The Financial Executives Research Foundation, in partnership with Workiva, is working on a research project focusing on the trends, opportunities and challenges private and public companies face in enhancing performance management.
In this video, FERF speaks with Joseph Howell, Executive Vice President, Strategic Initiatives at Workiva, about performance management, as well as the data and control-related challenges many organizations face. A transcript appears under the video.
FERF: How do companies define performance management?
Joseph Howell: Performance management is simply trying to set measurable goals that are important to the organization to meet for a range of purposes. Many of those goals are not related specifically to the things that the accounting department is measuring and reporting in the financial statements. And many of those measures that are important are things that are correlated, perhaps indirectly, with something that you really want to measure because you’re unable to really measure the things that you’re after.
For example, for many years people used revenue per head count as an important metric and it’s still important in many industries. How much revenue are you generating. But, the issue that you are trying to measure there is actually productivity, and revenue per head is merely a shorthand to get to productivity.
When you begin to talk about performance management, what you’re looking at in most instances, when most people are talking about that topic, they’re talking about the measures that you care about. How do you determine what measures are important to you? How do you report those measures? And how do you monitor your progress over time?
FERF: What are some common challenges with performance management?
Howell: Common challenge number one is finding something that is a good proxy for what you’re really trying to measure, because frequently what you are really after is something that is hard to measure.
The second thing is being able to get the information that you need reliably, and to appreciate the controls necessary to generate that information reliably, and to be able to use that information.
And third, but not least, is the ability to monitor when those metrics may no longer be relevant and may no longer be telling you the things that you think they’re telling you. That your model somehow, has somehow separated and that the proxy that you’re using may no longer be holding.
FERF: How do you know if a model isn’t working?
Howell: It is absolutely matter of judgment but it’s also a matter of having the right information necessary to inform that judgment. If I may add, perhaps one way to do that is to understand, specifically, where you have a risk of failure and to do a proper risk assessment of your measures.
Not all measures are going to be perfect for all time and you won’t know that unless you step back to do a proper assessment of the risks of having an inappropriate measure or having one of those measures that is, is no longer reliable for one reason or another. It’s important that from time to time you take a step back and look, and ask the question “what if we’re wrong?” And take that seriously.
That’s an important part of being able to manage in periods of uncertainty in particular, or when you’re dealing with rapid change or an environment which is subject to things that could be completely blindsiding you. And that’s true in technology in particular.
Let’s take a step back and look at performance management of an accounting organization that may be implementing the new revenue recognition standard. You’re looking at your accounting decisions and how you’re going to make the judgments with the contracts and how you’re going to assign them through the five-step process to determine when to recognize the revenue.
But you also need to step back and say, “what if that process that we’ve built is unsustainable? Or what if it is unreliable? Or if there are risks or errors that go undetected?” Those risk assessments are critical to being able to step back, to be able to allocate those resources where they are best suited to provide reliable, repeatable, sustainable information flows.•