The data-oriented colleague - Deepstash

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The data-oriented colleague

Their strengths are in analyzing data, logical processing, and solving complex problems.

They are focused on achieving the established goals and will ensure that you stay on budget.

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Their strengths are in establishing order, structuring projects and tasks, and accuracy.

They do not miss a typo and will ensure that work is completed on time.

In any organization you will usually find these main work styles:

  • Logical, analytical, linear, and data-oriented
  • Organized, sequential, planned, and detailed-oriented
  • Supportive, expressive, and emotionally oriented...

Work styles refer to the way we think, structure, organize, and complete our work

They the foundation upon which businesses operate and grow today.

Their strengths are in building relationships, facilitating team interaction, and persuading or selling ideas.

They will ensure that all of the project stakeholders are up to date on the project and that your ideas are effectively communicated throughout the organization....

Their strengths are: being a catalyst for change, coming up with solutions to problems, and integrating and synthesizing disparate ideas.

They will ensure variety in both thought and execution and they will make sure that you do not stagnate.

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Pioneers

Those with a pioneer working style are big-picture thinkers who want to take advantage of opportunities or create new ones.

They tend to not be detail-minded, and they make quick, spontaneous decisions.

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Communication during stressful times

Uncertainty has a way to reveal everyone's strengths and weaknesses. During drastic uncertainty, employees will seek more information in order to achieve a sense of certainty. During this unstable time, you'll discover the true quality of your team's communication skills. If you team is arguing, ...

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The Data Scientist presentation style

The Data Scientist uses data, analytics, facts, and figures to make his point and persuade the audience. 

Pros: This presentation style delivers data, information and analysis and will almost never be filled with fluff.

Cons: an audience that doesn’t want analytic...

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