Nidec Drives is a global leader in industrial motor control and drive technologies. Following the leadership awareness session that gave its senior team a shared understanding of AI, Nidec asked us to take the next step: find out, across the whole business, where AI could add value, and decide where to begin.
This is the discovery and prioritisation phase of the Converge Methodology, run in full.
The Challenge
The leadership session had moved the conversation from “should we use AI?” to “where will it create the most value, and what is the right approach for each opportunity?”. Answering that across a business of Nidec’s breadth needed more than a leadership view. It needed the people who do the work in every function to say where the pain is, what AI might do about it, and how ready the business actually is to do it.
It also needed an output that could enter Nidec’s own technology-investment process without rework, so that discovery produced decisions rather than another document.
Our Approach
We ran the divergent-convergent method across five business areas: R&D, manufacturing, procurement and supply chain, sales and service, and marketing, with product management and IT represented within each.
Five divergent workshops, one per function, surfaced every idea for where AI might help, without filtering for feasibility. Each was captured against the pain or opportunity, how the work is done today, the AI capability it would call on, and who would benefit. Ideas ranged from embedding AI inside the drives themselves, through engineering tooling such as AI-assisted coding and design, to the everyday productivity and knowledge work common to every department.
Five convergent workshops revisited each function’s output. Ahead of each, we clustered the ideas and pre-scored every cluster on the ten convergence elements, deliberately as a straw man for the room to challenge and force-rank. The scores that emerged were the business’s own, calibrated in the room.
Across the sessions, the same opportunities kept recurring in different functions: the same request for an assistant to draft and summarise, the same need to search scattered knowledge, the same appetite to forecast demand or monitor the market. Those became the cross-business themes, shared with every group.
What We Delivered
Ideas sharing a capability were consolidated into single, submittable use cases: eleven cross-business themes and sixteen function-specific candidates, each written in the format of Nidec’s own assessment process with problem, opportunity, what it consolidates, the scorecard, the adoption pathway, its position on the Opportunity Pyramid, and candidate vendors from a landscape of over a hundred evaluated across twelve functions.
The roadmap grouped them by readiness: ready now, nearly ready, strategic, and research, with the data foundations running underneath all four. A recommended first quarter followed directly from it. The complete working record, every one of the 250 ideas with its capture, cluster and scoring, was delivered as a workbook so that any decision could be traced back to the room it came from.
What We Found
Three findings shaped the recommendations, and they have held in every programme since.
Data, not technology, is the constraint. The tools for most opportunities already exist. What decides whether an opportunity can be delivered, and how soon, is whether the data it depends on exists in a usable form. Only around a third of the ideas had data ready today; the rest needed a research or data-foundation step first.
Appetite and readiness pull in opposite directions. The themes that attracted the most ideas were frequently the least ready. So the roadmap sequences by readiness rather than enthusiasm, and the master-data and knowledge foundations start early because so much depends on them.
Access was the biggest blocker, and the cheapest to fix. The restriction on AI tools was the loudest frustration in every workshop, and it stood between the business and its fastest, highest-value opportunities. The concern behind it was legitimate; the answer is governed, sanctioned access rather than a blanket block, which only pushes use into unsanctioned personal tools.
The programme turned a wide field of ideas into something the business could act on: a prioritised set of use cases, a clear sequence for delivering them, and a first quarter that shows visible value while the foundations for the larger prizes are laid.
What’s Next
The report is the basis on which Nidec’s participants confirm the use cases and their priorities, and on which the business owners take them into the investment process. Enceladus’s recommended first quarter: approve governed access, roll out the two switch-on wins, start the data-in-hand proofs of value, begin the data foundations in parallel, and adopt the responsible-AI framework. Pilot and scale, the fifth phase of the Converge Methodology, follows for the opportunities selected to proceed.