Digital Strategies Through Big Data For Sustaining In Competitive Market: A Business Case On Gap Inc

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Discuss About The Principles Monitoring Continuous Assurance.

Gap is a retail company providing clothing and personal products for every gender under the name of Gap, Banana Republic, Old Navy, Athleta and Piperlime brands. The stores of Gap are situated in the United Stated, China, United Kingdom and Canada. The Gap has also provided online benefits to its customers under the domain of gap.com, bananarepublic.com, athlete and piperlime.com (Loeb 2017). The company also provides a wide variety of clothing products range for family. The clothing from Gap is a merchandise which is privately labelled for the company specifically. The company has expanded since its foundation and it is one the leader in the global fashion marketing. The company is currently looking forward to introduce big data and through big data it wants to expand its company and retain in the competitive market. The purpose of this report is to provide a business case to Gap Inc to provide digital strategies through big data to sustain in competitive market.

The structure of this report is to provide a business case describing business problem, business and IT alignment, alternatives to the technologies, analysis of alternatives, best choice and implementation plan.

Gap is a growing company but it does not have any official organizational mission. They are however referred to as brand-builder. Gap works through by providing emotional connections and cooperation with consumers across the world through creative and inspired design of products, store experiences and growing markets.

Gap is currently working to improve its business and they are keen on using Big data. The company has specialty in family clothing and has shown importance towards it consumers and employees. The business strategy is to connect with people emotionally to make a strong bond. Gap provides translation of its code of ethics in 65 different languages that poses to address the various aspects of the business (Aloysius et al. 2016). The objective of Gap is to provide clothing to targeted customers to suit their requirement through adopting digital strategies.

• Customers returning products in offline to stores bought from online.
• The free alterations is offered by Banana Republic.
• The customers are allowed to research on a product initially on web and then decide to buy at the store termed brick and mortar.
• The customers are comfortable in buying online from Gap’s brand that is well-established brand.

• There is increase in demand of products for plus size females.
• Gap wants to penetrate in the global market through introduction in countries such as Asia and Europe.
• The growing demand of organic clothing materials among the customers.
• The production cost of clothing materials is increasing day by day posing a challenge for common people.
• The unemployment rate increasing and thus this has caused customers to spend less on buying products.
• The increasing competitive retail market where there are other major players such as Amazon.

The digital strategy has disrupted the retail industries rapidly and it has affected the future of retail industries. The other retail companies are focusing on digital strategies and they are trying to fill the gap between business and customers. The most popular digital technology that is currently adopted in the market is big data and analytics (Anshari, Alas and Guan 2016). The big data is adopted by the organizations at an increasing rate. The big data has potentials to change the retail industry and it has been already adopted by some big organizations. The further paragraphs will discuss how big data is helpful in driving the retail industry in terms of feasibility, benefits, costs and risks.

Gap’s current strategies that are benefitting its customers are as follows

The business of Gap is clothing and thus they are focused on providing services to large group of people. The big data is used for the following data generated and associated with Gap’s business.

Data of material- The data of material used in fashion product is the primary data that the company wants to analyses. The materials are yarn type, wave structure, warp density and yarn twist and others (Caldarola, Picariello and Castelluccia 2015). This data is useful to collect and analyze as this helps to understand the customers demand to connect with their emotions. The fabrics are of different types and hence they should be given priority.

Data of fashion design- The data of fashion design is required to get knowledge about the fashion design that directly connects with the customer’s demands. The fashion design data helps in understanding which type of design is required by the different customers.

Data of body- The big data analytics helps to get body data in the form of 2D or 3D. The 2D data is collected through conventional measurements and 3D data is collected through body scanners in 3D format (Chen and Zhang 2014). This helps to provide information such as measurement of body and body type.

Data of color- The data on color is collected to analyze the preferences of human choices. The preferences of color shows humans emotions and behavior (Donnelly et al. 2015). Thus it is important to collect data on different colors preferred by different people.

