Big Data and Business Analytics

This report analyzes Reckitt Benckiser's adoption of big data and business analytics, examining its strategic initiatives, key business decisions, and supporting drivers. It includes a critical analysis of the company's current position and provides recommendations for further analytics deployment. The report also features a case study demonstrating the application of a business analytics model in the context of Reckitt Benckiser's health and hygiene units. Desklib provides past papers and solved assignments for students.

Big Data and Business
Analytics

EXECUTIVE SUMMARY
Big data and business analytics is a complex procedure of examining large volume of
data sets to disclose information including unknown correlations, customer preferences, hidden
patterns and market trends that can help company in making informed business decisions.
Rekkitt Benckiser is a consumer goods company that adopts Big data and business analytics
which helps company in improving its performance in market. By adoption of this technology,
firm enables to empower its employees that helps them in making informed decisions. Two main
strategic initiatives are taken by company, i.e., acquisition of MJN and sale of food business.
These initiatives are supported by various key drivers like product innovation, organisation and
culture etc. Business analytics model is used by firm that provides it single common framework
that helps in developing successful business analytics.

Table of Contents
EXECUTIVE SUMMARY.............................................................................................................2
INTRODUCTION...........................................................................................................................1
TASK ..............................................................................................................................................1
Critical Analysis.....................................................................................................................1
Analytics Deployment Recommendations.............................................................................5
Recommendations............................................................................................................................8
CONCLUSION................................................................................................................................8
REFERENCES................................................................................................................................9

INTRODUCTION
Big data analytics refers to the complex process of analysing varied and large data sets to
reveal information including unknown correlations, customer preferences, hidden patterns and
market trends that can assist firms in making informed business decisions (Big Data Analytics,
2018). In the present assignment, given organisation is Rekkitt Benckiser which is a
multinational consumer goods firm located in Slough, England. This report covers identification
of firm's current position in adopting big data and business analytics and its main strategic
initiatives. Key business decisions that firm has to make about entities to support their strategic
initiatives is also defined. At last, useful data sources and business analytics models are
recommended that company can leverage for further analytics deployment and increasing big
data and business analytical competencies.
TASK
Critical Analysis
Big data analytics is the sort of advanced analytics that includes complex applications
with components like statical algorithms, predictive models and what-if analysis mechanized by
high performance analytical system. Driven by high powered computing system and specialized
analytical software, big data analytics various benefits to business including more effective
marketing, new revenue opportunities, competitive advantages over rivals, better customer
service and improved operational efficiency. Its applications enables data scientists, statisticians,
big data analysts, predictive modelers and other analytics professionals to examine growing
structured transaction data volume including other forms of information that are often left
unexploited by analytics and conventional business intelligence programs (Provost and Fawcett,
2013).
Reckitt Benckiser is a global consumer goods firm of United Kingdom that makes variety
of popular consumer hygiene, health and home products. Its brand includes Mead Johnson,
antiseptic brand dettol, nurofen, cillit bang, air wick, sore throat tablet strepsils, lysol and
clearasil. The main vision of company is to simply assist people to feel better and to fulfil that,
firm adopt big data and business analytics technique. For making strategic business decisions,
marketers, salespeople, executives and product developers, all require data or information to
understand the position of business and more importantly, to determine what to do next. About
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for years ago, global business intelligence team of Reckitt Benckiser realized that for getting
crystal ball insights, they needed more data than just internal operational data. In order to
determine what is going on in business or with its products at different retailers, where company
must grow, how it compare to other firms that deals in same industry and various other insights,
company decided to replace its business intelligence system with Azure and Microsoft Power
BI (Picciano, 2012).
In adopting big data and business analytics, the current position of Reckitt Benckiser is
improve. It helps company in determining what's going on in business and identifying its current
position. By implementing big data analytics, employees of firm gets clear understanding about
where should they grow and various other insights that helps in making effective decisions
regarding growth of company. It helps Reckitt Benckiser to empower employees and help them
in making sense of proliferating data. In order to enables them to make decisions on the basis of
data, company replaced its existing BI (business intelligence) solution with Azure and Microsoft
Power BI. By adopting big data and business analytics, firm empowers its manpower to work
smartly. Reckitt Benckiser use Microsoft Power BI and Azure technology to unlock power of
data, save money and empower workforce to make better decisions (Reckitt Benckiser
Empowers Employees, 2018).
