The struggle for ROI from new technologies is real, with leaders all too often reporting a disconnect between the hype of new tools and the cold reality. To be fair, technology implementation projects are often highly complex and disruptive. The sheer scale, scope and reach of these technologies extends beyond traditional software updates to every aspect of the business including customer experience, operational process changes, application enhancements and infrastructure adaptations. But with the excitement about the transformational capabilities of AI, and the rush to test and roll out the latest AI tools, the issue of ROI is more in the spotlight than ever. As the initial wave of enthusiasm passes, boards demand strong outcomes that justify their initial investment.

So why do organisations struggle to get ROI from technology? We reached out to Chief Disruptor members in our latest poll to see if they could shed light on this important issue.

By far the highest response in our poll (60%) was ‘workforce cultural inertia’ which commonly presents as a lack of cultural alignment with strategic goals and adaptability to change. Interestingly, ‘lack of alignment with existing culture and processes’ also came out as the main reason for ROI challenges in the 2024 Chief Disruptor Disruptive Trends Report. This matters because resistance to change can result in low technology adoption rates and decreased productivity, which makes sense; you can only benefit from new technologies if your people actually use them.

Some organisations, departments, or employees are more open to change than others, and we have seen the impact these characteristics can have on business performance in Chief Disruptor’s recent research on the power of the disruptive mindset. Since new technology often changes how people work, leaders need to anticipate and engage the naysayers and target the early adopters to build momentum. In our upcoming Chief Disruptor Forum: Harnessing the Power of AI on 22 November 2024, we will explore more on how to overcome such challenges by identifying the right internal advocates for digital transformation.

Chief Disruptor member, Tony Stanford-Beale (former Head of Architecture and Governance, Costain Group PLC), who selected this option in our poll commented,

“It's an interesting survey and also interesting to see that cultural inertia was the leading response. It's always important to remember the people part is vital if you want to change something.”

He went on to add,

“People are often in three camps - those that don’t see the need for change, (passive or active resistors), those who see the need for change, and those who want to make the change happen, (active promoters and evangelists.) The communication and change strategy needs to be tailored and planned accordingly.”

‘Unoptimised organisation design’ was the second most popular response in our poll (20%).

Speed and agility are vital to competitive advantage in this fast-moving, uncertain operating environment. In an AI-powered world, this translates into the ability to act swiftly on unprecedented strategic insights by designing streamlined decision-making and workflows. Leaders will need to explore agile methodologies and help teams work in new and more versatile ways that empower and encourage trust, collaboration and accountability. This will be a major topic in our dinner, Generative AI: The Future User Interface for Workplace Efficiency and Innovation, on 25 September 2024, where we'll discuss agile approaches for incorporating AI into daily workflows.

Data integration is fundamental with ensuring successful GenAI outcomes but all too often, organisations are held back by legacy constraints. Integrating AI solutions with existing IT infrastructure can be complex and costly. Legacy systems may not be compatible with new AI technologies, creating unforeseen costs through upgrade requirements or even complete overhauls. This integration process involves not only technological adjustments but also changes in workflows and processes, which can incur additional costs and affect ROI calculations. The complexity of integration can lead to extended timelines and unexpected expenses, further complicating the measurement of ROI. High-quality data is also crucial for the success of AI projects. Poor data quality can lead to inaccurate models and suboptimal outcomes, directly impacting the perceived ROI. Ensuring data quality involves rigorous data cleaning, validation, and management practices which can be resource-intensive. We will cover the importance of high-quality data and integration strategies in our Chief Disruptor Forum: Enabling Ethical AI on 23 October 2024.

Finally, the volume of data required for effective AI training can be substantial, driving a need for more robust data infrastructure and governance policies. These requirements add layers of complexity and cost to AI projects, influencing the overall ROI.

Finally, the lack of key digital skills is a huge challenge for leaders striving for competitive advantage. The government has reported that the digital skills gap is estimated to cost the UK economy £63 billion per year (Department of Culture, Media and Sport, UK Digital Strategy, 4 October 2022). In Chief Disruptor’s 2024 Disruptive Trends Report, a ‘Lack of skills and talent to implement new technologies’ was one of the biggest factors preventing organisations from investing in technologies that might enable competitive advantage. In an AI-powered world, the opportunity cost of poor digital skills is even greater as companies’ ability to harness AI depends on their ability to access and make use of their data. We spoke with Joanne Roxburgh (COO of Skilled Education) about the potential impact of a lack of digital skills and the importance of taking a ‘people-first’ approach. She told us,

“Digital skills are important, but the real competitive edge for companies comes not from training more people in technical skills, but from cultivating human skills. Companies that focus on tech alone may find themselves outpaced by companies that invest in critical thinking, adaptability and resilience. True innovation occurs when we combine technology with human insight, ethical considerations, and a culture of continuous learning alongside digital upskilling."

In our upcoming Chief Disruptor Breakfast Club: Plan, Align and Execute your Automation Strategy on 10 January 2025, we will delve into how organisations can tackle these skill shortages and develop the necessary digital and human capabilities to execute a successful automation strategy.

Conclusion

In our latest edition of Insights we set out to explore the challenge of getting ROI on disruptive technologies, however perhaps inevitably, the context for many members’ responses is ‘everything AI’. The evolving nature of AI means that metrics and methodologies for measuring AI are also constantly evolving. Tangible and intangible metrics, such as sentiment analysis and customer feedback metrics can provide some insights into customer satisfaction, but translating these metrics into precise financial gains remains difficult for many.

To close this month, I’d like to leave you with a very useful reflection on AI, that is probably applicable to any other technology rollout or integration. Chief Disruptor member, Alexander Alinia (Data & Digital Innovations Lead New Energies, Shell) advised,

"AI is no different to any other digital technology that has evolved over the past 40+ years. Same reluctance and lack of knowledge existed when using macros in Excel. At the same time, data has not changed in that time, there is no such thing as "clean" or "great" data. It is how the new technology is used and how data is utilised to achieve project goals, adding as many layers as possible to paint the picture. The misunderstanding of AI is what leads to delays, spiralling costs and lack of delivery, compounded by inexperienced individuals leading projects. Ensuring the same principles of product development are followed will help success rates, rather than give special conditions".