Congratulations, you got the job. Now what?
Even if you are experienced in your profession or lowly intern, being the new person is difficult. I have changed jobs in my life more times than I can tell you. Regardless of your position, everyone has to learn all the unwritten rules, culture and personalities of everyone. Hopefully, you have a sense of your supervisor from from your interview, but here are some strategies to get you through that learning curve quicker.
Ask specifics about dress code.
Libraries, particularly, have such a wide range of dress codes, it is difficult to pin this down. Don't assume that how they dressed for your interview is the norm. Even if they don't have a specific code or can't articulate it, always dress "up" initially. Shoes should be appropriate, flip flops are ALWAYS wrong. One manager told me she appreciated that someone thought about this and asked.
Refrain from judgments on rules/policy.
Even if you think the rule is crazy/stupid and utterly ridiculous, hang back from overt criticism. If you think it is utterly insane. Ask for clarification with a manager. Don't complain to co-workers or mutter "this is so stupid". (Even if it is.) File your objections away until you know more.
Manage your training.
This means you need to take charge of your training as you would any project. I have heard many managers complain that they show a procedure time again, and yet the trainee doesn't seem to really try. I have had employees ask me to help them with a patron on the copy machine or computer etc. Of course I will, but I want you to follow up on how that process/procedure works. Don't assume since I have "handled it", you are off the hook for learning.
Know how you learn best.
Personally, I have to do something many times before I am comfortable. Others work from step by step instructions or reading a manual. Often there is no structured training or the training is terrible. Develop a strategy to work around inadequate training. Strategies to try: shadowing an employee, taking notes, making lists of issues to clarify and making cheat sheets. Libraries can be chaotic. Makes it difficult to learn, but on the other hand, you are seldom bored.
Follow up
Ask for feedback about areas you need to re-learn or practice. Listen carefully and don't panic or be defensive if your trainer has issues.
Build up goodwill
Don't be the person who needs time off or favors until you have been there awhile. Build up your reputation by volunteering for duties or shifts no one else wants. Offer up help or do a favor for others.
Being the new person is difficult, but give yourself a break. You will be tired (learning is hard work). Most managers know that it might take awhile for you to get on top of things.
Good luck to all the newbies out there!
Mary
Monday, May 6, 2013
Wednesday, April 24, 2013
DIY Tech Training
One of the common complaints I hear from supervisors (not just in library work) is the lack of initiative when it comes to expanding your skill set. It is particularly tough for librarians as resources are not there for more training or conferences.Unfortunately, this does not relieve you of your responsibility to stay "on top" of the profession. Technology is tough. So, how do you do reasonable tech training with no money and limited time?
Start Small
You can start anywhere. Just start. How about using Excel more efficiently? HTML? Pick one thing you think might be interesting. Do not worry if it doesn't automatically turn into something you can use right away at your job.That doesn't always happen.
Let's use the Excel example. I am pretty good with Excel for my job but I am probably am not taking full advantage of all the possibilities of the software. Learning all of Excel would be overwhelming so just pick one thing. It can be anything. Just jump in with a question. "How do I make a Pivot Table?" Stick to just Pivot Tables and don't try to understand the entire world of Excel.
Reading a manual is hard for me when learning something for the first time. I like manuals after I get the basic idea for reinforcement. (Each person learns differently. Use what works for you.). Since I need a demo, I go right to YouTube for a demo. I play it a bunch of times and then try it on my own. Lather, rinse, repeat until you have this down solid. Depending on your topic, the time spent can usually be done in 10 minute bites.
Where to Find Training
Most examples of anything technology can be found somewhere in the library or on the Internet. The places I have been haunting in my quest:
Finally, talk to other librarians on what they have used to learn new technology or upgrade skills, Everyone has a unique perspective. Tap into your librarian network.
Commit to technology training even if you have no support or management in your library thinks its a waste of time.
Mary
Start Small
You can start anywhere. Just start. How about using Excel more efficiently? HTML? Pick one thing you think might be interesting. Do not worry if it doesn't automatically turn into something you can use right away at your job.That doesn't always happen.
Let's use the Excel example. I am pretty good with Excel for my job but I am probably am not taking full advantage of all the possibilities of the software. Learning all of Excel would be overwhelming so just pick one thing. It can be anything. Just jump in with a question. "How do I make a Pivot Table?" Stick to just Pivot Tables and don't try to understand the entire world of Excel.
