The impact of TOM on customer experience and performance

An Operating Model (OM) is the structural framework that defines how an organization creates and delivers value through its processes, people, systems, and technology. It determines how resources are organized, coordinated, and optimized to achieve operational efficiency. A Target Operating Model (TOM), on the other hand, is the aspirational blueprint of how an organization’s operations should function to meet long-term strategic goals. TOM bridges the gap between strategy and day-to-day execution, allowing the enterprise to align its resources, processes, and systems with the changing dynamics of the market and customer demands.

In the ever-evolving landscape of modern business, implementing a new TOM is not only a question of operational efficiency but a strategic necessity. As of 2025, with the rapid integration of AI agents and hyperautomation reshaping industries, organizations must adapt to close the gap between strategy and performance. This essay explores when it is essential to implement a new TOM, why aligning TOM with the enterprise’s business model is critical, and how it impacts both customer experience (CX) and business performance.

The necessity of aligning the TOM to the enterprise’s business strategy

For an enterprise to achieve operational excellence, its TOM must be seamlessly aligned with its overall business model and strategy. A misalignment between the two can lead to inefficiencies, suboptimal resource allocation, and a failure to deliver value to customers. The enterprise’s strategy defines its vision, objectives, and approach to gaining a competitive advantage, while TOM operationalizes this strategy through well-defined processes and structures.

For example, an e-commerce company expanding its international footprint must ensure that its TOM supports global supply chain management, local market customization, and regulatory compliance. Without a TOM that reflects these strategic needs, the organization risks delayed product delivery, higher operational costs, and a subpar customer experience in new markets. Recent research highlights that organizations updating their operating models in 2025 are better positioned to adapt to economic shifts and technological disruptions, such as AI-driven supply chains.

In many cases, an out-of-sync operating model manifests itself through stagnating growth, operational inefficiencies, and declining customer satisfaction. At this point, designing and implementing a new TOM becomes an imperative for organizational success. Precursory signs include rising customer complaints, slow service delivery, and difficulty adapting to new market conditions. Failing to address these early warning signs can jeopardize the enterprise’s competitiveness.

Techniques, tools, and methods for defining and optimizing a TOM

Modern TOM development relies heavily on data-driven methodologies. Rather than relying on perceived process inefficiencies or simulation-based models, businesses can now harness real-world operational data from systems such as Enterprise Resource Planning Systems (ERP), Warehouse Management Systems (WMS), Enterprise Performance Management Systems (EPM), Customer Relationship Management Systems (CRM), Service-Ticketing Systems, and Workflow Management Systems. These systems provide valuable event logs that track actual performance data across the organization, offering insights into bottlenecks, inefficiencies, and customer pain points.

Process Mining is one such technique that uses data from these event logs to create an accurate model of how processes function in practice. This enables businesses to identify deviations from standard processes, inefficiencies in operations, and areas that require optimization. For instance, a financial services company may use process mining to understand why loan applications are taking longer to process than expected, identifying issues in documentation workflows or approval processes.

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Advanced Analytics, Machine Learning, and Automated Learning Models can further augment this by identifying trends, predicting future bottlenecks, and suggesting process improvements. By combining Process Mining with Machine Learning, businesses can not only diagnose performance issues but also proactively mitigate them through Intelligent Process Automation. In 2025, AI Agents are increasingly orchestrating these processes, enabling more effective workflow reinvention and automation. This shift from reactive to proactive operational management is key to achieving Operational Excellence and improving customer satisfaction.

TOM and its relationship with customer experience

Customer experience (CX) is becoming the most critical differentiator for businesses across all industries. In this context, a well-designed TOM that prioritizes CX plays a transformative role. The TOM defines the processes, systems, and structures that affect every customer interaction, whether it’s how quickly an order is fulfilled or how effectively customer service inquiries are handled. By designing a TOM that focuses on delivering seamless and personalized experiences, enterprises can significantly enhance customer satisfaction and loyalty.

For instance, in the telecommunications sector, where customers expect uninterrupted service and instant resolution of issues, a TOM designed with customer-centricity ensures efficient service ticket resolution, minimal downtime, and personalized communication. Similarly, in the retail industry, a TOM that supports real-time inventory management and rapid order fulfillment ensures that customers receive products faster, resulting in higher satisfaction and repeat business.

At its core, TOM enables businesses to build operational capabilities that align with customer expectations. A TOM that integrates agile methodologies and advanced customer analytics allows businesses to respond swiftly to changes in customer behavior, offering personalized experiences that build trust and loyalty. Businesses using predictive analytics in their TOM report a 20% reduction in service issues and a 30% increase in customer loyalty.

When is it necessary to implement a new TOM?

