Public services shape some of the most important moments in people’s lives, from receiving welfare and renewing a passport to accessing a healthcare referral. When these services work well, they feel seamless, but when waiting lists lengthen and backlogs grow, the impact on citizens quickly becomes impossible to ignore. The typical reasons for backlogs often relate to factors such as too few staff, insufficient capacity or another digital transformation initiative that has failed to deliver. However, often these problems have a less obvious cause: queue drift, in which the way work is routed through a public service no longer reflects the volume or complexity it faces. Over time, processes continue to operate according to outdated assumptions, even as citizens’ needs and service pressures change around them.
Ironically organisations often have all the people and resources needed, but work is reaching the being handled in the wrong order or following processes designed for a different reality. Until public services address that mismatch, adding more capacity may only help them manage the symptoms rather than resolve the underlying cause.
What is queue drift?
Queue drift rarely appears overnight and is not usually the result of a failed process or a single operational mistake. Instead, it develops gradually as the environment around a service changes. A healthcare provider, for example, may experience shifts in referral patterns, while a local authority may see increasing demand for more complex cases than it did just a few years ago. As these changes accumulate, workflows that were once effective can become increasingly misaligned with the reality of demand.
This is what makes queue drift particularly difficult to identify because performance measures may remain largely unchanged and no obvious system failure may be visible. Yet a gap is created because beneath the surface work is no longer flowing through the service in the most effective way.
There are two common causes of queue drift. The first is over-escalation, where low-risk cases are repeatedly referred for additional review, creating avoidable pressure on specialist teams and slowing overall throughput. The second is under-prioritisation, where higher-risk or more urgent cases are not identified early enough and remain in the queue longer than they should. Both symptoms point to the same underlying issue of processes no longer reflecting current patterns of demand, complexity and risk.
Processing more isn't the same as working smarter
The consequence is that organisations often treat queue drift as a capacity problem rather than a flow problem. Rising backlogs are difficult to manage and the instinctive response is to add more staff, increase funding or invest in new technology. In reality these measures will provide temporary relief, without establishing whether work is actually moving through the service in the most effective way.
In fact, additional capacity can sometimes compound existing issues. If low-risk cases continue to be routed to specialist teams or routine enquiries are still subjected to unnecessary checks, organisations simply become more efficient at processing work through an imperfect system. The backlog may shrink in the short term, but the underlying causes remain.
For example, a government contact centre may continue to direct a high volume of enquiries to specialist caseworkers even though many issues could now be resolved through digital channels or first-line support teams. Similarly, a passport or licensing service may still subject a large proportion of routine applications to manual review, consuming valuable specialist capacity that could be focused on more complex or higher-risk cases.
This is why organisations should ask not only, “How do we process more cases?” but also, “Are the right cases reaching the right teams at the right time?” Without answering that question, efforts to increase capacity may simply mask the underlying issue rather than resolve it.
A case for continuous review
Gaining useful insight into how work moves through a service is the first step that should be taken when it comes to addressing queue drift. Many organisations will be able to see how many cases are waiting in a queue, but less have the context of why those cases arrived there, or whether the original routing decision was appropriate. Having this understanding is essential before investing in large-scale transformation programmes.
This is why an audit-first approach is more beneficial compared to a wholesale overhaul. Rather than redesigning entire services, organisations should focus on identifying where decisions, escalation rules and workflows no longer align with current patterns of demand. In many cases, relatively small adjustments can have a significant impact on reducing bottlenecks and improving service outcomes.
AI has an important role in assisting decision-makers, it could be deployed by teams to analyse thousands of historical cases to uncover patterns at scale. In these type of situationss it may reveal that a large proportion of cases being escalated to specialist teams are ultimately resolved without intervention, highlighting opportunities to refine routing rules. Here, the goal is not to replace people or existing processes, but to provide better insight so organisations can make evidence-based improvements before backlogs become entrenched.
Establish where work is directed
Queue drift is a reminder that public services operate in a constantly changing environment. As citizen needs evolve, even well-designed processes can become less effective over time. That is why tackling backlogs should not begin with the assumption that more people or technology are required. Instead, organisations should first examine whether work is being directed, prioritised and managed in the right way. Regularly auditing these decisions can uncover opportunities that would otherwise remain hidden. In the long term, organisational resilience comes not from continually adding capacity, but from continually adapting processes to match changing demand.
Chris Oakley
Chris Oakley, Head of Financial Crime Solutions at Sopra Steria. With over 20 years of experience across banking, fintech, and regtech, Chris has held senior roles at Form3, Featurespace, HSBC and Virgin Money, delivering AI-driven risk platforms and real-time fraud prevention strategies. At Sopra Steria, Chris is responsible for aligning innovative solutions like the Optimised Decision Engine (ODE) with market needs around explainable AI, scam prevention, and operational resilience.
