With the increased emphasis on in-house teams to track, provide and act on metrics-driven data, there is the potential for missteps that could result in poor morale, lowered productivity and unrealistic expectations. Fortunately, with focus and planning you can mitigate the downside of metrics.
The foundation of all metrics is the accurate capture of data, yet often in-house team members are unclear about how to do this. It's absolutely critical that job and task classifications be carefully defined and communicated to the team consistently and continually when first implementing data capture. If your team is incorrectly labeling project types and entering their time under the wrong task classifications your metrics will be worthless. It will take months of constant reminders and training before everyone truly adopts, embraces and gets their collective heads around this practice. While it may be time-consuming to engage in this practice, it is necessary to ensure you get the clean data you'll need to build out accurate and actionable metrics.
To prevent hysteria when your team realizes that their performance is now being captured and then jump to the conclusion that Big Brother has arrived and is watching their every move, communicate any metrics-driven initiatives on a need-to-know basis and in context. You shouldn't hide the fact that data is being gathered and analyzed, but you also don't need to remind the team of this fact whenever you work with your metrics. Most critical is to make sure you emphasize that the metrics are being used to identify process improvement opportunities (not individual performance) and that they will also assist in assigning the right team members to the right jobs. Just to be clear, not only should you be saying this to your team--this IS what you should be using the metrics for. There are way too many variables that make pinpoint performance evaluations nearly impossible making individual evaluations a dangerous misuse of this tool.
An overall caveat, that applies to any and all metrics that are tracked, is to avoid the belief in the law of averages--that with a relatively small sampling over a short timeframe, you can identify trends or factual root causes behind data. Samplings should be large and conducted over long periods of time. We're talking dozens of projects over 6, 12 and even 24-month stretches. If you don't adopt this discipline and respect for data, you'll be basing decisions about how to manage personnel, resources and processes on flawed analysis, and you could potentially take actions that might damage your operations and your team.
In addition to the larger issues noted above, below is a list of some potential potholes associated with specific metrics and recommended remedies.
- Utilization: Establish realistic utilization targets, otherwise you risk burnout , anxiety and churn over unrealistic performance expectations. Generally 75% to 85% for individual contributors is appropriate, but these targets can and should vary by role and position level with leadership and highly-skilled positions having lower targets and more transactional roles having higher ones.
With an emphasis on utilization there is also the risk of perverse incentivization where team members may be tempted to work more slowly to accrue more hours (and hence higher utilization) on their projects. Careful tracking of efficiencies and also agreed-upon timing for specific tasks should alleviate this problem.
- Duration: There are so many factors that impact duration (the time from a when job is initiated to when it is closed) that it's critical you break down a job's overall duration into smaller chunks bookended by key milestones. You wouldn't want it to look like your team is slow to deliver when actual causes may be excessive client revisions or clients taking their time in supplying content or feedback. Chunking duration down will allow you to identify the true causes of longer than expected turn-times.
- Efficiency: How quickly a particular task is completed is impacted by project complexity, the quality of client direction and the level of client expectations, making strict accountability to rigid time targets unrealistic and counterproductive. Imagine your best designer inheriting the more difficult jobs and consistently missing efficiency targets because it took her longer because she was assigned the most complex jobs as a result of her superior expertise. Not a particularly positive scenario.
The best use of efficiency is to track long-term trends on specific types of jobs and use any results to suss out process improvement or organizational redesign opportunities. Another productive use is to track expected efficiency improvements when implementing new process initiatives. For example, you may want to introduce the use of templates on a business that requires the same type of deliverables on a consistent basis. With the efficiency metric you can do a "before and after" implementation analysis to see if the templates reduced production time the way you envisioned they would.
Metrics can contribute greatly to the positioning, management and improvement of your business, but if executed poorly, they can cause much more harm than good. Fortunately, when implemented with care and forethought, the worst side effects can be avoided entirely, giving you the opportunity to reap all the benefits metrics have to offer.