Work with us
Executive Briefing: Architecting Your Next-Generation Operating Model
Explore how AI is reshaping global business and learn why reinventing your operating model is essential for survival.
This executive briefing breaks down the generative AI paradox, the shift to customer-centric journeys, intelligent automation, and scaling digital transformation.
Discover the leadership strategies needed to build a resilient, future-ready organisation.
The Unavoidable Mandate: Reinvention in the Age of AI
The global business landscape is being reshaped by Artificial Intelligence with a velocity that leaves no industry untouched. The window to treat AI as a competitive advantage has closed. It is now a brutal determinant of survival, and the C-suite is facing a stark choice: lead a fundamental operational reinvention or manage an inevitable decline.
Incremental adjustments are insufficient; a foundational redesign of how work is done, how value is created, and how customers are served is now the primary determinant of future relevance and growth.
The pace of adoption underscores this urgency, signalling a widespread recognition that the old ways of working are no longer viable.
- 78% of business leaders report their organisations have already adopted AI in at least one business function.
- Two out of five companies worldwide are now actively using AI in their operations.
- 76% of global CEOs acknowledge that their business requires fundamental reinvention to remain competitive.
Despite this rapid integration, many organisations are struggling to translate AI investment into tangible value—a disconnect known as the "Generative AI Paradox." While nearly eight in ten companies report using generative AI, an equal percentage see no significant bottom-line impact. This disconnect stems from a common over-reliance on simple, horizontal applications like enterprise-wide copilots.
These tools offer incremental productivity boosts but fail to deliver transformative results. The real value of AI is unlocked through vertical use cases that automate and reimagine complex, industry-specific business processes from the ground up.
Escaping this paradox requires more than better tools; it demands a new blueprint for the business itself—a next-generation operating model.
Defining the Next-Generation Operating Model
We define the next-generation operating model as a new architecture for the organisation that integrates digital technologies and operations capabilities to achieve step-change improvements in revenue, customer experience, and cost efficiency. It is not merely a technology upgrade but a complete reimagining of how teams, processes, and data interact to deliver value.
This model is built on a simple but powerful two-part framework.
- Reimagining Core Journeys: This involves a fundamental shift in perspective, moving away from organising work within traditional departmental silos and toward a holistic view centred on end-to-end customer journeys. This includes both customer-facing interactions and the internal processes that support them.
- Building Foundational Capabilities: This requires developing a specific set of digital and analytical capabilities to power these reimagined journeys. The two primary engines are Intelligent Process Automation and Advanced Analytics, which serve as the technological backbone for automation and data-driven decision-making.
The primary organising principle of this new model is the customer journey. This is a critical distinction from traditional, function-first models. Customer journeys, such as opening an account or resolving an issue, naturally cut across departmental silos like marketing, operations, legal, and IT.
By focusing on the journey, an organisation is forced to solve problems from the customer's perspective, breaking down internal barriers and aligning disparate teams around a common goal: delivering a seamless and satisfying experience.
This customer-centric approach provides the strategic clarity needed to redesign how work gets done across the enterprise.
Reimagining the Customer Journey
The strategic imperative in the digital age is to focus on end-to-end customer journeys, as optimising individual touchpoints is no longer sufficient. Overall satisfaction with a journey is what drives customer loyalty and creates sustainable value.
An organisation can deliver excellent performance at isolated touchpoints—a well-designed app, a helpful call centre, an efficient branch—and yet still fail to satisfy the customer if the overall journey is fragmented and difficult.
Redesigning these journeys requires adhering to a set of core principles that prioritise simplicity, customer value, and trust.
- Simplify Radically Before Digitising: The objective is not to digitise existing complexity but to eliminate it. Before streamlining its digital experience, one telecom provider first reduced its product portfolio by 80%. By rationalizing its offerings and eliminating unnecessary process steps, it ultimately cut the sign-up time for new customers by two-thirds.
- Focus on What Matters to the Customer: Deeply understanding customer needs allows an organisation to create value where it counts most. Satisfied customers not only spend more but are significantly more loyal. In the banking industry, for example, customers who are satisfied with their experience are seven times more likely to increase their deposits with the bank.
- Build Trust and Community: Digital touchpoints can be powerful tools for fostering credibility and connection. Beauty brands, for instance, build authority and educate their users with tools like a "Skin Decoder" quiz. They also build community and add a layer of credibility by featuring brand ambassadors and user-generated content on a dedicated "Routines" page.
Personalisation is a non-negotiable component of the modern customer journey. The data is unequivocal: between 78% and 91% of shoppers are more likely to purchase from a brand that personalises their experience. The risk of inaction is equally clear. A staggering 71% of consumers report feeling annoyed when their shopping experience feels impersonal, and 66% state they will stop buying from such sites altogether.
Successfully redesigned journeys provide a clear blueprint for the intelligent capabilities required to bring them to life at scale.
Powering Journeys with Intelligent Capabilities
Intelligent automation and advanced analytics are the dual engines of the next-generation operating model. These are not merely support tools but the core drivers of efficiency, insight, and data-driven decision-making. They provide the power to execute reimagined customer journeys with speed, precision, and intelligence that would be impossible to achieve through manual effort alone.