Reading a manual is hard for me when learning something for the first time. I like manuals after I get the basic idea for reinforcement. (Each person learns differently. Use what works for you.). Since I need a demo, I go right to YouTube for a demo. I play it a bunch of times and then try it on my own. Lather, rinse, repeat until you have this down solid. Depending on your topic, the time spent can usually be done in 10 minute bites.
Where to Find Training
Most examples of anything technology can be found somewhere in the library or on the Internet. The places I have been haunting in my quest:
- YouTube - My favorite since it requires very little effort.
- Code Academy - http://www.codecademy.com Courses include fundamentals, PHP, Python, Ruby and others
- Microsoft offers some free courses on Office. If you are really rusty, you would probably like a refresher.
- Udacity offers a beginning computer science
- Coursera offers a variety of science and technology classes.
Finally, talk to other librarians on what they have used to learn new technology or upgrade skills, Everyone has a unique perspective. Tap into your librarian network.
Commit to technology training even if you have no support or management in your library thinks its a waste of time.
Mary
Monday, April 8, 2013
Collection Analysis: Median vs Average
There is more to understanding a collection age beyond average and thanks to Emma, who made a comment on my last collection analysis post, I thought it would also help to discuss median age in a collection. My experience has been that often "average" and "median" are used interchangeably (which is so very wrong!). Median age of a collection really has some serious power in helping librarians talk about collection age.
First, let us get clear on the difference is between median age and average age of a collection. (Again, as I have done in previous posts, the best way to get a handle on the process is to use a small set of numbers until you feel comfortable.) The average is the sum of all the dates in the set divided by the number of items in the set. (If you are using Excel, it will be the @average function)
Here is the example of some publication dates:
Calculating the average is done by adding all the years published is: 19,925. Then dividing by the 10 books in the set, the average age is 1992.5.
The Median age is similar to average in that it can indicate an overall age of the collection, but it actually gives us more information by considering the distribution of that range. Taking the same 10 books, the oldest in the collection is 1975 and the newest is 2013. Median is calculated by examining the middle point of the range. In our example, the median age is 1982. Of course, the wonderful Excel will also help you calculate this with the @median function. You can find this under formulas tab in the statistical functions group.
In our little example, you can already see the dramatic difference in the resulting statistics. Average indicates an age around 1993 and the median is 1982. So what does this statistic mean? It means that most of the books are older and not just slightly older, but REALLY old. Remember 1982 is the middle of the age range.
The difference between median and average is pretty significant in this small set. Over a large set of data this can be very helpful in getting sense of the age. As with average, it is unfair to include items that are in special collections such as a geneaology or local history collection. Archival material should be excluded in such a context. Like average, using this statistic on the overall library collection. Distinct collections or subjects benefit from this statistic, especially where currency is an issue. (Think legal, medical etc.) I like using it with the teen fiction collection, where I really want the latest and greatest. Practice and compare the median and average ages of your particular collection.
Statistics and analysis of your collection should be a regular part of your management and decisions. Boards, directors and other assorted folks in the money part of the collection equation will appreaciate this analysis. It shows consideration and care in your collection.
Mary
First, let us get clear on the difference is between median age and average age of a collection. (Again, as I have done in previous posts, the best way to get a handle on the process is to use a small set of numbers until you feel comfortable.) The average is the sum of all the dates in the set divided by the number of items in the set. (If you are using Excel, it will be the @average function)
Here is the example of some publication dates:
Year Published
|
||
Book
|
A
|
1975
|
Book
|
B
|
1980
|
Book
|
C
|
1980
|
Book
|
D
|
1980
|
Book
|
E
|
1982
|
Book
|
F
|
1982
|
Book
|
G
|
2010
|
Book
|
H
|
2010
|
Book
|
I
|
2013
|
Book
|
J
|
2013
|
Calculating the average is done by adding all the years published is: 19,925. Then dividing by the 10 books in the set, the average age is 1992.5.
The Median age is similar to average in that it can indicate an overall age of the collection, but it actually gives us more information by considering the distribution of that range. Taking the same 10 books, the oldest in the collection is 1975 and the newest is 2013. Median is calculated by examining the middle point of the range. In our example, the median age is 1982. Of course, the wonderful Excel will also help you calculate this with the @median function. You can find this under formulas tab in the statistical functions group.
In our little example, you can already see the dramatic difference in the resulting statistics. Average indicates an age around 1993 and the median is 1982. So what does this statistic mean? It means that most of the books are older and not just slightly older, but REALLY old. Remember 1982 is the middle of the age range.
