Talent Vectia is a Finnish consulting company that helps companies grow, renew, and develop their operations. Talent Vectia has developed a digital discussion platform, LOGE, to help companies implement new practices and skills.
With the help of the LOGE environment, all users participate in joint discussion and learn together interactively. LOGE’s effectiveness is strongly based on communication between users. With LOGE, employees of companies can share their knowledge and learn new things together.
During and after the various implementation projects carried out with LOGE, Talent Vectia wants to summarize the discussions that have taken place during the LOGE sessions and to find out what topics the participants of the various sessions have discussed with each other. Going through such quantities of text material manually would be very laborious, and would also be subject to various errors and misinterpretations.
Loihde Advance helped Talent Vectia process all the discussions of one training session and search for panels (i.e. topics) that emerged from the discussions. Text material proved to be challenging. Many different abbreviations and the company’s own “slang” were used. The text also contained a relatively large number of typographical errors, and the ideas of the participants in the LOGE sessions were summarized very briefly in the texts.
The text material was successfully analyzed with SAS Text Miner. For each LOGE session, 3–5 different topics of discussion could be automatically identified. Although SAS Text Miner is specially designed for analyzing massive text materials, we were able to make it work surprisingly well even with smaller volumes of text.
Observations from LOGE sessions obtained with analytics help Talent Vectia’s customer company choose the most favorable follow-up measures for the change process and inform employees about the progress of implementation.