Report on the Wall Stores Big Data

Report on the Wall Stores Big Data


Since the wake of the 21st century and the embracement of the technology, research companies dealing with a great deal of data have taken on the use of t big data technology. Big data technology uses the software technology to analyze, extract and also to process data from a huge set of data that could be impossible to be handled by the use of the traditional methods of analyzing, processing and extracting the data. This paper therefore focuses on the application of the big data and the benefits of the technology in the research companies in the USA and the rest of the world. In the contemporary world of business, big data technology is not only useful in the big businesses but also in the small businesses. (Russom, 2011).  This is due to some of the benefits that are sure to come from the application of the technology in the small businesses too. There are many reasons that validate the small businesses to the use of big data in making the data driven decisions and this paper will look at in details. It can be said that the world is running in a big data revolution which is made possible with the improvement in the world technology that is the internet, wireless connections, smartphones and the social media in general. There are so many applications of big data and those discussed in this paper are the exhaustive applications of the technology but one is free to exhaust more other applications of the technology. The particular small business that could make the use of the big data technology is the case of the retail shops that may have a range of issues to handle and may need the use of the big data technology. The name of the specific retail shop is Wall stores.  Some of the benefits discussed in this paper are such cutting on costs and also increasing the efficiency of processes in the business organization. However, the paper goes beyond the two mentioned benefits and explains more benefits of the technology in the chain stores all over the world. (Zikopoulos & Eaton. 2011).  The two sectors which affect the businesses from the use of the big data technology is the motivation aspect and the planning considerations in the business. This report choses the Wall stores in the analysis due to the fact the company does not have robust techniques of the big data technology. The paper insinuates that the risks facing the company are due to their use of the traditional methods. It will be revealed that the use of the big data technology acts as a motivator to the new hires in the businesses and also to the company. The planning consideration will also be analyzed.

Big data and motivation in Wall shop retail

With the new technology in place and the big data taking over the many traditional programs used in the businesses. Most of the retail businesses are extensively using the big data technology in their hiring program. The big data technology in this case plays the role of digging dipper into the history of the applicants in a very technical manner. By using the big data techniques, an applicant’s historical background can be analyzed technologically thus unveiling all the traits of an individual. This means that the big data technology in this case will check all boxes and will ensure the hiring of only the best at the end of the vetting process.

The big data technology will be able to do what is called mining data of a sensitive nature and which all the other traditional strategies would have overlooked anyway. One thing is that the technique not only mines all the digital footprints of the individual applicant but it technically unveils all the personality of the individual and thus putting the HR team of the business in the best position to make the right decisions of who to hire and who not to hire. It is by the use of this technology that many companies such as the chemistry group. Due to the fact that this technique provides a far richer and detailed digital report of the individual applicant, it at the end of the day provides more accurate assumptions about the character of the applicant. Through the use of data mining and the algorithms the small and medium retails businesses will not only be able to look beyond qualifications and pressurized interviews on their best hires but also it gives a particular validation to the applicants too. All this seems to be centered only the business landing on the best picks for their hires but there is the motivation part for the successful applicants at the end of the day. From the complexity of the hiring process, the workers may be anxious and so excited from the thought that they may have landed on the jobs with luck. Another fact is that they may reckon that some slight exaggerations on their CVs may have helped in the acquisition of the jobs. Through the thorough vetting process and being accepted at the end of the day, the workers will have the motivation and pride that they are best for having been chosen as the workers. Normally, people will always cling hard on the hard earned things in their lives and would do anything to sustain the acquired objects or positions in their lives. Therefore the strict vetting process of the big data technology gives the hired workers the motivation. They will definitely work so hard and ensure to maintain their entry behavior into the business as workers. Usually it is the most motivated workers that are productive and work as if they owned the business just due to some appreciation from the nature of hiring accorded to them during the interviews. It is therefore the role of the HR team in the retail businesses, small or medium to pressure the management for the implementation of the big data in the hiring process. One specialist in the chemistry group defined the big data process in the hiring process as an, “Individual’s digital footprint” It was realized that the use of the technology is the best sieve for the best hires who make to the workers team and automatically cuts off those applicants with some questionable traits that may be of harm to the small retail businesses. One of the reasons that make the technology more suitable for retail shops is that they are more vulnerable to cases of fraud and theft due to worker infidelity and it is for this reason that data mining is important to ensure the hiring of only workers with integrity.

