The business information system is very much useful for the businesses as it can bring innovation in the organizations. By introducing the innovation in the organization, the organization can achieve the utmost efficiency in the execution of the business processes.
In this document, it will be discussed that how the organizations can apply the information systems to achieve the information system enabled innovation. For this discussion, four examples will be presented which will describe the use of an information system for the innovation purpose. Following that some of the success factors for the innovation will be highlighted and lessons learned from the implementation will be discussed. After that impact of the internal factors and the external factors on the innovation will be evaluated. Finally, some recommendation will be given to help the organization in innovation by using the information system.
Uses of Information System for Innovation by Organizations:
In the context of the innovation, there are various innovation has been made using the information system. In this document, some of those innovations will be discussed briefly. The selected innovation are the Artificial Intelligence, Serverless Computing, Chatbots and Cloud Repository. These innovations are used various organizations in their daily processes. Four organizations will be selected in this case, and this innovation technologies will be discussed in the context of these organizations.
Google LLC:
The first selected organization is the Google LLC for elaborating the innovation of Artificial Intelligence. This innovative technology uses the information system for executing its processes properly. In some scenarios, this artificial intelligence can act like a normal human being. One of the main effort provided by artificial intelligence is optimizing ads for the organization. By implementing the artificial intelligence, Google LLC can target the perfect audience for a particular type of ads (Guo et al. 2015). Also, artificial intelligence can gather data about these customers for the marketing purpose. Also, this innovation can help Google to motivate its employees. There is various artificial intelligence tool that is used by Google to provide HR support to the employees whenever needed. By assisting the employees in this way, AI is ensuring that the employees can provide their peak production.
The assistance of the information system for artificial intelligence is very much required. For proper execution, the AI required data, human ingenuity and some computational power. The data part is provided by the information systems in this case (Drucker 2014). By providing the data, it actually helps in the proper execution of the artificial intelligence which is essential in this case.
Success factors and Lessons learned for Artificial Intelligence:
When considering success factors for the artificial intelligence in Google, the main success factor is the availability of data. As mentioned previously the artificial intelligence requires some pre-processed data for its proper execution. So, the data availability must be ensured. The second success factor is not wasting time on improving the algorithms. In many cases, the developers spend the time to improve the algorithm of the AI system which is unnecessary for AI systems (Kogan et al. 2017). Instead of that, the developers can improve the AI system by providing more input data and pre-processing the data in a better way.
Also, the lessons learned from the implementation of the AI is the AI-complete and the AI-hard. This is the problem related to the computational problem. It is also a problem with the central artificial intelligence problem.
Impact of Internal and External factors on Artificial Intelligence:
The main internal factor which has affected the artificial intelligence is the organizational factor. The organization plays a big role in the development of the artificial intelligence system. The development depends on how the organization is adopting the system of artificial intelligence.
While considering the external factor, the main factor is the market factor. The artificial intelligence is an innovative technology which is new to the society and technological market. The market is greatly accepting the artificial intelligence and the applications of it. Thus the current market his reflecting a positive impact on the AI.
Recommendation:
For the innovative technology of artificial intelligence, the main recommendation is taking feedback from the users. Users can provide valuable feedback to the AI system which can be used for improving the overall system.
The serverless computing is a typical cloud server model in which the cloud provider plays the role of the server. This serverless computing is used by the Amazon in their AWS product for business purposes. With playing the role of the server it also dynamically manage the machine resources allocation. The Serverless Computing is considered an innovative technology as it is capable of hiding server capacity and management planning decisions from the operator and the developer.
In a serverless computing environment, the user only needs to upload the functions and only need to specify the resources which are required by it. After that, the cloud vendor takes the responsibility of rest of the things. This serverless computing works in a dynamic way for Amazon AWS. When the function demand goes high, the cloud vendors allocate more servers, and when the demand becomes lower, it decommissions the extra servers to tackle the situation.
The uses of the Information System very much essential for the serverless computing innovation in the organization is very much important. Serverless computing must be able to store and distribute the information or data among the various endpoints within the system (Grynszpan et al. 2014). Also, effective management of those data is required by the servers. In this case, the information system plays a big role as this is an organizational system which is used for processing, storing and distributing information. With such properties the implementation of the information system can help the serverless computing to manage the data effectively.
Success factors and Lessons learned for Serverless Computing:
The main success factors for the serverless computing are the backing services, port binding, disposability and the concurrency. The backing services contribute in the success of the serverless computing by swapping out old and outdated SQL database with the new databases (Miller et al. 2014). This increases the efficiency of the serverless computing. The port binding factor exports the services via port binding. The disposability ensures supreme robustness with by quick start-up and with a graceful shutdown. The concurrency factor scales each of the processes individually to ensure utmost efficiency. This much efficiency of the serverless computing can help the Amazon in their AWS business model.
