Alignment of business in robotic process automation

Ning Zhang, Bo Liu

International Journal of Crowd Science

ISSN: 2398-7294

Open Access. Article publication date: 7 February 2019

Issue publication date: 12 June 2019

6711

Abstract

Purpose

This paper aims to find out how business aligns with robotic process automation (RPA) and whether the alignment has the same factors as for IT–business alignment.

Design/Methodology/Approach

Condition configurations for positive and negative impact for business alignment with RPA.

Findings

The positive and negative configurations that possibly impact business alignment with RPA.

Research limitations/implications

There are some human instincts during conditions dichotomization and limited number of cases.

Practical implications

The findings can be used to guide practice application in real industry.

Originality/value

This paper adopted crisp-set qualitative comparative analysis to find condition configurations for alignment of business and RPA for more generalization.

Keywords

Citation

Zhang, N. and Liu, B. (2019), "Alignment of business in robotic process automation", International Journal of Crowd Science, Vol. 3 No. 1, pp. 26-35. https://doi.org/10.1108/IJCS-09-2018-0018

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Ning Zhang and Bo Liu.

License

Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


1. Introduction

With the development of science and technology, the automation technology, as the most possible way to replace human workers, has become mature. Robotic process automation (RPA) is a software robotic tool that can mimic human actions with computer systems to automate repetitive tasks (). It is the most mature solution and has attracted enterprise managers’ attention. Some studies have focused on the IT–business alignment that IT and business aligned into one whole together (; ). From these research studies, five possible key factors can be found: environmental shift, sustained low performance, influential outsiders, new leadership and perception transformation ().

How does business align with RPA? To answer this question and to summarize the RPA–business alignment key factors, this research is based on IT–business alignment theory and literatures to .

2. Literature review

2.1 Robotic process automation

RPA is a software robotic tool that automates routine tasks (; ). It is proved by scholars to be an effective way to cut costs (). Some studies have begun to explore the possible way to deploy it based on some real experiences.

RPA, as the replacement of human worker, can be deployed in many industry areas, for example, financial (; Mary et al., 2016), telecommunication (, ), business process outsourcing (, ), education (), banking () and legal (). Most empirical studies have assessed the possible ways for and obstacles to RPA deployment in the real industry. These studies are based on case studies. From empirical studies, researchers can find the key factors that aligns business with RPA.

2.2 IT–business alignment

The definition of IT–business alignment is applying IT in an appropriate and timely manner to harmonize with business strategies, goals and needs. The alignment addresses both how IT is in harmony with business and how business should or could be in harmony with IT (). The famous IT–business alignment model – strategic alignment model (SAM) – includes four fundamental domains: business strategy, information technology strategy, organization infrastructure and process and information technology infrastructure and process (). The SAM model consists of six dimensions, including communications, competency/value measurement, governance, partnership, scope and architecture and skills (; ).

There are two kinds of traditional IT–business alignment theories. One theory is that if IT and business are aligned, it can achieve the end-to-end close connection at strategic, organizational and operational levels (; ) to improve finance performance and catch competency advantage. The other theory is IT–business alignment needs more investment for reconstruction in infrastructure, organization and business process reengineering. If IT–business alignment is a failure, the IT initiatives will also be failure () and will impact business performance (). Even if there is “the alignment paradox” that better IT alignment cannot lead to business gains because of a too inflexible IT backbone ().

The latest studies are based on a punctuated equilibrium theory that recognizes that alignment is not a static event but a process of continuous adaption and adoption (). There are five possible antecedents of revolutionary change: environmental shift, sustained low performance, influential outsiders, new leadership and perception transformation. In another research result, two more antecedents were added: government support and organizational inertia ().

2.3 Literature review summary

From review result, the existing RPA literatures are based on case studies or concept explorations that have special backgrounds and these studies lack generalizations. This research aims to find out the key factors for business–RPA alignment in generality and whether they are the same key factors for IT–business alignment.

3. Empirical study

3.1 Research method

Qualitative comparative analysis (QCA) is a methodology for obtaining summarizations from cases. This based on set-theoretical logics method can characterize through causal asymmetry and well applicability of small-N sample sizes because causal conditions or combination conditions can lead to an equifinality (; ).

