In his book of essays entitled Mortals and Others, philosopher Bertrand Russell wrote “To understand the actual world as it is, not as we should wish it to be, is the beginning of wisdom” (Russell, 318). The line concluded a short essay on censorship in education, but his point applies equally well to many sorts of situations.
While his point seems obvious enough when taken at face value, it is nevertheless rather astounding to think about how easily people cling to wishful thinking or half-truths rather than face the challenging realities of their own situations. This is as true of organizations as it is of people.
In the world of development, part of the reason for the turn towards doing more with analytics is that, used properly, analytic techniques can be a great source of wisdom into the nature of the organization’s support. And prospect development professionals are perfectly situated to help provide the understanding that can lead to such wisdom.
The nature of this truth has become especially clear to me over the past six years or so, as my work has increasingly involved bringing forward insights drawn from analytics data about the nature of the prospect pool and the donor base at my organization. The more I look at the data, the more questions I begin to formulate about it, and the more interested I become in the relationships among different variables. As I start asking these questions and begin trying to answer them, they seem necessary and worthwhile, and yet the more I present my findings, I can’t help but notice a certain amount of resistance to them, as well.
Part of this is a matter of presentation format, and I expect that may change as I do more with data visualizations. Graphs, charts, maps and other visualizations can tell a story better than a table or a spreadsheet can.
But beyond the matter of format, though, part of the resistance is also possibly the shock of the new, as I try to find ways of counting, classifying, and quantifying things that had not been quantified in that way before. People are used to the metrics they have seen in the past, but combining different variables in an attempt to get a better understanding of the situation seems too abstract to some and threatening or unsettling to others.
One solution seems to be to limit what I report at first or to present it only in the most positive light and to let people draw their own conclusions before going further.
An alternate solution is to provide more data to those more willing to deal with it and then to use that experience to make the case for using more data in other realms, as well.
How have you dealt with these issues in your organization? What have you found to be the best practices and best techniques for introducing more analytics data into your work?
Retrieve and Herd 