Data Driven Decisions for Business

This report discusses the importance of data analysis and its value in business decision making. It explores the latest trends in data analysis and the use of AI and machine learning. The report also outlines the steps to clean data and applies relevant analytical techniques to answer business questions. The analysis includes sales volume, comparison of sales, highest selling product, and quarter-wise sales volume. The report concludes with recommendations for improvement and suggests advanced techniques for analyzing the effectiveness of UK marketing campaigns. Case study on Bangles.

DATA DRIVEN DECISIONS
FOR BUSINESS

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
a. Summarising key changes and trends resulting in importance of data analysis and adding
value in business.........................................................................................................................3
b. Summarising and justifying analytical approach....................................................................4
c. Analysis...................................................................................................................................5
I. Outlining steps to clean data..........................................................................................5
ii. Applying relevant analytical techniques for answering business questions..................5
d. Conclusion and next steps.....................................................................................................10
i. Conclusion and recommendation.................................................................................10
ii. Presenting different advanced techniques that can be used by Bangles to analyse the
effectiveness of UK marketing campaigns......................................................................11
REFERENCES..............................................................................................................................13

INTRODUCTION
For business decision making the most essential thing for company is to manage and
analyse data. This is done because of the reason that when data will be analysed then it will
provide some insight relating to profitability of business and in accordance to it decision can be
taken. Present report will outline latest trend in data analysis and how it adds value. Further it
will discuss about selection of analytical approach and application of different tools to analyse
data. In end conclusion will be drawn and along with some recommendation for improvement.
MAIN BODY
a. Summarising key changes and trends resulting in importance of data analysis and adding value
in business
The key trend in importance of data analysis for companies like Bangles is as follows-
 Current trend in data analysis is that data is becoming more strategic and managers have
become more responsible in saving data in clear manner. This is pertaining to the fact that
without data Bangles cannot take decision and in order to manage business, data is of
utmost importance (Eight trends in data analytics, 2021).
 In addition to this another trend in data analysis by Bangles is the use of AI and machine
learning is preferred in analysing collected data. This is pertaining to the fact that when
these technology is being used then this assist manager in taking better decision.
 Along with this, trend relating to change in data analysis pattern is drive towards quality
of data has intensified within Bangles. This is pertaining to the fact that in modern
business world more emphasis is being given over data in order to take decision by
Bangles. The reason underlying this fact is that this assist in proper and accurate decision
making (Kamilaris, Kartakoullis and Prenafeta-Boldú, 2017).
 Furthermore, another trend in data analysis is the use of robotic process automation and
increase in use of digital workers by Bangles.
 Moreover, another trend in data analysis is use of cloud applications by Bangles. This
will be assistive in storing data for future use and reference within the company so that it
can be used later.
In addition to these trends data analysis also adds value to business and its operations (Franke
and et.al., 2017). These values are follows-

 First and foremost, benefit of data analysis is that it assists in decision making and helps
Bangles in improving its operations and business performance.
 Furthermore, data analysis also assists Bangles in predicting different future data relating
to sales by taking into consideration past records relating to sales (Miles, Huberman and
Saldaña, 2018).
 Moreover, another benefit of using data analysis by Bangles is that it helps in setting
target and standards. This is because of the reason that these standard motivates
employees to work in better manner.
 Another benefit which adds value to Bangles operation is that it assists company in
creating new innovation as with help of data they can analyse current requirement of
business and can improve it (5 reasons why data analysis is important for every business,
2021).
 In addition to this data analysis also assist Bangles in cutting down the cost of business.
this is particularly because of the reason that by analysing cost of different time duration
current cost can be managed.
b. Summarising and justifying analytical approach
Analytical approach is the one which assist company to break the problem into small
elements so that it can be solved in proper and effective manner. For analysing and interpreting
any type of data use of analytical approach is very essential. This is pertaining to the fact that it
assists manager in breaking problem in smaller parts and then trying to solve it. Hence, in order
to analyse that whether marketing campaign have a positive impact on sales performance in UK
use of statistical analysis will be made. The reason underlying selection of statistical analysis is
that this involves collecting data, analysing it by applying different statistical methods like mean,
mode and others.
In the end interpreting the calculated result for taking proper decision is being undertaken
(Mahdavinejad and et.al., 2018). This method is very assistive to Bangles as this will evaluate
that whether marketing campaign in UK created a positive impact over its sales or not. Further as
this method involves application of several statistical tools like use of pivot table, data sorting
and other. this in turn provides more accurate and logical reason behind all the answers coming.
Under this analytical approach major benefit will be of company as with help of different types
of statistical methods the major question of success of company will be answered.