There are three types of QCA: crisp-set QCA (csQCA) (), fuzzy-set QCA (fsQCA) () and multi-value QCA (mvQCA) (). The csQCA handles the variable as “0” or “1” dichotomous variable and allows researchers to directly compare statistical techniques to better. The fsQCA is an extension of csQCA, which investigates how causal relationships are dependent on non-contextual conditions, and is more closed to statistical approaches. It provides a flexible tie between qualitative and quantitative characteristics because of variables that show a continuous degree of “belonging” or “membership.” A fuzzy-set variable changes continuously in a 0-1 closed interval. The mvQCA is another extension of csQCA. It allows some explanatory conditions to have more than two values and can be viewed as the middle-way between csQCA and fsQCA.

QCA can bridge the gap between qualitative and quantitative approaches with small-N cases support. This research will use the csQCA method to identify whether antecedents are the same key factors for the RPA-business with IT-business history researches.

3.2 Data source

For this research, the data sources are the literatures and RPA websites. First, by searching Google Scholar with the keywords “Robotic Process Automation” from 2015 to present with English or Chinese language, there are total 263 studies. Then searching public website with the keywords “Robotic Process Automation” from the year 2015 to present also. After a full review, there were 21 companies to be studied, as shown in .

3.3 Conditions definition and dichotomization

The first step of the QCA method is antecedent definition by the inductive or deductive approach (). For this research, the deductive approach is applied. By reviewing literatures about the IT–business alignment, five possible antecedents of revolutionary change were found: environmental shift, sustained low performance, influential outsiders, new leadership and perception transformation (). There are two more antecedents, government support and organizational inertia, that may impact IT–business alignment (), as shown in . The next step is the condition setting or dichotomization, as can be seen in .

3.4 Outcome definition and dichotomization

Delphi as a qualitative method is suitable for achieving consensus from a panel of consultants to address the maturity level. The same evaluation procedure is used to find business alignment with RPA maturity level (Assessing Business-IT Alignment Maturity, 2000). Two IT consultants with 15 years of experiences each in the enterprise IT field evaluated the alignment level with an average result . The outcome (RPA–business alignment [RBALIG]) set 1 when the level is above level 2, otherwise the outcome (RBALIG) set 0 in .

3.5 Calculation procedure

Every case is equally important for theory exploration. There will be contradiction configuration in certain situations. Researchers need a base on the real cases to summarize the generalization with previous results to resolve the contradiction (; ). The environment condition and outside have some overlap, for example, the business strategy shift maybe impact some outsider factors. So, the condition influential outsiders (INFOUT) can be replaced by organization inertia (ORGIN), as shown in .

With the help of TOSMANA 1.5 software, the csQCA calculation finds the conditions combination that can drive business alignment with RPA and solve the contradiction. Finally, there are 11 configurations, as can be seen in .

4. Conclusion

4.1 Positive result

To minimize with tools, there are two possible configurations that may prompt business alignment with RPA (

First, the new enterprise strategy with new leadership that has a digital-transformation perception can prompt RPA–business alignment. Managers realize the digital prompt enabler to the enterprises, they will make the alignment quicker and better.

Second, low performance with stable leadership that has a digital-transformation perception can also prompt RPA–business alignment. When financial results or market shares are down, the leadership will think about the future and a method that can improve this. If the managers also have a digital view and transformation perception, business alignment with RPA can be prompted.

4.2 Negative result

To minimize with tools, there are three possible configurations that may slow down business alignment with RPA (

First, digital-transformation perception can be a negative factor that can slow RPA–business alignment; enterprises do not realize the power of digital transformation for revolutionizing industries. There are many facts to prove this.

Second, when an enterprise’s financial performance or market share is down, even if there is stable leadership, RPA–business alignment can slow down because managers’ first priority would be to improve performance. Business is the root of an enterprise.

