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Identified Issues in Gap Inc

Discuss about the Leveraging Capabilities of Service-Oriented Decision.

According to the Berman, (2013), Increase in the online shopping and technology increases the competition among several organizations in e-commerce field. With the advancement of the information technology and introduction of the big data technology in business process helps the organization to improve higher performance and increase better customer’s satisfaction (Brown, Chui, & Manyika, 2011). Cuzzocrea, Song, & Davis, (2011) said that in order to improve the performance of the organization operations, the business (e-commerce organization) need to adapt BI (business intelligent) through Big Data Analytics. In present competitive market big data analytic has a significant impact on organization performance.

The present assignment mainly deals with the identification of the issues associated with the organization and also provides an effective opportunities regarding improvement of the performance. The assignment also deals with the identification of alternative and analysis of the alternative using different parameters such as benefits, feasibly, costs and risk. At last the assignment provides an effective recommendation and planning for implementation of ideas.

The organization Gap, Inc is mainly known as the Gap, is an American accessories retailers and worldwide clothing. It was established in the year of 1969 by Doris F Fisher and Donald Fisher and its headquarters are California, San Francisco. The organization is mainly functions five primary division banana republic, Gap, Waddington Way, Intermix and Athlete.  The organization is the largest retailer’s organization in the US and the third total international locations after H&M and Inditex Group. At the end of September 2008, the organization has approximately 135000 employees and functions more than 3727 stores in worldwide of which 2372 is located in the United State.

As per the organization financial statement, it can be found that the company can generate US$15.855 billion revenues in FY2017, US$1.479billion operating income in FY2017 and net income was US$848 million in FY2017. Moreover it can be found that the organization net sales performance was decline from FY2014 to FY2015 by 4.05 % [FY2014: US$16435, FY2015: US$15797].

The financial statement of an organization also indicates that performance of the organization also decreased from FY2015 to FY2016 by 1.81% [FY2015: US$15797, FY2015: US$15516]. The findings also shows that performance of the company in terms of gross profits continuously decline from FY2014 to FY2016 respectively. Therefore the findings and analysis shows that organization is not performing well in market and due to that they are not able to satisfy their customers that effectively impact on their performance.

Opportunities for Improvement

As per the findings and the given information, it is seen that Gap Inc performance in terms of share is not up to the mark. The findings shows that in FY2015, organization still disappointing with 24% decline performance in operating income, 6% fell in EPS as well as its net income was dropped 43% respectively. Therefore from the findings and analysis it can be observed that the main business problems that the company face in present situations are  related with the sales, revenues and income profits which decrease the performance of the organization in terms of profitability and liquidity. From the findings it can be seen that the company is not effectively able to satisfy its customers and that is the main reason of the degradation of the performance of the organization in competitive market. From the observation it can be found that Gap Inc has one issue that it cannot balm on financial situation: bad Fashion style. That the organization has not been able to offers such type of products that the customers expected from that. Its clothing style or fashion style is failed to entice customers. On the other hand, it is found that the organization adverstiment communication strategies are not much effective which also considered the main factors to reduce the performance of the organization.   From the organization financial statement it can be found that the organization is not able to manage their inventory effectively that has a significantly negative impact on its gross profit margin. The observation shows that the organization is suffered from the data security issues which could have negative impact on their results of consumer’s confidence and operations in their security measures.  The organization present strategies such as market expansion in several countries through different channel are not success. The organization also suffered issues related with the customer’s trends and tests, and as an outcome sales performance of the organization is decreased.                   

Therefore the analysis and findings shows that lack of the knowledge in marketing expansion strategies, inappropriate supply chain management strategies, data security issues, unable to identify customers trends and needs and highly competitive market in US and all over the world are the main reason of the degradation of the performance of an organization in terms of share, revenues and profitability (Brown, Chui, & Manyika, 2011). Therefore it can be said that the issues associated with the organization are decline share market, decrease customer’s satisfaction, decrease profits and revenues and issues that the organization or its franchises are unsuccessful is gauging changing consumers preferences and appeals trends.              

Business Intelligence with Big Data Analytics

In order to improve the performance and increase customer’s satisfaction in better manner Gap Inc needs to incorporate Business Intelligence with Big data analytics techniques. Implementation of this technology not only helps the business to increase performance but also helps them to identify customer’s preferences and taste in better manner. Moreover, the other opportunity is that the organization needs to enhance their supply chain market strategy which helps them to increase sales performance. In addition to this, it is seen that in US19% of appeals was sold with the help of online channel in year of 2016 as well as in year of 2015 clothing industries became the best selling through internet driven the by the organization Amazon. It is seen that the Gap Inc has more than 3000 physical stores; therefore it is the best opportunities for the business to offers their products and goods through online.

