The Not Yet Released tool fully takes advantage of the aggregated data from you and your Analytics-using colleagues to create a sort of a ‘cheat sheet’ for titles that have not yet been published. These titles obviously have no sales or circulation history yet, but they do have on-order information. This graph will take all on-order titles with a future publication date and filter to show you the titles that are most-ordered by the most libraries or stores, depending on your selected market. That’s an important distinction to recognize, that lots of places have to have ordered these titles for them to show on the list, so a single library ordering a larger than normal quantity of a single title won’t adversely affect the graph.

Click on a section of the pie graph to either see titles that you have on order or titles that you do not have on order at this time.

Looking at titles that you do have on order is an opportunity to check the average orders and see if you might be way off the mark. If the average order for a bigger title is, say, 75 or something, and you have a grand total of 3 copies on order, you might reevaluate that initial low-ball impulse. At the very least you have a bit more information. Checking titles you have not ordered has some relatively obvious benefits, as you can see those titles you either skipped or missed, and evaluate your position based on this market data.

This can be a great way to give yourself a quick double-check. You can generally increase your holdings for a title pretty quickly, but it can be tough to have to chase a title (or a bunch of titles) right off the bat, and be ‘out of stock’ in the crucial first few weeks after a title’s release. You can set this lane to view a specific timeframe, as well. This means you can look at, for example, all the most-ordered titles coming next month. Do that each month to be sure to not be caught unawares by a big title that you may have missed.

Note that when selecting a market, many library systems have a difficult time providing on order data. In that case, viewing the Indie Trade Retailers market might provide the most fruitful data.

Many find that the Family view is especially relevant in this lane.