1. Data in today’s world can assist in formulating a clear strategy. An organization’s data, generated from its
daily workflow, is the basis for Artificial Intelligence assisted modeling. This Artificial Intelligence further
allows for the prediction of organizational change and an objective view of complex human networks
through bespoke machine learning algorithms.
Characteristics of collaboration and malfunction (e.g. attrition and high employee turnover) become visible
through these machine learning algorithms and, thus, change management, strategy development, and an
organization’s ability to predict and control its future becomes clear.
What we do:
 We combine social network science with business
research and experience (more details: Gallup, Harvard
Business School, MIT, McKinsey, BCG, etc.).
 Our machine learning algorithms build up complex
knowledge on data which illustrates employee
interaction.
 Relationship revelations become visible and tangible
for corporate use.
 Change management and corporate development
initiatives are supported through intelligent modeling,
enhancing change planning and development.
As a result:
 We provide fact-based information for the decision-maker/s and ensure coherent, informed planning
through precise survey result analysis.
 The complex human organizational network becomes visible, demonstrable, and comprehensible.
 We support corporate communication and information efficiency by reducing network losses through
e.g. information redundancies, bottlenecks, and other knowledge and information operational
inefficiencies.
 Our solution improves investment returns through maximizing the efficacy of training programs to
improve human (and thereby corporate) development; this ensures recruitment costs are contributive
rather than continual, through informed processes, and salaries and other benefits are at optimal levels
for staff retention and continuity.
“The efficiency of communities depends on the participants’ interactional network as much or more than it
depends on everything else, such as combined knowledge with experiences, with IQ, with skills, etc.”
– Alex Pentland, MIT
References:
Data-driven human networks