A Heuristic Mathematical Decision-Support Model for SMEs Cloud ERP System Adoptability

A Heuristic Mathematical Decision-Support Model for SMEs Cloud ERP System

Adoptability

Paper presentation for320061 Advanced Resource Planning

W.J.A.M van den HeuvelTilburg UniversityNovember 2013

Roger Berkley Hassan Jamous Doruk Ozokan

(Group 5)

Contents

320061 Advanced Resource Planning, A Heuristic Mathematical Decision-Support Model for SMEs Cloud ERP System Adoptability. Group 5. 1

● Research Design○ Scope and Data Collection○ Research Methodology

● Qualitative Research● Heuristic Mathematical Modeling

○ Mathematical Model: Decision Support Level● Quantitative Research

○ The (w) Variable: Cloud Factor Weight○ The (y) Variable: Cloud Feature Impact in terms of Enterprise Size○ The (a) Variable: Executives Opinions○ Defining Result Measurability

● Testing Results● Validation

○ Results Comparison● Future Work

2

Research Design

320061 Advanced Resource Planning, A Heuristic Mathematical Decision-Support Model for SMEs Cloud ERP System Adoptability. Group 5.

3

Scope & Data Collection

● Related work research: 30 highly cited publications within the field, most published during 2012 and 2013.

● Case study research: 4 surveyed SMEs and 2 case expert opinions collected.


4

Research MethodologyLiterature Review

Qualitative Research

Formulating Statements

Developing Mathematical Model

Quantitative Research

Testing

Validation


5

Qualitative Research

Statement: SMEs decision to adopt a Cloud based ERP system is positively affected by capital & operating cost reduction.

Themes

● Accessibility & Mobility

● Business Continuity

● Capital & Operating Expenditures

● Deployment, Implementation and Service Extensibility

● Elasticity & Scalability

● Software Management

Themes

● Cloud Expertise Availability

● Cloud Migration

● Interoperability & Integration

● Security & Privacy

● Service Level Agreement

● Vendor Lock-In


6

Heuristic Mathematical Modeling


Heuristics Insilications

Used by theorists outside of physical sciences, measures qualitative indicators.

Used in physical sciences, measurements correspond closely to reality.

● a heuristic mathematical model is a way to turn verbal theories into more formal ones that can be tested for basic consistency.

● Assumptions based on such a model○ Need not be empirically testable.○ Statistics and calculations can be used to a varying degree of accuracy or

rigor.

n :is the number of cloud features tested.

:a value representing the importance of a specific cloud feature.

:cloud factor weight based on qualitative research.

:the impact of the cloud feature in relation to the size of the organization.

Emin:minimum value of

Emax:max value of

7

Mathematical Model: Decision Support Level


:direction of impact.

:surveyed companies percentage.

:cloud factor ranking.

: number of samples

8

The (w) Variable: Cloud Factor Weight


9

The (w) Variable: Cloud Factor Weight


Theme References Weight

Capital & Operating Expenditures

(Sahandi, Alkhalil and Opara-Martins 2013; ENISA 2009; Deloitte 2012; Hinde and Van Belle 2012)

50

Accessibility and Mobility

(Sahandi, Alkhalil and Opara-Martins 2013; Opara-Martins 2013; Deloitte 2012)

39

Elasticity and Scalability

(Sahandi, Alkhalil and Opara-Martins 2013; ENISA 2009; Opara-Martins 2013; Deloitte 2012; Hinde and Van Belle 2012)

56

Security & Privacy (Cal 2011; Kumar and Garg 2012; Deloitte 2012; Hinde and Van Belle 2012; Castellina 2012)

-68

… etc ...etc ...etc

10

The (y) Variable: Cloud Feature Impact in terms of Enterprise Size

Theme Small Medium

Capital & Operating Expenditures ⇔ ⇑ Accessibility and Mobility ⇔ ⇔ Elasticity and Scalability ⇔ ⇑ Business Continuity ↔ ↑Deployment, Implementation, service Extensibility

⇔ ⇔

Software Management ⇔ ⇔ …. etc …. etc …. etc

● Calculated for each feature, benefit or drawback.● Extracted from related publications.


