One of the most discussed trends is that of data - big data, small data, data analytics, predictive data. It’s all relevant, it’s all important and it should be on all our radars. Data is constantly growing and, as it does, we are finding new ways to harness it and fulfill our potential.
But first a point of clarification. Is it data or information - what is the difference?
Data are simply facts or figures — bits of information, but not information itself. When data are processed, interpreted, organized, structured or presented so as to make them meaningful or useful, they are called information. Information provides context for data.
Within the context of this blogpost, I want to examine two significant themes which have emerged. The first is how we can best use data to improve our current awareness service; and secondly, how you can ensure your current awareness service includis more data, and different types of data.
Using data to improve your current awareness service
Email technology means we have the ability to track email newsletter opens and clicks and is as useful for information professionals, as business development specialists. We can see on a recipient by recipient basis, who is opening our emails, when they are opening them and whether they are clicking through to the links that we send them. We need to work out how to use this data to our advantage.
Your email open rate
Your open rate - the percentage of recipients opening your emails - enables you to assess two factors - the convenience of the time of day that you are sending your emails, and the appealability of the subject line. If looking to improve your open rate, it is recommended to change only one factor at the time, e.g. the time of day or the style of the subject line - changing both at the same time will render your results inaccurate.
Don’t be afraid to experiment, for example, you may notice that your end users are more likely to open your newsletters at 9am as opposed to 8am so it may well be better to schedule your alerts to go out at that time as it will mean they always contain the most up to date information possible.
Your email click rate
Looking at your click rate (the percentage of those who click through to your links having opened your email) will enable you to determine the relevancy of the content you are sending to your end users. If this is consistently lower than you would like it then it may be that you need to spend some time meeting with your end users, sitting in on their own meetings and so forth in order to better determine the data they need.
Analysing this email data supports you delivering the best possible content to your users on a consistent basis. You can then use the information extrapolated from this data at a later date when it comes to demonstrating the need for your library budget by showing the number of users who are engaging with your service and how they are using it.
Including more data through your current awareness service
We are in the midst of an infodemic which presents both a threat and an opportunity. We have to search smarter to provide end users with that extra titbit of knowledge to give them the competitive edge. It's a challenge when it comes to managing and harnessing the potential power of such data. Though, if anyone can do it, it’s the librarian.
“There is so much information available, and it takes a trained researcher to sift through the dross to find the gold. [...]. As I tell my students, it only takes a few bucks and a little determination to become a content provider on the Internet. Many users, even well-educated lawyers, don’t always think to check the information they find on the Internet for currency, accuracy, and authenticity.”
Joyce Manna Janto, quoted from Michigan Law (2)
The quote at the start states that without sufficient surrounding context, quantitative data is rendered meaningless. Whilst numerical data brings with it an inherent sense of accuracy and reliability, if it serves no clear purpose to the discussion at hand it serves no use at all. As a trusted provider of information, the librarian is able to deliver both accurate data, and the relevant contextual information to surround it.
The future of data is here
Speaking at AALL in Chicago in 2016, Jean O’Grady cited big data’s complexity as one of its most important characteristics. The complexity of big data, Jean explained, means that data from multiple sources must be normalised, cleaned, matched and put into hierarchies and relationships to be analysed and assessed - a task that falls to the librarian.
An example of this is the current habit of lawyers to send an email around the firm to gather their coworkers’ experience of appearing in-front of certain judges (4) - insights that could be invaluable in making or breaking a case. New developments in technology mean that these are now able to be managed through analytics platforms, opening up a new space in which to manage information and collective knowledge.
This is predictive analytics in action. Similarly, law firms’ clients may also require data driven analysis through their need to understand how laws or contracts will impact upon their business, e.g. a bank wanting to know its financial risk based on its contractual obligations (5).
Machine learning is helping with these predictions. You can see such innovation in action by looking at companies such as Fiscal Note, who are using legislative and regulatory analytics in order to predict what laws are going to pass in the United States. As stated in March 2020 by Femi Cadmus,
Looking ahead, the integration of technology in the work of law librarians will only increase. Over 90% of government law library employees say that artificial intelligence or machine learning has already affected their workflow by automating routine tasks. Over a quarter of law firms or corporations now have at least one active artificial intelligence initiative. Of those, more than half involve the library. It is therefore not surprising that the skills law library employees plan to develop in the next two years include artificial intelligence or machine learning, data analytics, and blockchain (in that order).
As always, the skills of librarians are going to be required to assess these new and varying forms of data for accuracy and relevancy, as well as adding context to provide wider meaning to their end users.