I know a lot of artists and scientists, and the story is the same for both: be “proud” or be “paid”.

This came up when I was talking to a friend who has a band that plays some music I happen to like, Graveyard Fields.

I recently ran across Mark Joyner’s “Online Music Promotion Course”, and I recommended it to my friend the musician.

Mark Joyner is an “internet mogul” who pioneered many aspects of early online marketing, and now runs a series of courses on managing time, money, and energy. I’ve gotten a lot out of Mark Joyner’s various efforts. For one, I’ve learned how to better promote my own scientific work.

I thought that my musician friend needed some marketing help, so I told him about the course.

A few days later, I asked him, “did you sign up?”

His response distilled down was “it was too much marketing for me.”

I was a bit flabbergasted – but not surprised.

I see this all the time. I used to hold this attitude. In fact, I used to resent some of the well-known scientists who are good at “marketing” themselves (almost all well known scientists are good at marketing themselves, unless they were the 1-2% that got really lucky by being “discovered”).

A month ago, I attended a book writing session at the Science Online conference near Raleigh/Durham NC. I saw the same dynamic play out.

There were three published authors running the session. Guess which one of those was the most successful (in terms of buzz, interest, interviews, and perhaps, money made)? It was the author who had been doing her own marketing for more than a year before the book was published, through Twitter, Facebook, and blogs.

After the authors spoke, questions were asked. There were questions on how to get “discovered”. It seemed clear that at least part of the audience were only interested in practicing “their art” – not in doing their own promotion.

But the odds of being “discovered” without sufficient self-promotion are about the same as the odds of winning a lottery.

Hey, I didn’t make the rules. Sometimes I am not proud to have to “market” my work. But the evidence is all around: if you don’t promote your artistic (or scientific) work, you are very unlikely to get any gravy from it.

I’m not exactly sure why the world has changed to the point where this is so necessary, but I have an idea.

I believe that it is the constant cacophany of other “marketing” messages that are out there, screaming for your attention.

I know plenty of people who hate this. I know one person who changed cell phone providers simply because of their marketing.

But recently I had an interaction that was revelatory to me.

I joined an online copywriting course, focused on marketing copy.

I sent a sample of one of my bits of work to the instructor. He sent it back completely rewritten, and I thought it sounded like a late night infomercial. When I told him that was my response, he wrote back saying: “the reason it sounds that way is because that works – those guys spend millions of dollars on those infomercials, so they tune and tweak them until they pay off”

It is so bizarre to me, sometimes, to write ad copy. But I’ve done some testing myself – and the “late night infomercial” approach is statistically superior to bland and understated in terms of response.

Science is a creative product – just like books and CDs. While one can’t go about writing “late night infomercial” style headlines for manuscripts or grant proposals (I’m sure that would backfire), it is essential to pay attention to how the work is being “marketed”. (aside: most science work is not marketed at all – that’s why most articles get buried in the trashbin of history so rapidly).

Here’s another way I can verify this. My mother was a successful watercolor artist. What do I mean by “successful?” I mean that she paid the bills by selling her art – without ever holding a “side job”.

How did she do that? A majority of her revenue came from marketing notecards and prints with her art on it. Only a fraction of the revenue came from selling the paintings themselves. She figured out early on that she had to “market” her work. She didn’t necessarily love that aspect of the work. But she did get to avoid working as a clerk at Wal Mart.

While I don’t have hard statistical evidence on this, I think the anecdotal evidence is so strong as to be almost irrefutable – if you don’t learn how to market your own creative works effectively, then getting paid reasonable money to do that work is unlikely.

The bottom line for my friend (and many others I know who hate to hear mention of “marketing”): “you can be too proud to market your work, or you can can get paid for your work – but not both”.

Speaking of that, do you want a preview of my upcoming book, code named “Marketing Your Science”? People who sign up for my newsletter list right now get a free copy of Chapter 1 – Why Marketing Your Science Is Important.

It’s that little box in the upper left hand corner that is beckoning to you.

Science Online 2010 is a confluence of writers, scientists, bloggers, and folks figuring out how the internet, science and writing are coming together.

This session is an exploration of how to be a scientific author in today’s online world.

One of the main messages of the session is what I’ve been doing with this blog. The idea is that long before the book comes out, to build a community of people who are interested in the subject matter.

I’ve been doing that here, long before my book is ready. To me it seemed like “gut instinct” as part of the things I do now that I’ve learned a lot about marketing.

