30 Days of Gratitude: Day 15 - Librarians

Yes, I already said libraries, but this post is about librarians and information professionals. The other day I sat on a panel for a Michigan Special Libraries Association event called, "Doing Library Different." The four speakers, including myself, were all in non-traditional library positions - researchers, analysts, data directors, database managers. It was wonderful hearing the advice of my colleagues about how to use what you gained in library school in a variety of positions. And I'll be honest, I love sharing my experiences, too. It's my favorite part of the library and information community - we are all about sharing information, knowledge, stories, advice and encouragement. Here are some of the things I shared and heard:
  • Your experience and MLIS is what you have to highlight. The fact you can gather lots of information and tell a story with the data is what makes you valuable to an organization. If the company needs an engineer, they'll get an engineer. But if they're looking for someone that can find, analyze and present data, than it's our profession they can look to.
  • Indexing and cataloging are NOT dead.
  • Take the part-time work. Special projects interest hiring managers because it indicates that you are flexible and are willing to try different types of experiences.
  • Write a new resume and cover letter for every job posting. No exceptions. 
  • Writing, using Microsoft Office, presenting and customer service are all transferable skills and are sought after by employers.
  • Volunteer. If you want hands-on experience that you can add to you resume - go to your local library, school, historical society, museum and spend time working in an environment you like.
  • Seek work at places you like. Get familiar with their culture, jargon and people and when the right posting comes up, you will be ready.
  • Never data dump. We have to realize that even though we're comfortable with data, not everyone else is. In fact, most people are not comfortable with large sets of data. We need to abbreviate without losing the information's context and meaning.

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