Data Analysis for Business Growth: Trends, Techniques, and Approaches

This report provides a comprehensive analysis of data-driven decision-making in the business context, with a specific focus on the bangle industry in the UK. It begins by identifying and examining key trends and changes that have increased the importance of data analysis for businesses, such as the volatility in the market, the increasing use of AI, and the value associated with bangles. The report then evaluates different analytical approaches, including descriptive, diagnostic, predictive, and prescriptive approaches, with a recommendation for the diagnostic approach for the case study. Furthermore, it delves into various analytical techniques used in the current market scenario, illustrating how these techniques were applied in the context of the bangle industry to analyze sales data from 2017 to 2020. The analysis reveals a consistent increase in sales during this period, highlighting the effectiveness of marketing campaigns and the importance of data analysis in informing future marketing strategies. The report concludes by emphasizing the usefulness of data analysis techniques for businesses like Wood from the Trees (WFTT) in making informed decisions and recommending future courses of action to ensure continued business growth.

Data driven decisions
for business

Table of Contents
INTRODUCTION...........................................................................................................................1
MAIN BODY...................................................................................................................................1
1. Detailed identification and examination of the trends and key changes that increased the
importance of analysis of data in firms such as bangles..............................................................1
2. Evaluation of different analytical approaches that are used to answer the questions that are
related with the working of the business......................................................................................2
3. Detailed examination of various analytical techniques that are prevailing in the current
market situation which helps in answering the business related question in an appropriate way
......................................................................................................................................................3
CONCLUSION and Recommendations..........................................................................................7
REFERENCES..............................................................................................................................12

INTRODUCTION
Decisions making is one of the most important as well as essential aspect for each and every
business which is operating in the current market scenario irrespective of the industry in which it
is operational and decisions that are taken on the basis of the data that is formulated by the
experts of the company becomes much more crucial and critical as it has the potential to increase
and improve the value of the firm in the long run (Biswas and Sen, 2017). Wood from the Trees
is an organisation which is established in the UK and deals in providing various services of
business support decisions by analysing the data in a sequential manner for various firms which
are not capable of doing so and thus it has captured a larger share in the market because of it. In
this report there is a discussion about changes and trends of the bangle industry in the UK and its
importance from the organisation’s point of view. Apart from that this report also covers analysis
and evaluation of data so that it can help a firm to grow and prosper in the industry in which it is
working. Further this report also covers appropriate recommendations which can prove
beneficial for the company in the long term.
MAIN BODY
1. Detailed identification and examination of the trends and key changes that increased the
importance of analysis of data in firms such as bangles
Since the industry in which the above mentioned firm is working is highly competitive as
well as dynamic in nature and thus there are numerous trends of the market and by analysing
these trends a company make necessary and appropriate changes in its working so that it can
sustain in the market for a much longer time period as compared with its competitor that are
prevailing in the similar market conditions (Clark and et.al., 2020). There are a number of
changes and trends in the bangle industry too which are explained in an elaborated manner
below-
 Volatility- Bangle industry in the UK is highly volatile in nature and it mostly tends to
grow in an upward direction which helps in increasing its demand in the market because
of the value that it carriers with itself (Fruhwirth, Ropposch and Pammer-Schindler,
2020). Data analytics can add value in it as past and present situation can be evaluated
with the help of detailed study and rigorous research which can further prove useful in

investing in it for the future so that deviations can be minimised which can result in
increased profits and growth of the company in the long run.
 Use of AI- There is an increased use of the artificial technology in the bangle industry so
that all the resources can be utilised to the maximum which will result in reduced cost
and increased profits for the enterprise (Grandhi, Patwa and Saleem, 2020). Since AI is
one of the most important aspect in the current scenario as it proves beneficial in
increasing the performance by subsequently improving the conditioning of the business
and data analytics can help in adding value to it as it can gather relevant information
which can prove useful for the industry so as to male necessary changes and adopt
appropriate measures which can help the company to grow in the industry.
 Increased value- Since bangles carriers a lot of value in the market it is also used as an
asset and can help in fetching higher amounts and that too within a short period of time
giving higher returns to the owner (Härting, Reichstein and Schad, 2018). Also there is an
upward shift in the prices of it every now and then and thus it is beneficial to purchase it
as early as possible so that volatility can help in a positive way rather than affecting
adversely. Data analytics carriers a lot of value in it as it helps in evaluating the true and
fair picture of the current positioning of the market so that an individual can take
appropriate decisions about the investment so that it can add value to it in the long term
aspect.
2. Evaluation of different analytical approaches that are used to answer the questions that are
related with the working of the business
Analytical approach is one of the most crucial as well critical aspect as it is regarded as a
process of breaking down a bigger problem into smaller pieces so that all the factors can be
further evaluated in an accurate manner so that solution of each one of them can be identified in
a precise way (Hartmann and et.al., 2016). There are a number of different approaches that are
used by various firms in order to come to a conclusion so that they can sort out the problem that
is occurring in the current scenario and the most important ones are described below in a
systematic manner below-
 Descriptive approach- It is a type of approach in which all the relevant and important
data is summarised or described in such a manner so that it can help to understand the
current circumstances that are prevailing in the market in a better way by using advanced