Business intelligence system are technologies and applications for storing, accessing, analyzing and gathering information for better business decision making process. Business with IT alignment (including BI with big data analytics) helps the organization to monitor and measure the key performance of the organization and also helps them in forecasting sales performance, performing data mining and analysis the preference of consumers in order to find out organization opportunities and building better brand name (Furht, & Villanustre, F2016). As per the Gap Inc case study, it can be found that the organization is presently suffered from sales performance issues that adversely impact the organization gross profit margin and revenues. Therefore, alignment of an Information technology tools and techniques would help the organization to understand the issues associated with the organization in successful manner. As studies conducted by the Chen, & Zhang, (2014), IT tools helps the business to cleanse, extract, consolidated and transformation of the heterogeneous information into signal enterprise. Moreover it also helps the business to provide the information regarding upcoming trends that helps the management to formulate and solve business issues in better manner and also support in the process of decision making process (Buyya, Calheiros, & Dastjerdi, 2016). IT tools alignment helps the Gap Inc to determine buyer’s purchasing behaviours, helps in maintaining supply chain, offers personalized offers for buyers and making assure predication.                    

From the findings it can be seen that the organization Gap Inc is presently suffered from the fraud and cyber attacks, therefore alignment of IT tools helps the business to prevent fraud in successful manner. Implementation of the IT tools helps the business to promote their products in market in successful manner (Buyya, Calheiros, & Dastjerdi, 2016). The case study of Gap Inc indicates that the organization has lack of adverstiment marketing strategies and also not be able to fulfil the needs and wants of the customers; so that these issues can effectively solve if an organization can introduce IT tools and techniques in business process.

Alternative Strategies for Gap Inc

Consumers in present days are pretty good in comparing the services and products in different e-commerce organizations from different site. The comparison mainly involves in terms of quality and price, offers provided by the sellers, consumer’s reviews as well as number of products or goods sold out. Moreover, consumers are able to getting information regarding products from several channels and have better ideas where to purchase and what to why. Therefore in such situation adoption of the big data analytical techniques allows the organization to observe customer’s purchasing behaviours and collects the information trail of information regarding their online behaviours (Zsidisin, 2003).

Therefore in order to enhance the performance and increase better market share the management of the organization Gap Inc needs to implement considered several alternatives, these are

BI with data analytics techniques: Business intelligence with data analytics techniques helps the organization to analyze the data and presenting actionable information to manager and others executives to make an effective decision in critical situation (Chen, & Zhang, 2014). Implementation of these techniques in Gap Inc business process helps them to enhance decision making, market efficiency, and increased profits as well as reduce expenses in successful manner. Business intelligence with data analytics techniques helps the business to predict tends as well as competitor’s analysis in successful manner (Russom, 2011). Gap Inc case study, it is found that lack of the predication ability and competitor analysis has an adverse impact on organization performance. Thus the implementation of BI helps to solve such type of issues in successful manner.  

Making supply chain fashionable:-   The organization Gap Inc needs to implement digital transformation in their existence supply chain management strategies that helps them to reduce distribution lead times and product development, so that enabling gap to be more effective and responsive to consumer’s preferences (Zikopoulos, & Eaton, 2011). One of the key success factors for Gap Inc is an effectively and highly responsive supply chain management strategy in their business models that helps them to enable delivery of new fashion and trends. Implementation of digital transformation in Gap Inc business models helps them to allow wholesalers, manufactures as well as distributors to adjust effectively and reduce limits and inventory costs.             

Adverstiment strategies required digitalization: - Successful implementation of the product 3.0 need better adverstiment strategies with digitalization. It is seen that, Gap Inc has lack of adverstiment strategies that create confusion in front of consumers or buyers. Therefore it is said that implementation of the better adverstiment strategies with digitalization helps the business to promote their products and goods in successful manner.                                     

Feasibilities

The feasibilities analysis mainly dependent on the economical and technical feasibilities. From the findings it can be seen that to implement big data analytics in Gap Inc business process organization needs to recruit highly qualified IT staffs members. In economical feasibilities, it is said that implantation of big data analytic techniques Gap Inc business process helps the organization to increase huge traffics and improve performance effectively.             

Benefits

The main benefits associated with the implementation of the big data analytics are increase performance of sales, increase customer’s confidence, determine the trends of market and achieve business objective in successful manner (Zakir, Seymour, & Berg, 2015).  Apart from that implementation of the big data analytics also helps the business to reduce operational costs and Drive customer profitability in successful manner.     

Costs

The total cost associated with the implementation of BI analytics in business process is US$10000.

Risks (risks matrix and risks register)

Risk

Impact

Probability 

Mitigation strategies 

Lack of IT staffs

5

Low

Hire experience employees   

Lack of finance 

4

Low

Use different sources of fund including bank loan 

Lack of expertise in using big data

5

High

Training and development 

Feasibilities

 Gap Inc business process operates both national and international market therefore enhancement of the supply chain management system aids the management to increase performance in successful manner.  

