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Data Driven Decisions for Business

Context 

Many businesses utilise data for decision-making that are referred to as data-driven business. Data-driven businesses make decisions based on the data, which guarantees that their actions can help the businesses succeed and gain a competitive advantage (Ghasemaghaei and Calic, 2019). A company like The Bangles Company, which is impeccably suitable to accomplish data driven intuitions with rapidity and efficacy can impact the remarkable growth of data. Implementing a data methodology in a coordinated and knowing manner makes a difference in a large data driven undertaking from one that lone uses information on a spontaneous premise. With the regularity of data inside the Bangles organization business, it is easier to expect that it has set up essential proficiencies in big data examination. Since data driven organisations are mounting immensely, a few patterns arise over the long haul. A portion of the patterns are accompanying toward the expanded meaning of data investigation in The Bangles Company. 

Forecasting Analytics 

Forecasting analytics is the technique that obtains data and foresees the value for the data for future observing at its unique trends. For instance, predicting the average annual sales of the Bangles Company centered on the data from 3 years. Predictive analysis factors in an array of inputs and foresees the future conduct and not just the number. 

Data as a service

Data as a service (DaaS) tools offer businesses with all they require to improve assimilate, manage, and store their data in the cloud. It eliminates the necessity to install large costly software packages to handle large data sets in efficiently (Marques, 2016). It additionally implies that organisation can be more adaptable with how they utilize their data and scale it as desired. 

Sky-high expectations

The leaders of Bangles and IT identified that the value is masked within the data, and expectations are augmented that acquiring new instincts from this data would undo operating proficiencies and business growth (Marques, 2016). These suppositions transform into an array of business objectives that influence data investing, integrating improved decision-making, safety advancements, cost-effectiveness augmentations, and better client experiences. 

Blockchain

The popularity of blockchain technology can be seen in cryptocurrency. It can enhance predictive analytics because it affirms data legitimacy, preventing false info from incorporating into analyses. It additionally permits the data analytics applications to obtain enormous data (Ridgers and Dev, 2020).

With the current trends and succession of business with the help of data-driven decisions making it can be said that data analytics assist businesses to drive efficacy, gather profound operational info and outlooks, and ultimately generate added profits. It can assist in evidence-based decision-making, examining the business-related decisions, make appropriate use of information, apply a pull on preeminent talent, and improving the aimed audience. Furthermore, data analytics explored the paramount ways for lead generation, marketing and sales, buyers' devotion and collaboration, dealing with transactions, and enhance decision-making (Marques, 2016).

Planned approaches for analytics

At present, business analytics is a leading gizmo in business fairs. It is a transformation that is impossible to evade. According to Acito and Khatri (2014), using quantitative approaches to acquire data to make informed business verdicts is called business analytics. Four analytical approaches have been explored within business analytics, including descriptive, prescriptive, predictive, and diagnostic. The analytical approach, which analyses the already existing data to explore trends and patterns and to recognise what has occurred, is called the descriptive approach. The approach that focuses on former performance to determine what and why something happens is called a diagnostic approach. The analysis usually results in an analytical dashboard. The approach in which statistics are used to foresee outcomes is referred to as the predictive approach. The approach in which analytics and several other techniques are used to determine which outcome will produce the paramount results in a given circumstance is referred to as the prescriptive approach. 


(Fig 1: Business Analystics)

Picking which style to utilise depends on the scenario of business. For example, the provided scenario signifies that The Bangles Company invested in a marketing campaign in May '20 in the UK. Now what the firm is attempting to focus on is "Did the marketing campaign positively influence the UK's sales performance?"

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The descriptive-analytical approach was selected utilising business analytics. The intention to select this approach is to outline the outcomes and understand what is taking place. This approach is only used for understanding the true conduct and not to generate any estimations. The descriptive approach is appropriate when businesses intend to identify features, prevalence, trends, and categorisations. Descriptive analytics represent the data in graphs (bar graphs, line charts, pie charts, etc.) (Delen and Ram, 2018). This approach was chosen as the incident (market campaign) has already taken place. The Bangles Company wants to focus on whether or not the effect of a marketing campaign is positive on sales. The descriptive approach helps to examine and observe the trends within the sales. Hence, for this module, MS Excel has been used as an analytical tool. 

Analysis 

DATA CLEANING 

In order to analyse the data, it is of key importance to clean the data to avert inaccurateness. If data involves outliers and missing values, it can direct to biased results. Data cleaning refers to eliminating and removing inappropriate, missing, and repeating data from the dataset (Oliveira et al., 2019). There are several steps in data cleaning. Initially, the dataset must eliminate repeating values, for instance, US/USA and bracelet/ankle bracelet. The next step is to fix structural errors, for example, hairband/hairband. Step three is eradicating insignificant values. The fourth step is eliminating missing data, which was not in the case of the Bangles company dataset. Once all of these steps are carried out, now the data is ready for analysis as data without any errors is regarded as paramount in decision-making. 