Third, a business strategy adjustment with stable leadership and small organization inertia may also slow down RPA–business alignment. The enterprise/organization strategy orients operations daily. The strategy change is at a high level so that it may result into some turbulence for the enterprise/enterprise. Finally, it will slow RPA–business alignment.

5. Future research

RPA aligns with business to make enterprises achieve more productivity and better quality. By adopting RPA, organizations will enjoy a “Triple win” from automation (Fig 2): a win for customer, a win for employees and a win for stakeholders. Finally, RPA–business alignment can definitely improve business performance.

Future research on RPA implications can be from the perspective of the customer or stakeholder or business performance.

RPA adoption reference cases

Reference topic Object company Author or source
RPA at Xchanging Xchanging
Robotizing global financial shared services at Royal DSM Royal DSM ,
Service automation: cognitive virtual agents at SEB Bank SEB bank ,
Turning RPA into commercial success: case OpusCapita OpusCapita Group Annu et al., 2016
Rethinking legal services in the face of globalization and technology innovation: the case of Radiant Law Radiant Law ,
RPA at Telefónica O2 Telefónica O2 ,
Employing US military families to provide business process outsourcing services: a case study of impact sourcing and reshoring Liberty Source ,
RPA: mature capabilities in the energy sector European energy supplier ,
Vodafone Shared Services: exploring RPA opportunities Vodafone Shared Services (VSS)
RPA for real: Ascension Health takes on leading role Ascension Health
The rise of robots BNY Mellon
Strategy symposium of SINOCHEM Group was held SINOCHEM
Davies Turner transforms customer service with real-time insight into shipments and inventory Davies Turner
Union Bank accelerates time to revenue for mortgage loans MUFG Union Bank
Your biggest pain points: speed of change Leeds Building Society
RPA enables 100% process efficiency and 45% cost reduction in AP for global plastic manufacturer Coveris Holdings Sarl
Wipro’s success through hyper automation Wipro limited
Global convenience: Jacob Schram Circle K
Accenture and Blue Prism team to provide RPA to help clients accelerate business results, improve employee and customer experience Raifessen Bank International
Rise of the machines as ANZ brings in robot workers to do the ‘boring’ jobs ANZ Bank
DBS Bank accelerates digitalisation transformation with robotics program DBS Bank

RPA–business conditions form

Conditions Labels for conditions
Conditions Environmental shift ENVSHI
Sustained low performance LOWPER
Influential outside INFOUT
New leadership NWLDER
Perception transformation PERTRA
*Organizational inertia *ORGINE
Outcome RPA-business alignment RBALIG

RPA–business conditions dichotomization threshold

Conditions Threshold of the condition dichotomization
ENVSHI Environment or business strategy change = >1, else 0
LOWPER Shrink market share or reduced profits = >1, else 0
INFOUT Macro-environment change or policy change > 1, else 0
NWLDER Leadership or report process change = >1, else 0
PERTRA Realize the digital transformation = >1, else 0
*ORGINE The barrier to organization change = >1, else 0
RBALIG IT–business maturity level above level 2 => 1, else 0

RPA–business alignment maturity evaluation result

Communications Competency/ value measurement Governance Partnership Scope and architecture Skills Maturity level Outcome (RBALIG)
3 2 2 3 4 4 3 1
4 2 3 3 4 3 3 1
3 3 3 2 3 2 3 1
3 2 2 1 1 2 2 0
3 3 4 2 3 3 3 1
3 3 4 3 3 3 3 1
3 2 2 4 4 3 3 1
2 2 3 2 2 1 2 0
3 2 3 4 3 3 3 1
2 1 2 1 1 2 2 0
3 3 3 3 3 2 3 1
2 1 3 2 2 1 2 0
3 2 4 3 3 3 3 1
3 3 3 3 2 4 3 1
2 2 4 3 4 4 3 1
2 2 4 4 3 3 3 1
3 3 2 2 3 4 3 1
2 4 3 3 2 3 3 1
3 3 3 3 2 4 3 1
3 3 4 3 3 2 3 1
3 3 4 3 3 2 3 1
Notes:

