“Improvements made to DBS check delays” is the headline to a BBC article that I read recently. The article goes on say that the backlog in Sussex Police has been reduced from 13,000 to 9,600 with the average time to process applications reducing from 92 days to 34 days. Whilst I would agree that “things are moving in the right direction”, this still seems to be a very long time for a process that I imagine would require a few hours of work at most. The focus of this post is the use of effective demand management to avoid backlogs such as these arising in the first place.
Is it important to avoid backlogs in the DBS?
The Disclosure and Barring Service enables employers to check whether employees have a criminal record and any further information that the police may hold relevant to specific roles. First, let’s consider the impact that delays in processing these requests could have:
- Cost to employing organisations if candidates give up waiting and seek work elsewhere
- Chance that employees are allowed to start work without completion of DBS checks when such checks would have revealed risks to their employment
- Delays in the processes of the employing organisation due to protracted periods with vacancies
- The unnecessary “failure demand” created for Sussex Police in handling the enquiries relating to delayed applications and the work they do that becomes unnecessary as the applicant has moved on
The nature of DBS checks is that they are often undertaken in relation to services that involve security, protection and vulnerability. They often involve employing people at the lower end of the pay scale. Minimising unnecessary delay would therefore seem a worthwhile goal.
What might the causes be?
A common reason for backlogs to arise is an imbalance between the amount of demand and capacity to process it. This can be caused by:
- Inadequate resource provision when the process was set up
- Increases in the volume of demand
- Increases in the amount of time required to process demand, such as due to changes in process and systems, or trainees taking time to get up to speed
- Reduction in capacity, such as due to turnover of staff, increased absenteeism such as through sickness or maternity leave, bars on overtime
How can backlogs be avoided?
This is where effective demand management has a role to play. It starts with the an understanding of how to calculate the resources required to service demand.
Remember the basic formulae:
-
- resource required = work content / net hours worked
where
-
- work content = volume of demand * average unit process time
- net hours = contracted hours – abstracted hours
(abstracted hours are those lost for holidays, sickness, training etc)
Of course, it’s a little more complex than that, as there maybe multiple workstreams (e.g. basic, standard and enhanced DBS checks in the article referenced). Even within these workstreams, not all process steps may be required for all demand (e.g. appeals). Seasonality in both demand and staff availabilty present further challenges, as does simple day to day variability, particularly when service level standards (e.g. 80% of Basic checks within 2 days, 80% of Enhanced checks within 14 days) apply.
Not just a once-off
Applying these principles to a newly designed process or operating model is a key enabler to successful implementation of change. Many well intentioned change programmes have failed due to inadequate resourcing and the resulting backlogs rather than any flaw in the process design.
To my mind, however, effective demand management is an ongoing capability rather than something that is done once. To avoid backlogs arising in future, further steps are required. For example, monitoring demand over time enables trends to be identified. In processes where there is high turnover of staff and long training leadtimes, pre-empting vacancies by initiating recruitment programmes sooner can mitigate the effect of such turnover. Evaluating other changes that affect process times, such as new IT systems and changes to legislation to understand the resource implications before they occur can also prevent unexpected backlogs arising. Sometimes, these changes may even release resource if workload decreases!
Implementing effective demand management
Hopefully my former colleagues at Process Evolution are already on the case supporting police forces in the area of DBS checks. In my time at Process Evolution, we helped forces streamline their vetting processes in support of the Uplift Programme to recruit 20,000 additional police officers, and this would seem like a similar opportunity.
The government website suggests that national data is already collected on DBS demand. Using business analytics to drill down into the next level of detail (i.e. by Force) would enable benchmarking to understand productivity <> outcomes <> performance relationships; forces could be helped to drive local improvements by understanding the causes of any variability found. Predictive modelling could be used to determine resource requirements at the local level, and to extrapolate the effects of trends in demand on future needs.
If you would like to examine how demand management techniques can help reduce backlogs in your organisation, please get in touch via the links provided on this website.