SUMMARY TABLES

Table 1

Table 1 reports the statistics of the UK, Japan, and the USA from 2018-2020. In addition, it showed the count concerning the subtypes integrating bracelet, ring, necklace, bracelet, hair band, and accessory. The table shows that the highest sales were of bracelets in three consecutive years in all nations (bracelets=109). Moreover, the sales of items were most seen in the USA (USA=174) followed by Japan (Japan=164) and then the UK (UK=160). Hence, the total number of jewellery items sold in three nations from 2018-2020 was 498. 

Figure 2: Product Analysis


Figure 1 demonstrated the visual representation of table 1 and showed that the highest sale was of the bracelet in the USA in 2018. At the same time, the least sale was observed to be accessories in Japan in 2018. However, the sales of necklaces and hairbands were equal in all three nations in three consecutive years. 

Table 2


Table 2 reports the sum of the sales value of all subtypes of the UK from 2018-2020. The table shows that the highest sum of sales value was observed of subtype Necklace and least sales value was of accessory. This implies that the most profit can be gained by necklace dependent on its sales value. 

Figure 3: Sales Value


Figure 2 displays the graphical illustration of table 2. Figure 2 shows the trends in the bracelet, accessory, ring, necklace, and hairband. It can also be observed that the sales value of bracelets was increasing in the year range of 2018-2020. Moreover, the sales value of accessories was also increasing but not much as compared to bracelets. However, sales values of other subtypes, i.e. necklace, ring, and hairband, declined in 2020. 

Table 3


Table 3 reports the statistics of all subtypes in all nations of the 5th month of 2020. It was assessed that the number of all items sold in 2020 was the same in all nations.

Table 4


Table 4 reports the sum of sales volume of the 4th and 5th months of 2020 for the UK. It can be observed that the sales volume was less in the 4th month (sales volume=192) as compared to the 5th month (sales volume=329). It was additionally reported that there was a great difference in the bracelet sales in both months. Nevertheless, other subtypes like ring and necklace have also increased sales volume but not much.

Figure 4: Sales Against Products


Figure 3 showed the visualisation of table 4 and showed the peak of the bracelet as the most sold item in the 5th month, followed by the necklace and then ring. This might be the positive impact of a marketing campaign in the 5th month, which has helped the Bangles Company augment the sales of items. However, the sales volume of accessories and hairbands was decreased in the 5th month. 

Table 5


Table 5 reports the statistics of Japan, the UK and the USA from 2018-2020. Table 5 shows the sum of sales volume concerning the subtypes integrating bracelet, ring, necklace, bracelet, hair band, and accessory. The figures display that from 2018-2020, the hair bands sale was at the top with 8403 in Japan, trailed by bracelets (5379) in the USA, and afterwards bracelets (4836) in the UK. Concerning the total amount of sales volume, the most elevated number of sales has occurred in the USA with a sum of 11391 jewels.

Figure 5: Volume of Sales


Figure 4 is the visual illustration of table 5. Figure 4 displays the maximum sales were of hairbands in Japan; however, the least sales volume was of accessories in the UK. 

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Conclusion

Regarding the business question that was the focus of the entire examination, the results and findings have worked very well. Concluding the findings of the data set, the results showed the optimistic influence of the marketing campaign on sales within the fifth month of 2020 in Japan, the UK, and the USA. The results regarding the sales showed that sales volume of Japan augments from 210n in 4th month to 234 in 5th month, USA sales augment to 345 from 231, and the UK sales augment to 329 from 192. Since the business query emphasised the impact of the marketing campaign on the UK, the results conclude that there was a major optimistic influence of the advertising campaign on the sales of the UK in the 5th month. 

As the sales of the month in which the marketing campaign took place and a month prior to it, it was interpreted that the sales of the 5th month were higher as compared to the 4th month that was because of the marketing campaign. The statistics from table 4 and figure 4 are evidence for these statements, which openly demonstrate the boost in May sales of 2020. The total sum of sales was 192 in the fourth month, integrating accessories, rings, necklaces, hair bands, and bracelets. On the other hand, in the fifth month, the sales were 329, which was explicitly a substantial change to observe. Hence, in the concluding statement, it can be stated that an advertising campaign has an optimistic influence on the performance of sales volume within the UK. 

