10/2017
Characteristics of data set: Sequential, Multivate, Time-Series
Number of Instances: 541950
Area: Business
Characteristics of Attribute: Real, Integer
Number of Attributes: 9
Donated Date: 2018-11-09
Tasks Associated: Clustering, Classification
Number of Web Hits: 15930
The URL to the dataset is as follow
https://www.kaggle.com/jihyeseo/online-retail-data-set-from-uci-ml-repo

7INTEGRATION OF ENTERPRISE SYSTEM
References
Akter, S., & Wamba, S. F. (2016). Big data analytics in E-commerce: a systematic review and
agenda for future research. Electronic Markets, 26(2), 173-194.
Cohen, M. C. (2018). Big data and service operations. Production and Operations
Management, 27(9), 1709-1723.
Fan, S., Lau, R. Y., & Zhao, J. L. (2015). Demystifying big data analytics for business
intelligence through the lens of marketing mix. Big Data Research, 2(1), 28-32.
Frizzo-Barker, J., Chow-White, P. A., Mozafari, M., & Ha, D. (2016). An empirical study of the
rise of big data in business scholarship. International Journal of Information
Management, 36(3), 403-413.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter,
S. (2017). Big data and predictive analytics for supply chain and organizational
performance. Journal of Business Research, 70, 308-317.
Laudon, K. C., & Traver, C. G. (2016). E-commerce: business, technology, society.
Lee, I. (2017). Big data: Dimensions, evolution, impacts, and challenges. Business
Horizons, 60(3), 293-303.
Lima Francisco, L., Moura, W. F., Sabino, L. R., Santos, V. F. D., & Esquarcio, R. B. (2016).
Big Data as a Customer Management Relationship Tool. International Journal of
Business Administration, 7(6), 91-95.

8INTEGRATION OF ENTERPRISE SYSTEM