Case Study (CO-PC)-GBI-066
I am going to explain what I did for each
step in this case study. In 1st step, I manufactured a variant as a
new product for Black Bike, and record the activities in ERP. In 2nd
step, a frame for the White Bike is created, and record the activities in ERP.
In 3rd step, I manufactured a BOM for the White Bike, and record the
activity in ERP. In 4th step, I built s new routing for my White
Bike in ERP. In 5th step, a cost estimate is created for the White
Bike, and I evaluated the cost components. In 6th step, I moved from
the cost estimate to the material master record. In 7th step, I
checked the planned price in the material master record of the White Bike. In 8th
step, I updated the future price. In 9th step, I checked the current
In this case study, I learned how to use SAP
ERP for product costing. With each step, I practiced how to record activities,
and how to choose a right function for the right activities. Moreover, it was
the first time to see and use SAP ERP. I simply learned how it looks like and how
difficult it is for using. Before I start to work on SAP ERP, my account was
locked because I missed my password more than three times. I tried to use new
client ID to sign up the ERP. Then I finally was allowed to sign up SAP ERP. In
this happening, I realized how its security is strong as well. Moreover, when I
missed some steps, it was difficult to fix my mistake, and I had to start it
over again to fix all my mistakes. Thus, I learn how to use ERP for product
costing and its function through this case study, but also how complex and
difficult they are.
Gartner Inc. defines, “Big Data are high volume, high
velocity, and/or high-variety information assets that require new forms of
processing to enable enhanced decision making, insight discovery and process
optimization.” Moreover, Big data can handle both structured and unstructured. Big data
helps the organization to have better decisions and strategic business moves. Structured data that indicates any
fixed-record or file such as Excel and CSV file. In opposite, unstructured data
includes text and multimedia files such as email, video, photos, and
presentation etc. Additionally, 80 to 90 percent of the organization date is
unstructured. This means that organizations definitely need to use big data for
organizing their business data.
applications are able to be placed on the top of SAP ERP software. SAP ERP is
essentially created to handle big data. SAP ERP users can combine them with SAP
HANA. HANA project has been created by SAP as a big data platform like ERP. SAP’s
HANA help organization to keep high-volume data in memory. The volume of big data is
getting bigger as technology develops. SAP has invested in developing HANA
abilities to catch up these developments and social changes. However, HANA is
not a simple project to use as a big data platform. Thus, SAP suggests
customers for understanding HANA’s tools and function before they used it in
real business. In addition, if customers transfer their data from an old SAP to
HANA, it is better to decide what data should be transferred because HANA is
not a low price for data storage, and some data might not be necessary.
use big data to define the cost drivers of activities. According to the textbook of cost accounting, DHL
Express is the international shipping company. They changed from the conference
method to performing in-depth quantitative analysis with big data system.
Today, DHL Express has a single and worldwide activity-based costing system.
They use the new system to suggest the cost and profitability of each work
within its network. The profit of what’s being shipped on a particular flight
can be connected with the code of shipping by DHL Express with analyzing their
database. Then, they determine that 250 airplanes
would be best for their works based on the analyzing.
analytics is a process to exam, clean and model data due to finding relative information,
indicate conclusions and help decision making. Data analytics have a variety of
method and approaches encompassing data mining, text analytics, business
intelligence, and data visualization. Moreover, data analytics can also be
divided into quantitative and qualitative data analytics. The quantitative data
analytics focuses on numerical data which can be measured statistically. The
qualitative analytics can help companies to understand non-numerical data like
text, audio, and video. Thus, companies can increase revenues, improve
operational productivity, and develop customer services efforts.
SAP ERP is powerful, but not simple business software. Creating
SAP ERP data is helpful for data analytics. Timely data and analytics are need
by the business organization. The information allows their business to make
decisions. SAP ERP collects, organizes, and classifies data. Then, SAP ERP provides
users the right data when they need it. However, SAP ERP does not have enough
decision-support essentials, and complex project. It is difficult to figure out
the right tools for right data in ERP. Thus, SAP has developed SAP BW as the
new project which to compensate for the ERP’s weakness.
data analytics also relates to cost accounting. Cost accounting helps the organization
to determine the cost structure of business. The cost structure is decided by
collecting information about the costs incurred by the organization’s
activities, costs of goods, and other cost usage. The information is gathered,
classified by data analytics to get the right information for the
organizations. For example, allocating the IT and manufacture departments in
generating standard costs, if the company decide it is the better method for
the company based on their data analytics. Data analytics suggest companies
what method is good, how much the direct material and overhead, and how the
economic cycle is going on etc. Organization’s need to do data analytics to
determine cost their cost-structures.
analytics suggests the use of data, statistical system, and machine learning in
order to make the prediction about future or unknown events based on analyzing current
and historical facts. In business, organizations often use predictive analytics
when they need to determine risk and opportunities. In addition, predictive
analytics is able to suggest any type of unknown events including the past,
present and future. However, the accuracy of prediction depends on the quality
of data analytics.
SAP ERP can track and record day-to-day
activities of the organization, and provides historical information users based
on their activities. The historical information is necessary for predictive
analytics. Moreover, SAP has created a new project which is called SAP Lumira.
First, combining into a single installation can be practiced by SAP Predictive
Analytics 2.0, and business users have helped by using the automatic
capabilities of Predictive Analytic 2.0. Next, Predictive Analytics have
targeted business analysts and data scientists. Now Expert Analytics does it as
well. SAP Expert Analytics is the new predictive model. Then, SAP Lumira which helps business users for Predictive
Analytics has offered by the Expert Analytics. It also efficiently handles high-voluminous data in
memory like HANA.
Predictive analytics is also important for
cost accounting to estimate budgets and what-if scenarios. These budgets and
what-if scenarios are projected by predictive analytics which is based on
historical information and economic movements. For example, the selling price
is also determined by predictive analytics. When the company produces new goods,
companies forecast how many their product will be sold, how much the cost of
good will be, and how much consumer willing to pay. These forecasts are
estimated based on historical information. Then they decide the price of their
new goods or services. Thus, the predictive analytics is important to estimate
budgets and selling-price which is related to cost accounting.