Digital Product Management

Given the complexity of digital solutions, it is crucial to have a product portfolio team that includes a commercial executive team, business process owners, product owners, engineering, and technology leaders. Effective governance is essential to manage the portfolio from a value-creation perspective and to track delivery against established milestones and metrics. Additionally, the team’s role is to address critical issues and risks affecting the portfolio and support product teams in overcoming barriers such as investment challenges, platform limitations, customer feedback, and staffing. Ultimately, the digital council unites key stakeholders from both commercial and product development functions to ensure a consistent customer experience and the successful execution of the product portfolio vision and roadmap.

Throughout the product development journey, teams must maintain a balanced focus on vision, viability, and value. The product portfolio vision is established early in the process. It provides a clear definition of the minimum viable product (MVP), for bringing products to market quickly and allows for real world customer use and feedback. This vision serves as a guiding beacon, but goals and objectives should be adjusted as new insights emerge through the development journey. Viability should be assessed early in the lifecycle to identify gaps in maturity, capability limitations, and infrastructure needs to ensure scalability. A feasibility assessment completed early as part of the portfolio addition process provides the required investment and scope for the MVP. A continuous focus on value, viewed through the customer’s lens, is essential. If the value proposition shifts (due to changing customer needs, competitor actions, or other factors) it may be necessary to reprioritize the portfolio or fail fast within the development cycle, allowing select initiatives to be moved below the line in the portfolio.

Digitizing introduces new ways to use existing products or a new product category unto itself. It is critical to involve customers early in the digital visioning process to ensure the product meets real needs. Once the value “stories” are captured, customer journey maps should capture the end-to-end product experience. Customer focus groups can aid in using techniques like design thinking to ensure continuity in both customer value and overall experience. Simply digitizing an existing product with minor digital enhancements often falls short in terms of customer value, so innovative digital solutions and approaches are necessary to address perceived customer value.

Vision realization and effective execution are achieved through playbooks, prototyping methods, and disciplined digital portfolio management, all orchestrated by a diverse product management talent pool. By embedding repeatable methods and playbooks across initiatives, collaboration among business, technology, and engineering teams fosters measurable practices. Digital portfolio leadership can effectively communicate and manage these methods while tracking success throughout the product development lifecycle. Successful companies adopt a “fail fast” mentality, quickly adjusting or pivoting products based on early feedback or lack of traction. During digital product discovery, teams should regularly reassess the portfolio to determine if certain AI features or digital assets should be deprioritized or iterated upon. Utilizing an agile framework supports rapid adjustments to the product portfolio based on customer feedback and evolving solution needs. 

A digital PMO drives the execution of the product portfolio. Depending on the product development project's complexity and stage, the PMO adopts either agile or hybrid approaches to ensure milestones are met and deliverables, such as product compliance and design artifacts, are completed to meet regulatory requirements before launch. Serving as the central hub for communications, stakeholder alignment, change management, and value realization, the PMO provides end-to-end oversight in collaboration with commercial, engineering, marketing, compliance, customer support and technology teams through product launch.

An AI Center of Excellence (CoE) collaborates closely with the PMO to align AI use cases and digital opportunities with standardized AI technologies and cleansed data sets, executing projects throughout the development lifecycle. The product-centric AI CoE identifies potential business challenges, fosters a unified AI vision, implements a standardized framework for AI development, and recruits top talent in data science and AI.

To effectively bring digital products to market on a cloud infrastructure, several platform capabilities are essential for managing growth in data and user demand. A critical first step is establishing a single source of cleansed information by integrating machine-level and persona-level data sets at the product level. Developing API capabilities is also crucial for seamless integration with existing systems, providing the flexibility needed to scale the digital product with future updates. As the data foundation matures, data scientists can gain valuable insights into customer behavior, optimize feature sets, enhance personalization, and develop predictive analytics. With robust data science solutions in place, the platform can evolve further, incorporating advanced digital solutions such as machine learning, neural networks, deep learning, and generative AI.

Compliance requirements and controls must be integrated into every stage of the digital product development lifecycle. It is essential to address regulatory and compliance validation, along with pre-launch checklists, early on, particularly in critical areas such as healthcare, autonomous systems, privacy (GDPR, HIPAA, etc.), and security. Additionally, if AI is a component of the digital product, transparency about the algorithms should be a key part of the launch strategy to foster trust with customers.

Early adopter customers, particularly those involved in initial focus groups, can play a crucial role in crafting a clear and compelling value proposition that sets the product apart from competitors and resonates with target audiences. Marketing materials should include educational content that explains the digital features, especially for customers who may be unfamiliar with how AI enhances their experience. An omnichannel strategy can encompass digital marketing, webinars, and product demos, enabling opinion leaders to build momentum and raise awareness ahead of the launch. Additionally, training both internal teams and customers on effectively using AI features will facilitate smooth onboarding, supported by comprehensive customer care. Finally, implementing ongoing digital monitoring and support establishes a post-launch team to track performance metrics, gather customer feedback, and address any issues. Utilizing machine learning models to enhance AI performance over time will ensure continuous improvements based on real-time data.