Innovation Design Leadership

I played a pivotal role in navigating a complex challenge, spearheading the development and launch of our client's first intelligent product. As the Director of Experience Design, my involvement extended to the initial two service design phases and the subsequent post-launch phase. The Aspirational Discovery phase, which included the Analyze, Create, and Accelerate stages, laid the groundwork for the Product Discovery phase, which involved the Learn, Ideate, and Mobilize stages. Leading the charge in both the ambiguous Aspirational Discovery and subsequent Product Discovery, I adeptly applied design thinking methodologies and problem-solving skills. To address the inherent uncertainties of innovation, I orchestrated collaborative sessions, translating nebulous concepts into tangible visions to unite the team behind a shared vision.

The final phase focused on Post-Launch Feedback Enhancement and user adoption support.

As Design Lead, I designed and implemented a tailored process for each step, providing the team with efficient tools for user-centric problem-solving.

During this phase, I worked closely with the client to explore potential future scenarios using Slalom's Aspirational Discovery framework. This strategic approach provided a broad overview from a 10,000-foot perspective, emphasizing alignment, distillation, and activation.

I guided the client's team in identifying and addressing crucial missing components essential to overcoming their challenges with product innovation and strategic alignment. We focused on defining the business case, creating and validating preliminary concepts, and minimizing risks to lay a strong groundwork before moving on to the Product Discovery phase.

Employing a startup-like approach, I organized design-thinking workshops, conducted hands-on research, and facilitated co-creation sessions to develop a forward-thinking vision for the client.

During the initial two weeks of the Discovery phase, my main focus was understanding the problem and analyzing the data acquired from stakeholders and user interviews. I conducted several co-creation workshops involving SMEs and business and technical teams. These workshops were instrumental in identifying challenges related to innovation and business operations while providing clarity and alignment regarding business goals and expectations.

Innovation Challenges

The product has no known path to build, pilot, scale and operate

There needs to be a measurable plan for the product to return value and revenue to the business

Technical vision needs to be adequately explored, defined, and validated

Audience fit has yet to be defined or validated

Platform selection has yet to be validated against the problem definition

Business Challenges

Manual Anomaly Detection

High Knowledge Retention Risk

Opportunities obscured by data volume

Not all stakeholders can monitor the data

Missing foundation component for optimization

Design Thinking & Innovation

To be successful, an innovation process must deliver three things: superior solutions, lower risks and costs of change, and employee buy-in. It’s widely accepted that solutions are much better when they incorporate user-driven criteria. Bringing diverse voices into the process is also known to improve solutions. An innovation won’t succeed unless a company’s employees get behind it. The surest route to winning their support is to involve them in the process of generating ideas.

How Design Thinking can help? Design Thinking is a methodology that imbues the full spectrum of innovation activities with a human-centred design ethos. It usually describes processes, methods, and tools for creating human-centred products, services, solutions, and experiences. Immersion in the customer experience produces data, which is transformed into insights, which help teams agree on design criteria they use to brainstorm solutions. The structure of design thinking framework creates a natural flow from research to rollout.

By supplying a structure to the innovation process, design thinking helps innovators collaborate and agree on what is essential to the outcome at every phase.

From Abstract Idea to POC. A Collaborative Approach to Designing AI-Powered Application.

My main goal at this step was to design a concept for a practical solution. I collaborated with the Data Science team to devise a strategy for integrating the ML model into an innovative application. To achieve this, I focused on understanding the model’s feasibility and limitations, which informed my decisions regarding user experience and application design. I facilitated collaborative sessions with the team to address important questions such as:

What will this look like within the product?
What are the limitations/challenges? How can we mitigate them?
How do we measure success?
What are priorities? Is any challenge a showstopper?

The prototype conceptualization was based on user research, business requirements, ideas from co-creating workshops and data snippets from the Data Science team. I created visual interfaces, applying UX principles to ensure a smooth user journey. My design process was iterative, allowing continuous refinement based on team feedback, user testing and changing technical requirements.

