Internal vs. External Benchmarks: Measuring Team Performance

How do I know if my team’s performance is good compared to others?

In the previous article on this topic (Establishing Accurate Operational Baselines), we deconstructed how new managers can look at the operational performance of their teams and what tools they can use to better understand what is going on. As a first step to achieving success by using the correct methodology, this is perfect. However, with so much information available left and right at the present time, even the least experienced leaders are getting bombarded with tons of benchmarks. With a plate of both internal and external chunks, how should a first-time manager approach this topic? What is the best possible solution to check team performance: internal or external benchmarks?

The best solution is prioritizing internal benchmarks while using external ones only as a broad baseline. External data offers initial market context when no numbers exist, but it lacks specific accuracy. Real performance evaluation comes from tracking internal operational data, analyzing processes, and setting realistic floor-and-ceiling limits tailored to your team’s unique circumstances without creating toxic group competition.

In this article:

The No-Data Lead: Relying on gut feeling instead of analyzing deep data leaves you blind to your team’s actual quality.
Is Ignorance Bliss: Ignoring data-driven tracking causes team frustration, high attrition, and a loss of trust from senior leadership.
The Internal Benchmarks: Internal benchmarks set clear operational baselines to catch errors early without creating a toxic or non-compliant environment.
The External Benchmark: External benchmarks work well as a temporary reference when you lack data, but shouldn’t set firm targets.
Connecting the Dots and Creating the Full Picture: Great leaders investigate data gaps calmly, coach through variation, and use recurring internal metrics for continuous improvement.

The No-Data Lead

With the amount of free (in most cases) information out there today, this might come as a bit of a shock to some: a portion of managers (new and experienced alike) are not very keen on the concept of checking team performance as they should. What I mean by this is instead of trying to establish – either by internal or external means – a clear picture of how the team is actually performing, they just measure whatever they have on hand and take it from there. To be clear on this: your job as a leader in operations is not just to look at metrics and create your basic reports – it is much more than that!

When we choose to embrace this “flying blind” type of principle, we expose both ourselves (as leaders) and the teams we are in charge of to great risks. How could you tell if John from your team is doing well? On what basis are you establishing his performance, and what are you comparing it with? Are you using a set-in-stone target, and if yes, how do you know this target is actually correct? What about special situations, volumes, variation, outliers? How can one tell things are OK if they are not looking at the bigger picture?

Of course, with this type of behavior, other things will come into play: bad performance, poor decision-making, difficulty in trying to reach the metrics, added stress and pressure, potential attrition, and many more.

Some more experienced leaders will say they rely on “gut feeling,” and I am 100% for this in most cases… just not this one. While there is no replacement for the years of exposure and experience someone has built up, the lack of grounding will cause them to act a bit too cocky. When this happens, they tend to ignore the correct approaches and rely on internal feelings. But feelings are a tricky thing because they can’t tell you how things really are; they tell you what you think they are or how you feel about them right now. The only real way to approach the topic is by doing a proper analysis of the data.

There is also a confusion between measuring hard output and true quality. For you see, the output you look at is not the same thing as quality. You can measure Average Handling Time as much as you want to, but it will never reach the level of quality needed unless you start looking into multiple facets of the project and do proper in-depth analytics.

Is Ignorance Bliss?

If we were talking about any other topic, I would say it is – but we are not, so I will straight up call this out: ignorance, when it comes to proper performance in operations, is most definitely not bliss.

The first thing we must consider when talking about ignoring how to actually tackle the subject is the demotivation factor. You can’t expect people to stay motivated and eager to pursue the next big challenge on your team if they (and you) don’t really understand (or care about) the basic foundation.

There is also the frustration perspective you would have to address once goals are arbitrarily set instead of using proper tools and frameworks. Either by gut feeling or by blindly following corporate directions that don’t make any sense, people get mad and start developing frustration because they realize that whatever they do or say, things will not change. So, why stay in this job? Like many things in management, actions and reactions are connected, and a simple thing that could be taken care of with a few meetings might end up turning into an attrition issue.

And one last thing to keep in mind: senior leadership will also have its eyes on you, the leader, and they might get nervous if you can’t showcase your team’s value in numbers. This is why I have dedicated an entire pillar to data for my recommended first-time manager plan; you end up working with so much of it that it becomes a core part of what you do from now on in this job. You are not just a person who validates an email here, a chat there, approves a vacation, and signs some papers – you are in charge of these people and everything they do. If you are not using data in the proper way… it’s not the job for you.

