DF WIIG
AI AUDIT
Three days on site, six in-depth interviews and ten systems mapped, summarised in 68 concrete measures and a prioritised twelve-month plan.
DF Wiig develops and supplies high-pressure swivels for demanding drilling and offshore applications, supported by engineering and service throughout the product lifecycle. AIKI carried out an AI audit of the entire business, from the first customer enquiry to an approved certificate. The result is a catalogue of 68 measures tied to named work tasks, each with an owner, a complexity rating and an estimated gain, placed in an order that can be followed.
Almost a century of specialised mechanics
DF Wiig was established in 1929 and is based in Bergen, Norway. Today, high-pressure swivels for demanding drilling and offshore applications are the company’s core product, supported by engineering services spanning design, analysis, qualification, testing and operational support.
A small team of specialists covers the entire value chain themselves: design, structural analysis, certification documentation, order handling, sales and finance. That means a short path from customer enquiry to finished product, and at the same time a working day where a great deal of experience sits with the individual and a great deal of time goes into documentation.
DF Wiig is part of DF Group, and serves as the group's pilot for digitalisation.
Documentation follows every delivery
Equipment used on the Norwegian continental shelf must be thoroughly documented. Calculations, material data, test protocols and drawings have to be consistent and traceable, and the whole package must pass external approval before production can begin.
The underlying information comes from several specialist systems that do not talk to each other: CAD, structural analysis, calculation, order handling and file archives. The same detail is therefore recorded in several places, and assembling it all requires people with long experience in the field.
For a small specialist team, capacity rather than demand sets the limit for how much can be delivered. The question DF Wiig came to us with was therefore not whether artificial intelligence is interesting, but where in their own working day it would actually make a difference.
An AI audit: mapping before tooling
An AI audit does not start with technology. It starts with understanding how the work is actually done, by whom, and where the time goes.
AIKI spent three days at DF Wiig and went through the business together with the employees, from the first customer enquiry to an approved certificate. Six key people were interviewed in depth, and every work process was mapped as it is actually carried out, not as it is meant to work.
The findings were then quantified. Each measure was given an owner, a description of the current situation, a proposed solution, a complexity rating and an estimated gain. Measures that depend on integrations, licences or clean-up work were marked with those dependencies, so the sequence could be decided by what is feasible, not only by what is desirable.
The outcome of the audit
DF Wiig received a basis for decisions: a complete overview of where time goes, which tasks can be supported by artificial intelligence, what each measure will require, and in which order they should be taken.
The recommendation is to start with a few measures rather than all 68. Three completed measures are worth more than thirteen half-finished ones, particularly in a company without its own IT function. Each stage is run and measured on the company's own numbers before the next is decided.
The gain estimates are projections built on the time use the employees themselves reported, not a measured before-and-after study. They were deliberately adjusted downwards from what the first financial analysis showed, because freed-up time does not automatically become billable value. Even with the reduced figures, the total estimated gain is several times larger than the investment in the first stage.
What DF Wiig was left with
Preparation
The industry, the certification requirements and the company's constraints were mapped before the first meeting, so that time with the employees went to what we could not read our way to.
Three days on site
In-depth interviews with six key people, from design and structural analysis to order handling, sales and finance. Processes were drawn up along the way and confirmed by the people who carry them out.
Analysis and quantification
The findings were collected in a catalogue of 68 measures, each with an owner, complexity, dependencies and an estimate built on the time use the employees themselves described.
Prioritisation and plan
The measures were reassessed from several perspectives, finance, technical feasibility and capacity for change, and placed into a staged plan with decision points.
Where does the time go in your business?
An AI audit maps your work processes and gives you a prioritised list of what can actually be automated, with an estimated gain and complexity for each measure.