The IT company increased the incoming traffic by 44% thanks to collaboration analytics
increase in eNPS
increase in Managers Confidence Index
increase in incoming requests
The crisis has served as a catalyst for processes that began long before lockdown: companies that have not undergone digital transformation have to undertake it right now. Many established companies realized that they have lost flexibility and cannot adapt and innovate at the same speed as they used to, including our client, whose organic growth rate has slowed down from 32% annually in its early years, to just 3.6%.
To restore agility and to increase the declining growth, the company actively recruited new employees and acquired organizations–younger entrants to the market. However, the “new wave” of employees was isolated from the decision-making by “formal managers” with long tenure, which slowed down the entire transformation process. Company’s senior management decided to apply organizational network analytics technologies to optimize the managerial team and balance the number of managers with different tenure in the company. The ultimate goal was to complete the digital transformation and shorten time to market for new solutions.
With extra pressure from pandemics and the enforced transition of all operations online, the management had to act fast. COVID-19 made the split between formal leaders with long tenure and recent joiners even more prominent, and the implicit conflict was tearing the company apart in the times, when every minute mattered. The management couldn’t spare a month to wait for the results, so their primary criteria was the speed in obtaining ONA. Once they learned that Yva.ai can perform ONA using the historical passive data in just two days, they opted for the solution.
Orgchart: people with flags are formal managers
Blue - employees with long tenure
Green - employees of the “new wave”
Yva’s neural network analyzed communication of more than 4,000 employees of the company and processed over 11,3M Slack messages and emails sent over 6 months in order to detect informal leaders through communication data.
The senior management could see from the data they hold that the recently joined employees were underrepresented in the managerial team, but they wondered how this affected decision-making. To balance the team, they were ready to make some changes, but they didn’t know who should be promoted. Management decided to apply organizational analytics technologies to identify informal leaders among the "new wave" of employees and "old-timers", as well as identify "detached formal leaders" – those who kept a formal managerial position but had little to no influence on decision making.
After two days, the management could see the following picture:
Yva-generated OrgNet: large dots are “active decision-makers” among whom are both formal and informal managers. Detached formal managers are indicated with small dots in the centre
The analysis revealed the misalignment between formal and informal leadership in both target groups–not only the existing organisational structure was asymmetric towards the employees with longer tenure, but also only 58% of formal leaders were actively involved in the decision making process.
“Of course we made an educated guess about the results we would see – we knew one group of people was underrepresented and we could even suggest some of the changes had been blocked by formal managers with longer tenure. What we couldn’t imagine was the misalignment between the formal and informal management to be that astonishing.”
– a senior manager of the company
The action plan
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