Cost Allocations: Drivers cannot be captive to data availability
When it comes to cost allocations, there are few topics more emotive than drivers. Unsurprisingly when the metrics chosen determine how much indirect cost a given department will receive, they often become a point of intense, contested debate.
A good driver should; 1. ensure a fair and proportionate charge to all consumers, 2. incentivise desired behaviours and 3. be readily available and frequently updated.
Whilst few would disagree with these criteria, the challenge lies in satisfying all three simultaneously. All too often, this leads to organisations becoming captives to data availability.
To see how this occurs, let’s consider an example of a HR department selecting the driver for a ‘recruitment’ service in an activity-based costing allocation methodology.
The first point – ensuring a fair and proportionate charge to all consumers – is relatively straightforward; ‘number of new hires’, ‘number of interviews held’, or ‘number of positions advertised’ would all satisfy this criterion given their strong positive correlation with effort spent recruiting.
The second point – incentivising desired behaviours – may also be satisfied by these drivers, albeit to different degrees. All three will incentivise more cost-conscious decision making when considering recruitment, as front-office departments know hiring will increase their charge from HR.
However, using ‘number of positions advertised’ may incentivise direct recruitment via employee networks, which may not comply with other organisational objectives such as increasing diversity. Using ‘number of interviews held’ may have both positive and negative impacts. Positives: It encourages more rigorous screening of CVs and fewer unnecessary interviews. Negatives: As with ‘number of positions advertised’, it may incentivise network-oriented hiring, and may also reduce the rigour of the interview process.
In this hypothetical example, the HR department thus land on ‘number of new hires’. However, it’s here they run into a problem.
This data point is not collected anywhere centrally and, to make matters worse, neither is ‘number of interviews held’ or ‘number of positions advertised’. On discussion, and with a deadline to implement the methodology looming, HR decide to use ‘FTE’ as the driver.
I’ve observed this scenario more times than I can count, and it always causes the same two issues. First and most obvious; it compromises the integrity and usefulness of the methodology. Second, but more pernicious; driver selections become hostage to data availability as a driving constraint.
So how can this be avoided? Well, a number of partial methodological antidotes are possible.
The first is to introduce multiple drivers per charging department / service. This is effective where the desired driver is available, but not at the desired level of granularity. In our example, ‘number of new hires’ may be available at – and thus used to – calculate charges to total business level, before the charges are pushed down to business cost centres based on FTE.
Second is the introduction of ‘endpoints’. Endpoints require the allocating function to specify more precisely the departments or cost centres they wish to charge. This increases the accuracy of, and reduces the influence of drivers on, allocation outcomes, particularly where there is a single endpoint for a particular charging function, cost centre or service, as a driver is no longer required.
Third, and the logical extension of number two, is to eliminate drivers altogether. Moving to a timesheet-based charging system – similar to an external professional services provider – means charges are distributed exactly as per the time spent on them.
However, the problem with all these solutions is that they add methodological complexity, and a move to entirely time-based costing is inappropriate and impractical for the vast majority of organisations. The fact is drivers will always be required.
And so, as is so often the case, I believe the best antidote is the simplest. Finance, the custodians of any allocation methodology, should chair driver selection discussions, and ensure that drivers are always considered first on their methodological merits. Whilst this will inevitably lead to some frustration upon learning that data for a desired driver is unavailable, it at least highlights the problem.
Finance can maintain a list of drivers that are rejected on these grounds and highlight them to Chief Data Officers, feed them as business requirements into in-flight data enhancement programmes and, where appropriate, build a case for gathering the data for them independently. Over time, this will edge the methodology closer to purity.
Not being able to source the data for a painstakingly debated driver is hugely frustrating, of that there can be no doubt. But driver selection cannot become hostage to data availability. Doing so compromises their very purpose.
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