Ferranti: Strategising GenAI roadmap for an ERP Software Company

Need

Challenge

Defining priorities and opportunities for leveraging AI

In the midst of the current AI buzz, many organizations find themselves at a crossroads: they recognize AI’s potential to transform operations and products but struggle to pinpoint the most beneficial applications.

Ferranti, a leader in the Energy & Utility sector, found itself in exactly this position. Their flagship product, MECOMS 365, renowned for its global reach and flexibility, provides utilities worldwide with tailored solutions. Given the platform’s flexibility and global reach, Ferranti’s staff spend more than half of their time tailoring solutions for diverse client requirements and ongoing support requests.

Faced with this challenge, Ferranti approached Faktion with two main questions:

How can AI help with distributing knowledge across the organization?
What would an AI solution look like to ensure it is adopted and used by Ferranti’s employees?

With so many potential avenues for applying AI, Ferranti needed a clear way to prioritize use cases, understand the feasibility, and align efforts with organizational strategy. The risk of chasing AI hype without direction or measurable impact was too high. Therefore, defining a focused roadmap that addresses the most pressing business needs—particularly around knowledge distribution—became paramount.

The solution

Solution

To address this uncertainty and avoid ad-hoc experimentation, Ferranti partnered with Faktion. Instead of rushing into building AI applications immediately, we adopted a systematic, three-step plan to identify the most promising use cases. The goal was to ensure any AI initiative directly addresses a real business bottleneck, offers tangible value, and is fully aligned with Ferranti’s future vision for MECOMS and related services.

The resulting solution framework centred on:

Exploration & Inspiration: Identifying and prioritizing use cases where AI could deliver quick wins or long-term transformational value—especially in areas where consultants spend the most time searching for information.
Refinement & Planning: Establishing a high-level blueprint for implementing the most promising AI initiatives, ensuring technical feasibility, organizational buy-in, and measurable success criteria.
Validation & Roadmap Creation: Engaging functional and technical consultants, gathering end-user input, and producing a comprehensive roadmap for a Proof of Concept (PoC).

This structured approach ensured each AI concept was rooted in real-world business needs, giving Ferranti clarity on which projects to prioritize, how to plan them, and how to measure success over time.

Approach

Building on this overarching solution, Faktion led a series of workshops and user interviews aimed at discovering, refining, and validating the AI opportunities that matter most to Ferranti.

Workshop 1: Deep Dive and Inspiration

Lightning Talks: Key stakeholders from Ferranti, including end-users, technical leads, and product experts, shared their existing pain points, ongoing challenges, and ambitious goals. This created a transparent overview of Ferranti’s current landscape.
AI Trends & Case Studies: Faktion has introduced relevant AI solutions already succeeding in similar domains. Examples and demonstrations helped spark ideas and show the art of the possible.
Brainstorming Sessions: Attendees split into groups to explore potential AI applications—everything from automated document processing to predictive analysis and advanced search functionalities.
Prioritization Exercise: Through group discussions and feasibility scoring, participants collectively homed in on the top three AI initiatives deemed most actionable and valuable.

Workshop 2: Concept Development and Planning

Recap & Refinement: Faktion revisited the top three initiatives, integrating feedback from Workshop 1 to confirm alignment with Ferranti’s strategic objectives.
Solution Detailing: Cross-functional groups dove deeper, defining the required data, performance metrics, and user acceptance criteria for each initiative.
High-Level Implementation Plan: Teams outlined a phased approach, with responsibility assignments, targeted timelines, and early considerations for PoC development. This ensured each AI concept had a clear path forward and ownership.

User Testing & Validation

One-on-One Interviews: Faktion engaged functional and technical consultants to gather in-depth insights on the practical utility of the proposed solutions. These interviews examined day-to-day workflows and surface-level pain points that AI could solve.
Surveys for Quantitative Feedback: A broader survey confirmed the appetite for AI-driven tools and measured perceived value, feasibility, and potential challenges.
Comprehensive Roadmap: Collating all the inputs led to a robust plan for a PoC of an AI-driven Document Q&A system, fully tailored to Ferranti’s complex environment. This roadmap details user needs, data workflows, and performance objectives for upcoming development phases.

Outcome

Clear Roadmap for Deployment

By collaborating with Faktion, Ferranti successfully navigated the AI hype and emerged with a clear, actionable roadmap. Key results include:

Focused Prioritisation: Ferranti no longer has to guess which AI initiatives to pursue first. Through systematic evaluation, they identified the AI-driven Document Q&A system as a critical solution to enhance consultants’ workflow, knowledge management and and support processes.
De-risking the investment: The roadmap includes a structured plan to move from a pilot phase (PoC) to scalable deployment, reducing risks by confirming technology requirements, data availability, and user readiness.
Organizational Readiness: Through workshops and stakeholder engagement, Ferranti’s teams are now more informed and motivated about AI’s potential. This is typically the biggest hurdle in achieving success with technology projects. Hence, having the internal team’s buy-in increases adoption likelihood and sets the stage for a smooth implementation.

Looking ahead, the next phase involves building the prototype of the Document Q&A system, testing it with real-world data, and refining it based on performance metrics and user feedback. From there, Ferranti plans to operationalize and scale the solution, ensuring it seamlessly integrates into existing infrastructure. In short, Ferranti has laid a solid foundation for AI-led innovation, poised to unlock new levels of performance and value for both their teams and clients across the Energy & Utility sector.