Score! is hot off the presses and offers an excellent introduction to analytics and data-driven decision making in the world of advancement. Authors Kevin MacDonell and Peter Wylie bring years of experience and a candor that makes the book not just easy to read but also enjoyable. Long story short, you should read it!
Before you buy your own copy here, let me take you through what I liked about—and what I’d add to—the book’s three parts:
PART ONE
The overwhelming takeaway in Part One is the importance of building a culture of analytics (which is also, not surprisingly, the title of Chapter Two). The authors do an excellent job describing the current landscape of the advancement industry, highlighting its strengths and weaknesses.
The best analytics and insights in the world are worthless without buy-in from every level of the organization. Not everyone has to be a math genius, but everyone should understand and appreciate the value of numbers. Somebody or multiple bodies on your team should know enough to be dangerous. S/he should ask tough questions and hold everyone accountable. After all, if you can’t align around seeking ROI, then what’s the point?
One thing I’d add:
For advancement, it’s not just about building a culture of analytics; you should be building a culture of adaptability. Learning to not just accept change is hugely important, but capitalizing on that change could be the bigger fish that needs frying in advancement.
PART TWO
Part Two describes the various skills and talents seen in some archetypes (e.g. the authors) and lays out strategies for developing or acquiring those talents. The upshot is that almost anyone can learn this stuff well enough to be a real contributor. All you need is an intellectual curiosity and the opportunity to succeed.
But here’s where I would pick up where the authors left off:
Peter and Kevin talk a lot about a supposed lone wolf; the battle scars of their own journeys show through. While they do hint at the complementarity of their own personalities and skill sets within their own duo, they don’t speak enough about the importance of building a team.
The reality is, it’s really hard to find a single person with the right potpourri of skills and talents needed. By the way, it’s also risky! In software development, we often worry about bus factor, i.e. what if that person leaves or even worse, if they aren’t very good and they stay?!
Of course, the flip side is you can’t afford to hire five new people tomorrow. But all team members don’t all need to be 100% dedicated to “The A-Team” (“A” is for “Analytics”!) —but maybe a team leader can recruit 25% of the resident Powerpoint expert’s time and 25% from your favorite in-house annual fund expert and contract some of the data wrangling. Can you afford to build an insights and analytics team of 2 ½?
The real question is, can you afford not to?
PART THREE
Part Three demonstrates the value of basic scoring by walking through some simple case studies. There are compelling examples, including scoring potential annual fund givers using data you almost certainly already have. It’s a great introduction. Everyone should absolutely Grok these chapters.
Where I beg to differ:
The authors present fair and pragmatic views on working with traditional vendors. But with that, I can’t help but observe an undertone of undervaluing external data. Whether considering governmental data or the social data that pervades our daily lives, this external data cannot be made a second-class citizen. We live in a world where we no longer “own” all the data… and I don’t think there’s any going back.
No model or score is (even close to) perfect. But we can all agree higher-quality inputs lead to higher-quality outputs. Schools are really good at collecting data about their constituents up until graduation day. This book demonstrates why this data is valuable. But after graduation, our precious young leave the data nest.
Using your own data vs. external data is not an either/or choice. The only right choice is all-of-the-above.