Introduction
In an era defined by rapid technological advancement, businesses face both significant challenges and valuable opportunities as they pursue digital transformation and integrate AI-driven solutions. As organisations work to maintain a competitive edge, AI’s impact on business strategy, customer experience, and operational efficiency has become increasingly pivotal.
As part of my recent doctoral studies in Digitalisation, specialising in Technology Adoption and AI Integration at IAE Nice, Graduate School of Management, Université Côte d’Azur, I explored this evolving landscape in depth through research focused on SAP customers. I am Happy to share the key findings through a series of insightful and practical articles, each offering guidance for both SAP customer leadership and SAP executives navigating the complexities of AI adoption and technology transformation.
Maximising AI Potential: A Blueprint for Business Success (THIS ARTICLE)Roadblocks to AI AdoptionIs SAP Business Data Cloud the Answer to Your AI Ambitions?
In an era marked by rapid technological advancements, businesses face the dual challenge and opportunity of integrating AI-driven solutions. As organisations strive for competitive advantage, the role of AI in transforming business strategies, enhancing customer experiences, and driving operational efficiency cannot be overstated. This blog explores effective strategies for helping customers navigate the fast-changing AI world, drawing insights from my doctorate reproach aiming to develop a robust theoretical model and managerial blueprint for executive technology transformation and change management.
The Role of AI in Business
Over recent decades, AI has revolutionised how businesses operate, driving personalised marketing, strategic planning, and data-driven insights. Companies now rely on AI-driven chatbots for customer interaction, automated processes for operational efficiency, and data analytics for strategic decisions. The increasing digitization leads to the generation of vast amounts of data, making advanced digital technology indispensable for extracting value from this data. However, this shift also presents challenges, as many businesses struggle to adopt new technologies swiftly enough to remain competitive. Furthermore, technology vendors face the challenge of marketing their innovative solutions effectively and bridging the gap between innovation and adoption.
Key Factors for Successful AI Adoption
Key findings highlight the importance of strategic alignment, collaborative change management, cost considerations, customer experience, and vendor support in the successful adoption of AI technologies. Businesses must ensure AI solutions are in line with their strategic goals to add value and sustainability. Handling change effectively is crucial, involving stakeholders early and prioritising leadership support to cultivate an innovative culture. Financial implications are essential in decision-making, making it vital for organisations to perform detailed cost-benefit analyses to assure profitable returns on AI investments. Enhancing customer experience through AI-driven solutions with user-friendly and personalised interfaces can significantly boost business success. Finally, robust vendor support and training are necessary to facilitate a smooth transition and maximise the advantages of AI technologies, aligning with organisational needs and challenges.
Bridging the Gap: The Fast-Track Model
The Robust Technology Adoption and Contract Retention Model (Fast-Track) is a theoretical framework developed as part of my doctoral studies to provide insights into the multifaceted aspects of technology adoption and retention from both technology vendors’ and users’ perspectives. The model emphasises understanding and addressing barriers and enablers in three key categories: organisational, personal, and external.
Drawing on established theories like the Technology Acceptance Model (TAM), Diffusion of Innovations Theory, Task-Technology Fit, and the Unified Theory of Acceptance and Use of Technology (UTAUT), the model examines how organisational vision, planning, and stakeholder management influence successful technology adoption. Additionally, it considers strategic management theories such as Kaplan & Norton’s Balanced Scorecard framework, which aligns technology strategies with business objectives. The Fast-Track model comprises two primary lifecycle outlines: the Technology Utilisation Lifecycle (for customers) and the Technology Deployment Lifecycle (for SAP/vendors). The former progresses through strategic vision setting, planning, implementation, continuous improvement, and renewal, ensuring technology aligns with evolving business needs. The latter involves market research, sales, implementation, and continuous support, highlighting the importance of understanding customer needs and maintaining engagement.