c. Analysis
I. Outlining steps to clean data
For analysis of data it is necessary that data used is clean and for this following steps are
used by Bangles-
 First step involves removing irrelevant observation so that all the unwanted or duplicate
items in data list can be removed. This support Bangles as all irrelevant observation are
removed and only relevant data is present (Ho and et.al., 2019).
 Next stage involves the fix structural errors which occurs when data is transferred from
one place to another that is one department of Bangle to another.
 In addition to this next stage involves Bangles filtering the unwanted outliers as they do
not fit within the data which is being analysed.
 At the end the last stage used by Bangles is analysing and handling the missing data so
that remaining data can be used in proper and effective manner.
ii. Applying relevant analytical techniques for answering business questions
Total sales of all product year wise
Year Total sales of product
2018 £1933006
2019 £1794417
2020 £2259426

From the above data it can be evaluated that total number of sales has increased since last
three years. Further it is witnessed that in 2018 sales were good but during 2019 it decreased and
went till £1794417. But again it increased to £2259426 and this reflects that sales of Bangles
have increased to a great extent.
Comparison of total sales volume in UK
Year Total number of volume
2018 2303
2019 2247
2020 2583
Total number of sales product wise
Year Bracelet Ring Necklace Accessory Hair band
2018 1174 280 517 2 330
2019 1584 309 246 11 97
2020 2078 204 166 100 35

On comparison of all the various products it was viewed that there are many different
variety of product being sold by Bangles. This involves the various products being sold by
company in UK that is bracelet, ring, accessory, hair band and necklace. With analysis of graph
it is visible that the sales of all the products except for bracelet is higher in 2018. But in case of
bracelet the sales are higher in 2020 and because of this increases total sales of company were
higher in 2020.
Highest selling product
Year Bracelet
2018 1174
2019 1584
2020 2078

With assistance of graph it was analyzed that maximum revenue generating product is
bracelet. This was particularly because of the reason that in all years’ bracelet is the only product
which is sold maximum times. Furthermore, in 2020 as well the bracelet was the highest selling
product of Bangles.
Quarter wise sales volume
Year total number of volume
2018
Quarter 1 577
Quarter 2 664
Quarter 3 614
Quarter 4 448
2019
Quarter 1 601
Quarter 2 567
Quarter 3 640
Quarter 4 439
2020
Quarter 1 576
Quarter 2 883
Quarter 3 725
Quarter 4 399

By referring to the analysis of collected data it is clear that sales of company were very
fluctuating. After implementation of marketing campaign in UK in month 5 of 2020 the sales
increase in second quarter which was 883. But after implementation of marketing campaign the
sales of company has reduced to 725 in quarter 3. Along with this in quarter 4 as well the volume
of sales of company decreased to 399. Hence, it can be stated that even investing in the
marketing campaign it was not having positive impact over the sales performance in UK.
Month wise sales
Month 2018 2019 2020
1 175 168 161
2 190 193 175
3 212 240 240
4 235 161 192
5 190 189 329
6 239 217 362
7 179 174 258
8 184 177 230
9 251 289 237
10 111 85 134
11 123 145 151
12 214 209 114

Along with this, after the investment on marketing campaign in 5 months of 2020 the
sales increase in next month (Liu, Yang and Forrest, 2017). This reflected that after
implementation of marketing campaign there was positive impact but in next month sales
decreased again. After that there was a continuous decrease in the sales of company.
d. Conclusion and next steps
i. Conclusion and recommendation
With the help of above data analysis, it is summarised that investing in marketing
campaign by Bangles also did not assisted them in increasing sales performance of company (Ma
and et.al., 2017). This may be pertaining to the fact that company is not requiring a focus on only
marketing. This is due to the reason that with help of the data it was witnessed that there are
different products of company which are not performing good in UK.
For example, hair band is the product which has a continuous decrease in its sales
volume. In 2018, it was 330 then it decreased to 97 in 2019 and finally in 2020 it was 35. Hence,
for this Bangles must take into consideration this product as only marketing will not assist in
improving sales of company. It might be possible that the product of company is not worth it or
is not liked by consumers.
Hence, in this situation it is recommended to Bangles that they must disinvest this
product as it is not earning much profit. In addition to this, another recommended strategy to
Bangle in dealing with this situation is that they must conduct a market research. This is