Data of production design- The data related to production design helps to understand the production of products. This data also helps to analyze the production process such as sewing, pattern making and others, and the budget related to the production design.

The big data helps retail industries to get understanding of the global market. The big data collects data from various platforms and sources such as social media platforms. The social media platform is the major source of big data in retail industry (Dunovi?, Radujkovi? and Vukomanovi? 2013). This is because retail industry is majorly depended on social media data as this is the place where fashion enthusiasts discuss on fashion trends. The social media has contributed largely in the growth of retail industries. Thus Gap should also take into accounting the big data potential. Big data will help Gap in various ways that are discussed below.

Data from social media- Social media is the platform where people are increasingly sharing and discussing about fashion and trends. Big data collects this data to analyze and evaluate the people’s choices and their opinions (Evans and Kitchin 2018). This is then utilized by the retail industries to get knowledge of what people want and their choices. Gap will be benefitted from the comments, discussion and shared photos and videos on social platforms to utilize it to get knowledge about what people want from retail industries. The fashion shows are increasingly uploaded on social media such as Facebook, Twitter and YouTube that helps retail industries to sneak into the current trends in fashion. The social media platforms provides thinking of fashion enthusiasts so that retail industry work according to that to satisfy the customers demand.

The current business problems of Gap that they want to achieve are as follows

Engaging people- The engaging of people through effective content is important in retail industry. The people’s comments are turned into engaging sessions through retail industries using big data analytics. The contents of fashion brands helps to engage customers and big data is used to analyze these contents to develop innovative ideas and creative concepts (Ghazawneh and Henfridsson 2013). The people are bonded together through fashion contents on various platforms. The engagement of people leads to constant discussions, opinions and sharing of thoughts, boost in content and active presence on social media platform. This results in retail industries getting knowledge about people’ choices.

Latest fashion trends- The big data analytics tool is provided by different companies such as SAP that offers high-speed tools to convert the collected data into useful data for business purposes. The big data analytics thus helps to get understanding of latest trends of fashion to get knowledge which are popular among customers and which are on verge to get lost (Gregory 2015). The big data analytics make decisions based on the collected data from various platforms. The decisions are related to fashion products and its manufacturing that helps retail industries to know their target customers and collaborate to take forward the industry in the long run.

The alignment of business and Information Technology of Gap are effective to deliver satisfiable service to the target customers. However, with advanced digital technology such as Big data analytics it will become a top player (Hox, Moerbeek and van de Schoot 2017). The above discussions provide how the business and Information Technology alignment of Gap will be helpful to drive the business in present and future.

Art Peck after assuming the CEO post of the Gap Inc had brought some major changes in the organizational structure and one of them is adopting the predictive analytics to understand the preference of the customers. The adoption of the technology has emerged as one of the most successful decision made by them and it is has enhanced the goodwill of the organization in the market (Jonsson, Rudberg and Holmberg 2013). However, the question that needs to be discussed is whether the organization should invest its predictive analytic capabilities in the mode it is using or opt for a change. It has been identified that the option of outsourcing is not feasible for the organization as it is into service industry and the offerings offered by the organization if outsourced would cost the organization very much. Another notable fact which is evident after evaluating the case study that centralisation can also prove to be disadvantageous for the organization because all the responsibility is then laid upon Peck and in his absence, the proper functioning of the organizational operations are affected (Lu et al. 2015). Moving on to in-house, the deemed scenario will provide enormous authorities to the internal stakeholders which they can manipulate to fulfil their personal goal and agenda. The case for the decentralisation is same with in-house and hence it is recommended that the organization adopt the integrated mode to drive its analytic capabilities.

