Using Metrics For Performance

Privacy is a very sensitive topic and differs from country to country. In the metrics that we measure as an example behavioural analytics and cognitive capabilities many people find privacy important. In Europe, they are less sensitive about cognitive capabilities and more sensitive about behavioural analytics dynamics and in the United States it is reversed. They are very open with behavioural data but with very closed on cognitive data, and you can’t give one answer across the globe with respect to sensitivity to data, For example, South Africa, Brazil, Sweden, these are three countries with much stricter psychometric rules, which are tied into their histories.

With privacy, we try and keep the data appropriately private so that people can still use the data to manage but not breaking any personally identifiable information. It’s important that you don’t want someone to know you’re floating about the internet. Especially when Ai and new technology is introduced, so what is instore for the future? These tools really help people design and redesign and reassemble teams almost spontaneously, and still keep high performance.

With companies that pay attention to metrics, it is a critical word, this ability to track what you’re doing, and use that information to guide them in terms of the performance. But what’s the next evolution in terms of how we use data? The biggest thing is quality of performance data. So until we get better performance data, we’re not going to be able to make the correlations that we’re going need to make in order to optimise performance.

Certainly, you can drive to key data for most businesses. That don’t have as clear of outcomes that you’re going to have to really look at tying this to objectives, key results and the metrics which provide that in order to really refine what you’re doing. Most of us are doing well with unstructured interviewing, predominantly focused on resumes, and we have very little training, bringing in the conscious and unconscious bias. We all have the same problems.

All these difficulties you face, others do also, but just stepping back a second can help us look into data collection more effectively. You can ask yourself the questions. How does this company even know they are using data effectively, to assemble the teams and bring out the best one as a starting point to see what a consulting partner or executive business? What kind of self evaluation should they be doing?

Start with the executive. The most important thing when I’m speaking to an executive is get them to know themselves. There’s an element of self awareness so that they can be self aware of the role they play within their team. After the self awareness discussion, which depends on the person could be very quick or could be 90 minutes with all the reports. Sometimes we do use their board. So it’s who they report to, to talk about the joys and frustrations of the team that they’re all in because it’s very personal. And you can show them that you’re able to predict the joys and frustrations that they have given the datasets that we have there.

 All of a sudden, they ask “How did you know this person frustrates me in this way?” Are there gaps, who are the outliers, and how do we make sure that those outliers can feel comfortable? We then determine is that team a good fit for the work that needs to be done with the strategy that they have in place, because a team is not inherently good or bad. It’s about self awareness and then team a team endemic and that is a team a good fit. This is still before we get to performance.

Once you start using the data using this, you need someone who is using this data to put a team together almost like an arbitrator. It should be someone using the data to assemble the team and think of what the team needs to do in this formation. That’s a central role. These strategies and financial plans don’t execute themselves. People execute that.

On Monday morning when you look at your team’s performance and walk score, and you see which employees perform and which employees underperformed and you see the trends. And we see the stats, and you need to hold your teams accountable and their managers also. So if you are a middle manager, you’re being held accountable to certain outcomes, but you don’t know what are the stats that are driving that. Then who are the people responsible downstream or upstream that are causing this data to break down? Because if we have access to the data and gave the data to more people, there would be more people being held accountable.

Knowing how to deploy the best team in a lean way and reconstituting teams, the results speak for themselves when we look at the valuation of capital.