pertaining to the fact that when company will conduct a market research then they will come to
know about recent trends among the consumers. Hence, it might be possible that there may be
some other requirement or specification of consumer and company is not complying with it.
Furthermore, another finding from data analysis it was viewed that accessory is a
segment whose sale has increased after investment in marketing campaign. This might be
because of the reason that in 2018, sales volume of accessory was 2 but it increased to 11 in
2019. Further after investment in the marketing campaign by Bangles the sales of accessory were
100. This reflects that the marketing campaign was successful for increasing sales of accessory
(Heeringa, West and Berglund, 2017).
Thus, it is advisable to Bangles that they must invest more in marketing and bringing
innovation in this product range of company.
Along with this, it is suggested to company for analysing their performance they must
compare themselves with other competitors in UK itself. This will assist Bangles in actually
viewing its position in UK competitive market. Along with this it will also assist company in
analysing its actual position within the whole industry of UK. Further it will aid company in
making strategies and policies for facing and managing competition.
ii. Presenting different advanced techniques that can be used by Bangles to analyse the
effectiveness of UK marketing campaigns
In this digital era, most of the company uses advance technologies in order to forecast
their sales and analyse the data effectually. In the same way, currently Bangles uses statistical
analysis to examine its marketing campaign. Thus, there are many advance techniques which
includes econometric analysis, stream analytics etc. which company may use in its UK
marketing campaigns in order to analyse the data some of them are as mentioned below:
Econometric analysis: Willems (2017) stated that use of statistical methods that used in
quantitative data in order to develop theories and also helps to test the existing hypothesis with
regards to economics. In this, different tools and methods are used that assist to prove the
hypothesis such that regression model. Also, it can be used to forecast future economic or
financial trends. Further, by using this method, Bangle analyse the data in effective manner by
considering three components such that theory, statistics and data. Also, in order to improve the
UK marketing effectiveness quoted firm examine how the sales of a firm enhanced by making

valid decisions. As the model is concerned with quantitative relationship between economic
variable and it also provide input by making better decision for marketing campaign.
Pros: This method is considered as one of the best tool to analyse data effectually because it
helps in forecasting models and also increases reliability as well. Apart from this, it assists firm
to assess the consequences of implementing change within a business.
Cons: This method does not interpret the raw data in effective manner because it is used when
the company have heavy data. Due to having variation majority of the researchers do not use
such method, as it leads to generate wrong outputs. On the other hand, most of the work is relied
upon assumption and that is why, it does not identify the relation developed during testing
hypothesis and thus scholars do not use the same.
Stream Analytics: Another tool which can be used by Bangle in order to analyse the UK
marketing campaign in effective manner. With the help of such tool, company filter, aggregation
and analyse big data because company may store information in different platforms in multiple
formats (Poblet, García-Cuesta and Casanovas, 2018). That is why, suggested tool allow
connection to an external data source and further their integration into an application flow.
Further, with the help of such model, UK marketing campaigns rapidly connect with different
events to analyse the data which in turn assist to develop valid output.
Pros: With the help of such tool, company improve the operational efficiencies and also reduce
infrastructure costs as well. Apart from this, it also assists to provide faster insights and actions
that leads to identify the valid outcomes within UK marketing campaigns as well
Cons: Sometime, using such tool may crash on invalid data and as a result it causes negative
impact upon UK marketing campaigns. Therefore, most of the business do not use such method
in their campaigns in order to analyses the data for predict the sales. Also, it is not suitable for all
company because it is limited to language and also do not have openness of a full programming
language.

REFERENCES
Books and Journals
Franke, D., and et.al., 2017. ATSAS 2.8: a comprehensive data analysis suite for small-angle
scattering from macromolecular solutions. Journal of applied crystallography, 50(4),
pp.1212-1225.
Heeringa, S.G., West, B.T. and Berglund, P.A., 2017. Applied survey data analysis. CRC press.
Ho, J., and et,.al., 2019. Moving beyond P values: data analysis with estimation graphics. Nature
methods, 16(7), pp.565-566.
Kamilaris, A., Kartakoullis, A. and Prenafeta-Boldú, F.X., 2017. A review on the practice of big
data analysis in agriculture. Computers and Electronics in Agriculture, 143, pp.23-37.
Liu, S., Yang, Y. and Forrest, J., 2017. Grey data analysis. Springer Singapore, Singapore, doi,
10(1007), pp.978-981.
Ma, Z., and et.al., 2017. The role of data analysis in the development of intelligent energy
networks. IEEE Network, 31(5), pp.88-95.
Mahdavinejad, M.S., and et.al., 2018. Machine learning for Internet of Things data analysis: A
survey. Digital Communications and Networks, 4(3), pp.161-175.
Miles, M.B., Huberman, A.M. and Saldaña, J., 2018. Qualitative data analysis: A methods
sourcebook. Sage publications.
Poblet, M., García-Cuesta, E. and Casanovas, P., 2018. Crowdsourcing roles, methods and tools
for data-intensive disaster management. Information Systems Frontiers.20(6). pp.1363-
1379.
Willems, G., 2017. Digitale tools voor kwalitatieve data-analyse binnen historisch
communicatiewetenschappelijk onderzoek: toepassing en reflecties. Tijdschrift voor
Communicatiewetenschap. 45(3).
Online
5 reasons why data analysis is important for every business. 2021. [Online]. Available through:
< https://businesspartnermagazine.com/5-reasons-why-data-analysis-is-important-for-
every-business/ >
Eight trends in data analytics. 2021. [Online]. Available through: <
https://www.dbta.com/BigDataQuarterly/Articles/Eight-Trends-in-Data-Analytics-
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