Organisation Readiness for Digital Technology Adoption
How do you know if your organisation is ready for the adoption of technology such as Gen AI? From last year, we have seen many large organisations have been rushing to adopt Gen AI to bring efficiencies into their operations. One important aspect to consider is organisational readiness to adopt new technologies in terms of its current people, processes, and technology and how this is effectively and sustainably executed with Change Management considerations.
Here are tips to assess People, Process, and Technology Change that need to be considered if you want to start it right before you dive into investing into more digital transformation.
Organisation Readiness for Digital Technology Adoption (ORDTA)
Assess the Level of Digital Adoption Readiness
Organisation Readiness for Technology Adoption (ORDTA) framework, loosely adapted from the Data Management Maturity (DMM) Model by the CMMI Institute, expanded to include different technologies such as Gen AI.
The ORDTA framework helps organisations to assess their readiness and classify them into five progressive levels of readiness – initial, managed, defined, measured, and optimized. We provide a quick outline of the characteristics of each readiness level as well as some strategies that business leaders can focus on to progress to the next level.
Level 1 – Initial (Digital Awareness)
Characteristics: Organisations at this level have basic digital capabilities, often limited to essential IT infrastructure. Data management is ad-hoc, and there is minimal use of digital technologies and AI. Awareness of the potential of digital transformation and AI is growing, but initiatives are scattered and uncoordinated.
Focus: Identifying opportunities for digital technology and AI use, focusing on key business processes or areas that contributes the most value to the organisation. Organisations should also look at establishing foundational IT and data management practices, and building awareness about digital transformation's potential benefits. It is also crucial to start providing the relevant IT or technology training to employees.
Example Initiatives:
- Conduct a Digital Audit: Assess current digital tools, platforms, and data management practices to understand the baseline.
- Digital Literacy Training: Offer basic digital skills and AI awareness training to employees across the organisation.
Level 2 – Managed (Digital Engagement)
Characteristics: The organisation starts to engage more systematically with digital technologies. Initial governance structures for digital and AI initiatives are put in place. Some projects may be underway, focusing on automating processes or enhancing existing systems with digital technologies. Data management practices are becoming more structured, with efforts to ensure data quality and accessibility for digital projects.
Focus: Developing and managing digital projects with specific goals, such as process automation or customer engagement enhancements. Establishing standards for data governance and exploring the integration of AI and analytics in processes.
Example Initiatives:
- Implement Data Governance Framework: Establish clear policies and roles for managing data, crucial for supporting digital technologies and AI.
- Pilot Digital Projects: Initiate pilot projects focusing on areas with high potential ROI, like digital marketing campaigns or customer data analytics.
- Develop an AI/Digital Transformation Roadmap: Start planning for AI by identifying use cases where AI can solve specific business problems or enhance existing processes. Same applies to other digital technologies.
Level 3 – Defined (Digital Integration)
Characteristics: Digital technologies, including AI, are integrated into business processes. The organisation has clear strategies for digital transformation and AI adoption. Data management practices are well-defined and align with digital initiatives. There’s an emphasis on developing digital skills within the workforce and fostering a culture that embraces digital innovation.
Focus: Systematic integration of digital technologies across the organisation, leveraging data for insights and decision-making. Implementing AI solutions where they can add significant value, with a focus on scalability and sustainability.
Example Initiatives:
- Integrate CRM and ERP Systems: Ensure customer relationship management (CRM) and enterprise resource planning (ERP) systems are integrated and leverage digital technologies for seamless operations.
- Embed Analytics in Decision-Making: Use business intelligence (BI) tools and analytics to inform strategic decisions, ensuring data from digital and AI systems is effectively utilized.
- Setting Up Data Warehouse or Data Lakes: Consolidate multiple data sources into a single platform for better data management and utilization across teams and departments.
- AI for Operational Efficiency: Deploy AI solutions for operational areas such as inventory management, predictive maintenance, or process optimization.
