Assignment Sample on Data Driven Decisions For Business

Introduction

“Task 1: Introduction and project plan”
Business planning improves the success level of organisations and increases the goodwill of a
company in the operating market. It positively contributes in shaping the internal and external
structure of the business that improves the strategic and financial position. Moreover,
efficient planning of the business strategies improves the operational activities conducted
thereby increasing the engagement level of the customers in the market (Niemimaa et al.,
2019). In this regard, it can be mentioned that increased customer engagement reflects on the
increased sales of the company that further implies increased revenue earnings and improved
profitability performance. It therefore can be stated that efficient business planning is
crucially important for organisations as it contributes in gaining a substantial position in the
market. Furthermore, sales and marketing planning as a part of the overall business plan is
also essential as it improves the financial performance with respect to revenue earnings as
well as positions the brand in the market attaining the attention of the target customers (Le
Meunier-Fitzhugh and Massey, 2019).
Upon further discussion, it can also be mentioned that effective business planning contributes
in the business expansion planning of the organisations that fosters growth and development
in the global markets (Hofmann, 2019). With reference to this discussion, the current report
incorporates an analysis of the performance of “Cafe on the sea (COTS)” with specific
analysis of the sales of the company. The report is intended to be presented to the manager of
the “Corporate strategy department” with respect to the task given as a data analyst to
conduct a three-year strategic plan that further helps in developing a business expansion plan
for the mentioned organisation. Referring to the information gained, the company was
established 15 years ago in the UK and it has gained success along these years with a chain of
15 cafes in the locations such as “Newquay, Poole, Portsmouth, Southampton, and
Plymouth”. “The vision of the company has been to provide the UK customers with a relaxed
environment with respect to cafes like France and Italy”.
Upon further information, the company has been found to be highly reliant on data analytics
as it improves the strategic decision-making abilities of the same. The report integrates an
analysis of the sales performance of the company with respect to three specific coffee shops
which are located in the areas of Blackpool, Southampton and Portsmouth. However, the
company has been competing with top brands in the UK market such as “Costa Coffee, Cafe
Nero and Starbucks”.
“Structure and purpose of the report”The major intention of this report has been to prove the manager of the “Corporate strategy
department” regarding the knowledge that I have with respect to data analytics. In addition to
this, the study intends to help the corporate strategy manager in developing business
expansion plans considering different options available such as “expanding abroad, new
product development and diversification into new business areas” based on the sales
performance of the three coffee shops. Moreover, with the analysis of the sales performance,
the purpose of the report has also been to identify the non-performing products so that better
planning for business expansion can be made with the elimination of such products. The
study, however, also highlights the performance of the company in Blackpool with respect to
the “home delivery service” provided by the same to the customers.
Concerning the structure, in the first task a plan has been developed for the company that
effectively contributes in improving the management practices and performance. In addition,
an evaluation of the key performance indicators of the company has been assessed along with
an analysis of the future improvement opportunities of the organisation. In the second task, a
discussion regarding the issues usually faced by data analysts have been integrated with
respect to quantitative data. Also, a specific discussion regarding the data issues of the
company has been incorporated along with the remedies for the same. In the third task,
tabular analysis of the sales performance of the company has been integrated whereas in the
fourth task, charting analysis for the same has been done. However, in the fifth and final task,
conclusions of the report and recommendations for the company have been provided.
“Plan for the project”
Referring to the business goal of expanding, a plan of conducting sales performance analysis
has been made where consideration of quantitative data has been undertaken. This has helped
in understanding the performance of the company in Portsmouth and Southampton as well as
the effectiveness of the home delivery service provided by the company in Blackpool. In
addition to this, considering the analysis, a plan for business expansion with respect to the
three options available to the company has been made that can help the corporate strategy
manager in understanding the opportunities of business expansion in future years. On the
other hand, concerning the dependency of the company on data analytics, a plan to conduct
the sales performance analysis with the help of data analytics has been made as it can
improve the understanding level of the performance and also shed light on the future planning
and strategies that needs to be developed focusing on the growth and development of the
company in the UK market.
“Evaluation of KPIs of COTS and improvement opportunities” Analysis of the progress made along the years of operation is essential for companies as it
sheds light on the progress of achievement of the goals and objectives developed. In the
opinion of Hristov and Chirico (2019), KPI evaluation is considered to be one of the
beneficial methods for organisations where the company gets the opportunity to analyse the
performance with quantitative metrics. In addition to this, this evaluation further helps the
organisational managers in understanding the strengths and weaknesses of the company with
respect to quantifiable performances such as revenue growth, customer satisfaction, profit
margin, customer retention rate and many more. Concerning this view and considering the
information provided, it can be stated that the customer satisfaction level of the company has
been high as it has been capable of developing 15 outlets in different locations in the UK.
On the other hand, it has been evident that with the implementation of data analytics, the
company has increased the employee base as well as retained them for future years which
further reflect on the efficient employee retention rate of the company. In addition to this,
with reference to the three coffee shops in Portsmouth, Blackpool and Southampton, the
company has been found to be competing with large brands in the market which further
imp;ies on the profitability of the company. Hence, it can be stated that the performance of
the company has been stable, however, as customers are highly motivated to engage with
brands digitally, therefore, it can be stated that with the home delivery services where
customers get the option of ordering food in online platforms, the performance and growth of
the company can further increase.