Use of Big data and business analytics, improves performance of Reckitt Benckiser by
saving money. Microsoft Azure helps firm in developing modern data warehouse solution by
replacing Hadoop components and AWS data warehouse. It allows company to take advantage
of intelligence capabilities and advanced security of Microsoft Cloud and also saves its money
(Chawla and Davis, 2013). Azure provides back-end-data integration consumption tools with
front end data, like Microsoft Office and Power BI. This end to end data analytical solution helps
company in saving its licensing cost. By the assistance of Big data and business analytics, firm
enables to deliver enormous value that ultimately impacts on its sales revenues. In 2017, the net
revenues from constant operations is rose by 21% involving the positive benefits of foreign
exchange movements and initial contribution from MJN.
However, in year 2017, the top line performance of Reckitt Benckiser is influenced by
numerous issues. A sophisticated cyber attack is one of the major issue which originated in
Ukraine. This had significant influence of supply availability in third quarter.
Key business initiatives taken by Reckitt Benckiser:
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The strategic moves of Reckitt Benckiser during year 2017 position it extremely well for
future. It enables company to meet needs of even large group of customers. Different strategic
moves taken by company are defined below:
The first strategic initiative taken by company is to completed the acquisition of MJN. It
is a unique opportunity for Reckitt Benckiser to do much in pursuance of healthy lives,
supporting child nutrition in crucial starting 1,000 days of life, that are most vital for deciding
long-term outcomes of health (Simmha and et. al., 2013). The acquisition brings into acute
emphasize on the progress firm have made over previous five years, in changing the portfolio
from household cleaning to predominantly supported on health and hygiene. With base business
of Reckitt Benckiser, MJN is an excellent fit. Firm already reaches to millions of people by their
hygiene education programs and administers parents with relief at the time when their children
are not well through its world-class brands like Mucinex and Nurofen. A deep understanding
about journey of a new mother and leading global brand name in child nutrition, Enfamil is bring
by MJN. This acquisition gives an entry to company in fast-growing, structurally advantaged and
high-margin category. It also attain an essential goal for Reckitt Benckiser by providing it a
strong platform in developing markets. Such market includes China, Vietnam, Philippines and
some parts of Latin America. Company completed its acquisition ahead schedule and made good
progression with acquisition objectives, both operationally as well as financially.
The second strategic initiative of Reckitt Benckiser was sale of their food business. It was
a strong operation with great brands and people which generated respectable value for
shareholders or investors over long term. Yet, it wasn't core to purpose of Reckitt Benckiser and
conferred acquisition of MJN, but it was a right moment to determine the best owner for
business. The deal of MJN was completed for a good price that benefiting Shareholders as well
as enabling company to reduce its interest costs and debts (Gandomi and Haider, 2013). By
acquisition, consumer health attains over 50% of revenues on pro-forma basis. Accomplishing
this critical mass in customer health has provide an opportunity to company in terms of
determining where it sees itself to be in future. Reckitt Benckiser have created two agile, fully
accountable and focused business units – Health and Hygiene Home.
Reckitt Benckiser is transformed strategically in year 2017, it continued to face difficult
situations in key markets. Company also suffered from both unforeseen and known issues which
results in its ineffective performance and it not able to outperform its markets. The known issues
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involved impact of issue of South Korea Humidifier Sanitizer and Scholl/Amopé innovation in
year 2016. Firm continue to engage with its stakeholders involving other companies in order to
resolve the issue in Korea and stay committed to put victims first (Lin, Yao and Zadeh, 2013).
The unforeseen issue of company includes serious cyber attack, that hits Reckitt
Benckiser as well as various other organisations. This had significantly impact on activities and
performance of company. It disrupts key operations of firm including logistics, manufacturing
capacity and go-to-market operations. This puts corresponding impact on performance of firm,
specifically in third quarter of year.
Key business decisions:
In order to overcome these issues, various decisions are taken by Reckitt Benckiser.
Company had invested in cyber security to prevent further attacks and also enhance its
programmes for speedy detection of attack and respond to it effectively. This enables firm to
rapidly mitigate the impact and enhancing its ability to efficiently restore their systems. This
enables company to run again its operations in an effective and efficient manner (Demirkan and
Delen, 2013).
For improving performance of infant nutrition, Reckitt Benckiser put efforts to accelerate
innovation pipeline of MJN in key markets of U.S. and China. Simultaneously, firm bring its
expertise in digital and electronic commerce in order to drive transformational growth. Company
also invested in other key growth channels, including mom-and-baby outlets in China. Apart
from this, company have injected its culture with discipline, passion and emphasize on
performance.
