Rickard Sörlin

• Opportunity, vision & strategy: applied New Product Development (NPD) thinking and a Product Innovation Charter (PIC) to frame market need, technical opportunity and boundaries — then shaped a product vision and strategy for Talking SCADA, positioned so its value is clear to customers and the business.
• Concept generation & evaluation: planned lead-user involvement and cross-functional collaboration, with technical and commercial screening criteria for Go/No-Go decisions.
• Product definition & business model: connected vision, user needs, functional and quality scope, UX and service model through a Business Model Canvas — linking product definition to how the offer creates and captures value.
• Development planning & PRD: produced a product protocol and Product Requirements Document (PRD) covering target users, the whole offer, scenarios, MVP scope, success measures and acceptance criteria.
• Commercialisation, launch & lifecycle: planned positioning, SaaS packaging and partner channels with pilot use tests before wider introduction, then a staged rollout with performance monitoring and customer-feedback loops across the product life cycle.

• System requirements & traceability: produced a System Requirements Document (SRD) linking interview, observation and prototype findings to goals and requirement IDs — domain, functional, data, quality, integration and policy requirements.
• System & workflow specification: used a context diagram, conceptual data model, interface mockup and task description to define system boundaries and the investigation workflow.
• Value-driven prioritisation: ranked 22 requirements with a Software Value Map, and applied Cost-Value-Risk to critical requirements, considering dependencies and uncertainty.
• Assets & sourcing: analysed reuse of technical assets and domain knowledge with Make/Buy/Share and commodity, qualifier and differentiator classifications.

• Developed a Talking SCADA business plan connecting customer segments, value proposition and strategic direction, positioned around cross-system diagnostics and understandable operator explanations.
• Proposed tiered SaaS packaging, revenue logic, partner channels and a go-to-market path supported by integration, onboarding and ongoing service.
• Treated adoption, willingness to pay and financial viability as assumptions for further validation.

• Studied leadership styles in technology- and knowledge-intensive organisations, then interviewed a practising leader and analysed their style in real context — in my case the person leading and accountable for a data centre.
• Connected the analysis to cross-functional direction: how a leader aligns engineering, operations and business stakeholders around shared priorities, communication and trade-offs.
• Built a personal leadership development plan with structured self-reflection — mapping my strengths and growth areas against the leadership behaviours that fit technical environments.

• Applied agile and Scrum practices to iterative concept refinement — short cycles, scope refined through feedback, and MVP planning to test the riskiest assumptions first.
• Used Talking SCADA to plan a limited first scope and decide what to learn next — sequencing work so evidence could change priorities and the development plan.
• Connected development planning with project management and product-development governance — tracking progress, dependencies and delivery risk.

Talking SCADA — concept origin in Innovation in Practice

• Framed the original Talking SCADA concept around hidden energy problems in interacting building systems, connecting a familiar user problem with energy efficiency and societal value.
• Used PESTEL, VRIO and the Four Ps of innovation to examine external drivers, organisational capabilities and the proposed service innovation.
• Proposed a Design Thinking approach, with cross-functional collaboration, leadership support and psychological safety as conditions for implementation.

• Studied transformers, sentiment classification and domain adaptation, with PyTorch implementation and PEFT/LoRA.
• Strengthened my understanding of language-model capabilities, limitations and adaptation to domain-specific tasks.
• For Talking SCADA, this informs decisions about natural-language interaction and explanations grounded in building context.

• Studied sensor fusion, 3D perception, prediction, planning and reinforcement learning.
• Examined how uncertainty, data quality and sensor constraints affect decisions across an AI system.
• This informs how I assess reliability and uncertainty in Talking SCADA's proposed decision support.

• Studied predictive analytics and machine learning for decision support.
• Connected prediction to the decision it is intended to support.
• For Talking SCADA, this provides a foundation for assessing how predictions could help users investigate energy deviations.

• Studied deep learning and computer vision for industrial imaging.
• Broadened the technical foundation I bring to AI product decisions, including the fit between a method, the available data and the user problem.