Solution of Procter & Gamble Big Data Strategy Case Study | Turning Big Data into Big Value

Solution of Procter & Gamble Big Data Strategy Case Study Turning Big Data into Big Value

Solution of Procter & Gamble Big Data Strategy Case Study Turning Big Data into Big Value

Case Overview

Procter & Gamble is a major multinational consumer goods company, and referred as one of the first
initiators in adopting big data and digitalization to reveal patterns, trends and associations
relating to consumer psychographic behavior and react likewise. Digitalization and big data
analytics had helped P&G save billion dollars and is a key to its quick launch of products.
But some experts doubted that analyzing big data will consume more time and will lower
the speed of its decision making and it might damage company’s operations and reputation
due to privacy breach of consumer data.

The problem described in case is;

  1. How to sustain an equilibrium between efficiently use of big data and ensuring
    security and reliability of systems?
  2. How to work with top management to reform organizational structure according to
    big data requirements?

Big data known as the huge scale of information sets collected through devices and
technologies like social media, Wi-Fi sensors and electronic devices. And P&G was
referred as one of the most innovative culture companies in terms of applying technology
in developing products.
P&G analytics determined that what are the most favorable hours to display TV ads and it
also helped P&G to clearly and easily understand the rapidly changing a variety of new
digital structured and unstructured data as traditional approaches of data analytics were not
working. P&G also faced the problem of picking right data at right time. It launches a
Hadoop Ecosystem to set up a provincial big data cluster as a need for a business
intelligence(BI) tool. It finds many alternative solutions with new analytical competencies
and was able to load and integrate data faster and formed trustworthy analysis at scales that
were formally not possible due to Hadoop ecosystem. It sold its products through around
1500 websites. Its global nappy brand pampers created its consumer
relationship management wing positioned consumer at the center, to reach each possible
‘touch point’ around them like online, in a physical store or on television. P& G uses secure
file transfer protocol. It developed a special marketing mix assessment software, its data
management founded three principles;

  • Openness of data

  • Well-timed data

  • Transmission of data

Company raised use of online tools like high-speed networking, data visualization and
quick assessment of diverse data stands which results in reduction of time wastage in
decision making from months to minutes. To equip top management with all required
information it developed a conference room called Business Sphere. And each decision
maker in company avail all key information at their computer desktops via Decision
Cockpit which results in better and quick decisions. B 2011 it starts extensively use of
computer-based simulation to design evaluate virtual replicas prior to their manufacturers.
It installed control towers to handle its distribution structures also used a system
called distributer connect, which let it manage inventory in real time. It saved inventory
costs of over $1 billion by leveraging big data. Its analytics also used to forecast the best
exchange rates, shuffle production and ingredient quantity procurement between nations.
Over time it adopted a culture of data-driven decision making. In 2015 P&G admitted that
big data had the potential to change a company’s fortunes with respect to its idle revenues.
Instead of discussing the sources of the data or the quality of the data, decision-makers at
P&G now know that the data, brought into an understandable business context, is correct
and they can take faster and better decisions to answer the rapidly changing environment.


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