During the last presidential election, the role of analytics in decision making and prediction moved to the forefront in the minds of many as a way to gain an advantage in competitive situations.  For a data nerd like myself, this was refreshing, as the average citizen started to gain a new found respect for a set of skills that had always largely been viewed as the sausage making that decision makers weren’t necessarily interested in understanding.

Now, everybody is talking about “The Big Data Revolution”, and news stories are popping up consistently around how organizations or corporations are using data to drive sales, predict revenue, plan services, or even predict the life stage that their constituents are in (if you doubt this, Google Target and pregnancy).

So where does this lead?  There has been an ever-expanding market for statisticians, business analysts, and data analysts that is screaming for more qualified applicants.   More importantly, most managers are now skilled in the area of understanding analytics and how they should affect their business decisions.

In this post, I want to provide some tools for the average manager to better learn the areas of their fundraising efforts that could benefit from introducing analytics – whether major gifts, planned giving, direct marketing, amongst others – and how to manage from a position of ‘data strength’.

Self-Taught

There are a few important skills that can be easily learned through self-taught mechanisms.  The most important are the ability to identify the right problem, ask the right questions, and understand where data will help inform a decision.

There is a significant amount of literature available to start the pursuit of becoming ‘more data driven’.  The area of analytics and data consumption is still evolving.  I recommend finding some strong blogs (including this one!) that will help you understand.  I use a combination of non-profit and for-profit specific blogs.  There is a great deal to learn and I suggest you find a few and subscribe for daily updates.

There are a number of texts available around how to leverage data to make better decisions.  Most of these texts are targeted to non-statisticians – or the consumers of what statisticians produce.  The challenge with using texts is that the industry is moving so quickly, you chance some information being out of date.  Some of my favorite authors are:

  • Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t),
  • John Miglautsch (Spinning Straw into Gold: An Executive Guide to the Magic of Turning Data into Money)
  • Eric Siegel (Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die)

For fundraising specific analytics, I recommend:

  • Joshua M. Birkholz (Fundraising Analytics: Using Data to Guide Strategy)

Facilitator Led

There are many classes offered at various institutes of higher education or career learning around business intelligence.   I would highly recommend at least taking one class in an analytics overview to understand what questions can be answered with which analytical tools.  If you are interested in understanding the details of the ‘how’, there are statistics courses typically available for all levels, from beginners to advanced.  It is well worth the investment to take one of these as a night or weekend class from your local community college or university.

Conferences

There are a number of conferences that offer sessions on statistical analysis, business intelligence, marketing insights, and other pseudonyms.  I could start listing them out here, but I don’t want to give the impression that my favorites are the right ones.  Most of them are high quality in terms of content and offer a varying degree of insights.
At BBCON each year, there are a number of tracks which lend themselves to understanding more about how you can use analytics at your organization to help use data to drive results and understand your constituents and their motivations.  Last year, I presented with a few co-presenters around various methods of using business intelligence, including reporting and data visualizations, modeling, scoring, clustering, and data mining.

Conclusion

The three main areas I outlined are not the only methods for learning.  The best method I found is to get hands on.  Extract some data in excel and start playing.   Gather your team and start to outline areas of your business where you see opportunities and start building a portfolio of questions that will help you to understand the ‘What happened?’ and the ‘Why did it happen?’ of past performance, and move onto the  ‘What will happen?’ and ‘What should I do?’.  The road of analytics is long, but each step along the way will continue to add value to your organization.

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