Whenever we experience significant market volatility—specifically to the downside—the pressure on advisors to respond efficiently and effectively can increase dramatically. Furthermore, in prolonged bear markets, advisors could be challenged with covering their expenses while their revenues remain flat or decline. This is especially true because generally a majority of an advisor's overall expenses are fixed. Given this environment, what can you do today to understand the scalability of your firm, particularly as it relates to your technology processes and solutions?
The first and frequently overlooked step in understanding your scalability is measuring the time and effort currently required for your standard processes. This includes processes like portfolio rebalancing, client on-boarding, sending bulk letters, quarter-end reporting and billing. Too often we rely on general information in understanding the time required to complete a process. Therefore, it is important to establish a specific baseline measurement for each process. A word of caution to keep in mind as you conduct this process: The goal of measuring the time requirement can easily be misinterpreted by your staff as a way to evaluate if they are effective in their position. Therefore, make sure that your staff understands the primary goal and objective. Otherwise, the actual baseline numbers might be more time consuming than they report because they are worried about their own personal performance.
Once you have established your baseline number for each process, your next step is to forecast the expected growth. The ultimate goal is to achieve improved production and efficiency as the numbers grow with each process. Furthermore, with technology you need to be critical about whether a system or product is truly up to the task of meeting your expected growth projections. We all know the stories of solutions that were intended to meet a need for just a couple of years, but are still around years later. It is not worth the risk to let it get to this point, because it will likely crash at the worst time. There is nothing wrong with older systems that continue to perform and work well—just remember to be realistic of the system's overall life expectancy.
[Read more about how simple training on the tools you already have can help improve scalability.]