1: Xchanging; 2: Royal DSM; 3: SEB Bank; 4: OpusCapita; 5: Radiant Law; 6: Telefónica O2; 7: Liberty Source; 8: UTILITY; 9: Vodafone Shared Service; 10: Ascension Health; 11: Mellon Bank; 12: SINOCHEM; 13: Davies Turner; 14: MUGF Union Bank; 15: Leeds Building Society; 16: Coveris Holdings Sarl; 17: Wipro; 18: Circle K; 19: Raifessen Bank; 20: ANZ; 21: DBS

True table for RPA–business alignment after condition replacement

Case ID ENVSHI LOWPER ORGIN NWLDER PERTRA RBALIG
1 1 0 0 1 1 1
2 1 0 1 0 1 1
3 0 0 1 0 1 1
4 1 1 1 0 1 0
5 0 0 1 0 1 1
6 1 1 0 1 1 1
7 1 0 0 1 1 1
8 1 1 1 0 1 0
9 0 0 1 0 1 1
10 1 0 0 0 1 0
11 1 1 1 1 1 1
12 0 0 1 0 0 0
13 0 0 1 0 1 1
14 0 0 1 0 1 1
15 0 0 1 0 1 1
16 1 0 0 1 1 1
17 1 0 1 1 1 1
18 0 0 0 0 1 1
19 1 0 1 1 1 1
20 1 1 1 1 1 1
21 1 0 1 0 1 1
Notes:

1: Xchanging; 2: Royal DSM; 3:SEB Bank; 4: OpusCapita; 5: Radiant Law; 6: Telefónica O2; 7: Liberty Source; 8: UTILITY; 9: Vodafone Shared Service; 10: Ascension Health; 11: Mellon Bank; 12: SINOCHEM; 13: Davies Turner; 14: MUGF Union Bank; 15: Leeds Building Society; 16: Coveris Holdings Sarl; 17: Wipro; 18: Circle K; 19: Raifessen Bank; 20: ANZ; 21: DBS

Configurations true table without contradiction

Case ID ENVSHI LOWPER ORGIN NWLDER PERTRA RBALIG
18 0 0 0 0 1 1
12 0 0 1 0 0 0
3,5,9,13,14,15 0 0 1 0 1 1
10 0 0 0 0 1 0
1,7,16 1 0 0 1 1 1
2,21 1 0 1 0 1 1
17,19 1 0 1 1 1 1
6 1 1 0 1 1 1
4,8 1 1 1 0 1 0
11,20 1 1 1 1 1 1
Notes:

1: Xchanging; 2: Royal DSM; 3: SEB Bank; 4: OpusCapita; 5: Radiant Law; 6: Telefónica O2; 7: Liberty Source; 8: UTILITY; 9: Vodafone Shared Service; 10: Ascension Health; 11: Mellon Bank; 12: SINOCHEM; 13: Davies Turner; 14: MUGF Union Bank; 15: Leeds Building Society; 16: Coveris Holdings Sarl; 17: Wipro; 18: Circle K; 19: Raifessen Bank; 20: ANZ; 21: DBS

Configurations true table without contradiction

ENVSHI{1} * NWLDER{1} * PERTRA{1} + LOWPER{0} * NWLDER{0} * PERTRA{1}   
(Xchanging, US Military, Coveris Holdings + Telefónica O2 + Mellon, ANZ + Wipro, Raifessen Bank)   (Royal DSM, DBS + SEB Bank, Radiant Law, Vodafone, Davies Turner, MUFG Union Bank, Leeds + Circle K)  
Note:

Minimizing: 1 Including: 0 C

Configurations true table without contradiction

PERTRA{0} +   LOWPER{1} NWLDER{0} + NVSHI{1} ORGIN{0} NWLDER{0}
(SINOCHEM)   (OpusCapita, Big European energy)   (Ascension)  
Note:

Minimizing: 0 Including: R

References

Accenture (2017), “Accenture and blue prism team to provide robotic process automation to help clients accelerate business results, Improve employee and customer experience”, available at: https://newsroom.accenture.com/news/accenture-and-blue-prism-team-to-provide-robotic-process-automation-to-help-clients-accelerate-business-results-improve-employee-and-customer-experience.htm

Auxis (2017), “RPA enables 100% Process efficiency and 45% Cost reduction in AP for global plastic manufacturer”, available at: www.auxis.com/case-studies/rpa-enables-100-process-efficiency-and-45-cost-reduction-in-ap-for-global-plastic-manufacturer

Baker, J., Jones, D.R., Cao, Q. and Song, J. (2011), “Conceptualizing the dynamic strategic alignment competency”, Journal of the Association for Information Systems, Vol. 12 No. 4, p. 299.