Firm brings constant innovations in its Home and Hygiene categories which includes an
entirely new formulation of finish. As Reckitt Benckiser much depends on its competent
employees to drive success, it provides them new opportunities to flourish. Establishment of new
business unit enables company to deploy strengths of its employees (Carlson, Borman and
Robinson, 2011).
Drivers that support key business initiatives:
The business initiatives of Reckitt Benckiser is supported by various key performance
drivers. These includes better business, better society and better environment which are defined
below:
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Better business: In order to make business better and out perform in market, firm mainly
focus on its brands, people, markets and developing a digitally connected firm that leads it
towards long term growth and success. Health and Hygiene: Company invest heavily in its portfolio of 20 leading power brands
of market. These leading power brands of firm provides 80% of revenue and offer it high
margins and growth (Chatti and et. al., 2012). Organisation and culture: Company expanding its focus on talent and diversity by
improving women's retention rate from administrators to senior managers. Employees
enables Reckitt Benckiser to outperform in market, so firm emphasize on keeping them
safe as well as develop their skills and provide them growth opportunities to flourish.
Company identify and embrace the value that engaged, diverse and motivated workforce
can bring. Better society: For making the society better, firm supports its community and drive
safety and quality in all. It constantly brings products that helps in providing healthy and
hygienic life to people of society.
 Product innovation: Firm continuously emphasize on designing and introducing more
sustainable products in market which helps it in attaining high growth and long term
sustainability.
Better environment: Various initiatives are taken by firm to keep environment safe.
These moves includes reduction of green house gas emission by declining carbon footprint per
dose of good, reducing use of water in its manufacturing operations and decreasing
manufacturing waste. All these initiatives helps company in maintaining good its good image in
market (Wang and et. al., 2016).
Analytics Deployment Recommendations
In complex and large projects with numerous competencies and people, it is necessary to
develop an overview. Business Analytics model helps in that and provides an outline to Reckitt
Benckiser for understanding and developing successful business analytics. This model gives
single common reference frame for an entire structure in creating successful business analytics.
Business Analytics model:
In creation of business analytics, many people, processes and competencies are involved.
In business driven environment, the top layer of model includes management who specifies
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strategy that contains entire information elements which supports strategy. The second layer
involves operational decision makers who use knowledge and information in business processes
that supports chosen strategy. The middle layer consists of controllers, analysts and report
developers who create knowledge and information to be utilized by firm's operational decision
makers for the purpose of optimizing and innovating their regular activities. From the bottom, in
second layer of technically oriented environment includes ETL developers and database
specialist that merges and enriches data or information and makes it accessible to users of
business (Papamitsiou and Economides, 2014). In bottom layer, primary data of business
generating source system which are developed and run by IT professionals through information
technology development and operations. Successful business analytical processes must have
fixed structure which always initiates with specification of information strategy that is derived
from business strategy's objectives.
In collecting information, various data sources can be leverage by Reckitt Benckiser
including market research, analysis of competitors, internal business processes, conducting
surveys and customer feedback etc. that helps company in making rational decisions that assists
in its growth and success. Application of business analytics model helps Reckitt Benckiser in
getting single common reference frame for overall structure in successful creation of business
analytics.
Deployment of business analytics model:
Case study: How to make information strategy for health and hygiene units.
Reckitt Benckiser apply big data information to concrete example to understand it better.
The case study features business analytical initiative of health and hygiene units that offers
products worldwide. It is simplified and creative version of real case and its objectives is simply
to outline business analytical process. Its focus is on opening fully accountable health and
hygiene units (Crawford and Schultz, 2014).
Overall strategic business targets:
The mission of company is to become a market leader in health and hygiene products.
The specified goal of Reckitt Benckiser is to increase net revenue generated by firm to 40% by
year 2020. Apart from this, firm wants to increase 25% market share and 15% ROE. The
executive management monitor performance of business in relation to its strategic objectives.
Functional strategy and business case:
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The strategy of business analytics should always be based on business driven
surroundings with administration specifying single information strategy that should be subject to
overall business strategy for firm. The manager of health and hygiene unit has come up with a
initiative to maximize market share of business from 17% to 25%. Firm wants to hold more
customers for their health and hygiene products. Administrator specifies this strategy as “From
the current number of customers, firm increase their product users to 20% in future by its new
health and hygienic product units. Before introducing this business initiative, manager develops
business case for project (Davenport, 2014).
Business processes and actions:
The processes of production department should now be adjusted in a manner that it
actively depicts behaviour that secures large number of customers for longer. For this, employees
of Reckitt Benckiser needs more knowledge and information about needs and preferences of
their customers. Processes should be adapted to customer's profile that allows employees to
deliver products that they need.