Impact of Internal and External factors on Serverless Computing:
The management factor is the main internal factor for the serverless computing. Efficient management of data is required for the perfect utilization of the serverless computing. Robustness is also required in the organization which is essential for the serverless computing and this robustness is controlled by the organizational factor (Walrave and Raven 2016). Thus the organizational factor and the management factor is having a positive factor on the serverless computing.
Considering the external factor, the main external factor is the market factor. As this serverless computing is easy to use because of its simple cloud architecture, it has gained great popularity from the market. Thus the market factor is having a positive impact on the serverless computing.
Recommendation:
To improve the serverless computing improvement in three factors are required. These factors are the API gateway, FaaS and BaaS. Improvement in this three layers will make the serverless computing more effective. Thus the business process of the Amazon will be improved.
Pizza Hut:
The pizza hut organization uses the innovative technology of chatbots to execute its organizational processes successfully. The chatbots are the typical type of computer programs which performs a conversation with a human being via the textual or auditory method. Pizza Hut uses the chatbot system to delight their customer and provide support whenever required by the customer (Worm 2018). This type of systems is designed to simulate how humans will behave with a partner who has no physical existence. In the Pizza Hut, this innovative technology is used in some specific type of dialog system. This type of system includes information acquisition, human assistance and customer service (Gee 2013). There are many chatbots which are complex from the others, and this type of chatbots uses natural language processing.
The implementation of the information system is also required for effective management the chatbots. As mentioned earlier the information system helps in the design process by collecting, storing, processing and distributing the information. For successful operation of a chatbot, effective data flow is required. To manage this effective data flow information system is essential as it provides the functionality of the storing, processing and distributing the data which the necessary amendments of a regular chatbot (Baldini et al. 2017). Also, the advanced chatbots can effectively store the data provided by the interacting user thus in this case also the effective data storing is required which can be achieved by the implementation of the information system.
Success factors and Lessons learned for Chatbots:
The key success factor for the chatbots is the defining, validating, simplifying and adjustment. The chatbots are needed to define platform which is targeted on the basis of the user’s need. The knowledge base scope also needed to be validated properly (Atzori, Boratto and Spano 2017). Another success factor is simplifying the access of the knowledge for the users and providing precise outputs (Reichardt et al. 2016). Improvement in the system is another key success factor. To improve the system knowledge-based adjustment can be done after each of the tests to increase the performance of the chatbots.
Impact of Internal and External factors on Chatbots:
The individual factor is the main internal factor which is affecting the innovative technology of the chatbots. As this chatbot is used for interacting with humans and assisting them, the individuals need to agree with the use of chatbots in the Pizza Hut organization. This is because one might feel uncomfortable while interacting with the chatbots and it is not assured that everyone will be comfortable with the chatbots in a specific organization (Van Acker et al. 2013).
The social impact is the critical external factor which is affecting the chatbot technology. In many of the cases these chatbots are highly appreciated because of their always available assistance to the humans, but in many cases, the chatbots are not accepted as a solution. This is because many peoples are not comfortable interacting with the chatbots and for a reason, this technology is replacing the human jobs in Pizza Hut. Thus the social factor is having both the positive and negative factor on the chatbots for some specific cases.
Recommendation:
The chatbots work by gathering various types of data. Thus it is recommended to feed the chatbots with new data regularly. It can increase the efficiency of the chatbots.
Dropbox:
Dropbox is the organization which uses the innovative technology of cloud repository. The cloud repository is an integrated model of the cloud computing model which is used for storing the data into the remote servers (Rittinghouse and Ransome 2016). This data can be controlled by accessing the internet from the cloud repository. This data is mainly maintained and managed by the service providers of the cloud repository, and these services are mainly built on the technique of virtualization (Cross et al. 2015). Using the virtualization technique this actually provides virtual storage to the cloud service users. The main benefit of this type of virtual storage is that storage size is scalable and it can be adjusted according to the needs of the users. This type of storage works through a web-based API which is implemented remotely.
To implement this innovation in the organization field again the information system is very much important. The cloud repository is totally based on the principle of the data exchange and to exchange the data properly. The data must be processed and distributed properly and again in this case the information system becomes important to successfully exchange the data by data processing and distribution (Sen and Borle 2015). Also, when some data is pushed to this cloud repository, the server must be able to accept and store the data properly. For storing the data again, the role of the information system arises as the program of the information system effective stores the data.