“Task 2: Data preparation quality issues and remedies”
“Generic issues”
Preparation of data in an efficient manner is essential as it sets up a background or base for
conducting further analysis thereby helping the analysts in achieving the goals of
understanding the data in an effective manner that improves the decision-making processes.
In this context, it has been evident from studies that preparing data for conducting analysis
reflects the collection of quantitative data. Additionally, it has been observed that preparation
of quantitative data becomes challenging for a data analyst as there are several issues
associated with the collection of the data. As mentioned by Alam (2021), the first and
foremost issue that is faced while preparing data is the improper information as they are
collected from unauthorised sources. In addition, data is found to be manipulated by the
respective authorities who create an issue for the data analyst in drawing effective results.
On the contrary, Li et al., (2019) mentioned that quantitative data irrespective of the data
sources are found to have technical glitches where a large data set is downloaded that contains both relevant and irrelevant information. In addition, it contains data in an unsorted
manner where there is a mixture of structure, unstructured and semi-structured data. This
potentially creates a problem for the data analyst as without sorting, it becomes difficult to
analyse specific results. Furthermore, incomplete dataset are sometimes found along with
duplicate data that creates a numeric error at the time of preparation as well as analysing the
same. This further reduces the clarity of the data thereby increasing the issues for the data
analysts in drawing potential results as desired. However, it also affects the reliability of the
data and the study thereby making the overall research an invalid one.
“Issues related to data of COTS”
Concerning the case study of COTS, quantitative data has been derived from the internal
reports of the company. A three year data concerning the sales performance of COTS in three
different locations such as Blackpool, Southampton and Portsmouth has been obtained for
analysing the overall sales performance of the company. The major objective has been in
deriving effective results that supports in effectively developing a 3-year strategic plan for the
company following its vision of expanding the business for increasing long-term operations
in the markets. In this context, referring to the data collection source, it has been evident that
the Excel file that has been downloaded reflects unsorted data with the inclusion of all the
information in an unstructured manner. This has created issues in structuring the data for
analysing the sales performance of the company in the three areas.
On the other hand, it reflects a large dataset where information has been inconsistent such as
neither according to the year nor according to the products or the sale values. This increased
the challenges of generating charts regarding the product-based performance of the company
as sorting the data has been time-consuming. However, information related to sales volume
of few products in some years has been missing which further increased the challenges of
data analysis thereby reducing the understanding level of the financial sales performance of
the company as well as non-performing products of the same.
“Remedies for issues identified”
With respect to the unsorted data, it is essential for the company to integrate technology-
aided systems for identifying the issues included in a dataset reflecting the use of “data
profiling” technique (Ridzuan and Zainon, 2019). This can significantly help in structuring
the data in an effective manner. Moreover, with the application of "data cleansing", the issues
can be resolved which can assist the data analyst in sorting the information which can further
help in developing tables and charts for analysis. However, it is essential to obtain financial data from the published annual reports as they are developed by following suitable
accounting standards and are not manipulated.