A new TOM becomes necessary when the current operating model is no longer aligned with the business's strategic objectives, customer needs, or market conditions. Key indicators that signal the need for a new TOM include:

• Declining customer satisfaction scores, Net Promoter Scores (NPS), or other CX metrics.
• Increased operational inefficiencies, such as higher error rates or longer lead times.
• Difficulty scaling operations in response to growth or market expansion.
• Challenges in adopting new technologies or digital transformation initiatives.
• Unclear organizational structure leading to decision-making silos.
• Post-merger or acquisition integration issues.
  
  

The design and implementation of a new TOM should be viewed as a strategic business imperative during times of transformation. Whether the enterprise is undergoing digital transformation, expanding into new markets, or facing increased competition, a new TOM provides the operational foundation required to support these changes.

A retail company expanding into e-commerce may realize that its current operating model, focused on brick-and-mortar operations, is no longer adequate. To successfully pivot to online sales, the company would need to redesign its TOM to integrate online order management, digital marketing, and an optimized supply chain that can handle increased order volumes. Recent case studies, such as a wealth management firm's post-acquisition TOM implementation, show how this can create seamless client experiences in under three months.

TOM’s role in enhancing customer experience and driving engagement and loyalty

An optimized TOM can directly improve the customer experience by enhancing the organization’s ability to deliver personalized, efficient, and seamless services. Service delivery becomes more agile and responsive, allowing businesses to anticipate customer needs and exceed expectations. This, in turn, leads to increased engagement, loyalty, and ultimately, customer retention.

For example, Amazon’s TOM is built around operational excellence in logistics and customer service. Its fulfillment centers, advanced supply chain management, and real-time customer support systems allow Amazon to deliver products quickly and resolve issues almost instantly. This customer-first approach has been integral to Amazon’s ability to build trust, loyalty, and market dominance. Similarly, companies that excel at omnichannel service delivery, such as Starbucks or Nike, design TOMs that ensure consistent and personalized interactions across all touchpoints—whether in-store, online, or through mobile apps. By aligning operational processes to the customer journey, these companies drive engagement and create meaningful customer experiences that translate into long-term loyalty.

In 2025, AI-driven hyper-personalization within TOMs is amplifying this impact, with 86% of executives noting that AI agents make process automation more effective for CX.

Future trends in TOM for 2025 and beyond

The evolution of TOMs in 2025 and beyond will be characterized by greater reliance on artificial intelligence (AI), process automation, and predictive analytics. Businesses will increasingly leverage AI to automate repetitive tasks and improve decision-making. Robotic Process Automation (RPA) will play a pivotal role in streamlining routine tasks such as data entry, freeing up employees to focus on more value-added activities. Hyperautomation, combining AI with RPA, is a key trend, with 92% of companies planning increased investments in AI Automation.

Another emerging trend is the hyper-personalization of customer experiences, made possible by TOMs that integrate advanced Customer Data Analytics. Companies will use real-time data from multiple touchpoints—such as CRM systems, website interactions, and customer support logs—to continuously refine and optimize customer experiences.

Finally, sustainability will increasingly become a focus area for TOMs. With growing pressure for organizations to reduce their environmental footprint, TOMs will need to integrate green operations and supply chain optimization to minimize waste and emissions, while also enhancing brand reputation and customer trust. By 2025, sustainability is being treated as a full business-model transformation, requiring reexamination of processes across product design, operations, and governance.

Conclusion

A well-designed Target Operating Model (TOM) is essential for organizations seeking to align their operations with strategic objectives, improve performance, and deliver exceptional customer experiences. By leveraging real-time data from ERP, CRM, EPM, WMS and Workflow Systems, businesses can diagnose inefficiencies, design more agile processes, and drive operational excellence. A TOM aligned with customer experience goals ensures that companies can meet evolving customer expectations, build trust, and foster loyalty in an increasingly competitive landscape.

In 2025, the implementation of TOMs will continue to be driven by AI, process automation, and sustainability, enabling businesses to achieve greater operational efficiency and deliver personalized experiences at scale. By acting early to detect misalignments in their current OM and proactively designing new TOMs, enterprises can secure their position in the marketplace, ensuring long-term success and growth.

Documentary References

1. McKinsey & Company. (2025). A new operating model for a new world. McKinsey & Company.
2. (2025). 2025 AI Business Predictions. PwC.
3. (2025). Top Customer Experience Trends for 2025. IBM.
4. McKinsey & Company. (2024). True customer-centricity: An operating model for competitive advantage. McKinsey & Company.
5. (2024). Beyond the noise: Orchestrating AI-driven customer excellence. KPMG.
6. Harvard Business Review. (2025). Sustainability as a Business-Model Transformation. Harvard Business Review Press.