Workforce Mix: Why Data Should Decide, Not Habit

How Life Sciences and STEM Employers Can Make Smarter Permanent, Contract, SOW and AI Hiring Decisions

Perm, contract, SOW or AI: most hiring choices default to habit. See why workforce mix decisions need market intelligence, not guesswork.

Most hiring decisions are not really decisions. They are habits. A role opens, and the usual engagement model kicks in before anyone asks what the work actually needs. If the last three hires were permanent, the fourth one probably will be too. If a team has always used contractors, it keeps using contractors. Even after the original reason has disappeared.

This matters more now than it did five years ago. Organisations in life sciences and wider STEM now face four live options for almost every role. They can hire permanent staff. They can bring in a contractor. They can commission a statement of work team. Or they can use AI to do the task instead. Each option has a different cost. Each carries different risk. Each moves at a different speed. So treating this choice as a habit is an expensive way to run a workforce.

Why organisations default to habit, not evidence

Workforce mix decisions often sit wherever they landed last time. Procurement, HR and hiring managers each pull in a different direction. Procurement wants cost control. HR wants headcount governance. The hiring manager just wants the role filled by Friday. None of those goals is wrong. But none of them answers the real question. Does this piece of work need a permanent employee? A specialist on contract? An outcome-based SOW team? Or a tool that can do the job without a person at all?

Contingent labour has grown from a stopgap into a structural part of the workforce. Deloitte reports that contingent workers now make up between 30% and 50% of an overall workforce in many organisations. That scale turns workforce mix into a permanent planning question, not an occasional one. Yet most organisations still make the call role by role, on instinct, rather than against a consistent set of criteria.

What the market data actually shows

The AI question adds a genuine fourth branch to the decision tree. It is not a simple substitute for headcount. KPMG’s 2025 Life Science CEO Outlook found that life sciences leaders are moving from AI experimentation to real operationalisation. At the same time, those leaders are still working out how to retrain their existing people alongside the new technology. AI has not removed the workforce mix decision. It has added a fourth option. That option needs the same scrutiny as the other three, role by role.

That scrutiny has to come from outside the building. Internal data only tells you what you did last time. It rarely tells you what a pharmacovigilance or biometrics specialist actually costs in your market this quarter. It will not tell you how fast comparable employers are filling similar roles. Nor will it tell you whether a skill is scarce enough to justify a premium contract rate over a slower permanent search. Market intelligence closes that gap. It shows a hiring leader what the labour market will actually bear. Not what last year’s budget cycle assumed.

Building a workforce mix decision that holds up

A workforce mix decision that holds up asks the same four questions of every role. First, how volatile is the demand? Is this a six-month spike, or a permanent capability the business will always need? Second, how sensitive is the work? Does it sit close to regulatory or IP-critical processes that favour continuity over flexibility? Third, how fast does value need to land? A three-month contract start often beats a five-month permanent search. Fourth, where does AI genuinely remove a task, rather than just moving the bottleneck to whoever has to check its output?

No single organisation can answer those four questions from its own hiring history alone. Leaders need current market data to answer them well. That means rate benchmarks. Time-to-fill trends by function. Skills scarcity data. And a clear read on how comparable employers in the sector are actually splitting their workforce right now. This is the intelligence layer most organisations are missing. It is the gap between a workforce mix decision built on evidence and one built on whatever worked last time.

Why the answer cannot sit with one function alone

Take a mid-sized biometrics team hiring for a data management specialist. On instinct, the default is a permanent hire, because that is what the team has always done. However, current market data might show that specialist candidates in that niche are scarce and expensive to hire permanently, while a contract market for the same skill is deep and fast to access. In that case, a contractor delivers the same outcome sooner and at lower risk. Without the data, nobody in the process would know that. As a result, the team defaults to the slower, costlier option, simply because nobody asked the market first.

This is why the decision cannot sit with one function alone. Procurement, HR and the hiring manager all hold a piece of the answer, but only market intelligence gives them a shared, current picture to work from. Once that picture exists, the four-way choice between permanent, contract, SOW and AI becomes a genuine comparison. Not a guess dressed up as a policy.

Skills Alliance Enterprise works with talent and procurement leaders across life sciences and STEM. We bring current market intelligence into the workforce mix conversation, before the engagement model gets chosen by default. If your organisation is weighing permanent, contract, SOW and AI options for a critical function, get in touch. We can talk through what the market actually supports, role by role.

By Dave Watson, VP Talent Solutions, Skills Alliance Enterprise