How might we use ideas and opportunities as the currency of innovation to create value for a business through data, technology and platforms?

THE PRIMARY QUESTION—

OVERVIEW—

In an enterprise, the workforce represents creative capital. Therefore, you need an environment that allows ideas to grow—hence, incubation. Generating and utilizing ideas and recognizing opportunities are fundamental to driving innovation. These ideas and opportunities are the "currency," valuable resources for creating new, beneficial solutions. The goal is to enhance the business by improving processes, products, or services, leveraging data, technology, or specific platforms.

OUTCOMES—

Achieved a 100% increase in the number of projects initiated through the establishment of an incubation environment.

Out of 86,000 employees, 400 (0.46%) were engaged in AI-Innovation through structured programs within 12 months.

Increased the number of innovative solutions implemented across business units by 4 within 18 months

Improved efficiency in identified business processes, products, and services.

Doubled operational effectiveness by laying groundwork for innovation team's ideas and experiments.

How to streamline the progression from idea exploration to impact, while also ensuring a strict governance model to enable accountability and product stewardship. This is crucial as many innovation teams struggle to transition a multitude of ideas into experimentation, accumulate evidence for funding, and satisfy business stakeholders with idea maturity. This includes enabling rapid testing and delivering solutions at scale.

THE CHALLENGE—

The discussion began by exploring what the governance model would look like and what services or engagements could be offered. A 4-prong approach was developed, starting with opportunity governance, which represents the initial stages of the innovation funnel. This involves engaging with the business, running ideation workshops for those less familiar with AI, and conducting both internal and external idea scouting. During ideation workshops, some initial skepticism about AI was observed. These sessions aim to address such concerns and demonstrate the potential benefits of AI, helping teams become more receptive to its possibilities and maturity.

Figure 1.1
Innovation Governance Framework

The journey of establishing innovation and AI practices for multiple clients started two years ago. With no existing innovation or AI teams, collaboration with senior stakeholders was the beginning of building these capabilities. Leads for AI, data science, and engineering were hired, and responsibilities were divided between engineering labs and data science domains. Recognizing the challenges innovation teams face in advancing numerous ideas, a governance model with an AI governing board was implemented to ensure proper oversight and alignment. The focus was on viewing innovation through a product lens, prioritizing business needs, customer experiences, and end-user requirements. This approach aimed to streamline the innovation process and address potential legal and technological concerns effectively.

Opportunity, Product, Design, and Delivery stages guide the journey from idea inception to impactful AI solutions. Opportunity facilitates rapid idea testing with GenAI for evidence. Product structures evidence into roadmaps and documentation. Design focuses on user stories and epics in workshops. Delivery integrates AI for complex tasks. Together, they create a structured path from exploration to practical AI deployment.

STAGES & ENGAGEMENT 
ACTIVITIES—

Figure 1.2
Innovation Funnel

All this happens with technology access at each stage. Users experiment and test their ideas, conducting research in real time. The Stage-Gate Process guides new product creation from small experiments, giving idea owners immediate tools at the start. This boosts engagement, visibility, and socializes the innovation team's efforts, attracting more idea owners to participate in experiments, research, and design sprints.

STAGE-GATE IDEAS FUNNEL—

Figure 1.3
AI Design Sprints

A 5-day design sprint tailored for AI involves rapid problem understanding, ideation focused on AI patterns, and prototyping solutions. Beginning with problem mapping and expert insights, teams sketch AI-driven solutions on day two, selecting and storyboarding ideas on day three. Prototyping occurs on day four, utilizing AI frameworks, followed by user testing and feedback collection on day five. Emphasizing pattern identification and ethical considerations, the sprint culminates in a validated prototype, guiding next steps in AI solution development.

DESIGN SPRINTS—

Design governance is often overlooked in the innovation processes. Design sprints, are time-bound initiatives where stakeholders and designers work together to create no-code prototypes. These prototypes, created with tools like Figma, Sketch, or Abobe, provide a high-fidelity representation of the product experience from the end-user perspective.

Teams have hands-on experience with off-the-shelf technology and can develop a clickable prototype aimed at a more refined and complete set of requirements. These prototypes can be turned into videos with voiceovers explaining the application and how it fits into daily workflows. This approach helps in securing funding and showcasing the product internally.

Design is a choice, and for many, it’s an optional element. You can choose to rationalize decision-making with design metrics and what design offers, or you can opt out and still achieve similar outcomes. It’s not mandatory. In practice, design has been highly effective for several clients. However, it’s not essential for success. If you're trying to rationalize decision-making in a complex environment involving user needs and emerging technology, design can be a significant factor.

The outcome was increased engagement and visibility, with more idea owners participating in experiments, research, and design sprints. Technology access and the Stage-Gate Process enabled real-time testing and new product creation from small experiments, enhancing innovation efforts.

WHAT WAS ACHIEVED—

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