The Internal Benchmarks

Since we have an entire article about this, I will not waste more time going over it. I would, however, recommend the following articles to check up on some basics:

With the basics of internal benchmarking established and cleared, we now look at tracking progress across different teams (or people) without creating a toxic environment. You don’t want high competition between people’s performance – you need steady, healthy peer encouragement that comes naturally. Plus, depending on where you live, there are a bunch of rules regarding how to communicate individual performance in a group (for example, in the EU, you are not permitted to share each person’s performance with other people on the team; according to Article 6 of the GDPR, to share personal data, an employer must have a valid legal justification, and routine team updates or internal comparisons do not meet the strict threshold required to justify exposing an employee’s detailed performance to colleagues).

The entire idea of using internal benchmarks is, on one side, to have a set of starting points for what is considered an acceptable performance, and on the other side, to compare each person on the team with that acceptable performance in order to quantify the individual results everyone brings (which eventually feeds into the annual review process and many other aspects: future jobs, salary increases, new opportunities, etc.). Alongside this, internal benchmarks offer a very unique possibility: observing – in real time – what errors appear and taking care of them before they become major issues.

The External Benchmark

This is always a strange topic, and one that people always have more to say on. Mostly, I personally attribute this to the fact that external analytics are done outside our immediate control, and there are no absolute guarantees that whatever insights they have in them are correct or apply to us.

What is an external benchmark anyway?

To put it very simply, they are analytics other companies do by gathering data from multiple sources and selling them back to companies at a price. Say you have a Finance department in your company and you do not have data for one of your processes, but you need to know what the current market numbers are for your metrics. Instead of waiting on your team to gather the data organically (in time), you just look at different vendors, pay, and get the information you need.

I believe that it’s always good to have as many sources of information as you can; however (and to be very honest and transparent with how I see things), I am not a big fan of external benchmarks. Here are some of the reasons I am not:

What proof do I have that the collected data is correctly analyzed and proper quality proofing is done? Especially now with AI all over the place, the probability of a non-human doing the analysis and creating the insights is very high. While I am not saying there aren’t any trustworthy companies out there, I am saying I generally don’t feel OK with someone else’s analytics.
How can I apply externally analyzed data to my own team’s performance? Things don’t go by the book in operations, and what works very well for one company is not a guarantee for another. If companies had the exact same frameworks, maybe things would be different, but there is just too much diversity and room for exceptional circumstances – “one man’s numbers are not the same as another one’s.”
Benchmarks should be amended for each specific situation: Expecting a standard “market metric” to fit your exact business model, customer requirements, and special situation is not a good way to do business.

Rather than using them as you would internal ones, I always use external benchmarks as a point of reference without making actual decisions that would impact performance. I look at them when there is no actual data available to gather a basic “starter information package” just to help me understand – on a basic level – what I should expect (at least until I have my own team’s data to rely on).

Connecting the Dots and Creating the Full Picture

Firstly, a good leader must learn how to look at gaps. The fact that you see something as a performance issue doesn’t really mean it is so. Defining what performance looks like is the key. There’s just no way to skip this.

Not panicking when something doesn’t go as planned would be the next step, as variation is all around us and perfectly normal. A process will never stay without very absurdly established limits, but it should stay within properly and data-driven calculated ones.

And don’t be too quick to assign blame left and right when things don’t go as planned. Good leaders first act like Columbo and do the proper due diligence: investigate, check facts, look at clear evidence, ask questions, clarify points, and then draw conclusions.

A good practice to have (and a habit, if I may) is turning gaps into practical coaching opportunities for your team. It’s not about the fact that metric X was missed; it’s always about what you can do about it right now to fix it (if you can) and how to mitigate similar cases in the future. By turning a classic “your fault” scenario into a “let’s see what to do now and how to avoid it in the future” approach, people are less likely to panic, get stressed, or get upset. You are not there to blame and shame; you are there to help, teach, and grow.

Creating a future cadence on benchmarking is always a good way to close this chapter: instead of doing it on demand, try to build up a proper database with recurring analytics you can perform. This way, you have a month-by-month situation, you can look at a much larger interval of time, put in less effort overall, and adapt, change, and improve things in real time – not just once every year or so.

And as far as the external or internal dilemma goes, I see things this way:

Use external when you have no data and you can’t wait for internal data, but only use it to get a basic idea of what YOU should expect. Don’t push it on your team or set it in stone; take it as a point of reference only for your eyes.
Start tracking internal benchmarks as soon as your project starts. Keep good track of all metrics, look at variation, use the mean and median properly, establish floor and ceiling limits, and run workshops with your team as often as you can to understand why things are as they are.
Any past data you have can be turned into an internal benchmark, so make sure you clean the data and ensure it is accurate and sufficient for what you need.

Until the next article, stay safe, happy, and healthy!