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How to Reset Operating Models to Scale Digital Products Beyond POCs

How to Reset Operating Models to Scale Digital Products Beyond POCs

How to Reset Operating Models to Scale Digital Products Beyond POCs

As part of Solutions Review’s Contributed Content Seriesa collection of contributed articles written by our enterprise tech thought leader communityMichael Duffy, the Vice President of Intelligent Operations, Resources, and Energy Transition at Capgemini Americas, goes in-depth into how companies can reset operating models to scale digital products beyond proof of concept.

In the modern economy, digital transformation is not a market differentiator—it’s a business staple. This is especially true for energy organizations contending with supply chain challenges, increased costs, and disparate legacy equipment. However, after years of developing agendas, many energy enterprises struggle to scale their digital product and service offerings, stalling at the proof of concept (POC) or minimal viable product (MVP) stage and never seeing a return on these investments.

With the benefit of hindsight and a graveyard of failed POCs and MVPs, now is the time for energy companies to reconsider their operating models to scale the next generation of solutions that consumers are expecting. Of course, redeveloping decades-long, cross-organizational strategies after numerous setbacks can be daunting and disheartening for any enterprise. That’s why leaders should not try to tackle too much at once and seek quick wins, or they’ll continue to take one step forward and two steps back. 

So, how can energy leaders take a fresh approach to an age-old transformational challenge and develop an operating model that will scale their digital operations and products? 

Key Components  

First, it’s essential to understand the key elements of an effective operating model for digital products and services. In the energy industry, operating models should combine innovative technology integration, streamlined processes, and a robust data infrastructure. Embracing cutting-edge technologies such as IoT (Internet of Things), AI (Artificial Intelligence), and advanced analytics is crucial for optimizing operations and enhancing efficiency. These technologies enable real-time monitoring and control of energy assets, predictive maintenance, and data-driven decision-making.

Additionally, incorporating agile methodologies into the operating model allows flexibility and adaptability in responding to rapidly evolving market dynamics and customer demands. Collaborative partnerships with technology experts and startups can foster a culture of innovation within the industry, driving continuous improvement and the development of scalable digital solutions.

Furthermore, a resilient cybersecurity framework is imperative to safeguard critical infrastructure and sensitive data. By rethinking operating models to incorporate these key elements, the energy industry can not only navigate the digital transformation successfully but also scale digital products to meet the market’s evolving needs.  

Organizational and Architectural Design Tactics 

Energy companies should be prepared for the massive cross-functional challenge of developing new operating models and recognize the necessity to pair a “traditional” organizational change strategy with a cohesive architectural design strategy. Developing a new operating model to scale your digital offerings isn’t just a business or tech team responsibility; it should be a shared goal with a blended strategy. 

From an organizational change perspective, companies should follow the below tactics: 

  • Move away from monolithic thinking to a service-oriented mindset, emphasizing the benefits of modularity, agility, and scalability. 
  • Form cross-functional teams aligned with microservices to foster collaboration, autonomy, and accountability and empower teams to own and operate their microservices independently, promoting faster development cycles and efficient problem-solving. 
  • Foster a DevOps culture to drive collaboration and streamline development and operations. 
  • Establish robust monitoring and support systems to detect and resolve issues promptly. 

From an architectural design perspective, leaders should consider the following complementary tactics: 

  • Invest time and effort in defining appropriate service boundaries. 
  • Embrace data isolation by assigning data ownership to individual microservices. 
  • Design for failure by implementing resilience patterns. 
  • Utilize automation for deploying, scaling, and monitoring microservices, implementing robust CI/CD pipelines, automated testing, and infrastructure-as-code practices. 

Like many other companies across industrial sectors, energy organizations have spent too much time and money on failed POCs and MVPs. They must reevaluate their digital products and services, introducing a new and improved operating model to get their digital program off the ground. Leaders may need to go back to the drawing board to do so and adopt new approaches. Still, it will be well worth the effort as digital products and services are only increasingly gaining importance in today’s energy market.

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