User Research & Agile

Based on McKinsey’s “Value of Design” survey of global companies, only half of companies conduct user research before creating their initial design ideas or specifications. Another survey found that 96% of innovations fail in the market due to a lack of adoption.

User research is crucial for uncovering barriers to adoption. We can secure business buy-in and user adoption by constantly integrating user feedback and conducting usability tests throughout delivery. As a design leader, I help business and product teams understand the importance of user-centricity and how to incorporate user insights from the initial idea until long after the final launch.

The most successful outcomes stem from continually merging user research—both quantitative (analysis) and qualitative (interviews)—with product development cycles. Research offers value to the team through learning rather than just tangible artifacts. This learning fuels continuous iteration to reduce development risks by consistently listening, testing, and iterating with end-users.

Many product design teams encounter the challenge of integrating user research into the iterative process of Agile Delivery. Agile development typically focuses on constructing features and dividing work into bite-sized pieces. User research isn’t always tied to a single feature, which makes it difficult to fit it perfectly into two—or three-week increments.

Some common challenges I’ve observed with Agile Delivery include:

Research spanning multiple sprints, where the entire study cannot be finished within a single sprint, leaving the backlog item open across several sprints.

Research findings being disregarded after completion, with user feedback not being funnelled back into the backlog for action.

Lack of tangible artifacts from research makes it challenging for stakeholders and teams to understand how to use the insights obtained, as they are accustomed to receiving completed designs or production-ready code.

Strategies that I found efficient in resolving this issue are:

Represent research efforts in an Agile backlog to enable teams to focus on continuously learning about users throughout the project.

Respond to change over following a plan. Teams should focus on continuous discovery — meaning continuous learning — throughout their projects. Research should be the driving force behind this continuous discovery and should be ongoing throughout the entirety of a project. Teams can achieve greater success in crafting user-centric products by conducting some research every sprint, ensuring constant learning and refinement of project objectives.

Foster collaboration among UX specialists, designers, developers, and product owners to seamlessly integrate user research into Agile workflows.

Utilize adaptable research methods tailored to fit within Agile timeframes. Optimizing the user research process using AI UX tools enhances the efficiency of design teams, enabling designers to streamline data consolidation and user research analysis.

Adopt an iterative approach where user research guides design iterations within short development cycles, facilitating continuous feedback loops.

Prioritize research efforts based on sprint goals and user needs, focusing on areas with the most significant impact on product success.

Following the successful product launch, I continued to champion innovation and improvement, underscoring the importance of maintaining leadership in innovation as an ongoing commitment. I arranged and conducted sessions to collect quantitative and qualitative feedback from users post-pilot launch. I then relayed this data to business and technical leaders, helping key decision makers to refine their processes towards more compelling and satisfactory outcomes.

Stakeholder & User Interviews
Conducted interviews with stakeholders and users to gather qualitative feedback on their experiences.

Usability Testing & System Evaluation
Performed usability testing and evaluated the system’s performance to identify usability issues and technical glitches.

Feedback & Gap Analysis
Analyzed feedback from users and stakeholders to identify improvement areas and bridge gaps between expectations and actual outcomes.

Feedback Prioritization
Evaluated and prioritized feedback from various sources based on factors such as impact, feasibility, and alignment with strategic objectives.

Future State Map
Developed a future state map to visualize the desired outcome and identify areas for improvement, aligning with the long-term vision and goals.

Product Strategy Update
Updated the product strategy based on insights gathered from post-launch feedback, ensuring alignment with market needs and organizational objectives.

Continuous Product Improvement Strategy
Established a systematic approach for ongoing product enhancement, incorporating user feedback and insights to drive iterative development.

Enhancement of Features & Functionalities
Prioritized updates to features and functionalities based on user feedback, aiming to enhance user experience and address evolving needs.

Streamlining Tech Integration
Steered the organization through a digital transformation journey, ensuring the smooth integration of new technologies across different employee groups.