Procter & Gamble Case Study: Business Intelligence and Analytics

This case study analyzes Procter & Gamble's (PG) utilization of data analytics and business intelligence to drive decision-making and enhance business performance. The report examines PG's organizational structure, including Global Business Units (GBUs), Market Development Organizations (MDOs), Global Business Services (GBS), and Corporate Functions. It highlights the role of IT systems, particularly data analytics, in providing insights for product development, sales forecasting, and market strategies. The case study discusses the benefits of business intelligence, data warehouses, and Information and Decision Solutions (IDS) in improving operational efficiency and customer satisfaction. It also explores PG's use of big data, real-time analysis, and innovation to gain competitive advantages and adapt to market changes. The analysis includes a review of the North America Laundry Detergent market and the impact of forecasting on sales and business models. Furthermore, the case study references various sources to support the findings and recommendations.

2/6/2020
Running Head: DISCUSS AND CRITIQUE 0
Discuss and Critique
Report
Student name

DISCUSS AND CRITIQUE 1
Discuss and critique
Procter & Gamble (PG) is a well-known company in the international market because of its
products and survives. Moreover, the organizational structure of the company is very good,
ass per the current environment of businesses. PG has employed 129000 employees for
various services in four independent global organizations, which are Global Business Units
(GBUs), Market Development Organizations (MDOs), Global Business Services (GBS),
and Corporate Functions (Akter & Wamba, 2016).
In addition, IT-systems are one of the reasons for the success of PG, as data analytics can
possibly using IT-system. Moreover, there are many benefits of data analysis, which is a
good thing for a company, which has worked in the international market. Most of the
functions are based on the decisions, which can be possible using data analytics. In addition,
Big data is beneficial for the company as well (Chen, et al., 2012).
In addition, data analytics is a centralized process in which all the data has collected at data
centers for business analysis and data analysis. Moreover, PG has managed large amounts of
data using information technology. The organization can know about the growth of products
and services using data, which is collected on a daily basis. A manager can identify loss and
profit based on the daily and weekly sales of a product. Therefore, they can take proper
action. In addition, business intelligence and data warehouses are useful for a large
organization (Collier, 2012).
Moreover, Information and Decision Solutions (IDS) has used for decision processes around
PG. many processes can be managed using results and reporting of data analytics. The
company has included technology and business intelligence for innovations, which has
increased the productivity of employees and operations as well (Zeng, et al., 2012).
According to Bob, business intelligence has provided many good things to manage a
business, such as data analytics, reports, and many others (Shmueli, et al., 2017).
IDS provides many possible ways to develop business in market places, such as decision
making, collaboration, strategic development, and advanced technology. All the things are
necessary for the management of various processes. Moreover, customers are happier with
the new systems, as it is feasible and reliable in terms of trust and honesty. Data analytics can
be managed using basic processes (Linden, 2015).

DISCUSS AND CRITIQUE 2
The company has taken competitive advantages based on business intelligence and
innovations. The company has used business intelligence and business analytics to manage
all the things, which are important for real-time analysis. In addition, the role of embedded
IDS analysts is important in a company, which provides the right decisions. In addition, the
business sufficiency model has used for managing all the things in a better manner.
Moreover, all business units have used centralized data, which is more reliable (Vercellis,
2011). The IDS analyst has played aa great role in the success of PG, as they have multiple
components. Moreover, PG has involved new technology for managing their large amount of
data, which is useful for business analysis. Big data is a recent technology, which is a good
trend in the market (Gupta, et al., 2018).
The company has managed various employees and business services using business analysis.
Moreover, basic employees’ services can be managed in a better way using business analysis.
People management is easy with technology including meetings and travel services.
Moreover, financial services will be better using business analysis. GBS has used business
analysis for various solutions to customers issues. In addition, business performance can be
measured using busies analytics and IDS. Many processes can be managed using IT-system
especially enterprise resource planning (ERP) and Information Systems. In addition, PG has
managed various processes through IDS and analyst. Moreover, GBS has included decision
cockpit to take decisions, which are good from the business point of view (Datafloq, 2019).
PG has used proper technological innovations in their marketing and business strategies. In
addition, organizational culture has managed using proper strategies, which is a good way to
enhance business. Moreover, a business can be managed using corporate strategies. The main
benefit of IDS is providing real-time information of the market. Moreover, many processes
can be managed using reporting and data sources. The company has provided better decisions
to their subsidiaries, which is based o the various things. Moreover, PG has introduced new
concepts in its business, which is applicable to their products and services. Moreover, PG is
successful because of its business analytics. In addition, propose agendas have created based
on the basic processes (Davenport, et al., 2013).
PG has used business analysis for North America Laundry Detergent market. The company
was found that liquid detergent has used in high quantity as per the records. Thus. It is
necessary to improve the basic sale of various products, which are Cheer, Ivory, Era, and
many others. There are many processes in the company, which can be managed using various

DISCUSS AND CRITIQUE 3
processes. Moreover, it will improve the efficiency of the business functions as well
(Nedelcu, 2013).
Wave 1 is a compaction roll-out in which products have distributed to retailers with a fixed
target. However, there is no growth in sales. Moreover, the IDS system has managed all the
reports as well, which is a good source of information. There is a huge impact of forecasting
o the sales of PG. moreover, a particular department has changed its strategies based on
forecasting about the sales of products (Obeidat, et al., 2015). The whole systems are based
on the supply chain, manufacturing, and procurement. However, sales have increased by 1%,
which is not good but beneficial for the company as well. BI provides many types of
visualization (Isik, et al., 2013).
There are some bad decisions of the company but data and statistical model has provided bets
knowledge about the market, which has used for the forecasting. Moreover, basic
performance can be improved using forecasting. It makes a huge impact on PG’s markets in
the overall world. In addition, there is some disruptive changes tat count not be ignored by
the firm, as they are impacting the forecasts. The revenue of the company has increased
because of IDS and forecasting processes. Moreover, there are many changes in the business
model because of the data and statistical model, which has provided better outcomes
(Sabherwal & Becerra-Fernandez, 2012). Most of the processes can be managed using
centralized systems. However, PG has included innovations in most of the field especially in
the development and marketing. Business intelligence is a basic need for a firm (Chaffey,
Dave & White, 2010).

DISCUSS AND CRITIQUE 4
References
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Chen, H., Chiang, R. H. & Storey, V. C., 2012. Business intelligence and analytics: from big
data to big impact. MIS quarterly, pp. 1165-1188.
Collier, K., 2012. Agile analytics: A value-driven approach to business intelligence and data
warehousing. London: Addison-Wesley.
Datafloq, 2019. Big Data Analytics Paving The Path For Businesses With More Informed
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Available at: https://datafloq.com/read/big-data-analytics-paving-path-businesses-decision/
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Davenport, T. H., Iansiti, M. & Serels, A., 2013. Managing with Analytics at Procter &
Gamble..
Gupta, . A. et al., 2018. Big data & analytics for societal impact: Recent research and trends.
Information Systems Frontiers, 20(2), pp. 185-194.
Linden, A., 2015. Advancing Business With Advanced Analytics. [Online]
Available at: https://www.gartner.com/doc/3090420/advancing-business-advanced-analytics
[Accessed 7 July 2019].
Shmueli, G. et al., 2017. Data mining for business analytics: concepts, techniques, and
applications in R. New Jersy: John Wiley & Sons.