“Task 3: Data analysis and commentary”
“Monthly analysis of sales for COTS”“Sum of sales volume 2020 2021 2022 Grand total Months

January 1077 940 750 2767

February 890 780 880 2550

March 900 840 695 2435

April 1040 855 933 2828

May 971 920 980 2871

June 932 910 840 2682

July 768 859 734 2361

August 700 800 900 2400

September 900 867 960 2727

October 500 780 860 2140

November 1060 899 985 2944

December 930 645 900 2475

Grand total 10668 10095 10417 31180”

Considering Table A, the monthly sales evaluation showcased that the company's sales has
been more in 2020 compared to the other years with respect to the volume. Furthermore,
going by the results of the table, it has been noticed that although the highest sales volume
has been in 2020, the performance of the company has also been better in 2022, however,
lower in 2021. This reflected a fluctuating performance along the three years. However, on
the other hand, it has been difficult to evaluate the sales volume with respect to locations.
“Performance analysis with respect to products”

“Southampton 2020 2021 2022

Coffee 71 12 12

Hot drinks 48 12 12

Cold drinks 44 12 10

Cakes 48 12 12

Sandwiches 46 11 11

Pastry 45 11 10

Portsmouth

Coffee 12 12 12

Hot drinks 12 12 12

Cold drinks 10 11 12

Cakes 12 11 11

Sandwiches 12 12 11

Pastry 12 12 12

Blackpool

Coffee 12 12 12

Hot drinks 12 12 12

Cold drinks 12 12 12

Cakes 12 12 12

Sandwiches 12 12 12

Pastry 12 12 12

Total 444 212 209”

“Table B: Location based product performance”

(Source: Self-developed)

Concentrating on Table B, analysis of product performance has been done which has helped
in differentiating between performing and non-performing products of the company. In this
context, apart from the data of Southampton, the data analysis of Blackpool and Portsmouth
reflected a similar performance of all the products which made it difficult to analyse which
product has been not performing. However, on the other hand, relating to the third question of
the study regarding the analysis of two new products ranges of breakfast and healthy snacks
in Plymouth, the analysis has not been conducted due to missing information.
“Analysis of sales”

“Particulars Southampton Portsmouth Blackpool Total

Sales value 41490 60659.25 293541.36 395690.6

Sales volume 12875 19426.5 59056.692 91358.19

Total 54365 80085.75 352598.052 487048.8”

the sales volume and the values for COTS
have been the highest in 2022 compared to 2021 and 2020. Also, unlike the other results, this
table depicts that the sales have been higher in Blackpool compared to other two locations.
This implies the data issues that have been there which reduced the clarity of results and
understanding.

“Task 4: Data visualisation and commentary”
“Comparative sales trend”

As stated earlier, the dataset has been large and included mixed information. This potentially
created a barrier in effective analysis of the sales trend. As depicted above, the sales volume and values denote a mixed representation of the results thereby reflecting unpredictable sales
trends.
“Product-category performance”

Referring to the chart, it is evident that compared to all the existing products of the company,
the sale of coffee has been the highest reflecting the most performing product of the
company. On the other hand, the sale of cold drinks has been the lowest compared to other
products and thus be considered to be the non-performing product. However, the analysis of
two product ranges of Plymouth was not included.
“Impact of home delivery services on Blackpool sales”With reference to the above chart, it has been analysed that the “sales in Blackpool” has been
the highest in comparison to other locations. This indicates that the “home delivery service”
provided by the company significantly impacted the sales of the same in Blackpool.

“Task 5: Conclusions and recommendations”

“Conclusion”
The report hereby concludes that the COTS have been planning to expand its business in the
market in order to stabilise its strategic position. In this regard, following the KPIs of the
company, it has been evident that the customer retention, profit generation and employee
retention rate have been strong reflecting the reliance of the company in data analytics.
Furthermore, with respect to sales performance evaluation along with the new product ranges,
the data provided reflected missing information and unsorted data which lacked the
understanding of me as a data analyst. However, from the charts, it has been evident that the
service of home delivery positively impacted the sales of the company in Blackpool.
“Recommendations”
The company can be recommended to provide the data analysts with the tools of data
profiling and cleansing so that sorting the data becomes easy. In addition to this, a
recommendation for the data analysts can be made that reflects on collection of data from
authorised sources such as financial statements (Reid et al., 2019). However, a further
recommendation of continuing the business through digital channels can be given that can
improve the sales reflecting the “positive impact of home delivery service” in all locations.

Reference List

Alam, M.K., 2021. A systematic qualitative case study: questions, data collection, NVivo
analysis and saturation. Qualitative Research in Organizations and Management: an
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(KPIs) in implementing sustainable strategies. Sustainability, 11(20), p.5742.
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