Tuesday, May 7, 2013

Ball of Confusion

The following is a guest-post from UPM Director Leila Salisbury. This article, appeared in the issue of Against the Grain. Against the Grain is a great journal for those interested in how academic libraries think and operate and how vendors shape their strategies to work within the changing landscape of scholarly communication.

As I received the deadline reminder for this quarter’s ATG column, I was finishing an email exchange with our marketing and business directors that had begun with celebration over a healthy payment from one of our electronic content vendors and had concluded with something to the effect of: “What’s the sales model for that vendor? Will those checks be getting smaller as the number of new customers diminishes after the initial launch period?” This exchange reminded me that some/much of the time, I couldn’t rattle off the exact terms and offerings of our numerous e-vendors. In-house conversations often go something like: “Ebrary, wait, did they add the STL model that becomes a full purchase after four lends, or am I thinking of EBL?” It might be comical if it also didn’t also seem kind of scary. (In an interesting twist, after I began this article, I learned that ProQuest had just acquired EBL, as it earlier had Ebrary. Mergers and acquisitions may be the ultimate solution to this issue!)

In this burgeoning era of digital content (where talk is rife with acronyms such as PDA, DDA, MUPO, SUPO, STL and the like), I sometimes hear librarians say that there are so many options and models out there that it’s all highly confusing and difficult to determine which vendors and what types of plans will best suit the needs of their library and patrons. To this I say, believe me, I hear you. Or to quote the lyrics to “Ball of Confusion” (pick your favorite version of the song, but they’re all surprisingly applicable to today for something written in 1970): “So round ‘n’ round ‘n’ round we go / Where the world's headed, nobody knows.”

I tend to believe that this profusion of offerings and models is a natural result of the “offer the customer a lot of options, a choice to suit every customer profile” mentality. Perhaps we are like the consumer standing in the cereal aisle at Whole Foods, trying to determine which of the 18 available organic cereals is the right one for us. “Which is more important to me, high protein or fiber? I like that this one has flaxseed, but wait, Jimmy is allergic to strawberries. This one looks good and I like this brand, but can I really justify spending $6.50 on a box of cereal?” Sure, this takes longer and requires more consideration than did simply grabbing the box of All-Bran in days past, but there are upsides as well. There are many tantalizing flavors (user models) to choose from. We have the option to preference either protein (collection/subject based building) or fiber (PDA). We are increasingly romanced by the benefits of flaxseed (STL) but refuse to knowingly cause allergic reactions in our family members (too-quick browsing purchase triggers in PDA plans). Finally, we are lucky to have that $6.50 at all, not to mention that we also have the choice to spend it in the way that best benefits our family (library and patrons).

I won’t further belabor this already-strained cereal metaphor. What this scenario means in practicality, though, is that we (both as publishers and librarians) are being forced to get much better at math, forecasting, and multi-criteria decision making. Mark Saunders, of the University of Virginia Press, characterizes the publishers’ challenge in this way: “we have to become masters of the variables involved in making scholarly content available. Not only are the models increasing, but the variables reflected in those models are multiplying, too. Just think of the variables that a lending or demand-driven model adds to your ebook calculations.”

At many university presses, a book’s life will begin with a profit & loss estimate, designed to calculate the costs of editing, typesetting, permissions, printing, and electronic conversion and distribution/storage, among others. However, these formulas only work when estimated sales for the book’s various formats are entered into the spreadsheet. And there’s the rub. Sales forecasting pre-recession was a tricky and largely imperfect art, so after the crash of 2008 and the advent of ebooks—which in turn led to our current splintering of sales and income models, rent vs. own, subscription vs. perpetual access, etc.—putting realistic numbers into that spreadsheet in 2013 can seem alternately like an exercise in futility or eerily remind one of advice typically given by SAT test preparation coaches: “Think about the information you do know, and then carefully make your very best guess about the answer to this question.”

This exercise in sales forecasting is far more than a theoretical concern. Certainly, a press needs to know how many of a book it should plan to sell (and plan to print, taking into account that the print number should be lowered by the amount of projected sales that will be for electronic rather than print copies) to determine if the book is a financially viable project. Increasingly, though, as presses’ budgets are being examined, a publisher also needs to know what their cash flow will look like in a given year. Traditionally, patterns of library buying and the prevalence of approval plans gave forecasters a rough idea of an ideal print run, since the bulk of library sales occurred in the first two years of a book’s life. In the same way libraries, too, could budget for what they projected to spend on monographs and subscriptions. But the many new sales models, particularly for electronic content and in plans involving PDA or STL, money is earned (or in the case of the libraries, spent) according to use. Use may be the new metric that will ultimately determine cost, but that cost, according to Saunders, “needs to be metered in a way that doesn’t bankrupt libraries or publishers.” How do presses guess at—let alone budget for— the actual use of their books, taking into account the fact that the income earned by a particular title may now trickle in over a series of many years rather than primarily at the beginning of its life? Similarly, how can libraries accurately predict their own costs in this on-demand approach to content access? See the previous advice of the test-prep coach. 

So there it is. We all make our best guess. We have to guess at how many books we can sell (short term, long term, in whole or in part) and price the books and the access plans according to numbers that we believe will get us to a break-even status (if you’re a non-profit university press). We make these guesses knowing that we may not make the numbers and knowing that we’ll be participating in a number of sales and access models so that we can gather some actual data about what seems to be working for the vendors, the libraries, and the patrons they serve. We make guesses knowing that we will be selling fewer copies of our books due to increased consortial activity, textbook rental programs (both print and electronic), and campus-wide electronic access to titles that would have previously sold vigorously as course adoption titles. We make guesses based on the knowledge that unlike scholarly print books, which carry smaller discounts since they travel to more specialized markets, ebooks are considered all the same (in terms of discount) by the vendors. As a result, presses give up significant revenue on this format, a matter of increasing concern as ebook sales and licensing to libraries increase and print sales continue to decrease.

This is one explanation for why there are so many sales models and so many different pricing and access options out there today. I don’t believe publishers are deliberately trying to add to the confusion, and indeed we likely suffer from it as much as anyone else in the chain of scholarly communication. We experiment because we want to give our customers what they want according to their needs. We also experiment in order to build a set of data that will help us determine which models work most successfully and sustainably for us as publishers.

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