This is exactly the book I was looking for about four years ago, when I was exploring the use of data to support decisions around my own organisation's library and information services – having been published just last year, though, it didn't exist back then. But it's certainly been worth the wait, as this work does exactly what it says on the front cover, in being a practical guide which helps readers feel comfortable with data resources and how data can be used to shape decisions about services.

The information in the book is presented in an accessible format, while it focusses on questions and scenarios which are specifically relevant to library and information professionals, all of which helps to bed in the concepts and knowledge shared within its pages.

In the first half of the book Amy Stubbing – who is Academic Engagement Lead at the University of Westminster – explains how the toolkit embedded in the book functions, by providing a context and outlining why data is important, while also giving practical applications of its use in informing decisions.

The toolkit itself centres on a model comprising six steps to follow for each instance where data is collected, or where an attempt to answer a question with data is formulated. Chapters three to eight provide the meat of the work, by taking each distinct step and walking the reader through the theory behind them, before giving practical advice into how to carry them out.

Step one is to identify the data need, query and source, and it forms the basis for using the toolkit. As Amy Stubbing succinctly states: “One of the biggest crimes you commit in data-driven decision making is to collect data with no purpose nor plan about how you can use it.”

Step two is collecting, storing and preparing your data for analysis. This chapter of the book focusses on the differences between quantitative and qualitative data; and provides practical tips on how to collect your data along with some excellent examples of poorly laid out spreadsheets and how not to store your data. It's one of the longer chapters, and rightly so, as getting this stage right is fundamental to the model working or failing.

Step three of the toolkit is to map your data, through translating, overlaying and visualisation, to enable a more thorough understanding of it. There is some useful discussion on ‘normalising’ data here, as well as practical tips on using graphs for visualisation purposes.

The fourth step in the model is to analyse and draw conclusions from the data, by identifying anomalies, using context to understand the data, and reviewing visualisations.

Step five is acting on your data – in short planning and executing actions based on your understanding of the data after you have gone through the previous steps. There is an emphasis at this stage on ensuring that plans are documented and, crucially, shared with stakeholders before changes to services are made, to ensure buy-in and engagement.

The final step of the model is to ensure that you review your processes regularly to ensure that strategic decisions are driven by data, while creating a culture of continuous service development.

The second half of the book comprises a series of chapters contributed by authors in academic institutions who have used data-driven decisions in practice. These are real life case studies, demonstrating how data can support and drive strategic change, and there is also some useful discussion about what worked and what didn't work, and the lessons learned. These case studies are very helpful as they each focus on a specific need and how the toolkit model helped to effect the changes required.

For the reader, these real life scenarios really help to bring to life the possibilities of the toolkit, and to then translate its use to your own environment. In particular, two case studies resonated for me; one being the chapter by Helen Rimmer on ‘Moving from a Transactional to a Transformation Service Using Data’, which focusses on team-leading data and creating what Rimmer summaries as a ‘compassionate data-driven service’. The other is Emilia Brzozowska-Szczecina's case study on ‘User Experience and Qualitative Data’, which explores techniques for undertaking user experience (UX) research in a library environment; and how to analyse this type of qualitative data in a meaningful way.

In summary, this is an excellent work and it provides a practical toolkit for both new and experienced data users to develop their own techniques and approaches to implementing data-driven decisions in their organisations.