Part 3 – Workforce is the strategy
Ask any government technology leader what their biggest challenge is, and the answer is rarely the technology. It is people. Skills shortages, capability gaps, difficulty attracting and retaining talent in a market where the private sector offers more flexibility and often more money. Every agency feels it. Almost every programme plan treats it as a constraint to be managed rather than a strategic problem to be solved.
That framing is costing government significant amounts of money and producing technology programmes that deliver less than they should.
Government technology programmes are persistently designed around the technology, with workforce considerations bolted on at the end as a change management workstream.
The standard model for a major government technology programme goes something like this. A policy change or problem is identified and assessed. A business case is developed around the solution options. A procurement is run. A vendor or integrator is selected and engaged. Implementation begins. Somewhere in the middle of delivery, a 'change management workstream' appears. It runs training sessions, produces communications, and manages the transition. Then the programme closes, the integrator leaves, and the agency is left with a system it understands incompletely and a workforce that is operating it at partial capacity.
This is not a description of failure. It is a description of normal.
Flipping the model
The agencies that get the most sustained value from technology investment are not necessarily the ones that chose the best technology. They are the ones that understood before the procurement, what their workforce needed to be capable of doing, and designed the programme to achieve that outcome alongside the technology outcome.
This means starting with capability mapping, not solution selection. What do people in this agency need to be able to do that they cannot do today? What skills exist, where are the gaps, and which gaps are genuinely addressable through training versus which require a different resourcing model? The answers to these questions should shape the procurement, not follow from it.
It means building skills transfer into contracts as a deliverable, not an afterthought. If an integrator is engaged to implement a platform, the contract should specify (along with measurable outcomes) how much of the knowledge required to operate, maintain, and evolve that platform will reside within the agency at the end of the engagement. Too few contracts do this. Too few agencies hold their vendors to account for it when they do.
If an integrator is engaged to implement a platform, the contract should specify how much of the knowledge required to operate and evolve it will reside within the agency at the end. Too few contracts do this.
And it means rethinking what 'delivery' means. A programme that delivers a working system but leaves the agency dependent on external support to operate it has delivered the technology, but not the capability. In a resource-constrained environment, that distinction has direct budget consequences every year thereafter.
Why this matters now
The pressure on government workforces is not going to ease. AI will automate some functions and create demand for new ones. Agencies that have invested in genuine workforce capability including the ability to understand, adapt, and evolve their own technology environment, will be positioned to take advantage of that shift. Agencies that have accumulated a series of systems they do not fully understand will find it harder and be continually reliant on the external workforce market.
NCS works with government agencies on programmes where workforce capability is treated as a first-class outcome, not a workstream. That means co-designing solutions with the people who will operate them, building training and knowledge transfer into delivery milestones, and measuring success not just by whether the technology went live, but by whether the agency can drive it forward independently.
The technology in any programme will change. The next AI model, the next platform version, the next architectural standard will all arrive. The agencies that will adapt well are the ones with workforces that understand the fundamentals and not just the current implementation. That capability does not appear at go-live. It must be built deliberately, from the beginning.
