It is essential that libraries move into an all digital readers’ advisory service platform as it provides the best way of managing the extensive knowledge of readers. There are an abundant number of online resources and libraries themselves are building extensive recommendation services from their own data analysis. A good example is the QUT library search which provides extensive recommended categories. Users are also becoming more digitally literate in finding titles they are after. As Michael Lascarides in Next-Gen Library Redesign states “For the library of the future to have as passionate an audience in decades to come, we need to ensure that we’re offering interactive and discovery experiences that are as good as the offering they are becoming used to outside the library.”
I believe readers’ advisory is a service that by its nature is fundamentally better provided digitally. The knowledge that is stored by staff and users should be moved into knowledge management (KM) systems as otherwise individuals silo this information. One of the biggest negatives with information silos is that when staff leave for other positions this information leaves with them. It also means that staff that may be more engaging in a certain genre may not be available when needed. As Nowacki & Bachnik state in Innovations within knowledge management “Employees serve as transmitters of knowledge.” Transmission of knowledge needs to be captured digitally so that results don’t end up only being produced by computer algorithms.
The role of readers’ advisory should move to one of managing KM solutions and teaching readers how to search using the internal systems available. If an extensive KM solution can be built around crowdsourcing the views of staff then this can be utilised with search results by accessing staff under separate “personalised” categories.
A great article discussing readers’ advisory was published by the Ontario Public Library Association.
The main topics of effective advisory were listed as:
2. Conversation or Interview
3. Actions to offer suggestions
4. Closing and follow up
These topics can be digitised by:
1. Providing easy to access computers that provide highly visible suggestions after search results.
2. Digital forms during search results that can be easily answered and suggestions provide. This would differ from standard search and suggest to one of suggested based on interview.
3. Searching already allows suggestions to be provided from a database of analytics.
4. If the user has an email attached to an account it should be used to engage with suggestions like any other corporate mailing list is used.
Finally, with thousands of books being published each year how does a reader access an exhaustive list of suggestions? This can only be performed digitally. Crowdsourcing the knowledge of staff into KM solutions is essential in maintaining relevant and engaging suggestions.