But it is clear that this is not a natural approach for many people.  At the conference today, Thomas Levenson discussed how he had failed to do this for previous books, and they hadn’t been as successful as he’d hoped.  He pointed to the example of Rebecca Skloot (who was also there at the session) who had been building an audience for years through blogging and twitter before the release of her upcoming book “The Immortal Life of Henrietta Lacks”.

Blogs (and social media) are all about having a discussion.  As Rebecca pointed out, you can’t just show up and say “hey, I’m here, buy my book!”  Would you do that at a dinner party?  Nope.  You have to get people interested first.

From the perspective of marketing (what I’m writing about in my own book), this is about a value exchange.  You have to give people something to get something from them.  So, if you want people to follow you and pay attention to you, you have to give them value.  Value is the key medium of exchange, but few of us are taught about the importance of this.

I think that comes from a perspective where most people work in paid jobs of some kind where there is no clear concept of the “value exchange”.  Often when working for pay, that equation gets lost.  It just becomes a “job” that one “has to do” rather than “hey, I’m giving my time in exchange for the salary I’m getting.”

But in business, this equation comes clear quickly!  If you don’t pay attention to this in business, that business won’t be around for long!  The business must offer value to its customers in order to get their money.

So, my take on this session is to give out great value, and build an audience based on that value – then publish your book.  That audience will probably go buy it because you’ve already given them lots of value, and they will probably want more of it.

Why is the format changing?

Starting in January, NIH is implementing a shortened grant format for all of the main grant types, including R01’s and K awards.  This came from very long and involved deliberation with many members of the research community, spanning years. The key message that prompted the NIH to do this was that everyone felt like the whole grant writing and grant reviewing endeavor was wasting far too much time. On that point I am in complete agreement!

Whether or not the new format will fix this problem remains to be seen.

What is the new format?

First, the length is much shorter.  The old R01 format was 25 pages for the research plan, whereas the new one is 12 pages. That is a significant change. (See Page I-15 of the new PHS 398 forms for details on the new length requirements for various grant types.)

But there is another change that is also important, the reformulation of the “Research Plan” from the old format into a “Research Strategy” in the new format.

The research plan in the old format consisted of the following subsections: Background & Significance, Preliminary Studies and Progress Report, Research Design and Methodology.

The rules for the new format ask for a different set of subsections: “Significance, Innovation, Approach” (see page I-41 of the phs398 guidelines).  This is an important change. I discovered this when I attempted to write a few proposals using the new format for ARRA grants.  My old methodology for putting together a proposal had to be significantly revamped to make it work.

Perhaps the most important attribute of this change is that the “Preliminary Studies and Progress Report” is gone!  All preliminary studies and progress are wrapped into the approach section.  So, this one little section must convey, in about 5-6 pages, what 15 or more pages would have conveyed in the old format.

In my submitted proposal using the new format, I got hammered for “lack of detail” provided.  But apparently, everyone else must have been hammered for that, too, because I got funded.

Another important difference is the inclusion of a complete subsection addressing “innovation”.  In the old format, while “innovation” was supposed to be there, it wasn’t made so explicit as this.

This seems like an experimental gambit on the part of NIH, to try to force the system to provide more funding for truly novel and innovative work.  It attempts to address one of the biggest critiques of the NIH review process in the past, which is its rampant conservatism.  The saying has always gone something like: “You can’t get funding to do the work until you’ve already done most of the work.”

Will the inclusion of an “innovation” subsection help with this?  I think it is a baby step in the right direction, but I doubt it will overcome the overall conservatism of the NIH review process.  Nonetheless, in formulating a proposal, it will be important to start out with a clear picture of “what is innovative” about your work from the start.  I suspect that proposals lacking a clear statement addressing this won’t do too well.

Perhaps the most minor change is the switch of the subsection “Background and Significance” into just a “Significance” section.  This can be boiled down to the NIH saying something like: “We want to hear more about why the work is important than we do about the history of the science leading up to it.”

Given the low available page count, that makes sense.

How will it impact you?

There was a recent article in The Scientist about concerns that the new format would harm young investigators:

Specifically, some critics say the new, shorter forms — down from 25 to 12 pages for R01 grants — will favor better writers, making it more difficult for younger investigators to compete for NIH funding.

The argument of this article is that if you are a young scientist, then you aren’t as capable of writing a concise, focused proposal, and so you are less likely to succeed.

