What gets measured gets improved is the old saying, or as management thinker Peter Drucker also put it:
"You can't manage what you can't measure".
But in today's business world, especially with remote-working and cloud apps, it can be a bit overwhelming to think about how much data actually can be measured. It presents a unique problem to businesses who don't have a specialised data science team to focus on these problems, which is unfortunate as a lot can be learnt just by joining the dots between a few data sources.
It's probably not immediately obvious on how much data you could be leveraging, so let's use an example. Let's say you're a professional service firm working 80% remotely, you use a job management platform for project management and time-sheeting, a financial management platform and a communication app for video calls and internal messaging.
That's already three data sources you could be leveraging to measure performance. But what benefit would they be to your company and leadership team? Well, let's say for every employee you have, we want to see their data on a monthly scale. You can take their billable hours and total work hours from your PM tool and pop it into a spreadsheet.
That on its own won't tell you much that you don't already know, so then you could put in the number of emails sent and total meeting times from your communication tool for each employee, month-on-month. Now you've got some comparative performance data, and can't start asking real questions like:
Which employees are less productive the more time we spend in meetings?
Are people billing more when they work more hours, or do they bill more when they work less?
If I added financial data into the mix, what other insights could I gain?
It's a simple example, but one we see every day when analysing customer data and providing them key performance insights. Hopefully, that's given you an idea of how potentially useful data from different sources can be, so let's walk through some of our favourite data-sources for measuring performance, and what metrics you can get from them.
Microsoft Teams/Microsoft Graph (Team Communication)
If you're on Microsoft Teams, you've got a plethora of data you could be leveraging. It will take some tech knowledge to get access to it, but it's worth looking at, especially for measuring how effectively and consistently your team communicates. Some data points you can access are:
Time spent in meetings
Number of meetings/calls
Number emails sent/received
Checkout Microsoft Graph documentation for a list of other data points you can access.
Slack (Team Communication)
A great tool for internal communication, we use across our organisation to centralise our collaboration and cut down on emails. If you're on Slack, here are a few data points you could leverage:
Some other great communication data-sources include:
A great source of data to look at an organisation as a whole, we tie in our financial data with productivity, marketing, sales and other data sources to see how our efforts are impacting our bottom line, and where we can improve. Some data points you can get are:
Total Cash In
Total Cash Out
Xero Practice Manager/WorkflowMax (Job Management and Time-sheeting)
If you're using Xero Practice Manager/WorkflowMax for your job management or time-sheeting, there's a bunch of data you could be looking at per employee when analysing performance, including:
Asana (PM and Tasks)
If you're not in the professional services industry, chances are you're using some sort of project management/task management tool like Asana. There's a bunch of data points you can collect from here, including:
Number of Projects
There are an almost unlimited amount of data-sources to measure productivity, here are a few of our other favourites:
Most data sources mentioned above do require some tech/developer knowledge to start utilising, but it doesn't mean you need to go out and hire. There a few companies who can help you get started by analysing your data from different sources, including us at Everperform.
Data can be a very powerful tool when analysing performance, especially when different sources are mixed to tell a story. If you're not leveraging your data as much as you should, we would encourage you to start doing so. As mentioned at the start, you can't improve what you don't measure.