Analytical Processes and Front Ends:
In analytical environment, the responsibility of analyst is to develop knowledge and
information to derive processes of business in direction of delivering product to large group of
customers as per their needs. The main questions for analyst are:
 Who are the customers?
 Which product they like to buy more? What amount they can charge for the product?
Data Warehouse:
Analyst requires data warehouse to provide data on customers. For this, they ask to
information technology department to develop new source of operational data on customers
(Chen and Zhang, 2014).
Data Sources: IT Operations and Development:
At this stage, data is collected to customers form various ways like by taking their
feedbacks. This data is stored by IT department by using technologies like Azure and Microsoft
Power BI which provides advanced security to Reckitt Benckiser in storing data and save its
money. This big data can help firm in increasing analytics competencies and attaining business
targets.
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Recommendations
From the above analysis, it has been recommended that, firm can use business analytics
model as it helps in generating its targeted revenues. Reckitt Benckiser can also use some
advanced technologies other than Azure and Microsoft Power BI as it helps in increasing its big
data and analytical competencies. If more data the firm have, more it will be able to take
informed business decisions.
CONCLUSION
As per the above mentioned report, it has been concluded that big data and business
analytics helps company in examining large volume of data to uncover information like
unknown correlations, hidden patterns, customer preferences and market trends that are assistive
in making informed decisions. Along with big data and analytics initiatives, firm emphasize on
deploying tools and executing data extraction processes that seeks to enhance quality, quantity,
timeliness and availability of information. This information helps employees in taking effective
decisions of business. Various key indicators like organisation and culture, product innovation
etc. are considered as the main factors behind success of company. Business analytics model
provides single common reference frame to company that helps in creating successful business
analytics.
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REFERENCES
Books and Journals
Provost, F. and Fawcett, T., 2013. Data science and its relationship to big data and data-driven
decision making. Big data. 1(1). pp.51-59.
Picciano, A. G., 2012. The evolution of big data and learning analytics in American higher
education. Journal of Asynchronous Learning Networks. 16(3). pp.9-20.
Chawla, N. V. and Davis, D. A., 2013. Bringing big data to personalized healthcare: a patient-
centered framework. Journal of general internal medicine. 28(3). pp.660-665.
Simmhan, Y. and et. al., 2013. Cloud-based software platform for big data analytics in smart
grids. Computing in Science & Engineering. 15(4). pp.38-47.
Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and
analytics. International Journal of Information Management, 35(2), pp.137-144.
Lin, T.Y., Yao, Y.Y. and Zadeh, L.A. eds., 2013. Data mining, rough sets and granular
computing (Vol. 95). Physica.
Carlson, D., Borman, G. D. and Robinson, M., 2011. A multistate district-level cluster
randomized trial of the impact of data-driven reform on reading and mathematics
achievement. Educational Evaluation and Policy Analysis. 33(3). pp.378-398.
Chatti, M. A. and et. al., 2012. A reference model for learning analytics. International Journal of
Technology Enhanced Learnin. 4(5-6). pp.318-331.
Wang, G. and et. al., 2016. Big data analytics in logistics and supply chain management: Certain
investigations for research and applications. International Journal of Production
Economics. 176. pp.98-110.
Papamitsiou, Z. and Economides, A.A., 2014. Learning analytics and educational data mining in
practice: A systematic literature review of empirical evidence. Journal of Educational
Technology & Society. 17(4).
Crawford, K. and Schultz, J., 2014. Big data and due process: Toward a framework to redress
predictive privacy harms. BCL Rev.. 55. p.93.
Davenport, T., 2014. Big data at work: dispelling the myths, uncovering the opportunities.
Harvard Business Review Press.
Chen, C. P. and Zhang, C. Y., 2014. Data-intensive applications, challenges, techniques and
technologies: A survey on Big Data. Information Sciences. 275. pp.314-347.
Demirkan, H. and Delen, D., 2013. Leveraging the capabilities of service-oriented decision
support systems: Putting analytics and big data in cloud. Decision Support Systems.
55(1). pp.412-421.
Online:
Big Data Analytics, 2018. [Online]. Available through:
<https://searchbusinessanalytics.techtarget.com/definition/big-data-analytics>
Reckitt Benckiser Empowers Employees, 2018. [Online]. Available through:
<https://customers.microsoft.com/en-us/story/reckitt-benckiser-consumer-goods-power-
bi>
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