Deficiency to be solved

For the case of the Wall Shop is that there is a low motivation rate to the workers from other ways apart from the use of salaries. The workers in the company are simply elected on the basis of their performance during the interviews and also the information presented on their CVs. This is not the best strategy in hiring of the workers as it risks the hiring of those applicants who forge their CVs and also those who fake their personalities during the interview sessions. Every applicant is aware of the importance of the interview and they will always mascaraed as the best workers to pick and then unveil their real characters after they are accepted as workers. This is a threat to the business as the business may hire unqualified and untrustworthy works who may slow the achievement of the company’s goals. It is also a risky situation as there is no motivation among the workers as they know they easily found their way into the company. Unmotivated workers don’t work for their own development and also for the development of the businesses they work for. It is therefore important for the Wall shops to come up with strategies of including big data techniques in their hiring programs.

Big data and planning consideration in the retail businesses

Planning is one core objective in all businesses including the small and medium retail businesses as it aid in the prevention of risks occurring in the businesses. Risks are due to come to any business operation but when planning is maintained in the businesses, the risks are either reduced or prevented from happening totally. With the use of the big data technology in the businesses, planning will be effective at the end of the day and therefore propel the operations of the businesses towards the achievement of the financial goals of the business.

One of the most common for the collection of big data in retail businesses is through the use of the loyalty programs. This way the businesses get a picture of the market trends and the behavior of the consumers in a given region where the operations of the business are evident and actively operational. Big data can be collected from the statistics taken from the credit card transactions, user login statistics and the tracing of the IP addresses. The data is collected strategically from the techniques of the big data technology and thus used in the planning and prediction of the businesses future operations. For instance, a retail business which operates online sales may use the online purchasing numbers and behavior of the customers to make future plans of how to conduct their business. In case of increased online purchases of a particular product, there may be need to increase the production of the product on the online stores and also in the physical stores which the clients may access easily. A low purchase record from a particular products may invite analysis of the situation to discover what to be done to improve the sales of the product. In such a situation the business may decide to come up with a pilot program of intruding a substitute of the same product and watch the purchasing behavior of the clients and thus make amendments in real time.

By using the big data techniques, some algorithms may be used in analyzing trends on the social media platforms to predict what may be the preference of the masses in an anticipated time. For instance the algorithms may provide suggestions that the most searched product on the internet by most youths is the muscle boosting supplements. (Wang, 2018) The management of the business will therefore use the statistics to provide more and more of the products on their online stores to meet the demands of their online clients. The big data technology may also provide the insights into the weather changes to come up with the bets programs to suit the demands of the clients in real time. An example that the retail businesses may copy is the case of the Walgreen Company used the big data statistics to anticipate the weather changes. (Custers & Uršič.2016).  They anticipated the increase in humidity and therefore matched this situation to the most suitable products that could be used more by their clients. The predicted product was the anti-frizz products which could most preferred by the women. Providing the products in real time is a benefit to the clients and also the company as it gets to sell more than any other time of the financial year.

Deficiency to be solved

Inaccuracy of the traditional prediction techniques

The Wall shops are currently using the traditional methods in the prediction of the future business trends and it is due to this reason that sometimes they are caught unawares with the unforeseen risks. The traditional methods of predicting business trends are usually inaccurate due to their overuse of the aspect of assumptions. The company may use traditional strategies in predicting the buying trends of a particular product and due to the changing nature of the world economy, the assumptions could be wrong and misleading. Big data technology uses a range of statistics that are close to accurate in coming up with the future business trends.( Wang et al.,2018) The use of a range of aspects provides a more accurate prediction and thus the decisions made by the company have high chances of being correct than false.


The application of the big data techniques to the Wall stores company will be of great benefit in terms of mitigating the risks made by the business due to lack of proper planning and also mitigate workers from a technique other than just increasing in salaries.