Operations data offers insight on how well processes and work activities deliver the intended outcomes. Often, service companies pay less attention to monitoring the day-to-day activities. The lack of monitoring leaves managers scrambling for adhoc measurements when problems arise. These adhoc measurements likely rely on manual approaches that are onerous.
There is an easier way to do it. Instead of playing catch up, why not plan ahead and build the capability for capturing data right off the back?
To do so, start with identifying data that is useful for monitoring operational performance. This can be addressed by asking this question.
What outcomes do you aim for?
These outcomes could include completing the work in an expedient manner, error free, and consuming as little resources as possible. They translate into speed, quality and cost. You need to articulate the desired outcomes as clearly as possible in order to know the specific data elements you need to gather.
Once you identify what you need to capture, the next step is to build the capability. In addition to having the capability to capture the data, you also need the ability to easily extract data for consumption.
This involves identifying an existing application that either contains the needed data already or making the enhancement for users to input the data. In mechanizing the data capture, you eliminate the tedious manual approach. This also provides a repository where you could access the data any time.
With respect to data extraction, consider who would need to look at the results. The more flexible you design the data extract, more users would be able to pull the data they need on their own. Self-serve data improves productivity.Self-serve data improves productivity. Click To Tweet
When you plan ahead, you could also incorporate intelligence in the application to monitor performance. If the results fall outside a pre-defined range, the application can alert you immediately. This allows you respond in a timely manner.
A note about data quality and discipline about data entry. It is essential for users to understand the importance of inputting the appropriate data in the proper format. Consistency and completeness are key to quality data. Otherwise, you could end up spending time on fixing data gaps and cleaning data, a frustrating experience.
With an effective approach to capture pertinent operations data, you would be able to monitor proactively areas that require attention. A little pre-planning goes a long way in building a trove of useful insights.