Teams are not only fundamental to the sustainable growth of small and medium-sized enterprises. Teams are also crucial in large companies where the required update speed is exponential in the changing environment of the markets.

The teams in the organizations are like rowing boats with helmsman so they should develop their activity in perfect synchronization, where the balance of the team is more important than the individual talent.

Each member of the team must be aware of their responsibilities and actions, competing with their opponents abroad and collaborating internally with the members of the team, while giving space to the helmsman as an action advisor.

“An organization’s capacity to improve existing skills and learn new ones is the most defensible competitive advantage of all.” – Gary Hamel

Developing new skills and learning from mistakes improves team results. This means that members of a team or teams are working towards a common purpose and goals and in doing so, are sharing their different capacities by playing complementary and collaborative roles with each other.

A clear and compelling purpose is the glue that binds together a group of individuals. It is the foundation on which the collective “we” of a real team is built. Purpose plays this critical role because it is the source of the meaning and significance people seek in what they do. ”

Organizations tend to perform well when their employees work effectively as a team. This happens not only because synergy is created (the whole is greater than the sum of the parts), but also because working together a team can share individual perspectives, experiences and skills to solve problems that are not defined or poorly articulated, creating solutions that would be out of the reach of a single employee.

In addition to improving the performance of teams and organizations, effective teamwork also benefits individuals because it enables mutual support and constant learning, generating a sense of belonging and commitment.

Solving problems is a constant need within the teams of an organization. Understanding the users, consumers, or employees of an organization and questioning existing models often leads us to reformulate the problem and find new, richer and broader contexts.

For this, organizations need new skills and a new frame of mind that embraces empathy, integrative thinking, optimism, experimentation and collaboration. Empathy is a high-performance fuel that leads us to the realization of projects with passion and shared purpose with all who interact with the organization.

If we accept these statements as useful for thinking about problem solving in organizations, then in light of the Predictions about Data Science, Machine Learning, and AI for 2018, we will have to ask some questions:

How to create a common purpose in team members who are confronted with this problem?

“Prediction 1:  Both model production and data prep will become increasingly automated.  Larger data science operations will converge on a single platform (of many available).  Both of these trends are in response to the groundswell movement for efficiency and effectiveness.  In a nutshell allowing fewer data scientists to do the work of many… working in code is incompatible with the large organization’s need for quality, consistency, collaboration, speed, and ease of use. ”

How to integrate and develop new competencies to respond to the evolution of different business approaches?

“Prediction 2:  Data Science continues to develop specialties that mean the mythical ‘full stack’ data scientist will disappear…

Similarly, the needs of different industries have so diverged in their special applications of predictive analytics that industry experience is just as important as data science skill…. Whoever hires you is looking for these specific skills and experiences. ”

How to bridge the change of direction of functional content of many employees?

“Prediction 3:  Non-Data Scientists will perform a greater volume of fairly sophisticated analytics than data scientists… the reality is that advanced analytic platforms, blending platforms, and data viz platforms have simply become easier to use, specifically in response to the demands of this group of users. ”

How to prepare the teams of organizations for the evolution of Deep Learning?

“Prediction 4:  Deep learning is complicated and hard.  Not many data scientists are skilled in this area and that will hold back the application of AI until the deep learning platforms are significantly simplified and productized….

Prediction 5:  Despite the hype, penetration of AI and deep learning into the broader market will be relatively narrow and slower than you think.”

How to make employees aware of the possible harmful effects of misuse of AI?

“Prediction 6:  The public (and the government) will start to take a hard look at social and privacy implications of AI, both intended and unintended.

Since the purpose of an organization is the direction it intends to follow, supported by its values ​​and habits shared by its employees (culture), how can talent management teams keep the boat with a strong paddle and direction in the face of these predictions?

 

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