The difference between median and average is pretty significant in this small set. Over a large set of data this can be very helpful in getting sense of the age. As with average, it is unfair to include items that are in special collections such as a geneaology or local history collection. Archival material should be excluded in such a context. Like average, using this statistic on the overall library collection. Distinct collections or subjects benefit from this statistic, especially where currency is an issue. (Think legal, medical etc.) I like using it with the teen fiction collection, where I really want the latest and greatest. Practice and compare the median and average ages of your particular collection.
Statistics and analysis of your collection should be a regular part of your management and decisions. Boards, directors and other assorted folks in the money part of the collection equation will appreaciate this analysis. It shows consideration and care in your collection.
Mary
Friday, March 29, 2013
Reader's Advisory Strategies
Reader's Advisory is one of my favorite parts of library service. Knowing this, you would think I am a high volume reader. This is NOT true. I don't think I read books much more than the average person. I have some favorite authors and I am addicted to my Google Reader. (We can talk about the retirement of Google Reader another time, suffice it to say, I am bitter and feel betrayed.)
Good advisory comes from the reference interview and discussion with the patron. It has nothing to do with being able to recall thousands of books at the drop of a hat. Engage your patron and share your own ideas. Think less about specifics and listen to your patron and their problems. Listen for themes that might trigger some book/movie idea.Here are some sample clues from my own reference interviews that have helped me pitch ideas:
"I had a horrible week at work and I think my boss is crazy!"
Of course ask follow up questions. What happened? How long has it been this way? Is this normal job frustration or is it something serious? Engage and share. Looking for light or are we talking something more serious? Now start searching: Here are some keywords to get you going. workplace fiction, bad managers, toxic work environments,careers, stress, co-workers.
"My kids are driving me crazy!"
Again think out of the box. Does this parent want to escape with a romance or something serious? Are the kids teens or babies? Maybe something from the nonfiction section. You can also suggest some parenting books but that is almost too obvious. Make sure you listen.
Lots of general day to day chit-chat about co-workers, kids, in-laws, friends, spouses can lead you directly toward some reading suggestions. Also think outside of just books. Think movies, music, library programs/classes. Read Holly Hibner's Library Blog for more ideas on Multi Type Advisory. Holly is also a music geek and also has a series of posts on Music advisory that are really worth reading especially if you don't have music training.
Each conversation we have with a patron is our opportunity to pitch a book, movie, program. Listen and engage and the rest will come!
Mary
Update! This wonderful article popped up on my Twitter feed and I couldn't agree more with this article by Shelley Ann Clarke Learning to Read over at Wonk-o-Mance.
Good advisory comes from the reference interview and discussion with the patron. It has nothing to do with being able to recall thousands of books at the drop of a hat. Engage your patron and share your own ideas. Think less about specifics and listen to your patron and their problems. Listen for themes that might trigger some book/movie idea.Here are some sample clues from my own reference interviews that have helped me pitch ideas:
"I had a horrible week at work and I think my boss is crazy!"
Of course ask follow up questions. What happened? How long has it been this way? Is this normal job frustration or is it something serious? Engage and share. Looking for light or are we talking something more serious? Now start searching: Here are some keywords to get you going. workplace fiction, bad managers, toxic work environments,careers, stress, co-workers.
"My kids are driving me crazy!"
Again think out of the box. Does this parent want to escape with a romance or something serious? Are the kids teens or babies? Maybe something from the nonfiction section. You can also suggest some parenting books but that is almost too obvious. Make sure you listen.
Lots of general day to day chit-chat about co-workers, kids, in-laws, friends, spouses can lead you directly toward some reading suggestions. Also think outside of just books. Think movies, music, library programs/classes. Read Holly Hibner's Library Blog for more ideas on Multi Type Advisory. Holly is also a music geek and also has a series of posts on Music advisory that are really worth reading especially if you don't have music training.
Each conversation we have with a patron is our opportunity to pitch a book, movie, program. Listen and engage and the rest will come!
Mary
Update! This wonderful article popped up on my Twitter feed and I couldn't agree more with this article by Shelley Ann Clarke Learning to Read over at Wonk-o-Mance.
Friday, February 8, 2013
Value of Library Institutional Knowledge
Everyone knows that labor cost is a huge concern to library managers (and civilian managers too!). More than one library director has faced cuts and looked at the hourly rate on the more experienced staff and thought about cutting costs by replacing the more experienced bodies with newbies, interns, part timers and even volunteers. I get it. It looks awesome on a spreadsheet, but managers, you are shooting yourself in the foot by failing to recognize the value of what is called "institutional knowledge".
