We take you through 10 best practices, considerations, and suggestions that can enrich your Microsoft Teams deployment and ensure both end-user adoption and engagement.
In a world of broadband internet connections, online collaboration tools and the ability to work from almost anywhere – office culture can be difficult to sustain. This especially holds true for people who live in large cities (where the commute can be problematic) or in harsh climates (like the never ending winter in Chicago this year). Yammer can help by creating remote social interactions.
Yammer is an enterprise social network that aims to connect people in the office. A few of its features are instant messaging, user profiles, a primary news-feed, interest groups, recommendations for people to follow, groups to join as well and a recent activity feed. The interface is clean and well designed. One of the great things is that once you start using Yammer it is really easy to continue.
There is one area where Yammer seems to fall short. There is no clear way to bring people together who have common interests. The other users and groups that are recommended to me by Yammer are made based on the groups I am a part of and people I follow. It does not take into consideration any of the data in my user profile.
Perficient recently held a hack-a-thon where my team identified this short coming. Social interaction via online collaboration tools wasn’t cutting it. In an online culture how can we leverage all of our tools to help facilitate more meaningful social gatherings? The answer was to use interest data that co-workers have provided through Yammer to generate meaningful recommendations. A Yammer profile consists of many different “interest groups”. It lists categories such as Expertise, Interests, Previous Company and Schools Attended. All of these can be classified as conversation topics and can be used as a common social interest.
This is where HDInsight powered by Hadoop and Mahout can help. Mahout can consume massive quantities of information and return logical connections represented within the data. For additional reading about Hadoop and Mahout click here.
Using an HDInsight Hadoop cluster in coordination with the Mahout recommendation engine we could provide meaningful recommendations to users based on their individual interests. This wouldn’t just recommend topics that a user might be interested in but also groups they could create or join with other users based on their mutual interests – similar to the recommendations Facebook suggests regarding people you may know, groups to join or pages you may like.
Creating these logical, online groups would “connect the dots” to uncover a similarity between people where it might otherwise remain hidden. It could also help facilitate in-person group outings, social gatherings or simply more friends and comraderie in the office. Through this you are creating a more meaningful environment aided by technology.
A thriving office culture can stand out in a world where telecommuting tends to be more convenient. This may not convince everyone to come to the office. However, instead of viewing it as obligatory, implementing a solution like this can encourage more people to choose to commute to the office for the social comraderie. All of this can be done for free through the Yammer API and a Windows Azure account.