In our last post, we discussed how the richness of content data can give information above and beyond metadata. We looked at individual relationships between managers and their direct reports and found that those relationships look different depending on the metric you use to examine them. For individuals, that information can be extremely valuable. We also wanted to investigate relationship types at the company level, so we aggregated those metrics to create a holistic look at relationships across companies.
To effectively measure different aspects of managerial relationships, we created four variables which we call communicative, informative, responsive, and tone. Communicative is restricted to metadata, but the other three variables use message content to unlock different elements of the digital relationship between a manager and her direct report.
- This is our metadata variable. It includes the number of hours a manager and direct report spend in meetings together, the number of events they share, how long they spend communicating, and how dense those communications are (e.g. number of messages and sentences exchanged across all emails and chats).
- This variable looks at the richness of information shared between a manager and direct report, giving a deeper dive into the content of their communications. It includes instances of praise, informing doubt, sharing opinions and requesting feedback. This variable is normalized by the number of sentences shared within the relationship as well.
- This variable measures the attentiveness in a relationship between a manager and direct report. It includes how quickly they respond to one another when information is requested, how much information they share in those instances, and how often they request ad hoc meetings.
- This variable examines how a manager communicates with her direct reports. It includes measures of politeness and kindness in the relationship and how closely those variables are matched between the manager and her direct reports.
For the aggregate analysis, we used a median split to categorize individual relationships as high or low on each dimension. The median was calculated with data from all nine of the companies in the analysis. This resulted in sixteen different relationship types, ranging from H-H-H-H (high on all four dimensions) to L-L-L-L (low on all four dimensions). Below you can see the percentage of relationships that fell into each category for nine different companies.
The first thing to note is that most of the relationships fall on the edges of this chart. Specifically, the majority of relationships are either high communicative, high informative and high responsive or low communicative, low informative and low responsive. We can think of these as strong relationships and weak relationships in terms of volume and quality of communication. Tone is the most interesting of these dimensions in that it appears as both high and low in both strong and weak relationships. One interpretation is that strong relationships with low tone occur between parties who are close enough that they do not bother with niceties in their communication, while weak relationships with high tone occur between people who are not as comfortable with one another. Since tone is so variable, the below chart examines relationship types without tone.
Here we can visually identify whether companies tend toward stronger or weaker relationships between managers and direct reports. For instance, Company 4 has very communicative, informative and responsive managers, while Company 2 has weaker relationships across the board. Of course, as with any data, we must take context into account. In this instance, weak relationships do not necessarily mean that managers are neglecting their direct reports. It could instead indicate a mismatch between the company’s organizational structure and the actual communication patterns within and across teams.
It is also interesting that a quarter of Company 7’s relationships are L-H-L, which indicates that they do not communicate super frequently and do not respond quickly, but what communications they do have are very information-rich. Conversely, at Company 9, 20% of relationships are H-L-H, which means they talk a lot and respond quickly, but their conversations are much more surface level and do not contain as much useful information. As with any data that we share, we do not make any judgments about company culture here. Communicating less than people at our median company does not necessarily indicate a cultural problem, and it is always important to put this data into the appropriate context for the specific situation.
The above analyses break down relationship types at various companies, but they do not offer information about the actual values of these dimensions. Below we share a chart that shows how companies compare to themselves and to each other on each of the four dimensions we measure.
Here we are highlighting two companies with interesting patterns. Let’s look first at Company 1, the purple line. At this company, managers communicate with their direct reports often and quickly, but do not share a lot of information in those communications. These relationships could be considered strong in that they talk frequently, but they may lack substance, consisting more of casual conversation and banter. We discussed Company 7 above and here we can see the same pattern more clearly. Company 7’s managers communicate less frequently and respond less quickly to their direct reports than at some of the other companies we studied, but they share the most information when they do communicate. This pattern can be considered “bursty,” which studies have shown is the most successful way for remote teams to communicate. However, Company 7 also has the lowest tone of all the companies we studied. While this may be acceptable within the context of their particular norms, it could also be something they need to keep an eye on.
This analysis provides a novel way to examine different types of relationships that occur between managers and their direct reports. It improves relationship intelligence at the company level and offers insights that metadata alone cannot. In subsequent analyses, we can dig deeper into the content-related variables to separate them by outgoing behaviors exhibited by the manager towards her team and ingoing variables exhibited by team members towards the manager to learn even more about these important relationships.