I’m not sure that I agree with that viewpoint.

On the one hand, young scientists seem to often have a harder time conveying the big-picture value of their work to the audience (which is one of the main reasons for this blog and the book I am writing).

On the other hand, the old format allowed for sometimes excruciating experimental detail and methodologies.  I believe that benefitted established investigators who already had this stuff worked out (i.e. “who had already done the work”).

The first few major proposals I submitted were rejected, until I submitted one where I had already made the major innovative leap (i.e. done the most important work), and the proposal was just to fill in the details around it.  The old format allowed me to describe in quite gory detail how we had made it work, and how we would extend that.

This new format wouldn’t allow this.  With its combination of much shorter length, and focus on an “innovation” section, it will make it much harder to take work that has a long history and provide a bunch of impressive detail about that work.  This should actually remove some of the traditional advantage that experienced investigators have had over their newer colleagues.

Further, there is some benefit for young investigators in not being habituated to the old format.  My first ARRA proposal in the new format was a lot harder for me, because I am so habituated to the old format that I first attempted to write that proposal the way I would have written a regular R01.  After writing 15 pages of stuff, and still having a lot more to go, I realized that I had to completely re-think my approach.  I ended up rewriting a lot of it.  In this sense, a new investigator has little disadvantage over someone like me, because we are both new to the format.

So on balance, I don’t agree with The Scientist that this new format harms young investigators disproportionately.

Being a stellar writer is a key to science career success

I was somewhat offended by the article’s implication that young scientists weren’t as capable at writing as their more senior counterparts.

Any young scientist who wants a successful scientific career must absolutely learn how to write well, regardless of the whims of the current grant formatting requirements.  This is a vital foundation for nearly all scientific career success.

To imply that this is only something that can be gained after many years of grant writing experience is silly.  It can be learned – if you pay attention to learning it and focus your efforts on doing so.  The reason most people don’t learn this until later in their careers is because nobody teaches it to them.  Most seem to go into new positions not realizing that their lack of training in critical skills like this is a problem, and so they have to learn about their own deficits in training the hard way (e.g. grant rejections).

I am a good example of that.  When I wrote about my experiences with my colleague giving me major critical feedback on my specific aims, there was a key point I was making, without being explicit about it: that the experience with my colleague forced me to realize that I had a lot of learning to do, and that I needed to get my butt in gear to do it.

And so I did.  Since that single decision I made, my proposals have had much better track record than before.  I was able to learn how to do it, simply because I decided that I needed to learn how to do it better. I sought out a mix of resources, some of which I’ll be talking about in future posts.  But the key is in wanting to learn to improve.

The first step is acknowledging there is a deficiency.

But for young scientists who acknowledge their own limitations with respect to writing well, and who work hard to overcome them, I don’t think that senior scientists will have an advantage over them. I’ve seen some not so great writing from many senior scientists (perhaps because things weren’t so competitive when they got started).  On a skill as important as this, it is better to start learning earlier than later.  The brain seems a bit more flexible when young.

Additional resources

First, if you are about to prepare a proposal, have a look at the new phs398 forms and documents earlier rather than later.  Writing to the new format requires a different approach.

Second, you can sign up here to gain free access to a foundational preview chapter from the book I am writing, “Marketing Your Science,” that will help you see any scientific communication you produce in a new and more effective way. You’ll also get access to a video covering one of the key points of grant writing: “You have 60 seconds”.

If I run across any other good discussions of the new format, I’ll send them out to my list members or post them here.

One of the reasons I started this blog was to give pointers to young scientists who are trying to learn how to effectively convey their science to their audience.  I see many challenges that graduate students and post-docs face in this arena.  In fact, I believe that the inability to effectively convey one’s science is the biggest road block most of my trainees have faced. While that may not be a valid statistical sampling, I suspect that it represents a wider and deeper indication about the lack of preparation that many folks have to face the real-world needs to convince an “audience” that one’s scientific work is worthwhile.

I want to cover just one example of this today.

I am working on a book chapter project with a person in my lab, describing a new algorithm we developed. (I am intentionally vague here so as to not put that person on the spot).  One of the main components of this book chapter is going through an example of the program running on a data set, then discussing its output.  My co-author chose as the sole example of program operation one that had many pathological features.  He did this in order to illustrate where and how the program might fail.

