Ral functionalities to enhance the corresponding business area, and the user

Ral functionalities to enhance the corresponding business area, and the user selects the preferred ones. doi:10.1371/journal.pone.0134563.gPLOS ONE | DOI:10.1371/journal.pone.0134563 July 31,9 /Cloud Computing Adoption Decision ToolFig 6. Recommendation of the decision tool to implement the selected functionalities. Final window capture, the decision tool offers and describes different solutions, basically in the form of SaaS, to enhance and deploy the business strategy within the cloud, based on the user’s previous selections. doi:10.1371/journal.pone.0134563.ginnovation does not clash with any specific sector and, as mentioned, sooner or later all enterprises will face cloud computing adoption. When it comes to size, most of the enterprises fall within journal.pone.0077579 the 0?0 employees category, whereas larger ones are less represented. It should be noted for future work that the 0?0 scale should be further subdivided, considering that most of the participants will be SMEs. The exact values are shown in Fig 8. The analysis based on the participants’ answers is two-fold: ?On the one hand it is a discussion about business areas and priority levels. ?On the other hand the functionalities for each business area and the different solutions (i.e. SaaS) for those functionalities can be discussed. Thus, when it comes to business areas, it is important to FruquintinibMedChemExpress HMPL-013 distinguish the participants’ preferences in terms of which business areas have attracted most interest. As a result, the tool asks the user to evaluate their interest in each of them by selecting from high, medium, low and no priority levels. There are 10 business areas reflected in the diagnosis and, as seen in Fig 9, not all of them JC-1 dose obtain the same interest from the users.Fig 7. Profile of potential fnins.2015.00094 pilot study participants. The chart shows the profile of the potential participants of the pilot study using the tool. doi:10.1371/journal.pone.0134563.gPLOS ONE | DOI:10.1371/journal.pone.0134563 July 31,10 /Cloud Computing Adoption Decision ToolFig 8. Typology of pilot study participants. The chart shows the typology of the final group of pilot study participants using the tool. doi:10.1371/journal.pone.0134563.gThe arrangement on the graph is performed by weighting the priority with 5, 3, 1 and 0 respectively from high to no interest. It is worth noting that the Clients business area has obtained more than 70 of high interest, along with ERP and Suppliers areas on the positiveFig 9. Participants’ interest level by business area. The chart shows the initial interest generated by each business area, among the pilot study participants. doi:10.1371/journal.pone.0134563.gPLOS ONE | DOI:10.1371/journal.pone.0134563 July 31,11 /Cloud Computing Adoption Decision ToolFig 10. Participants’ interest level by business area. Wholesale sector companies. The chart shows the initial interest generated by each business area, among the pilot study participants pertaining to the wholesale sector. doi:10.1371/journal.pone.0134563.gside of the balance, which obtain more than 80 of high and medium interest. At the other end lie the Human Resources and Quality Management areas which obtain 60 of that kind of interest. This may be due to the fact that cloud computing offers clear advantages when dealing with clients and ERP management in terms of ubiquity and flexibility, whereas Quality Management and probably Human Resources are not particularly benefited by the irruption of cloud computing. This has been well perceived by th.Ral functionalities to enhance the corresponding business area, and the user selects the preferred ones. doi:10.1371/journal.pone.0134563.gPLOS ONE | DOI:10.1371/journal.pone.0134563 July 31,9 /Cloud Computing Adoption Decision ToolFig 6. Recommendation of the decision tool to implement the selected functionalities. Final window capture, the decision tool offers and describes different solutions, basically in the form of SaaS, to enhance and deploy the business strategy within the cloud, based on the user’s previous selections. doi:10.1371/journal.pone.0134563.ginnovation does not clash with any specific sector and, as mentioned, sooner or later all enterprises will face cloud computing adoption. When it comes to size, most of the enterprises fall within journal.pone.0077579 the 0?0 employees category, whereas larger ones are less represented. It should be noted for future work that the 0?0 scale should be further subdivided, considering that most of the participants will be SMEs. The exact values are shown in Fig 8. The analysis based on the participants’ answers is two-fold: ?On the one hand it is a discussion about business areas and priority levels. ?On the other hand the functionalities for each business area and the different solutions (i.e. SaaS) for those functionalities can be discussed. Thus, when it comes to business areas, it is important to distinguish the participants’ preferences in terms of which business areas have attracted most interest. As a result, the tool asks the user to evaluate their interest in each of them by selecting from high, medium, low and no priority levels. There are 10 business areas reflected in the diagnosis and, as seen in Fig 9, not all of them obtain the same interest from the users.Fig 7. Profile of potential fnins.2015.00094 pilot study participants. The chart shows the profile of the potential participants of the pilot study using the tool. doi:10.1371/journal.pone.0134563.gPLOS ONE | DOI:10.1371/journal.pone.0134563 July 31,10 /Cloud Computing Adoption Decision ToolFig 8. Typology of pilot study participants. The chart shows the typology of the final group of pilot study participants using the tool. doi:10.1371/journal.pone.0134563.gThe arrangement on the graph is performed by weighting the priority with 5, 3, 1 and 0 respectively from high to no interest. It is worth noting that the Clients business area has obtained more than 70 of high interest, along with ERP and Suppliers areas on the positiveFig 9. Participants’ interest level by business area. The chart shows the initial interest generated by each business area, among the pilot study participants. doi:10.1371/journal.pone.0134563.gPLOS ONE | DOI:10.1371/journal.pone.0134563 July 31,11 /Cloud Computing Adoption Decision ToolFig 10. Participants’ interest level by business area. Wholesale sector companies. The chart shows the initial interest generated by each business area, among the pilot study participants pertaining to the wholesale sector. doi:10.1371/journal.pone.0134563.gside of the balance, which obtain more than 80 of high and medium interest. At the other end lie the Human Resources and Quality Management areas which obtain 60 of that kind of interest. This may be due to the fact that cloud computing offers clear advantages when dealing with clients and ERP management in terms of ubiquity and flexibility, whereas Quality Management and probably Human Resources are not particularly benefited by the irruption of cloud computing. This has been well perceived by th.