Furthermore, the model highlights the significance of external factors like industry standards, adoption costs, and vendor support in shaping technology deployment strategies. By addressing these factors, both vendors and users can enhance satisfaction, competitive advantage, and the lifecycle value of technology. Personal attitudes, user training, and change management are additional aspects considered vital in mitigating resistance and enhancing technology adoption. Integrating concepts from technology acceptance models, the framework details how perceived usefulness, ease of use, and associated personal and organisational barriers impact technology uptake and retention. In essence, the Fast-Track model provides a comprehensive strategic pathway for navigating technology adoption and contract retention complexities. It encourages continuous engagement, adaptation, and alignment of technology with organisational goals, thus facilitating successful integration and sustained competitive advantage.
Key Findings and Analyses:
My doctorate research delves into the multifaceted dynamics of technology adoption and contract retention among SAP and various user industries by studying 29 SAP Customers and their Partners across diverse sectors. Utilizing Lexical analysis with NVivo software, the research categorizes and quantifies essential terms, phrases, and themes from interview transcripts, providing a structured and numerical understanding of the content with an emphasis on explicit aspects such as words and visual elements. Key findings include the pivotal role of technology perception in adoption, where strategic alignment with company goals and operational enhancement is crucial, influenced by both internal and external factors like market competition and regulatory requirements. Effective technology adoption requires strategic planning, cost management, and user acceptance, while organizational and personal barriers such as resistance to change and fear of job loss need addressing through robust change management and leadership support. Externally, factors like industry norms and regulatory compliance shape adoption strategies. The cost of technology emerges as a critical determinant, with companies needing to consider both direct and ancillary expenses versus strategic benefits. Positive end-user experiences significantly influence IT contract renewals, with organizations valuing user satisfaction highly. Evaluating alternative vendors involves a detailed analysis of various metrics including solution capability and cost-effectiveness. The study proposes a Fast-TRACK model emphasizing strategic vision, comprehensive planning, and continuous improvement to navigate technology adoption and retention challenges effectively. Practical implications suggest that companies should adopt a holistic approach centered on strategic alignment and robust change management, with SAP urged to demonstrate the strategic value of their solutions and engage customer stakeholders early in the adoption phase to ensure technology implementations meet long-term goals and achieve higher satisfaction and retention rates.
Conclusion
This study explores technology adoption and contract retention using semi-structured interviews and NVivo’s Lexical analysis, highlighting the importance of aligning technology with business needs, effective change management, cost considerations, and strategic implementation. Key themes include the influence of perception, organizational alignment, cost, complexity, ease of use, effective change management, and vendor support on technology adoption and retention. The research, set within a leading software corporation, provides valuable insights and validates findings with additional data. It introduces the Fast-Track model, emphasizing strategic considerations and practical implementations for leveraging technology for competitive advantage. The study also underscores the importance of understanding external barriers and enablers, such as cost, industrial norms, competition, and vendor support. The contributions of the research include extending the Balanced Scorecard approach to incorporate digital transformation, offering managerial recommendations, and providing a comprehensive framework (Fast-Track model) for navigating technology adoption and retention. Managerial recommendations include adopting a structured approach to technology integration, fostering a culture of continuous learning, and investing in robust knowledge management systems. Future research topics suggested include the impact of customer confusion on technology adoption, testing the FUTARE model across different regions and company sizes, and its effectiveness on upselling or expanding service contracts. The study provides valuable insights and practical recommendations for organizations aiming to enhance their technology adoption strategies and retain contracts effectively.
The Robust Technology Adoption and Contract Retention Model (Fast-Track) highlights the need for strategic alignment between technology vendors and users within organizational, personal, and external domains for successful technology adoption and retention. Vendors should deeply understand client structures to tailor technologies that integrate seamlessly into client workflows, enhancing operational effectiveness while maintaining compliance with industry regulations. Prospective clients must ensure these technologies align with strategic goals and existing systems. Proper training for users and insightful adjustment to external factors such as competitive trends are paramount. Broadly, managing the dynamics at the vision to planning phase involving pre-sales to sales within both organizational users and technology vendors is critical. This structured approach will help navigate through barriers and enablers, setting a solid base for adopting new technologies and retaining contracts effectively.
If you’d like to explore further, my full research article with reproach is available here. Please don’t hesitate to contact me if you wish to discuss the research findings.