11

The (a) Variable: Executives Opinions

Sample Element Company A Company B Company C Company D

company size Small Small Medium Medium

Capital & Operating Expenditures

90 75 90 95

Accessibility and Mobility 75 30 80 80

Elasticity and Scalability 15 10 40 35

Business Continuity 60 75 85 90

Deployment, Implementation, service Extensibility

10 80 25 40

Software Management 10 75 60 45

..etc ..etc ..etc ..etc ..etc

● Calculated for each feature, benefit or drawback.● Based on a designed survey.


Final Recommendation

1 → 20 Adoption not recommended

20 → 40 Adoption deemed as risky to implement

40 → 60 Sufficient level of perceived benefit

60 → 80 Adoption recommended

80 → 100 Adoption highly recommended

12

Defining Result Measurability

● The value of ( ) achieved by a case analysis, provides a final recommendation to SME executives, regarding the adoption of a cloud ERP system.


13

Testing Results

Sample Element Final Recommendation

Company A 55.6 Sufficient level of perceived benefit

Company B 65.6 Adoption Recommended

Company C 62.0 Adoption Recommended

Company D 58.2 Sufficient level of perceived benefit

● Results reached for all 4 case studies.


Validation

14

● Expert opinion validation method.

● Results referred to 2 case experts, they were asked to provide an adoptability score based on their educated opinion in the cases (0-100).

● Expert opinions are compared to the results reached through the mathematical model.


15

Result Comparison


➔ Further support to the qualitative basis of the research.

➔ Enhancements to the decision support mathematical by adding factors to quantify

strategic and/or compliance risks associated with cloud ERP adoption.

➔ Adding factors to rank different cloud providers in terms of services needed by a

specific possible cloud adopter. Such factors will help executives in SMEs choose the

most suitable cloud provider which delivers the services needed for their cloud ERP

solution.

➔ Applying historical case studies validation method.

➔ Questions raised through the course of our research include possible SLA

standardization efforts, as well as researching how continuous improvements in cloud

security and privacy affect the opinions of probable cloud adopters who perceive this as

a high ranking risk factor.

16

Future Work


References (1/3)[1] Arnesen, S. 2013. Is a Cloud ERP Solution Right for You. White paper. Available via <http://www.imanet.org/PDFs/Public/SF/2013_02/02_2013_arnesen.pdf> [Accessed: 1st October 2013].[2] Cal. 2011. 35 Questions Every CFO Needs to Ask About ERP Software In the Cloud, White paper. Available via <http://www.erpsoftwareblog.com/white-papers/the-cfo-s-essential-guide-to-cloud-based-erp--35-questions-you-need-to-ask-23/> [Accessed: 1st October 2013][3] Sage ERP. 2011. ERP and the Cloud: What You Need to Know, White paper. Available via <http://www.burcomconsulting.com/resources/Benefits%20of%20Cloud-Based%20ERP%20Implementations.pdf> [Accessed: 1st October 2013][4] Holland, D., Horvath, M., Utzig, C. and Manohar,M. 2013. ERP in the Cloud: Is It Ready? Are You?, White paper. Available via <http://www.booz.com/media/file/BoozCo_ERP-in-the-Cloud.pdf> [Accessed: 1st October 2013][5] Hofmann, P. and Woods, D. 2010. Cloud Computing: The Limits of Public Clouds for Business Applications, Internet Computing, IEEE , Vol.14:90,93 [6] Sahin, N. 2013. Cloud ERP Security: Guidelines for Evaluation. Master thesis. KTH. Available via: <http://www.diva-portal.org/smash/get/diva2:614895/ATTACHMENT01> [Accessed: 1st October 2013][7] Kumar, V. and Garg, K. 2012. Migration of Services to the Cloud Environment: Challenges and Best Practices, International Journal of Computer Applications, Vol.1:1,6.[8] Rao, D., Rao, G. and Prasad, R. 2012. A Study of Cloud Privacy and Privacy Patterns. (IJCSIT) International Journal of Computer Science and Information Technologies Vol.3:4896-4899. [9] Singh,M. and Shrivastava,M. 2012. Overview of Security issues in Cloud Computing. International Journal of Advanced Computer Research, Vol:2[10]Krishna, B., Reddy, E., Jagadamba, K., Krishnamoorthy, S. and Krishna, P. 2009. A Unified and Scalable Data Migration Service for the Cloud Environments. 15th International Conference on Management of Data COMAD 2009. Software Engineering and Technology Labs, Infosys Technologies Limited, India[11] Cisco. 2010. Planning the Migration of Enterprise Applications to the Cloud, White paper. Available via<http://www.cisco.com/en/US/services/ps2961/ps10364/ps10370/ps11104/Migration_of_Enterprise_Apps_to_Cloud_White_Paper.pdf> [Accessed: 1st October 2013]

