DATA DRIVEN DECISIONS FOR BUSINESS
DATA DRIVEN DECISIONS FOR BUSINESS
Task 1
Introduction
Data analysis has become an important facet of each organization aiming at growth and expansion. It has become an integral part of the business operations. Decisions based on data provide insights into a company’s working capacity and competency in a global world. This data-driven decision-making acts as an asset to each organization it promotes better decision-making. It analyses real-time data to achieve objectives and set goals (Shamim et. al. 2019). This report aims towards analyzing the performance of COTS in the current business scenario. It further focuses to identify plans of expansion for the firm by evaluating current business strategy and performance through data analysis and interpretation. The major benefit that data-based decision reflects is the ability to foresee and predict future sales and profit accurately. The purpose of the report is to:
- Obtain and identify the performance gap in the current and future potential of the business.
- Evaluate the current strategy of the business and the need for business diversification, expansion or product development to cater to new markets.
- Evaluate market demands of current products and sales of the three best coffee shops in Poole, Plymouth and regions.
Project planning:
The project is focused towards analyzing the performance of the organization as a whole considering market demands, consumer taste, the need for expansion and current strategic goals. It will analyze the impact of chosen business strategy and the requirement of a new business model to attain higher growth prospects in future.
The suitable framework of data analytics for COTS
A data analytics framework is a scientific approach that aims to develop a broader understanding of the database and its interpretation to make informed decisions. It evaluates collected data and summaries information to strategies the firm’s operations and performance standards (Rialti et. al. 2019). It provides a custom-made solution to an organization’s productivity issues and scrutinizes profitable alternatives through data analysis.
For COTS, considering its objectives the firm must use PPDAC software to assess the current performance of the company. This tool enhances flexibility and eliminates data errors which provides faster and more accurate data timely. This helps to make decisions that are rational and logical based on a scientific approach and supported by facts.
Key performance indicators for COTS
Every organization assesses its performance to determine its position and competitiveness in the global business community. Performance evaluation is indicative of a firm ability to nurture and grow. It highlighted the capabilities and competencies of a firm in an industry or a region. For COTS KPIs are extremely important as they assess the firm’s performance from all aspects. The market is competitive for COTS therefore a consumer-centric approach will help the firm in the long run. For this, the organization must evaluate consumer preferences, local demands and competitor’s policies to improve data quality and decisiveness (Côrte-Real et. al. 2020).
Task 2
Data quality issues in general:
For every organization data has been an integral information provider source to enhance decisiveness. An accurate database can bring growth and development to a firm and enhance its potential (Berndtsson et. al. 2018). However, large databases are difficult to handle and possess errors and mistakes that can lead to inaccurate results and unrealistic outcomes. For instance, data duplication leads to inaccuracy whereas inconsistency leads to errors. Ineffective handling of data can result in data loss it tempering whereas improper analysis depicts false results. All these affect data quality and decision-making.
Data issues in COTS
For an organization such as COTS data is highly crucial as it helps the firm to stay competitive and innovative. It aims to develop an understanding of consumer preferences and market conditions. This can be beneficial for futuristic decisions (Ghasemaghaei et. al. 2019). However, as the organization deals in amsaove day collection, a few errors were identified in the given database of the company. These are mentioned below:
Eliminated data:
After a thorough analysis of the data, it was found that many entries were blank as the data was incomplete and missing. This reflects data inaccuracy. To resolve this value of these missing entries was assumed to be 0 to make calculations easy and were marked as yellow.
Negative values:
The database also included negative values at a few places which made the data interpretation difficult. To resolve this, the values were assumed as positive and then taken into account to depict results. These were further highlighted as green.
Spelling and number mistakes:
The dataset included many spelling mistakes and wrong data collection in numerals. This led to duplication of data, inaccuracy and inconsistency. All these enhanced data errors and impacted the quality deeply. For this, the Organization is advised to use data analysis tools and techniques to make necessary modifications or recheck the information to be precise. These changes are also highlighted in red to enhance visibility.
Task 3
Table A
- By month
- By year
- Overall analysis
From the identified figures it can be analyzed that the volume of sales in accordance with the month has been reported as 54 and it can be stated that the value has been identified as 16185.88. Moreover, analyzing the year the value is 64743.53 while the volume is 20084.39. Moreover, the standard deviation has also been calculated which is 4823.95. In order to identify the highest sales volume, the data has been collected as well as analyzed and it has been reported that in the year 2020, Newquay has reported the highest sales as 6073.5. Moreover, again the UK has reported the highest sales in the year 2021 while 2022 has the highest sales volume of Plymouth.
Table B
- By Quarter
- By year
- Overall analysis
As per the identified tabular results, the overall quarter results have been identified as 194230.61. Then after, in accordance with the year-wise data the table reports that the year 2022 is having the highest sum of sales volume which is 21988.192. Further bifurcation has been done based on families with children, retired people, married young couples, tourists, young people and single professional people. Considering the tabular representation of three-year data the overall sum of sales value is 194230.61. Considering the categorization, the year 2022 has the highest sum of sales volume which is 21988.192.
Table C
- By Quarter
- By year
- Overall analysis
To elaborate on the tabular representation, it can be stated that the sum of sales value in quarter four has been identified as 48977.13. Moreover, the bifurcation has been done between Newquay, Plymouth and Poole. As per the year-wise analysis, the year 2021 reported the sum of sales volume as 19660.5 while the year 2020 has reported it as 18604.5. Lastly, the comparison of three years can be done based on the sum of sales value and as per this year 2022 has the highest some of sales volume and sales value which are 21988.119 and 70052.61 respectively.
References
Ghasemaghaei, M., (2019). Does data analytics use improve firm decision making quality? The role of knowledge sharing and data analytics competency. Decision Support Systems, 120, pp.14-24.
Rialti,R., Zollo, L., Ferraris, A. and Alon, I., (2019). Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model. Technological Forecasting and Social Change, 149, p.119781.
Shamim, S., Zeng, J., Shariq, S.M. and Khan, Z., (2019). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information & Management, 56(6), p.103135.
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