Find my Linked Profile: https://www.linkedin.com/in/mi4po/
IntroductionIn an era defined by rapid technological advancement, businesses face both significant challenges and valuable opportunities as they pursue digital transformation and integrate AI-driven solutions. As organisations work to maintain a competitive edge, AI’s impact on business strategy, customer experience, and operational efficiency has become increasingly pivotal.As part of my recent doctoral studies in Digitalisation, specialising in Technology Adoption and AI Integration at IAE Nice, Graduate School of Management, Université Côte d’Azur, I explored this evolving landscape in depth through research focused on SAP customers. I am Happy to share the key findings through a series of insightful and practical articles, each offering guidance for both SAP customer leadership and SAP executives navigating the complexities of AI adoption and technology transformation.Maximising AI Potential: A Blueprint for Business Success (THIS ARTICLE)Roadblocks to AI AdoptionIs SAP Business Data Cloud the Answer to Your AI Ambitions?In an era marked by rapid technological advancements, businesses face the dual challenge and opportunity of integrating AI-driven solutions. As organisations strive for competitive advantage, the role of AI in transforming business strategies, enhancing customer experiences, and driving operational efficiency cannot be overstated. This blog explores effective strategies for helping customers navigate the fast-changing AI world, drawing insights from my doctorate reproach aiming to develop a robust theoretical model and managerial blueprint for executive technology transformation and change management.The Role of AI in BusinessOver recent decades, AI has revolutionised how businesses operate, driving personalised marketing, strategic planning, and data-driven insights. Companies now rely on AI-driven chatbots for customer interaction, automated processes for operational efficiency, and data analytics for strategic decisions. The increasing digitization leads to the generation of vast amounts of data, making advanced digital technology indispensable for extracting value from this data. However, this shift also presents challenges, as many businesses struggle to adopt new technologies swiftly enough to remain competitive. Furthermore, technology vendors face the challenge of marketing their innovative solutions effectively and bridging the gap between innovation and adoption.Key Factors for Successful AI AdoptionKey findings highlight the importance of strategic alignment, collaborative change management, cost considerations, customer experience, and vendor support in the successful adoption of AI technologies. Businesses must ensure AI solutions are in line with their strategic goals to add value and sustainability. Handling change effectively is crucial, involving stakeholders early and prioritising leadership support to cultivate an innovative culture. Financial implications are essential in decision-making, making it vital for organisations to perform detailed cost-benefit analyses to assure profitable returns on AI investments. Enhancing customer experience through AI-driven solutions with user-friendly and personalised interfaces can significantly boost business success. Finally, robust vendor support and training are necessary to facilitate a smooth transition and maximise the advantages of AI technologies, aligning with organisational needs and challenges.Bridging the Gap: The Fast-Track ModelThe Robust Technology Adoption and Contract Retention Model (Fast-Track) is a theoretical framework developed as part of my doctoral studies to provide insights into the multifaceted aspects of technology adoption and retention from both technology vendors’ and users’ perspectives. The model emphasises understanding and addressing barriers and enablers in three key categories: organisational, personal, and external.Drawing on established theories like the Technology Acceptance Model (TAM), Diffusion of Innovations Theory, Task-Technology Fit, and the Unified Theory of Acceptance and Use of Technology (UTAUT), the model examines how organisational vision, planning, and stakeholder management influence successful technology adoption. Additionally, it considers strategic management theories such as Kaplan & Norton’s Balanced Scorecard framework, which aligns technology strategies with business objectives. The Fast-Track model comprises two primary lifecycle outlines: the Technology Utilisation Lifecycle (for customers) and the Technology Deployment Lifecycle (for SAP/vendors). The former progresses through strategic vision setting, planning, implementation, continuous improvement, and renewal, ensuring technology aligns with evolving business needs. The latter involves market research, sales, implementation, and continuous support, highlighting the importance of understanding customer needs and maintaining engagement.Furthermore, the model highlights the significance of external factors like industry standards, adoption costs, and vendor support in shaping technology deployment strategies. By addressing these factors, both vendors and users can enhance satisfaction, competitive advantage, and the lifecycle value of technology. Personal attitudes, user training, and change management are additional aspects considered vital in mitigating resistance and enhancing technology adoption. Integrating concepts from technology acceptance models, the framework details how perceived usefulness, ease of use, and associated personal and organisational barriers impact