Berg-Schlosser, D. and Cronqvist, L. (2005), Multi-Value Qualitative Comparative Analysis (MV-QCA)–a New Tool for Cross-National Research, American Political Science Association Washington, DC (September 1-4).

Berruti, F., Nixon, G., Taglioni, G. and Whiteman, R. (2017), “Intelligent process automation: The engine at the core of the next-generation operating model”, McKinsey Quarterly, March.

BNY MELLON (2017), “The rise of robots”, available at: www.bnymellon.com/us/en/who-we-are/people-report/innovate/the-rise-of-robots.jsp

CEO Magazine (2017), “Global convenience: Jacob Schram, CEO of circle K”, available at: https://www.theceomagazine.com/business/jacob-schram

Chan, Y.E., Huff, S.L., Barclay, D.W. and Copeland, D.G. (1997), “Business strategic orientation, information systems strategic orientation, and strategic alignment”, Information Systems Research, Vol. 8 No. 2, pp. 125-150.

DBS (2017), “DBS bank accelerates digitalisation transformation with robotics programme”, available at: www.dbs.com/newsroom/DBS_Bank_accelerates_digitalisation_transformation_with_robotics_programme

Fiss, P.C. (2007), “A set-theoretic approach to organizational configurations”, Academy of Management Review, Vol. 32 No. 4, pp. 1180-1198.

Hanna, A.J. (2016), “RPA for real: ascension health takes on leading role”, available at: www.ssonetwork.com/technology-automation/articles/rpa-for-real-ascension-health-takes-on-leading-role

Hellström, A. (2016), “Machine learning in finance management: Case OpusCapita”.

Henderson, J.C. and Venkatraman, H. (1999), “Strategic alignment: Leveraging information technology for transforming organizations”, IBM Systems Journal, Vol. 38 Nos 2/3, pp. 472-484.

Herbert, I.P. (2016), “How students can combine earning with learning through flexible business process sourcing: a proposition”.

Holder, C., Khurana, V., Harrison, F. and Jacobs, L. (2016), “Robotics and law: Key legal and regulatory implications of the robotics age”, Computer Law and Security Review, Vol. 32 No. 3, pp. 383-402.

Ketchen, D.J., Jr, Thomas, J.B. and Snow, C.C. (1993), “Organizational configurations and performance: A comparison of theoretical approaches”, Academy of Management Journal, Vol. 36 No. 6, pp. 1278-1313.

KOFAX (2017), “Davies turner transforms customer service with Real-Time insight into shipments and inventory”, available at: www.kofax.com/Learn/Case%20Studies/2016/Davies%20Turner

KOFAX (2017), “Union bank accelerates time to revenue for mortgage loans”, available at: www.kofax.com/Learn/Case%20Studies/2015/Union%20Bank

Lacity, M. Willcocks, L.P. and Craig, A. (2015a), “Robotic process automation at Telefonica O2”.

Lacity, M. Willcocks, L.P. and Craig, A. (2015b), “Robotic process automation: mature capabilities in the energy sector”.

Lacity, M., Khan, S. and Carmel, E. (2016a), “Employing US military families to provide business process outsourcing services: a case study of impact sourcing and reshoring”, CAIS, Vol. 39, p. 9.

Lacity, M., Willcocks, L.P. and Craig, A. (2016b), “Robotizing global financial shared services at royal DSM”, The Outsourcing Unit Working Research Paper Series.

Lacity, M. Willcocks, L.P. and Craig, A. (2017), “Service automation: cognitive virtual agents at SEB bank”.