technology of business intelligence so that all the aspects can be deeply studied
(Wingard, 2019).
 Diagnostic approach – In this type of approach mostly the past performance is evaluated
and analysed so that it can be compared with the present situation so as to identify the
things that are happening and to find out the possible reasons too for the problems and the
result of it is mostly an analytical dashboard (Wu, Chen and Tsau, 2017).
 Predictive approach- This is an approach in which prediction is done for the possible
outcome with the help of different tools and techniques that are prevailing in the current
scenario like machine learning technique, statistical models, etc. so as to come to a
concrete conclusion about the things that can be done in order to overcome all the
problems that are faced by the company (Hazen and et.al., 2018).
 Prescriptive approach- It is mainly a part of the previous approach as it is mainly used
for finding out one or more solutions to the problems so that the best one could be chosen
from the number of alternatives that are present in front of the enterprise (Zhang and
et.al., 2017).
All the analytical approaches are of equal importance but the one that will be used for the
firm that is Wood from the Trees is diagnostic approach as in it past performance is compared
with the present and thus chances of any type of error is minimum which will subsequently result
in increased performance of the organisation in the long run.
3. Detailed examination of various analytical techniques that are prevailing in the current market
situation which helps in answering the business related question in an appropriate way
There are various steps which were taken in WFTT for the purpose of cleaning the data
are as follows-
 Identification of methods- With the use of methods a company like WFTT was able to
make sure that the data analysis was done in a right manner which helped in deriving of
conclusions and recommendations in a better manner (Kim, 2016).
 Filtering of data- The raw data was taken at first by WFTT and it was used by the
company so that the right decisions were taken in an effective manner by it to analyse and
interpret the data in a proper manner.
 Arrangement of data- The raw data obtained by WFTT was arranged in the right
manner which helped a lot in ensuring that the company was able to effectively use the

data in a proper manner for deriving the conclusions and recommendations which can be
useful for the future (Pera, 2019).
 Alignment of data- WFTT had to align the data according to the various parameters
which were available which helped the company a lot in ensuring that the data analysis it
was carrying out can be done in a highly appropriate manner.
The dataset of Bangles for the analysis of WFTT is given as follows-
Analysis- The Sales in the year 2017 was 50000 which increased to 60000 in the year
2018. This shows that with the use of appropriate techniques and methods Bangles was able to
enhance its overall level of sales without problems and issues. Also this can shows that the
1 2
44000
46000
48000
50000
52000
54000
56000
58000
60000
62000
Row 3

company has made rapid progress in the terms of sales as well as revenues generated by it which
helps in ensuring the overall goals and objectives related to the sales can be attained.
Analysis- The Sales in the year 2018 was 60000. This increased to 70000 in the year
2019. Therefore in this way it can be said that Bangles has been able to increase the sales from
the previous year using appropriate techniques and methods which is helping the company to be
able to enhance the revenues and the level of profitability in a proper manner.
1 2
54000
56000
58000
60000
62000
64000
66000
68000
70000
72000
Row 7

Analysis- The Sales in the year 2019 for Bangles was 70000. This increased to 80000 in
2020. This signifies that the company has been able to use its marketing campaign in a better
manner to be able to attract the various types of customers for the purpose of enhancing the
overall level of sales effectively and efficiently without facing problems and issues. Further this
was helpful for it in being able to increase the level of profitability.
Key points from the analysis-
 The Sales of Bangles has increased rapidly after the year 2017 till the year 2020. This has
been the result of the extensive marketing campaign which was carried out by the
company in these years which helped it a lot in enhancing the level of sales.
1 2
64000
66000
68000
70000
72000
74000
76000
78000
80000
82000
Row 11

 The increase has been constant in between the years by 10,000 pounds. Therefore it can
be said that due to the extensive marketing campaign efforts made by the company in
these years it has been able to ensure that the overall marketing goals and objectives are
achieved effectively and efficiently. Thus it can be said that the company has been able to
ensure that it has maintained a constancy in the increase in sales.
 The overall analysis suggests that there is a particular importance of using the data
analysis which helps in ensuring that the right marketing techniques to be applied in the
future can be identified for enhancing the level of sales which will put an impact on the
profits. This will help a lot in ensuring that the techniques to be applied in the future can
be determined in a proper way.
CONCLUSION and Recommendations
The conclusion from the above discussion is that the Data analysis techniques can be
highly useful for ensuring that WFTT is able to use analytical approaches and methods for the
purpose of performing the relevant analysis and interpretation of the data of Bangles company.
This has been very helpful in ensuring that the future course of action is determined without
problems and issues.
Thus it can concluded that from the year 2017 to the year 2020 the overall level of sales
of Bangles has increased due to the marketing efforts which have been made by the company in
U.K. Thus it can be said that the company has been able to ensure that the sales revenues can be
enhanced in an appropriate manner without problems and issues. This can help it a lot in
targeting a higher-level of performance in the future.
However the Data analysis which was performed by WFTT has some scope for
improvements which can be helpful for it in ensuring that the efficiency and effectiveness
through this particular data analysis can be improved. For this purpose some steps which can be
taken are explained as follows-
 Identifying the data properly- The identification of the data can be done more properly
when this particular data analysis is performed in the future by WFTT. This will be
helpful in ensuring that the sales are analysed and interpreted in a much better manner.
 Use of additional data- The additional data should be made available for ensuring that
there is no problem in performing analysis and interpretation. Thus in this way WFTT
will be able to ensure that with the availability of this particular additional data the

