Most technology leaders know the hiring process is slow. Few have calculated what that delay actually costs a running programme.
The global average time to fill a senior data or engineering role sits at 60 to 70 days, according to Workable's benchmarking data across millions of hires. In APAC, that number stretches further. The Josh Bersin Company's 2023 research flagged the region as one where time-to-hire is increasing fastest, driven by a structural imbalance that has only deepened since: 77% of APAC employers report difficulty filling positions, with IT and data roles identified as the single hardest category to source, cited by 81% of IT sector employers (ManpowerGroup Talent Shortage Survey, 2025).
That is not a temporary squeeze. ManpowerGroup's own data shows the shortage has grown from 45% in 2014 to 77% today. It is a structural feature of the market, not a cycle.
So when a programme requires a data engineer, a migration specialist, or an analytics engineer, and the answer is "we'll hire for it," the realistic timeline is two to three months before that person is onboarded and productive. In practice, often longer.
What is actually happening during those 60 to 90 days
The programme does not pause while recruitment runs. Deadlines hold. Stakeholders ask for updates. Adjacent workstreams wait on data that is not yet migrated, pipelines that are not yet built, validation that has not started.
In migration projects specifically, this creates a compounding effect. A data migration that cannot begin in week one does not simply start later in week ten. Every downstream dependency shifts with it: the platform go-live, the automation layer that depends on clean data, the reporting that executives are waiting on. The delay multiplies.
From engagements we have run across APAC, a common pattern emerges: a programme loses between six and twelve weeks of effective execution time not because of technical complexity, but because the specialist needed to do the work arrived too late. By the time they are onboarded and familiar with the environment, the programme is already behind and the pressure has transferred to every remaining phase.
The Standish Group has estimated that project delays can cost organisations roughly $97 million per $1 billion of programme value. Even at a fraction of that scale, the arithmetic is uncomfortable.
Why internal reallocation is not the answer either
The reflex response is to pull someone from another team. A data analyst who knows the systems. A developer who has done migration work before. It seems pragmatic.
What it actually does is create a secondary shortage. The person reallocated carries the context and capacity of their original role. Their existing deliverables do not disappear. They split attention between two priorities, and both suffer. This pattern is common enough that we see it as a leading indicator: when a team starts cannibalising itself to cover a capability gap, it means the programme has already exceeded its real execution bandwidth.
The case for embedded specialists
The embedded outsourcing model exists precisely to close this gap without the recruitment timeline, the onboarding ramp, or the fixed headcount cost that follows.
A specialist deployed through We+ Asia arrives scoped to the programme. Not to a permanent role with a three-month notice period and a remit that outlasts the project. They integrate into the existing team, adapt to the tools and governance already in place, and are productive within days rather than months.
On a recent data migration programme across multiple APAC markets, over 100,000 lines of data were analysed and migrated without disrupting live operations. The speed was not incidental. It was a direct function of deploying a team whose only priority was that migration scope, rather than absorbing it into a function already running at capacity.
That is the practical difference between hiring and embedding. Hiring solves a long-term resourcing problem. Embedding solves a delivery problem, now.
What this means for how you structure the next phase
If your programme has a data workstream that is currently waiting on headcount, the question worth asking is not "how do we accelerate the hire?" but "what does the programme lose for every additional week this remains unresourced?"
At 60 to 90 days for a typical APAC hire, with an onboarding period on top, the answer is usually more than the cost of an embedded specialist for the same duration. The maths tend to resolve quickly once the delay cost is made explicit.
The talent shortage in APAC is not getting easier. According to ManpowerGroup, the scarcity of IT and data skills has been the top unfilled category for over a decade and shows no sign of reversing. Building a programme delivery model that depends on finding that talent in the open market, on the timeline a programme needs it, is a structural vulnerability.
The specialists are available. The question is whether you bring them in before the programme feels it, or after.
Talk to our experts and assess your delivery gaps before they compound.
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