http://www.imanet.org/PDFs/Public/SF/2013_02/02_2013_arnesen.pdf



http://www.erpsoftwareblog.com/white-papers/the-cfo-s-essential-guide-to-cloud-based-erp--35-questions-you-need-to-ask-23/





http://www.burcomconsulting.com/resources/Benefits%20of%20Cloud-Based%20ERP%20Implementations.pdf




http://www.booz.com/media/file/BoozCo_ERP-in-the-Cloud.pdf



http://www.cisco.com/en/US/services/ps2961/ps10364/ps10370/ps11104/Migration_of_Enterprise_Apps_to_Cloud_White_Paper.pdf



References (2/3)[12] Gregg, M. 2010. 10 Security Concerns for Cloud Computing. White paper. Available via<http://www.globalknowledge.com/training/whitepaperdetail.asp?pageid=502&wpid=689> [Accessed: 1st October 2013][13] Monogenis, D. 2012. Understanding Pricing and Migration Cost for Cloud Adoption in Business Environments, Project Report. Available via <http://www.comp.leeds.ac.uk/mscproj/reports/1112/monogenis.pdf>[Accessed: 1st October 2013][14] Wang, H., Jing, Q., Chen, R., He, B., Qian, Z. and Zhou, L. 2010. Distributed systems meet economics: pricing in the cloud. Proceedings of the 2nd USENIX conference on Hot topics in cloud computing. pp. 6--6.[15] Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A. and Stoica, I. 2009. Above the clouds: A Berkeley view of cloud computing. Dept. Electrical Eng. and Comput. Sciences, University of California, Berkeley, Rep. UCB/EECS, 28.[16] Sahandi, R., Alkhalil, A. and Opara-Martins, J. 2013. Cloud Computing From SMEs Perspective: A Survey-based Investigation. Journal of Information Technology Management, Vol.24[17] ENISA. 2009. An SME perspective on Cloud Computing. Survey. Available via <http://www.enisa.europa.eu/activities/risk-management/files/deliverables/cloud-computing-sme-survey/at_download/fullReport> [Accessed: 1st October 2013][18] Opara-Martins, J. 2013 Understanding Cloud Computing From An SME Perspective. White paper. Available via <http://www.budigitalhub.com/sites/default/files/white_papers/Cloud%20Computing.pdf> [Accessed: 1st October 2013][19]Marston, S., Li, Z., B, Yopadhyay, S., Zhang, J. and Ghalsasi, A. 2011. Cloud computing—The business perspective. Decision Support Systems. Vol.51:176-189. [20]Benlian, A. and Hess, T. 2011. Opportunities and risks of software-as-a-service: Findings from a survey of IT executives. Decision Support Systems. Vol.52:232-246.[21] Engebrethson, R. 2012. Comparative Analysis of ERP Emerging Technologies. Master thesis. California Polytechnic State University.[22]Islam, M., Morshed, S., Goswami, P. and Dhaka, B. 2013. Cloud Computing: A Survey on its limitations and Potential Solutions. IJCSI International Journal of Computer Science Issues. Vol.10:159-163

http://www.globalknowledge.com/training/whitepaperdetail.asp?pageid=502&wpid=689



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http://www.budigitalhub.com/sites/default/files/white_papers/Cloud%20Computing.pdf