company is able to achieve its particular goals and objectives. Additional data is useful
for ensuring that the appropriate support is available.
 Use of more graphs- More graphs can be used by WFTT so that it is able to ensure that
the overall graphical representation of the data figures which have been given can be
carried out appropriately. In this way the company will be able to ensure that the data
analysis of a company like Bangles can be performed in a better way. For this it is needed
that more data can be gathered about the company's sales and the change which was
brought in it which increased the amount of sales. This will be helpful in the preparation
of more graphs which will provide an accurate representation of the data.
There are also certain type of steps which can be used by Bangles to be able to analyse
the effectiveness of the UK marketing campaign. Some of these steps are explained as follows-
 Econometric analysis- This is a method in Statistics which can be used in order to
determine the empirical content in the economic relationships. Thus in this way a
company like Bangles can make the right use of this particular analysis to be able to
ensure that the overall analysis and interpretation can be done in a proper way.
 Regression analysis- Through the use of Regression analysis the change in the various
types of variables can be identified clearly. Therefore in this way it can be said that
Bangles can make use of this particular analysis to be able to use the findings in a proper
manner.
Thus, By Summarising all the above information it can be said that Data analysis is quite
an useful technique to be able to summarise and make use of the data in a proper manner. There
are different types of trends which can be useful for the purpose of ensuring that the Data
analysis is done effectively and efficiently.
The use of an analytical approach is quite helpful for ensuring that the analysis of the data
is done appropriately. This helps in identifying the changes which have occurred in the last one
year and determining the future course of action to be taken.
In the Analysis part, the use of data was made by arranging them into different types of
tables. Further the use of Graphical representation was made by ensuring that Bar Graphs were
used to be able to represent the data correctly. Further the analysis of these graphs was carried
out appropriately.

The Key Points from the analysis were obtained which helped a lot in ensuring that the
conclusion of this particular part was made for the purpose of analysing and interpreting the
given information and also determining the course of action to be taken in the future.
Slides from the board meeting-

REFERENCES
Books and Journals:
Biswas, S. and Sen, J., 2017. A proposed architecture for big data driven supply chain analytics.
arXiv preprint arXiv:1705.04958.
Clark, A. and et.al., 2020. Industrial Artificial Intelligence, Business Process Optimization, and
Big Data-driven Decision-Making Processes in Cyber-Physical System-based Smart
Factories. Journal of Self-Governance and Management Economics. 8(2). pp.28-34.
Fruhwirth, M., Ropposch, C. and Pammer-Schindler, V., 2020. Supporting Data-Driven Business
Model Innovations. Journal of Business Models. 8(1).
Grandhi, B., Patwa, N. and Saleem, K., 2020. Data-driven marketing for growth and profitability.
EuroMed Journal of Business.
Härting, R.C., Reichstein, C. and Schad, M., 2018. Potentials of Digital Business Models–
Empirical investigation of data driven impacts in industry. Procedia Computer Science.
126. pp.1495-1506.
Hartmann, P. M. and et.al., 2016. Capturing value from big data–a taxonomy of data-driven
business models used by start-up firms. International Journal of Operations &
Production Management.
Hazen, B. T. and et.al., 2018. Back in business: Operations research in support of big data
analytics for operations and supply chain management. Annals of Operations Research.
270(1). pp.201-211.
Kim, P. T., 2016. Data-driven discrimination at work. Wm. & Mary L. Rev.. 58. p.857.
Pera, A., 2019. Towards effective workforce management: Hiring algorithms, big data-driven
accountability systems, and organizational performance. Psychosociological Issues in
Human Resource Management. 7(2). pp.19-24.
Wingard, D., 2019. Data-driven automated decision-making in assessing employee performance
and productivity: Designing and implementing workforce metrics and analytics.
Psychosociological Issues in Human Resource Management. 7(2). pp.13-18.
Wu, P. J., Chen, M. C. and Tsau, C. K., 2017. The data-driven analytics for investigating cargo
loss in logistics systems. International Journal of Physical Distribution & Logistics
Management.
Zhang, Y. and et.al., 2017. A framework for Big Data driven product lifecycle management.
Journal of Cleaner Production. 159. pp.229-240.