There are several problems with this.  One, it is likely that this book chapter will be the first time that a reader will have heard about our algorithm.  If we tell them all the ways that it can fail as the first example of its operation, they’re going to go away thinking that it is junk.  Have you ever gone to buy a car and had the car salesman point out all the ways the car could fail or break down?  Never – because you would not ever buy a car from that person, and that person would very soon be out of a job.  While one would hope that scientists are a bit more circumspect than car salesmen, the underlying psychological principles are the same.

A second issue is that this is the only example provided in this chapter draft, so the only result the reader will see is this one that has a number of issues where the program failed.  However, the chapter is aimed at potential users of the algorithm.  Telling them how it is likely to fail doesn’t convey how they should maximize the use of the program on their own data.  Nor does it encourage them to do so.  It may be ok to include this as a second example, after a first one is shown that works well.  By showing the differences between proper operation and poor operation, we might expect the reader to learn more about the strengths and weaknesses.

As scientists, one of the biggest hurdles all of us face is convincing others that our work is worthwhile.  This problem is particularly acute for those of us who develop software as part of our science.  It is all to common to develop a piece of software, then have it just sit there, mostly unused.  That is a big waste of time and money.  I used to think if I developed great software, the world would come knock down the door looking for it.  That was naive. There are thousands of pieces of software out there, and many of them work poorly.  A potential user (e.g. biologist) could waste a tremendous amount of time trying them and attempting to get them to work, so most people don’t.  The biggest barrier we face as developers is getting people to even consider or try our software in the first place. This is followed by a second big barrier, which is convincing people to keep using the software, especially if it doesn’t work perfectly the first time out of the gate (what software ever works perfectly?).  To address these hurdles, it is our job as authors to convey emotions such as enthusiasm and excitement to the reader.  Only if we can get the reader sufficiently emotional about the software (in a good way) will they be likely to ever give it a shot, and persist through any problems encountered.

So if the first document that people see about our software shows more about how it can fail than how it can succeed, most people will never bother trying it.  Describing things that way does not engender positive emotion or enthusiasm, so they’ll just move onto the next thing.

In the case of this book chapter draft, the use of the negative example was exacerbated by the way it was described.  My co-author chose to leave the fact that the example had several pathologies as a “surprise”, meaning that it wasn’t until after the output of that example was presented, that the pathologies were discussed.  When I first read this part of the draft, I expected that I would see a good working example.  As I got into the text describing it, the deficiencies were then described matter-of-factly, as if they were just par for the course (read: normal behavior).  If the “normal behavior” is deficient operation, the reader’s enthusiasm is substantially quelled.  I probably wouldn’t try software that had been described like this.  I would move on.

This illustrates that how one sets up readers’ expectations are important. If my co-author had indicated from the outset that an example was intentionally chosen to illustrate some pathologies, and clearly indicated that this was not the usual, expected behavior, I might not have been so surprised (on the downside) when I encountered the actual output.

This is not by any means the first time I’ve encountered this type of problem in a student’s writing.  And it is not associated only with writing about software.  The problem can plague writing about any kind of science that one might do.  I believe it stems from prior training in undergraduate or graduate laboratory classes, where a student is asked told to do experiments then write them up to turn in for grading.  In my experience, the number one focus of such assignments is making sure that the student has accurately performed and represented his/her research. If the student overstates or misstates any results, he/she gets harshly penalized.

It is well and good to definitively teach students not to overstate or misstate their results, because to do so can be career destroying.  But in focusing on the negative, I believe many instructors overlook the nearly equal importance of teaching students to emphasize the positive in their work. That’s pretty hard to teach when the students are just doing the same old experiment that has been done by thousands of other students and replicates something originally discovered by someone now long-dead. There’s no room in such a context to teach the importance and power of conveying excitement and enthusiasm about positive results (while retaining a proper balance with realism).  Because of that, when students come to my lab, almost none of them seem to understand this crucial balancing act, and in fact it is often a long, slow road to teach them.  In my own career, I struggled with this point all through my graduate work, post-doc work, and even through my first years as an assistant professor.

In the case of our book chapter, my co-author could have presented a positive (but realistic) example, then either presented a second, more pathological example, or just discussed in the text what pathologies might occur in certain circumstances.  This approach would have the likely effect of more positively conveying the work, while realistically acknowledging its limitations.

So that concludes my first pointer, and it is a very important one: nobody is going to tout your work for you, you have to do it yourself, and it is a critical part of any type of communication you produce as a scientist.