Benefits

The main benefits associated with making supply chain fashionable is that it would improve product rich to the market and customer can effectively reach to the products (O’Donnell, 2016).   Moreover it can be said that it helps the business to optimize customer’s services which directly improve the performance of the organization in better manner.      

Costs

The total cost associated with Making supply chain fashionable in business process is US$5000.

Risks (risks matrix and risks register)

Risk

Impact

Probability 

Mitigation strategies 

Lack of  staffs

5

Low

Hire more employees   

Lack of finance 

4

Low

Use different sources of fund including bank loan 

Feasibilities

The organization Gap Inc has high rich in market therefore that implementation of the adverstiment strategies with digitalization improve the customers reach in website.   

Benefits

The benefits associated with the digitalization strategies are increase products reach in huge customers, increase sales performance and revenues.   

Costs

The total cost associated with Adverstiment strategies required digitalization in business process is US$2500.

Risks (risks matrix and risks register)

Risk

Impact

Probability 

Mitigation strategies 

Lack of IT expertise  

4

Low

Hire experience employees   and promote training and development

Lack of finance 

4

Low

Use different sources of fund including bank loan

On the basis of above findings and analysis it can be recommended that the organization needs to implement business intelligent with big data analytic techniques in their business process. Implementation of the big data analytics helps the business to gather relevant information and process data in correct manner and offers quality information to management in their business marking procedures (Sanders, 2016). Moreover, in present technology ear, main objective of business is to fulfil the needs and requirements of stakeholders including customers, suppliers and vendors in successful manner and the utilization of big data analytics in business process helps them to satisfy their needs and wants in better manner. Big data analytics mainly implemented predictive analysis techniques which is mainly based on the three main key attributes captures, predicts and act (Srinivasa, & Bhatnagar, 2012). Capture mainly focused on gathering information from different sources whereas predicts includes the data mining, text mining and statistical analysis techniques (Zikopoulos, & Eaton, 2011). . Implementation of the predict analytics techniques automatically synchronized with the big data, business rule, mathematical science as well as machine learning that helps the business to make predation of upcoming trend and provide recommendation in decision making process to fulfil the demands and take benefits of future opportunities.

Implementation of the predictive analysis techniques in big data technology helps the business to provide meaningful information that learns from the past data to predict the upcoming behaviour of person in order to fulfil their needs and drive better decision (Handfield, 2006). Implementation of big data analytics Gap Inc business process helps to connect information effectively and draw a valid conclusion regarding market trends and future trends. It would help the business to exploit the pattern found in the past data to determine opportunities and potential risks before they take place (Russom, 2011). Big data analytics techniques help the business in map reduction solutions explained in below figure. It helps the business to take huge amount of data in short time of period and allow processing the collected data in parallel that helps to reduce time to process the data in successful manner.

With the help of predictive analytical techniques the organization can sell their existing products and goods in successful manner. The organization such as Netflix and Amazon uses predictive analytics techniques in its business process in order to mine the data and find the customers preferences in successful manner. Therefore it is recommended that implementation of the big data analytics helps the organization to identify the uses of pattern of consumers buying behaviour through customer’s history or express preferences.


Big data analytics helps the business to launch new product development in market in successful manner. With help of findings and findings of consumers past preferences, Gap Inc business can generate such products which the customers wants (Buyya, Calheiros,  & Dastjerdi, 2016). Moreover it also helps the organization to lean new fashion elements as well as utilized that insight to design its own products and goods.                     

It is recommended the organization needs to implement big data analytics techniques in their supply chain management process that would helps them to enhance supply chain management strategies in successful manner. This solution helps the organization to sell their goods or products in market through cost saving. In addition to this it is recommended that the management of the organization also needs to adopt better security techniques in big data analytics and their website that would helps them to increase customers confidence in successful manner (Furht,  & Villanustre, 2016). Therefore from the findings and analysis it can be said that implementation of big data analytics helps the business to execute its business operations in smooth manner.