References (3/3)[23] Deloitte. 2012. Cloud computing solutions distribution between SME’s and Enterprise Clients. Survey. Available via<http://deloitteblog.co.za.www102.cpt1.host-h.net/wp-content/uploads/2012/10/Cloud-Computing-Survey-L.pdf> [Accessed: 1st October 2013][24] Hinde C. and Van Belle J.P. 2012. Cloud Computing in South African SMMEs: Risks and Rewards for Playing at Altitude. International Journal of Computer Science and Electrical Engineering. Vol.1:32-41. [25] Castellina, N. 2012. SaaS and Cloud ERP Observations: Is Cloud ERP Right for you? White paper. Available via <http://aberdeen.com/Aberdeen-Library/7857/RA-enterprise-resource-planning.aspx> [Accessed: 1st October 2013][26] Xu, X. 2012. From cloud computing to cloud manufacturing. Robotics and Computer-Integrated Manufacturing. Vol.28:75-86.[27]Scavo, F., Newton, B. and Longwell, M. 2012. Choosing between cloud and hosted ERP, and why it mat-ters. Computer Economics Report. Vol.34[28] ContrysideWorks. 2013. Erp – Enterprise Resource Planning. Available via <http://countrysideworks.com/services/erp-enterprise-resource-planning/> [Accessed: 1st October 2013][29] Duan, J., Faker, P., Fesak, A. and Stuart, T. 2012. Benefits and Drawbacks of Cloud-Based versus Traditional ERP Systems. Research paper. Available via <http://www.academia.edu/2777755/Benefits_and_Drawbacks_of_Cloud-Based_versus_Traditional_ERP_Systems> [Accessed: 1st October 2013][30] Joyent. 2011. CapEx and OpEx for Cloud Computing. White paper. Available via <http://cloud.libero.it/it/wp-content/uploads/2013/05/dalla-campagna-201111-Cloud-Computing-Economics-White-Paper.pdf> [Accessed: 1st October 2013][31]Zhu, K. and Zhou, Z. 2012. Research Note—Lock-In Strategy in Software Competition: Open-Source Software vs. Proprietary Software. Information Systems Research, Vol.23:536--545.[32] Sidaway, G. 2013. Cloud computing: are projects being compromised by a skills gap. Available via <http://www.theguardian.com/media-network/media-network-blog/2013/nov/08/cloud-computing-compromised-skills-gap> [Accessed: 1st October 2013][33] Davis, H. and Chenoweth, S. 1992. The mathematical modeling of heuristics. Annals of Mathematics and Artificial Intelligence, 5 (2-4), pp. 191--227.

http://deloitteblog.co.za.www102.cpt1.host-h.net/wp-content/uploads/2012/10/Cloud-Computing-Survey-L.pdf



http://aberdeen.com/Aberdeen-Library/7857/RA-enterprise-resource-planning.aspx



http://countrysideworks.com/services/erp-enterprise-resource-planning/



http://www.academia.edu/2777755/Benefits_and_Drawbacks_of_Cloud-Based_versus_Traditional_ERP_Systems



http://cloud.libero.it/it/wp-content/uploads/2013/05/dalla-campagna-201111-Cloud-Computing-Economics-White-Paper.pdf



http://www.theguardian.com/media-network/media-network-blog/2013/nov/08/cloud-computing-compromised-skills-gap



Any questions? :)

Roger Berkley Hassan Jamous Doruk Ozokan

(Group 5)

“All models are wrong, but some are useful”-George Box, a prominent statistician.