Potential impact of business results

The organization should move with an integrated model that would be formulated by integrating the centralisation, decentralisation and the outsourcing (Yoon, Hoogduin and Zhang 2015).). The model would consist of a model which will outsource the most sophisticated analytics to its partnering firm and save the organizational cost and time invested in the process (Martin 2015). The integrated model would also enable the organization to keep the process centralised with all the control vested with Peck however, a limited power will be provided to the local bodies to make the predictive analysis and take the decision accordingly. Taking the deemed measure will enable the organization to shoulder off extra responsibility from Peck and enable him to make more productive decision along with providing the opportunity to other prominent officials specially to make fast and urgent predictions and decisions (Merat and Bo 2013). However, there are alternative that can assist the organization in driving its analytics capability towards more productive approach and they have been discussed as follows:

There are many alternative available in the market that can assist the organization in attaining their objective. The three alternative selected are do nothing, hire data scientists and integrated mode.

Do Nothing: The first alternative to drive the analytic capability is to do nothing and maintain the quo. In the deemed scenario, the organization will continue its operations as it is and avoid the fact that there are challenges that the organization is facing.

The proposed alternative is feasible for the current scenario because it will save the effort and investment put forth by the organization in mitigating the challenges, however in the long-run the organization will suffer (Nicolaisen and Næss 2015). The reason for stating the above-mentioned fact reals on the fact that the challenges would disrupt the organizational processes periodically and will also affect the quality of organizational offerings. The deemed scenario will eventually lead to lack in competitive advantage and adversely affect the organizational sustainability.

However, the deemed alternative has its share of benefits. The foremost benefit offered by the deemed alternative is that it will ensure the operationalization of the organization in the current scenario and may eventually lead to mitigation of the challenge faced by the organization.

The cost involved in the discussed organization is minimal because no additional tools or techniques is being adopted in the discussed scenario and the organization is continuing its basic operations.

Data Scientists: The second alternative that can prove to be a significant move for the organization is hiring of a team of data scientists who will do the predictive analysis for the organization. It will also include formulating the system internally.

The deemed method is feasible because the pattern and the consumer base of the organization are the factors that would be readily understandable to the organization themselves (Nosek et al. 2014). Additionally, the data required by the analytic team would be easily provided by the organization without worrying about the cheating or leaking of the data that generally occurs with the outsourcing of the data. Hence, it can be stated that the discussed measure is feasible and can readily be adopted by the organization.

The benefits offered by the discussed measure would be that as the analytic process would be carried out within the organization, it will offer accuracy and reliability along with complete control over the operations (Pigni, Piccoli and Watson 2016). The strategies developed after analyzing the data through the deemed method will also be accurate because of the strategies are developed internally taking account of the organizational operations, pattern, environment & other crucial factor and not on a general pattern.

However, the cost involved in the deemed process would be high because the hiring the data scientist would be costly and would also include the cost incurred on maintain the system and requirements of the data analytic process (ur Rehman et al. 2016). Additionally, it would not be a onetime expenditure as the organization would have to pay the scientists on a regular basis. The data scientist would also be eligible for all the perks that the internal stakeholders of the organization are applicable for. Hence, in terms of cost the discussed measure can prove to be challenging for the organization.

Integrated: The deemed alternative is also known as alternative which divides the organizational needs and according to it divide the data analytic. The discussed mode would shift the most sophisticated tasks to the outsourcing while the simple task can be evaluated within the organization taking consideration of the organizational factors (Vasarhelyi, Alles and Kogan 2018). The results from the outsourced data analytic can then be utilized by the internal system to devise most suitable plan for the organizational sustainability and marketing strategy.

The discussed method is feasible because it offers the organization opportunity to save costs and only the complicated analytic tasks are outsourced and that too in dire situations. If, it is within the capability of the organization and its data analytic system then they can do it themselves which will save the organizational money, time and effort (Wamba et al. 2015). Additionally, as no or very less organizational data is shared outside the organization, the deemed method also increase the safekeeping of data which can be considered as one of the most prominent advantage for the organization.