Institutional knowledge is all that stuff experienced staff people know that can't always be quantified, but does translate into real cost savings. I have seen time and time again those situations where those experienced librarians just know more and it really translates into efficiency. For example, a librarian I know working in children's section with a newbie could simply "recall" titles, authors and other library information at the drop of a hat. If we translate that into "savings". This librarian served more customers and delivered more "outcomes" in an hour compared to the newbie librarian. Of course the newbie is going to have to "look up" more stuff, find a person that knows that particular policy or rule. That's how we learn our jobs. Long term experienced librarians are worth a higher salary. These experienced people contribute to the long term success of the library by training (even if it isn't formal) new people, smoothing over problems and maintaining critical relationships with customers.
Managers and boards that trade high experience/higher cost employees with low experience/low cost are going to end up paying more in the end. And I mean a LOT more. Think of those up coming millages, or fund raising times in libraries. Long term, experienced staff can increase a community's investment in a library. Think about those teens that came to programs with the library and now are growing up with families of their own. Seniors (who are way more likely to pay attention to library tax issues) have a relationship with the library, and more specifically, a librarian, for decades.The value of long term relationships with the community is essential for long term success.
Mary
Managers and boards that trade high experience/higher cost employees with low experience/low cost are going to end up paying more in the end. And I mean a LOT more. Think of those up coming millages, or fund raising times in libraries. Long term, experienced staff can increase a community's investment in a library. Think about those teens that came to programs with the library and now are growing up with families of their own. Seniors (who are way more likely to pay attention to library tax issues) have a relationship with the library, and more specifically, a librarian, for decades.The value of long term relationships with the community is essential for long term success.
Mary
Thursday, January 3, 2013
Another Baby Step in Collection Analysis
As we discussed in my post Using Excel in Collection Analysis, go slow and work a small data set into the ground until you feel comfortable. While you are in "learning mode", use enough data to fit comfortably on the screen, so you can "see" everything at once. For this example, I am using 20 random records from my Juvenile Fiction collection and I am going to focus on evaluating age.
Average is a term thrown around a lot in data analysis. Calculating average is adding up all the dates and then dividing by the number of titles. In other words a couple of really old books can skew the average. So, for library and collection purposes, you need to look deeper. As you can see in my sample data set, the average age of this group of items is 1990.3 or for our purposes 1990. That seems really old, given we are starting 2013. I am now going to re-order the spreadsheet to organize the 20 records in Date Published order (oldest to newest).
In this particular group, 3 of the titles are almost 50 years old and another is a whopping 71 years old. I can feel the panic as everyone collectively gasp: "you can't weed these classics just because they are old!". Before everyone collectively panics and writes to tell me I am a no-good, censoring book burner, hell bent on destroying classics, relax!* The purpose of this sheet is to flag your attention to the collection. When I say "flag" your attention, that means investigate further. It doesn't mean weed.
For this set, I am going to pull the items highlighted in RED as my oldest examples and the first thing I am going to do is check on condition. For Juvenile fiction, I expect paperbacks to hold up about 5 years and hardbacks will last maybe 10 years, if people are gentle. Your mileage may vary.
Average age discussions are best used in the context of sections of the library. When you go through sections of the library and use pieces of the collection, it is easier to catch those needing attention. I particularly like using the average age when dealing with nonfiction areas of legal, business and medical.
Again, I want to remind everyone, what I consider hanging onto in my tiny library in Michigan, is not going to be the same as what goes on in your library. To give you an idea what I did for the above "red" titles, I weeded the Ghostly Tales and bought new editions of the others.
Now go forth and play with the average of your collections and see what pops out!
Mary
* People have already written that shortly after Holly and I started Awful Library Books.
Average is a term thrown around a lot in data analysis. Calculating average is adding up all the dates and then dividing by the number of titles. In other words a couple of really old books can skew the average. So, for library and collection purposes, you need to look deeper. As you can see in my sample data set, the average age of this group of items is 1990.3 or for our purposes 1990. That seems really old, given we are starting 2013. I am now going to re-order the spreadsheet to organize the 20 records in Date Published order (oldest to newest).
In this particular group, 3 of the titles are almost 50 years old and another is a whopping 71 years old. I can feel the panic as everyone collectively gasp: "you can't weed these classics just because they are old!". Before everyone collectively panics and writes to tell me I am a no-good, censoring book burner, hell bent on destroying classics, relax!* The purpose of this sheet is to flag your attention to the collection. When I say "flag" your attention, that means investigate further. It doesn't mean weed.