Luftman, J. (2004), “Assessing Business-IT alignment maturity”, In Strategies for Information Technology Governance, Igi Global, pp. 99-128.

Luftman, J. and Kempaiah, R. (2007), “An update on business-IT alignment: a line has been drawn”, MIS Quarterly Executive, Vol. 6 No. 3, pp. 165-177.

Mowlesy, K. (2016), “Your biggest pain points: Speed of”, available at: www.ssonetwork.com/customer-experience/articles/your-biggest-pain-points-speed-of-change

Obtv-admin (2016), “Wipro’s success through hyper automation”, available at: www.outbounders.tv/wipros-success-hyper-automation

Oliveira, J. (2016), “Robotic process automation (RPA)”.

Ragin, C.C. (2009), Redesigning Social Inquiry: Fuzzy Sets and beyond, University of Chicago Press.

Ragin, C.C. (2014), The Comparative Method: Moving beyond Qualitative and Quantitative Strategies, Univ of CA Press.

Ravishankar, M.N., Pan, S.L. and Leidner, D.E. (2011), “Examining the strategic alignment and implementation success of a KMS: a subculture-based multilevel analysis”, Information Systems Research, Vol. 22 No. 1, pp. 39-59.

Sabegh, M.A.J. and Motlagh, S.M. (2012), “The role and relevance of IT governance and IT capability in Business-IT alignment in medium and large companies”, Business and Management Review, Vol. 2 No. 6, pp. 16-23.

Sabherwal, R., Hirschheim, R. and Goles, T. (2001), “The dynamics of alignment: insights from a punctuated equilibrium model”, Organization Science, Vol. 12 No. 2, pp. 179-197.

Salvatore, R. (2016), “Vodafone shared services: exploring RPA opportunities”, available at: www.ssonetwork.com/technology-automation/articles/relieving-the-pressure-of-recruitment-through-rpa

SINOCHEM Group (2016), “Strategy symposium of SINOCHEM group was held”, available at: www.sinochem.com/en/s/1569-4170-20037.html,SinochemGroup

Smith, P. (2015), “Rise of the machines as ANZ brings in robot workers to do the ‘boring’ jobs”, available at: www.afr.com/technology/rise-of-the-machines-as-anz-brings-in-robot-workers-to-do-the-boring-jobs-20150820-gj3fp6, Financial Review.

Tallon, P. (2003), “The alignment paradox”, CIO Insight, Vol. 1 No. 47, pp. 75-76.

Wang, N., Xue, Y., Liang, H. and Ge, S. (2011), “The road to business-IT alignment: a case study of two Chinese companies”, CAIS, Vol. 28, p. 26.

Willcocks, L.P., Lacity, M. and Craig, A. (2015), “Robotic process automation at Xchanging”, Lse Research Online Documents on Economics.

Willcocks, L.P. Lacity, M. and Craig, A. (2015), “The IT function and robotic process automation”.

Willcocks, L., Lacity, M. and Craig, A. (2017), “Robotic process automation: strategic transformation lever for global business services?”, Journal of Information Technology Teaching Cases, Vol. 7 No. 1, pp. 17-28.

Further reading

Asatiani, A. and Penttinen, E. (2016), “Turning robotic process automation into commercial success–Case OpusCapita”, Journal of Information Technology Teaching Cases, Vol. 6 No. 2, pp. 67-74.

Barkholz, D. (2017), “Ascension’s cost-management efforts boost its financial performance”, available at: www.modernhealthcare.com/article/20170515/NEWS/170519898,ModernHealthcare

Lacity, M.C. and Willcocks, L. (2016), “Rethinking legal services in the face of globalization and technology innovation: the case of radiant law”, Journal of Information Technology Teaching Cases, Vol. 6 No. 1, pp. 15-22.

Acknowledgements

This research was supported by the National Key R&D Program of China under grant number 2017YFB1400701, and the National Social Science Foundation of China under grant number 13AXW010.

Corresponding author

Bo Liu can be contacted at: neal.liu@foxmail.com

Related articles