Level 4 – Measured (Digital Optimization)
Characteristics: The organisation measures the impact of digital technologies and AI on business outcomes. There are established KPIs for digital transformation success, including efficiency gains, customer satisfaction improvements, and innovation metrics. Data-driven decision-making is widespread, supported by mature data management and analytics practices.
Focus: Continuous improvement of digital processes through measurement and feedback. Optimizing AI implementations for better performance and exploring advanced technologies such as machine learning and deep learning for strategic advantages.
Example Initiatives:
- Establish Digital KPIs: Define and regularly monitor key performance indicators related to digital and AI initiatives to measure impact and identify areas for improvement.
- Implement Integrated Analytics: Use leverage on data from multiple sources to optimize business process or provide decision intelligence. Example would be automated ordering and fulfilment using inventory levels, past purchase levels and frequency, sales and sales forecasts data.
- Enhance Cybersecurity with AI: Implement AI-driven cybersecurity solutions to protect against increasingly sophisticated cyber threats, ensuring the security of digital platforms and data.
Level 5 – Optimized (Digital Transformation)
Characteristics: At this highest level, the organisation is fully transformed by digital technologies and AI, using them to drive innovation, create new business models, and maintain a competitive edge. The organisation is agile, able to quickly adapt to market changes and new technologies. AI and digital technologies are integral to the organisation’s strategy, operations, and culture.
Focus: Leveraging digital technologies and AI not just for operational efficiency but as core elements of the business strategy. Innovating continuously with data and technology, fostering a culture of learning and adaptation, and leading the market through digital excellence.
Example Initiatives:
- Innovate with Data and AI: Launch new products or services powered by AI and digital technologies, such as AI-based predictive analytics services or digital platforms that offer unique customer experiences.
- Adopt Advanced Technologies: Explore and integrate advanced technologies like blockchain for supply chain transparency or Internet of Things (IoT) for enhanced data collection and analysis.
- Foster a Culture of Continuous Innovation: Encourage ongoing learning, experimentation, and adaptation across the organisation, enabling quick responses to technological advancements and market changes.
Many organisations are currently already in Level 2 (Digital Engagement) and Level 3 (Digital Integration). While organisations in Level 5 (Digital Transformation) are mostly digital native companies and technology firms. Hopefully, organisations can leverage on this ORDTA expanded framework to assess the current readiness and fully leverage the potential of digital technologies and AI most effective to its current readiness. Moving through the levels, organisations can systematically enhance their digital capabilities, align digital strategies with business objectives, and transform their operations and offerings to thrive in the digital age. Focusing on the wrong initiatives in different stages would result in the gaps in either or all of the three pillars (people, process, technology), resulting in resentment, adoption failure, and high change management efforts. It is important for business leaders to view technology adoption as a journey instead as a one-off initiative, to increase the effectiveness and reduce barriers to adoption.
Many organisations are currently already in Level 2 (Digital Engagement) and Level 3 (Digital Integration). While organisations in Level 5 (Digital Transformation) are mostly digital-native companies and technology firms. Hopefully, organisations can leverage this ORDTA expanded framework to assess current readiness and fully leverage the potential of digital technologies and AI most effectively for their current readiness. Moving through the levels, organisations can systematically enhance their digital capabilities, align digital strategies with their business objectives, and transform their operations and offerings to thrive in the digital age. Focusing on the wrong initiatives at different stages would result in gaps in either or all of the three pillars (people, process, technology), resulting in resentment, adoption failure, and high efforts in change management. It is important for business leaders to view technology adoption as a journey instead of a one-off initiative to increase effectiveness and reduce barriers to adoption.
Watch this space next week as we unveil our approach to complement successful digital transformation with Change Management.
This article is written by Lee Gang (AI & Data Co-creation Satellite, Founder & CEO of ELGO Technologies), Wong Mei Wai (Founder, CEO & Chief Change Advisor of APAC Global Advisory) and Chang Hui Tze (Marketing & Business Development Manager of APAC Global Advisory).