For this set, I am going to pull the items highlighted in RED as my oldest examples and the first thing I am going to do is check on condition. For Juvenile fiction, I expect paperbacks to hold up about 5 years and hardbacks will last maybe 10 years, if people are gentle. Your mileage may vary.
Average age discussions are best used in the context of sections of the library. When you go through sections of the library and use pieces of the collection, it is easier to catch those needing attention. I particularly like using the average age when dealing with nonfiction areas of legal, business and medical.
Again, I want to remind everyone, what I consider hanging onto in my tiny library in Michigan, is not going to be the same as what goes on in your library. To give you an idea what I did for the above "red" titles, I weeded the Ghostly Tales and bought new editions of the others.
Now go forth and play with the average of your collections and see what pops out!
Mary
* People have already written that shortly after Holly and I started Awful Library Books.
Monday, December 3, 2012
Using Excel With Collection Data - A Baby Step
I am not even going begin to explain the million reasons that I haven't posted something on this blog for almost 6 months. Suffice to say it was mostly distractions, nothing to say and then the habit of not writing. Now Holly and I are in the process of doing a new edition of Making a Collection Count.As we go through the chapters and start really re-thinking the content and updating this book, I really wanted to make the idea of using statistics more palatable to those folks who avoid math at all costs. I used to be the queen of math avoidance. As I got older, went to business school and started working in libraries, I realized that I am actually more mathematically inclined or maybe more comfortable with with data, than my fellow library people.
Aside from budgets, there are lots of ways numerical literacy helps in managing a collection. What I am talking about is really thinking in terms of expressing library functions and trends with hard data. Modern technology makes this much easier than back in the 1970s when I was trying to pass algebra. Calculators and my personal favorite, Excel, can make analysis of library collections an absolute dream.
So how do you get over your aversion to analysis in library science? Use a small example of something you love and work it to death. Start with a small piece of a shelf list of a particular collection. Practice with excel in organizing this spreadsheet in various configurations.
Here is a screen shot of what I am talking about. This is a list of 19 records of Juv Fiction "A" in my collection. (I use Sirsi Dynix Symphony through our consortium. I downloaded a shelf list from Director's Station which can provide all sorts of downloadable data sets.) I only have a handful of records, but really with Excel, size doesn't matter! Practice with a tiny set to work out kinks and figure out Excel functions. When you get more confident, use a bigger data set.
First, you should maybe try some basic analysis to learn what your collection can tell you. Try calculating an average "age" (publication age) of this sample. Use the @average function over the range of dates. Sort your data set by number of circulations. Sort your data by date last checked out. Just a simple couple of Excel functions will begin to give you a start on some great collection analysis.
Of course a couple of hundred words and a screen shot is hardly a breakthrough, but often when I am talking to people they are paralyzed about starting somewhere. Think of this a first baby step into collection analysis.
Not sure where to get a data set? Talk to anyone in charge of your ILS and ask if you can have a report or shelf list downloaded. Jump in and start poking around a shelf list.
Mary
PS Of course if you find something in your wonderful data pile worthy of a mention on Awful Library Books, by all means SEND IT IN!
Aside from budgets, there are lots of ways numerical literacy helps in managing a collection. What I am talking about is really thinking in terms of expressing library functions and trends with hard data. Modern technology makes this much easier than back in the 1970s when I was trying to pass algebra. Calculators and my personal favorite, Excel, can make analysis of library collections an absolute dream.
So how do you get over your aversion to analysis in library science? Use a small example of something you love and work it to death. Start with a small piece of a shelf list of a particular collection. Practice with excel in organizing this spreadsheet in various configurations.
Here is a screen shot of what I am talking about. This is a list of 19 records of Juv Fiction "A" in my collection. (I use Sirsi Dynix Symphony through our consortium. I downloaded a shelf list from Director's Station which can provide all sorts of downloadable data sets.) I only have a handful of records, but really with Excel, size doesn't matter! Practice with a tiny set to work out kinks and figure out Excel functions. When you get more confident, use a bigger data set.
First, you should maybe try some basic analysis to learn what your collection can tell you. Try calculating an average "age" (publication age) of this sample. Use the @average function over the range of dates. Sort your data set by number of circulations. Sort your data by date last checked out. Just a simple couple of Excel functions will begin to give you a start on some great collection analysis.
Not sure where to get a data set? Talk to anyone in charge of your ILS and ask if you can have a report or shelf list downloaded. Jump in and start poking around a shelf list.
Mary
PS Of course if you find something in your wonderful data pile worthy of a mention on Awful Library Books, by all means SEND IT IN!
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