As product complexity accelerates, value chains require data-centric product development to address rising market diversity, resource constraints and integrated compliance requirements. In his fourth entry to the Industry Reflections series, Lio Grealou sticks with the theme of new product development (NPD), this time asking how established OEMs can reinvent their product development practice from within to foster faster design to line times.
The process of taking a product or service from conception to market is typically based on a series of milestones and gateways. Often referred to as new product introduction (NPI), such framework covers the extended product lifecycle, from ideation and concept definition, through development and testing to prototyping and commercialization before ending with the product being launched to the market.
New product development (NPD) expands the scope of NPI to include upfront product line or service platform strategy, business analysis, marketing, commercialization, maintenance and aftersales operations.
OEMs build NPI-NPD frameworks to organize how they bring ideas to market, funneling concepts and plans into lean and scalable delivery operations. This covers concurrent engineering, supplier integration and regulatory compliance, plus organizational focuses such as ongoing learning, mitigation of risks and issues, leveraging design for excellence and the embrace of digital and rapid prototyping.
Established OEMs mature their NPD process over years, learning from feasibility, prototyping and pilot builds, as well as operational efficiency with economies of scale and scope. NPD must remain a facilitating process that helps teams get products to market, rather than a bureaucratic process that stands in the way. It is a process of continuous discovery and reinvention, especially due to constant introduction of disruptive business models and technologies, as well as the rise of global sustainability imperatives.
In this article, I elaborate on how established OEMs can continue to innovate and reinvent their product development practice from the inside out. Particular focus will be on how they can co-innovate across business networks, become more agile and compete against new entrants.
Effective product development requires a joined-up combination of creativity, benchmarking, concurrent engineering, consensus building, design and process verification, pilot product validation, and continuous improvement. As a product matures, it must comply to market-based standards and industry legislation. Simultaneously, from a quality assurance perspective, it needs to be compliant with the minimum level of safety, effectiveness, and efficiency, supported by approved certification warranties from suppliers. This implies a level of agility is required to experiment and learn about new technologies and processes, combined with a level of rigor and data traceability to implement consistent and sustainable operations and changes. The required balance evolves as the product matures into manufacturing and sourcing requirements.
Mind-set shift towards rapid learning cycles and faster product development iterations
In a 2018 article by McKinsey, five fundamental “trademarks” were outlined for organizations to successfully progress towards agility:
- North Star embodied across the organization
- Network of empowered teams
- Rapid decision and learning cycles
- Dynamic people model that ignites passion
- Next generation enabling technology
With each of the above characteristics, established OEMs need to assess their ability to change and possibly deviate from their standard operating procedures, methods, and tools. Without embedding continuous improvement, enterprise processes and tools can over time hinder co-innovation, creativity, learning and the speed of delivery industrialization. Effective learning implies rapid decision-making and failing fast. Change can require a mindset shift for OEMs, especially as they develop execution frameworks and associated governance based on how they operated in the past with previous delivery models that may no longer be optimum when implementing new business models.
Developing products through sprint-based experimentation and a minimum viable product (MVP) approach might contradict, or perhaps conflict, with most legacy NPD frameworks which are waterfall-based with rigid stage-gate program deliverables. In the same article mentioned above, McKinsey noted a series of mindset shifts needed when helping organizations transform toward rapid decision-making and learning cycles, including new approaches to managing risk and uncertainty:
From:
"To deliver the right outcome, the most senior and experienced individuals must define where we’re going, the detailed plans needed to get there, and how to minimize risk along the way."
To:
"We live in a constantly evolving environment and cannot know exactly what the future holds. The best way to minimize risk and succeed is to embrace uncertainty and be the quickest and most productive in trying new things."
Data traceability and enterprise collaboration play a critical role in supporting such a mindset shift, often associated with digital transformation and organizational change.
Fostering effective data stewardship towards competitive advantage and sustainability
In the current time, agility links to both competitive advantage and sustainability:
- The ability to do things differently, more effectively and/or efficiently, unlocking new value, such as new business models, etc
- The ability to holistically embed new sustainability requirements, and associated experimentation to unlock new solutions
- The ability to effectively implement change, do things differently, and ultimately outperform competitors when accelerating time to market and / or wining new market shares
In seeking organizational agility, mature OEMs can ring-fence pilot projects to experiment ‘outside the box’ they currently operate in, thereby removing legacy constraints and contextual barriers to change. In practical terms, this can translate into a combination of two concurrent strategies in:
- Optimizing what already exists, becoming more agile without re-inventing the wheel
- Introducing skunk projects or shadowed operations to experiment on removing existing barriers, thus opening the door to implementing new product-service ideas and operating models
This implies building new NPD variations or enhancing the existing framework with agile-based delivery models, governance, and tactical operational tools to get digital fast without compromising data continuity requirements. Furthermore, though stage-gate events might not disappear, they do not have to remain the bottleneck for decision-making culmination. Waterfall-driven gateway events often drive the wrong behaviors and outcomes with teams that ‘use the process’ as a collaborative tool, rather than proactively connecting with other functions and teams to effectively and timely solve problems.
Pushing boundaries: new business models, from digitalization, sustainability and servitization
Such approaches to experimentation can be described as more entrepreneurial - perhaps initially riskier due to the mindset shift - but certainly more rewarding, requiring role-based leadership and proactive engagement across all stakeholders. These are typical patterns observed in start-ups as they strive to make things happen with limited operating barriers and avoiding bureaucratic processes and tools.
For established OEMs, a change in existing practices will certainly imply a change of enterprise architecture and master data structure. For example, complex engineering and manufacturing operations rely on global sourcing networks and agile supply chains vulnerable to external market conditions ranging from inter-industry rivalry to implications from the latest pandemic. Accordingly, new operating models could include the need for collaboration tools to track deliverables, focusing on supplier-customer performance management rather than resource supervision.
In such context, Hallstedt et al. (2020) highlighted transformational implications to the manufacturing industry from digitalization, sustainability, servitization and their interconnectivity—which directly affects product-service development practices. Such context is illustrated with the following figure, highlighting the underlying convergence of information technology (IT) and operating technology (OT) to ensure reliable data exchange.
Finally, these business trends translate into system-centric requirements for data continuity, enterprise integration, change and knowledge management across functions and teams.
What are your thoughts?
References
Hallstedt SI., Isaksson O, Öhrwall Rönnbäck A (2020); The Need for New Product Development Capabilities from Digitalization, Sustainability, and Servitization Trends; Sustainability, 12(23), 10222.
Aghina W, Ahlback K, De Smet A, Lackey G, Lurie M, Murarka M, Handscomb C (2018); The five trademarks of agile organizations; McKinsey.