technology uptake and retention. In essence, the Fast-Track model provides a comprehensive strategic pathway for navigating technology adoption and contract retention complexities. It encourages continuous engagement, adaptation, and alignment of technology with organisational goals, thus facilitating successful integration and sustained competitive advantage. Key Findings and Analyses:My doctorate research delves into the multifaceted dynamics of technology adoption and contract retention among SAP and various user industries by studying 29 SAP Customers and their Partners across diverse sectors. Utilizing Lexical analysis with NVivo software, the research categorizes and quantifies essential terms, phrases, and themes from interview transcripts, providing a structured and numerical understanding of the content with an emphasis on explicit aspects such as words and visual elements. Key findings include the pivotal role of technology perception in adoption, where strategic alignment with company goals and operational enhancement is crucial, influenced by both internal and external factors like market competition and regulatory requirements. Effective technology adoption requires strategic planning, cost management, and user acceptance, while organizational and personal barriers such as resistance to change and fear of job loss need addressing through robust change management and leadership support. Externally, factors like industry norms and regulatory compliance shape adoption strategies. The cost of technology emerges as a critical determinant, with companies needing to consider both direct and ancillary expenses versus strategic benefits. Positive end-user experiences significantly influence IT contract renewals, with organizations valuing user satisfaction highly. Evaluating alternative vendors involves a detailed analysis of various metrics including solution capability and cost-effectiveness. The study proposes a Fast-TRACK model emphasizing strategic vision, comprehensive planning, and continuous improvement to navigate technology adoption and retention challenges effectively. Practical implications suggest that companies should adopt a holistic approach centered on strategic alignment and robust change management, with SAP urged to demonstrate the strategic value of their solutions and engage customer stakeholders early in the adoption phase to ensure technology implementations meet long-term goals and achieve higher satisfaction and retention rates.ConclusionThis study explores technology adoption and contract retention using semi-structured interviews and NVivo’s Lexical analysis, highlighting the importance of aligning technology with business needs, effective change management, cost considerations, and strategic implementation. Key themes include the influence of perception, organizational alignment, cost, complexity, ease of use, effective change management, and vendor support on technology adoption and retention. The research, set within a leading software corporation, provides valuable insights and validates findings with additional data. It introduces the Fast-Track model, emphasizing strategic considerations and practical implementations for leveraging technology for competitive advantage. The study also underscores the importance of understanding external barriers and enablers, such as cost, industrial norms, competition, and vendor support. The contributions of the research include extending the Balanced Scorecard approach to incorporate digital transformation, offering managerial recommendations, and providing a comprehensive framework (Fast-Track model) for navigating technology adoption and retention. Managerial recommendations include adopting a structured approach to technology integration, fostering a culture of continuous learning, and investing in robust knowledge management systems. Future research topics suggested include the impact of customer confusion on technology adoption, testing the FUTARE model across different regions and company sizes, and its effectiveness on upselling or expanding service contracts. The study provides valuable insights and practical recommendations for organizations aiming to enhance their technology adoption strategies and retain contracts effectively.The Robust Technology Adoption and Contract Retention Model (Fast-Track) highlights the need for strategic alignment between technology vendors and users within organizational, personal, and external domains for successful technology adoption and retention. Vendors should deeply understand client structures to tailor technologies that integrate seamlessly into client workflows, enhancing operational effectiveness while maintaining compliance with industry regulations. Prospective clients must ensure these technologies align with strategic goals and existing systems. Proper training for users and insightful adjustment to external factors such as competitive trends are paramount. Broadly, managing the dynamics at the vision to planning phase involving pre-sales to sales within both organizational users and technology vendors is critical. This structured approach will help navigate through barriers and enablers, setting a solid base for adopting new technologies and retaining contracts effectively. If you’d like to explore further, my full research article with reproach is available here. Please don’t hesitate to contact me if you wish to discuss the research findings.Find my Linked Profile: https://www.linkedin.com/in/mi4po/ Read More Technology Blog Posts by SAP articles
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