Success factors and Lessons learned for Cloud Repository:
The main success factor for the cloud repository is the security, dynamic storage capacity, availability and the integration. Security is a key factor for many peoples or organization as they use the cloud to secure their valuable and confidential data. The dynamic capacity allocation of the storage is also another success factor for the cloud repository (Kosba et al. 2016). By the dynamic storage allocation, it is possible to allocate storage dynamically to the users so extra unused space can be saved and the cost of this services can be reduced (Russell and Norvig 2016).
Availability is another main success factor as the user may require the cloud based data any time. So, this type of system must be active always. Also, various type of organization may use the same service for the different type of architecture so, integration is a key factor successfully integrate into the system. This success factors can help the Dropbox organization to achieve the utmost efficiency in their business process.
Impact of Internal and External factors on Cloud Repository:
For the cloud repository, the main internal factor is the management factor of the Dropbox. The management of the Dropbox must ensure that all the system which are required for the cloud repository system is running properly. Also, this type of critical system often need some maintenance which is obvious responsibility of the management and in most of the cases management successfully provides these systems (Wang and Wang 2014). Thus the management is having a positive impact on the cloud repository technology.
The main external factor affecting the cloud repository is the technological factor. This type of cloud repository system is new to society, and it is very much useful to the peoples and the organization. The main issue, in this case, is that it is becoming very problematic for the general peoples to understand these new technologies. Thus technological barrier is arising. Thus this is having a negative factor on the cloud repository systems.
Recommendation:
To improve the efficiency of the cloud repository load balancing and WANOP can be implemented. Also to improve the cloud repository system storage environment can be the environment. Converged infrastructure can also significantly improve the efficiency of the cloud storages. Also, better security is required for a perfect cloud repository. Thus it is recommended to implement all the above factor in the cloud environment for better performance.
Conclusion:
From the above discussion, it can be concluded that the innovation-related with information technology is very much important to fulfil the goals of the organization. The implementation of the innovation can help the organization through the implementation of the preparing, storing and payroll and by implementing storage recording in the organization. In this field of technology, implementation of this innovative technologies will help the society and the communities in a more efficient way. This innovation has been done in the industry to fulfil the growing demands of the customers or consumers. In this fast-moving world the culture of the innovation actively helped the organization which were discussed above by introducing new products and services to the market.
By creating the innovations, the above organization has simplified the daily life of the humans which has helped them to gain a competitive advantage in the market. Using the innovations, this organizations can go further by testing new models of businesses in their organization. The innovations have also helped the organizations to develop the services and the products directly with the beneficiaries and the consumers. From the last decade, most of the companies are focused on the innovative services and products due to the benefit of the completive advantage in the market.
References:
Atzori, M., Boratto, L. and Spano, L.D., 2017. Towards chatbots as recommendation interfaces. In CEUR WORKSHOP PROCEEDINGS (Vol. 1945, pp. 28-31). CEUR-WS.
Baldini, I., Castro, P., Chang, K., Cheng, P., Fink, S., Ishakian, V., Mitchell, N., Muthusamy, V., Rabbah, R., Slominski, A. and Suter, P., 2017. Serverless computing: Current trends and open problems. In Research Advances in Cloud Computing(pp. 1-20). Springer, Singapore.
Cross, J.N., Mordy, C.W., Tabisola, H.M., Meinig, C., Cokelet, E.D. and Stabeno, P.J., 2015, October. Innovative technology development for Arctic exploration. In OCEANS’15 MTS/IEEE Washington (pp. 1-8). IEEE.
Desale, R.D. and Ahire, V.S., 2013. A study on wearable gestural interface–a sixthsense technology. IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN, pp.2278-0661.
Drucker, P., 2014. Innovation and entrepreneurship. Routledge.
Gee, J.P., 2013. The anti-education era: Creating smarter students through digital learning. St. Martin’s Press.
Grynszpan, O., Weiss, P.L., Perez-Diaz, F. and Gal, E., 2014. Innovative technology-based interventions for autism spectrum disorders: a meta-analysis. Autism, 18(4), pp.346-361.
Guo, Q., Qu, J., Han, B., Zhang, P., Song, Y. and Qi, T., 2015. Innovative technology for processing saprolitic laterite ores by hydrochloric acid atmospheric pressure leaching. Minerals Engineering, 71, pp.1-6.
sKosba, A., Miller, A., Shi, E., Wen, Z. and Papamanthou, C., 2016, May. Hawk: The blockchain model of cryptography and privacy-preserving smart contracts. In 2016 IEEE symposium on security and privacy (SP) (pp. 839-858). IEEE.
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Reichardt, K., Negro, S.O., Rogge, K.S. and Hekkert, M.P., 2016. Analyzing interdependencies between policy mixes and technological innovation systems: the case of offshore wind in Germany. Technological Forecasting and Social Change, 106, pp.11-21.
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