First Level Activities

Second Level Activities

Third Level Activities

Time Duration (Days)

Preparation

Establishing scope and objectives of the big data analytics project

10

Appointing the project manager for the Big Data Analytics project

Forming the team members for accomplishing the project

Identifying the key stakeholders involved in the Big Data Analytics project

Defining the system architecture for supporting the Big Data Analytics project 

System environment identification  

Defining the technical infrastructure required for the Big Data Analytics project

15

Development environment identification for the big data project

Quality assurance environment identification for the big data project

Training environment identification

Production environment identification for the big data project 

Defining the blueprint for the business

AS-IS process analysis for the business

End-to-End Current Business Processes identification for the big data project

12

Identification of processes that need to be integrated    

Efficiently mapping the big data analytics project to the business  

Identifying and the processes to be carried out  

End to end future business processes definition for the big data analytics project

Gap identification

Identifying solutions to the gaps identified

Reporting

Program defining

Interface defining

Manual processes are defined

Business blueprint documentation

Closing the stage

Conducting the configuration and  development  

Solutions configuration

Documenting the unit test scripts

10

Solution configuration

Unit test configuration

Code development for identified gaps 

Documenting the technical specifications needed 

Unit test scripts documentation

Reporting the interface and unit tests

Closing the configuration and development stage  

Authorization definition  

Identifying and defining the roles in business

9

Defining the role of operating big data analytics

Authorization definition  

Authorization tests

Closing the authorization stage  

Data conversion

Defining big data analytics solution fields

10

Mapping legacy system fields with the big data analytics fields 

Cleaning the data

Closing the data conversion stage

Migration of data program

Data mitigation program

9

Conducting unit test for migration of data

Closing the migration stage

Testing

Documenting the test scripts

5

End to end test

Closing the test stage

Training

Organizing training  

7

Training documentation

Conducting training

User acceptance testing

Identifying scenarios of business

9

User acceptance testing documentation

Preparing scripts for user acceptance testing

Functionality test of the big data analytics

Closing the stage

Cutover

Clean data migration

1

Making the big data analytics systems fully operational

 

Total

97

Symbol

Activities

Time Involved (Days)

A

Preparation

10

B

Defining the system architecture for supporting the Big Data Analytics project 

15

C

Defining the blueprint for the business

12

D

Conducting the configuration and  development 

10

E

Authorization definition 

9

F

Data conversion

10

G

Migration of data program

9

H

Testing

5

I

Training

7

J

User acceptance testing

9

K

Cutover

1

Conclusion

Therefore from the findings and analysis it can be concluded that in order to success in competitive market and attract huge amount of customers towards products and services IT technology plays the vital role. The observation shows that in present era taste of the customer’s changes continuously therefore it is vital for the organization to identify needs to the customers in successful manner. This can be effectively obtained by the organization with the help of the implementation of the big data analytics techniques. Utilization of the big data analytics technique provides the meaningful information to management in decision making process.

References

Berman, J. J. 2013. Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information. Waltham: Elsevier

Brown, B. Chui, M. & Manyika, J. 2011. Are you ready for the era of ‘big data’? McKinsey Global Institute

Buyya, R., Calheiros, R. N., & Dastjerdi, A.V. 2016. Big data: principles and paradigms. Cambridge: Elsevier.

Chen, C. L. P. & Zhang, C.-Y. 2014. Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, vol. 275, pp. 314-347

Cuzzocrea, A., Song, I. Y., & Davis, K. C. (2011, October). Analytics over large-scale multidimensional data: the big data revolution!. In Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP (pp. 101-104). ACM.

Demirkan, H. & Delen, D. 2013. Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, vol. 55, iss. 1, pp. 412-421. Dobre, C. & Xhafa, F. 2014. Intelligent services for Big data science. Future Generation Computer Systems. vol. 37, pp. 267-281.

Furht, B. & Villanustre, F. 2016. Big Data Technologies and Applications. Cham: Springer. Gadde, L.-R., Håkansson, H. & Persson G. 2011. Supply Network Strategies. 2nd ed. Chichester: John Wiley & Sons.

Handfield, R. 2006, Supply Market Intelligence: A Managerial Handbook for Building Sourcing Strategies. Boca Raton, FL: Auerbach Publications.

O’Donnell, E. 2016. The Digital Procurement Process: How the Integration of Data and Analytics is Revolutionizing the End-to-end & Cognitive Procurement Process. Empower 2016 IBM, October 4 - 6, Orlando, Florida.

Russom, P. (2011). Big data analytics. TDWI best practices report, fourth quarter, 19(4), 1-34.

Sanders, N. R. 2016. How to Use Big Data to Drive Your Supply Chain. California Management Review, vol. 58, iss. 3, pp. 26-48.

Srinivasa, S., & Bhatnagar, V. (2012). Big data analytics. In Proceedings of the First International Conference on Big Data Analytics BDA (pp. 24-26).

Zakir, J., Seymour, T., & Berg, K. (2015). BIG DATA ANALYTICS. Issues in Information Systems, 16(2).

Zikopoulos, P., & Eaton, C. (2011). Understanding big data: Analytics for enterprise class hadoop and streaming data. McGraw-Hill Osborne Media.

Zsidisin, G. A. 2003. A grounded definition of supply risk. Journal of Purchasing & Supply Management, vol. 9, pp. 217–224. Östring, P. 2004. Supplier Management: How to Identify Risks and Recognize Opportunities. New York: AMACOM

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