The core benefits offered by the discussed alternative is in terms of cost, effort, complexity, scalability, data safekeeping and other (Wu et al. 2014). In simpler, terms it can be stated that the deemed method would enable the organization to save its organizational resources which they can use for other productive means.

The cost involved in the deemed method is conflicting because, if the organization gets in a dire situation where the data is extremely large or complicated for them to analyses then in that scenario they have to outsource it which would be costly (Yoon, Hoogduin and Zhang 2015). While in the other cases the organization is maintaining its quo and working with the resources available to them which will save them a lot of money, time, effort and other organizational resources. Additionally, as the chances of data loss are minimal in this scenario, the organizational resources involved in safekeeping of the data will also be utilized adequately which is a prominent benefit for the organization in terms of cost (Yoon, Hoogduin and Zhang 2015). Hence, it can be stated that in most of scenarios, the discussed measure is cost-effective for the organization, however, in dire situations it would demand extra investment which could prove to be challenging for the organization depending on the size and complexity of the data to be analyzed.

It has been analyzed that the organization is facing some data analytic problem that the organization needs to tackle, however, it is not willingly to adopt the method that would prove to challenge the financial status of the organization. Hence, the hiring of data scientists is not recommended though it being the most appropriate choice because it will affect the organizations financial approach. So, considering all the factor of the organization the most suitable approach for the organization is to adopt the embedded approach because it will ensure that the organization keeps in motion while maintaining its long term sustainability. Additionally, following the deemed approach will also offer the organization to better understand the needs for data analytics and while pursuing the discussed approach will also make the organization capable of devising their own data analytic team in future.

The biggest technology that has garnered the retail company’s focus is big data analytics as it is widely popular and beneficial technology. It has largely disrupted the retail sector and continue to disrupt this sector. The discussed points in the report shows that there are need of big data analytics in the company that will help the company to grow in this digital age. The discussed points show how the big data analytics will help the company to reach maximum customers and provide huge benefits to the company in terms of various aspects. The technology will also help to sustain in the competitive market. The reason for stating the above mentioned statement lays on the fact that the organization will gain experience from its self-analytic process and can also uncover some significant tips from the results received by them from the outsourcing services. It will enable the organization to develop skills to understand the analytic needs and formulate a system for themselves which in conclusion, makes the embedded approach most suitable for the organization. Therefore, the company should adopt big data analytics to improve its business functions and to provide great satisfaction to the customers.

Phase 1:

Quality and affordable clothes- The quality and affordable clothes are the ultimate objective of Gap to provide to its customers. There are various competitive brands that are there in the current market providing valuable and affordable clothes to the customers. Gap should focus more on satisfying the need of customers and providing products at affordable price without compromising the quality.

Phase 2:

Clear market segmentation- Gap should provide clear market segmentation towards its customers. The fashion industry is the industry that changes rapidly and it is uncertain in terms of rapid changing of fashion trends. The customers should be aware of what materials are used in the fashion products. The products should not only be available to the customer but they should also have knowledge about the products and materials used in it.

Phase 3:

Penetration in the domestic market- Gap should focus on entering in the International market to get more opportunity to reach the target. The moving to International market will improve the business growth in the company. The various ways of promotion will add to global recognition of the company. The Gap brands under the name of Banana Republic and Old Navy are not well recognized due to less promotions. This are the areas where there are opportunities to grow.

Phase 4:

Enhancement of sales- The franchising of business will be helpful for Gap organization as it will give the organization a chance to improve its businesses and raise revenues. The franchising of the company will help the business of Gap to become strong and attentive in the current market. The fees and regulations related to franchising will give back the money the company.

Phase 5:

Vertical integration- The fashion products of Gap is manufactured under third party vendors. This should be minimized and the company should make the fashion products on its own. This will help to make the company more recognizable. The company invests on its branding and marketing however, the products when outsourced acquires the copyright. Thus producing its own products will help to make a long lasting effect on customers.

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