Even exceptions need rules: In Lean methodology, exceptions should be caught at an early stage of a process to minimise waste. Knowing the limitations of systems and models can assist in handling exceptions and integrating them into business as usual (BAU).
Avoiding the hidden costs of successful transformation projects
Over the last few weeks, we have published a series of articles on common pitfalls we have come across when companies take on actuarial transformation projects.
In this last instalment I will examine how to deal with exceptions.
Mismanagement of Exceptions: Exception expectations
Most processes contain some exceptions that are not worth building into the automated steps as they are immaterial or overly complex.
In every actuarial process we have seen, there have always been exceptions, errors and manual adjustments. This in itself is not a problem, but businesses rarely design their BAU processes to strike a balance between processes which are flexible enough to allow for true exceptions and those which can only manage standard, predictable inputs.
This typically results in a list of manual adjustments which grows and grows without ever being resolved at the source. The tendency is to continually bend and change processes to handle every exception rather than looking for optimised solutions which seek to minimise exceptions and promote process flow.
Know your (model’s) limits
A team we worked with recently was responsible for delivering asset stress results from a very complex model.
Each reporting period, the model would fail to run due to a number of exceptions. Because the software did not specify which model points were causing the exceptions, the team (consisting of high-value employees) would spend hours scouring the input files, and running and rerunning the model, trying to narrow down the problematic model points by a process of elimination.
What we found after analysing the exceptions was that they each had certain characteristics which fell outside of the model’s limitations, for example: bond assets with negative yields, or market price to nominal ratios in excess of a certain value.
A lack of awareness of the model’s limits led to a significant waste of resources every month. If limitations are known upfront, it is not necessary to wait for the results of a model run to address them – they can be monitored and resolved before they become exceptions.
The case for transformation
When considering the business case for transformation projects, decision-makers often find it difficult to spend the money if the only tangible benefit is reducing the amount of (unpaid) overtime worked by their employees.
At MBE Consulting, we always try to encourage thinking about the hidden costs of manual processes and inefficiencies: the decreased staff morale, the errors that slip by, the extra margins that need to be built in because of uncertainties around certain steps, the risk of falling behind the rest of the industry…
Perhaps a question to ask when deciding whether or not to go ahead with any such project is: will the benefits of this project be reflected as a reduction in your operational risk capital?
If the answer is yes, and you avoid the pitfalls we have described, an actuarial transformation project may add untold value to your business.
MBE’s Actuarial Performance Management (APM™) Framework is structured to help actuarial teams design well-defined processes that deliver consistent and reliable risk data and actuarial results, produced to the appropriate quality standards, and on time to meet business objectives.
Contact us to find out how the APM Framework can support you in your transformation project.