Concerning the information provided via dataset, it might be suggested that analysis can get better if the individuals' costs of the jewel items were provided. In this way, when the prices were provided, it would be not challenging to scrutinise how much the marketing campaign has impacted the sales if we compared it to the individual costs. Moreover, with the help of individual prices, other factors can also be observed that either the positive influence on sales was due to the variation in jewellery prices over the years or does marketing campaign has to do something with it. Prices do play a major role in sales and demand. Besides, the analysis can also be enhanced if the signs of progress in the prices of the entireness of month have been provided. This can helps with distinguishing the market benefits of the jewels. The demands of these jewellery items usually depend on the prices, despite the fact that advertising techniques also play a significant role in sales. 

Next steps for The Bangles Company 

The use of advanced approaches can assist the leaders of the company in increasing sales. Though advertising through an advertising campaign is a good tactic to foster the brand, it can add to the performance of sales volume. However, as opposed to this, econometric results also confirmed providing a useful method to the company. Econometrics is not new. With the help of suitable and proper data, econometrics can compute the effect The Bangles Company can have on sales and profit. Likewise, it can assess the impacts of future objectives. The major benefit is its capability to disseminate concurrent impacts and ascertain their singular impacts. It demonstrates the amount of sales that fluctuate for each unit of marketing, for each course point, and for each degree Celsius; in all jewellery items. 

As an element of the econometric procedure, the central facets impacting the sales of Bangles Company are recognised, along with the timescales over which they produce outcomes (substantial for indorsing where bearings might undergo for fairly an extended time). Likewise, evaluating advertising impacts, econometrics has an array of eminent applications. It is probably to be utilised up to gauge the effects of the most publicising impacts, such as prices, headways, marketing campaigns, and so forth and the impacts of large-scale financial trends. In addition, it can provide every bit of information on episodic impacts severely on sales and can be utilised to discover the implications for sales of the range of uneven components such as dispatches, adverse openness, problems related to supply of items, and so forth (Cook and Holmes, 2004). 

Econometric models allow the Bangle Company to go ahead with demand by breaking the financial parts involved (Faccia, Al Naqbi, and Lootah, 2019). For instance, the econometric evaluation disclosed that the advancement in the sales of the bracelets in the UK was observed to be an enormous part of the organisation sales business from 2018-2020. The tactics to handle assessing marketing feasibility vary from one brand to another and campaign to compete and can drive the degree from advanced acknowledgement to econometrics. The Bangles Company can further utilise econometrics to determine which advertising strategy productively impacts sales or added pivotal measures (Faccia, Al Naqbi, and Lootah, 2019).

Understanding the econometric components that trigger demand makes it feasible to consider the success of the entire business. For example, what comes about to Bangles if the bracelets or hairbands or various products or if females do not want to wear out these products? It is not anything, however, a necessary and direct examination, rather have the appropriate data and comprehending how the inclusive unescapable trends are shifting can avert a business from vast continuous challenges. From high-level attribution to econometrics, there are numerous ways to cope with gauging the efficacy of marketing. Nevertheless, Bangles Company should make sure they are not merely evaluating what is direct and constantly summon up the meaning of originality (Cook and Holmes, 2004). 

References

Acito, F. and Khatri, V., 2014. Business analytics: Why now and what next?.

Church, A.H. and Burke, W.W., 2017. Four trends shaping the future of organizations and organization development. OD Practitioner, 49(3), pp.14-22.

Cook, L., and Holmes, M., 2004. Econometrics Explained, Retrieved from https://www.holmesandcook.com/_webedit/uploaded-files/All%20Files/Econometrics%20Explained.pdf

Delen, D. and Ram, S., 2018. Research challenges and opportunities in business analytics. Journal of Business Analytics, 1(1), pp.2-12.

Faccia, A., Al Naqbi, M.Y.K. and Lootah, S.A., 2019, August. Integrated Cloud Financial Accounting Cycle: How Artificial Intelligence, Blockchain, and XBRL will Change the Accounting, Fiscal and Auditing Practices. In Proceedings of the 2019 3rd International Conference on Cloud and Big Data Computing (pp. 31-37).

Ghasemaghaei, M. and Calic, G., 2019. Does big data enhance firm innovation competency? The mediating role of data-driven insights. Journal of Business Research, 104, pp.69-84.

Marques, E., 2016. Five ways data analytics can add value to your business. Available at: https://www.uktech.news/news/five-ways-analytics-data-science-can-add-business-value-2-20161106

Oliveira, A., Gaio, R., Baylina, P., Rebelo, C. and Reis, L.P., 2019, April. Data Quality Mining. In World Conference on Information Systems and Technologies (pp. 361-372). Springer, Cham.

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