Intelligent Process Automation (IPA)
Intelligent Process Automation is an emerging set of technologies that combines fundamental process redesign with robotic process automation (RPA) and machine learning. Its primary function is to replace manual, rote tasks, freeing human workers to focus on higher-value activities that require judgment, creativity, and empathy. The impact of IPA is both significant and measurable, delivering transformative results across the value chain.
- Automation of 50% to 70% of tasks within targeted processes.
- Reduction in logistics costs by 15% through better routing and forecasting.
- Reduction in inventory levels by 20% by enabling smarter stock control.
- An 18% reduction in cart abandonment by powering smart reminders and personalisation.
These are not discrete improvements; they represent a fundamental re-architecting of the value chain, driving efficiency from procurement and logistics through to the final point of sale.
Advanced Analytics
Advanced analytics is the autonomous processing of data using sophisticated tools to discover insights, make recommendations, and improve decision-making. In a world where unstructured data—such as text, images, and video—represents 80% of all available information, the ability of business intelligence platforms to simplify this complexity is critical. By turning vast datasets into actionable insights, advanced analytics fuels tangible productivity gains.
A landmark study on the impact of AI tools revealed dramatic improvements in output. Customer service agents handled 13.8% more inquiries per hour, business professionals wrote 59% more documents per hour, and programmers coded 126% more projects per week. These gains demonstrate the power of analytics not just to accelerate work but to fundamentally enhance human capability.
Yet, even the most powerful technological engines will stall if they are installed in a legacy chassis. Without the foundational elements of scale—the right structure and culture—these capabilities remain trapped in "pilot paralysis," failing to deliver enterprise-wide value.
Building the Foundation for Scale
The most sophisticated technology initiatives will fail to deliver enterprise-wide value without a concurrent transformation of the organisation’s culture and structure. Without these foundational elements, promising technology initiatives often remain isolated experiments, a phenomenon known as "pilot paralysis."
Many large organisations, including governments, suffer from this condition, having "no systematic mechanism for bringing together learning from pilots and there are few examples of successful at-scale adoption."
To overcome this challenge and build for scale, organisations can establish a Digital Factory. This is a dedicated, cross-functional group that balances the need for focused incubation with the imperative of broader transformation. A digital factory models new, agile ways of working and serves as a center of excellence for developing digital capabilities.
Critically, it is designed to integrate these capabilities back into the main business, ensuring that innovations do not remain siloed but are instead scaled across the enterprise.
This structural change must be supported by the cultivation of an AI-literate, data-driven culture. This requires a deliberate and sustained investment in people.
- Acknowledge the Skills Gap: Leaders must recognise that existing teams may lack necessary skills. For example, 44% of CFOs have noted a workflow automation skills gap among their finance teams, highlighting the need for targeted upskilling.
- Democratise AI and Data: Limiting access to advanced tools is counterproductive. Research shows that organisations empowering employees with access to AI-based data analytics tools experienced an increase of more than 10% in annual revenue more often than those that gatekept access.
- Invest in People: A crucial principle for success is to invest more in people than in technology. The guiding mantra should be: "for every pound/dollar you invest in tech, invest two pounds/dollars in people and change."
Driving this comprehensive transformation of structure, skills, and culture ultimately depends on the active and visible commitment of executive leadership.
A Call to Action: The Executive's Role in Leading the Transformation
Ultimately, leadership underpins whether the next-generation operating model becomes a reality or remains a boardroom aspiration. As the primary change agents in the business, senior executives have an outsized influence on the success of this transformation.
This transformation demands a specific mindset, and every executive must ask which role they are playing: the "Chief Today Officer," who protects the present, or the "Chief Tomorrow Officer," who architects the future. The distinction is not subtle, and it determines the outcome.
To guide the organisation through this evolution, leaders must take ownership of three core responsibilities.
- Set a Clear, Company-Wide Direction: Without strategic focus, AI becomes chaotic, leading to tool sprawl, redundant efforts, and missed priorities. A strong AI strategy must define not only which high-value use cases to pursue but also, critically, which opportunities not to chase.
- Champion New Ways of Working: Success requires forging alignment at all levels of the organisation around end-to-end customer journeys. Leaders must actively champion and embed agile, cross-functional ways of working that break down traditional silos and foster collaboration.
- Anchor the Transformation Through Bold Decisions: The journey must move beyond endless planning. This means rapidly building prototypes, testing minimum viable products in the market, and decisively reallocating resources from old operating models to new ones—even when legacy businesses are still profitable.
The companies that architect their operations for the age of AI will not just navigate disruption—they will become the disruptors, defining the new economics of value in their industries and leaving competitors to operate within a framework they no longer control.
Related articles
Passing the Test: 4 Questions Investors Will Ask About Your D2C Tech
Preparing for technical due diligence isn't a last-minute scramble; it's a strategic process. It requires transforming your technology from a simple operational function into a compelling asset that de-risks the investment and proves your capacity for disciplined growth.
Beyond the First Box: Why Your Subscription Model Is Leaking Revenue (And How to Fix It)
Optimising a subscription business is a continuous process of refinement. It requires a deep, hands-on understanding of both the customer lifecycle and the technology that powers it.
The D2C Health & Beauty Playbook: 3 Tech Strategies for Hyper-Growth
Scaling a D2C Health, Beauty, or Wellness brand requires specialised expertise. The technology strategy must be purpose-built to handle the unique demands of subscriptions, global markets, and regulatory scrutiny.