Deep automation: A CIO weapon for turning disruption into opportunity

The IDC CIO Sentiment Survey has consistently shown automation climbing the priority list since 2020. Indeed, according to the 2023 survey (September 2023), 71.1% of respondents said they were accelerating or continuing to invest in automation to replace part of the workforce, and 73.7% said it was to improve processes in the context of difficult economic conditions.

However, traditional automation approaches are no longer sufficient to compete today. A new perspective is needed — one that operates at the scale of the future enterprise and the speed of environmental changes.

Unleashing deep automation: Evolving enterprise intelligence

Deep automation transcends traditional automation approaches, offering a holistic, adaptive, and evolutive strategy at the enterprise and ecosystem level. Unlike siloed or shallow automation efforts, deep automation architects a perspective that integrates customer experiences, value streams, human-machine collaboration, and synergistic technologies to create intelligent, self-adjusting businesses.

Deep automation, like deep learning, combines simple components vertically — in multiple layers — to create sophisticated capabilities. It leverages hierarchies, synergistic transformation, and distributed processing to produce complex, intelligent systems. This approach enables exponential improvements beyond standard automation, emphasizing intelligent decision-making and orchestration.

Deep automation transforms enterprises into living organisms, integrating technologies, processes, and data for self-adjustment. It emphasizes end-to-end integration, intelligent design, and continuous learning. Unlike traditional approaches, deep automation is holistic, adaptive, and evolutive, prioritizing human-machine partnership and customer experience for optimal efficiency and impact. Let’s drill down a bit into those three characteristics.

• Holistic: Deep automation considers the entire enterprise ecosystem, breaking down silos among departments and functions.
• Adaptive: Deep automation can adjust to changing conditions in real time, allowing businesses to pivot quickly in response to market shifts or disruptions.
• Evolutive: Deep automation continuously learns and improves, leveraging AI and machine learning to enhance its capabilities over time.

John Deere’s precision agriculture exemplifies deep automation. AI-integrated tractors, planters, and harvesters form a data-driven team, optimizing tasks and empowering farmers. John Deere’s customer-centric design leverages technology synergy (GPS, sensors, etc.) to create a continual learning system, ultimately leading to higher yields and improved resource management for farmers.

Overcoming obstacles to deep automation deployment

Implementing deep automation isn’t without its challenges. Here are some key hurdles and strategies to overcome them:

• Foster an automation culture by involving employees early and showcasing benefits. This might involve creating cross-functional teams to identify automation opportunities and demonstrating quick wins to build momentum.
• Address technical debt and system complexity through modular development and continuous improvement processes. Consider adopting microservices architecture to make systems more flexible and easier to automate.
• Implement robust risk assessment and mitigation strategies encompassing automation initiatives. This includes regular security audits of automated systems and ensuring compliance with data protection regulations.
• Prioritize data quality to ensure accurate automation outcomes.

Mastering deep automation: Six principles for excellence

To guide your deep automation journey, consider these principles:

1. Drive for speed and real-time insights: Aim to reduce decision-making latency and increase the velocity of business processes.
2. Apply business-centric thinking: Manage deep automation as a business transformation, prioritizing agility and resilience over mere cost optimization.
3. Seek end-to-end automation completeness: For greater adaptability, automate entire processes, not just isolated tasks, aiming for automation that surpasses 100%. Look beyond individual tasks to automate entire value streams.
4. Prioritize openness and flexibility: Adopt open standards and APIs to ensure flexibility and interoperability. Avoid vendor lock-in and plan for potential exits, ensuring a dynamic deep automation ecosystem.
5. Enforce responsible automation practices: Consider the ethical implications of automation and ensure transparency in AI-driven decision-making.
6. Create a harmonious human-machine partnership: Deep automation does not replace humans but augments their capabilities. The World Economic Forum estimates that by 2025, technologies like automation will create at least 12 million more jobs than they eliminate.

Implementing deep automation: A CIO’s action plan

IDC’s Worldwide CEO Survey 2024, February 2024, shows that automation technologies climbed five positions since last year to emerge as the second biggest tech spending priority for CEOs in 2024. The role of the CIO is crucial in driving deep automation.

• Start by engaging key stakeholders and sharing an enterprisewide vision. Develop clear automation principles and leverage different perspectives — system-centric, labor-centric, decision-centric, and customer-centric — to understand the whole automation ecosystem.
• Consider establishing a center of excellence to facilitate learning and set enterprisewide standards. This can be a hub for best practices, training, and cross-functional collaboration on automation initiatives.
• Develop holistic metrics aligned with business objectives, integrating KPIs and OKRs into automated systems. Implement real-time dashboards to track performance across the organization. Establish clear metrics demonstrating deep automation’s value to stakeholders, addressing the common struggle to measure its impact on business outcomes effectively.

The CIO’s imperative: Leading in the deep automation era

Deep automation represents a new perspective on enterprise efficiency and adaptability. By embracing this holistic, adaptive, and evolutive approach, CIOs can transform their organizations into self-optimizing entities capable of thriving in an era of disruption.

Deep automation is about reimagining the business as an intelligent, adaptive organism. It’s about creating an organization that can sense, respond, and evolve in the face of change.

By leveraging this perspective, you can position your organization to weather disruptions and harness deep automation’s energy for unprecedented growth and innovation.

Learn more about IDC’s research for technology leaders.

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Dr. Serge Findling is a senior IT and business executive and a CIO, CEO, and C-suite advisor. As an adjunct research advisor and former vice president of research with IDC’s IT Executive Programs (IEP) and the CIO and Technology Professionals Agenda program, Serge focuses on digital transformation leadership for business and technology executives. He also helps organizations thrive with AI, data excellence, and strategic architecture in today’s digital landscape. He is a frequent speaker, presenter, and moderator at industry conferences and provides analysis for multiple media outlets.