How today’s “data is man’s best friend” attitude can lead you far astray

 While most of my posts are specific to volunteer management, this one reaches out more to fundraisers and IT folks. 


In business I can very easily justify spending $100,000 if it guaranteed (i.e. no risk) that  it  would reduce costs by $100,000 or boost sales enough that the profit from each sale would add up to be $100,000 a year for the next three years. (I get there is rarely a situation where there is no risk, but let’s work under that assumption to keep things simple for now.) By spending the $100,000 I would save/gain $300,000 over the three years and in the end, be $200,000 ahead!  .  It would still be an easy justification if the net effect on the bottom line was +$50,000 a year.  By spending the $100,000 I would save/gain $150,000 over the three years and, in the end, be $50,000 ahead!  One could even argue that if there truly was no risk, it would be justifiable to spend $100,000 once to create an extra $33,667 on the bottom line for three years. The business would then end up $1,000 ahead three years down the road.   It’s only $1,000 but that’s still $1,000 (remember that in this scenario there was no risk).

As a business owner, it would be easy to justify any of the above because I would be trading money in my pocket for more money in my pocket. That sounds simple and in business it is. I get the feeling though these days that the charitable sector sees this just like it would be seen in business. Although I am a big advocate of charities and nonprofits adopting appropriate strategies from the for-profit sector (and visa versa), this is one that I don’t see as appropriate.  While in the business case, I would be trading money in my pocket for more money in my pocket, in a charity’s case, it would be trading money in the donor’s pocket for both money in the charity’s pocket (the pocket that does the good stuff the donor wants to support) and also the pocket of the technology providers.

In some of the chatter I read and hear about donor databases connecting seemlessly to membership databases or volunteer databases and donor databases talking to each other etc. etc., I have seen too many examples lately where the mentality seems to be, “If we spent $X and we think it will generate donations anything greater than $X, it is worth pursuing”. I have various issues with this but there is only one I want to focus on today.

Picture for a moment that you have recently donated $1,000 to the ABC charity to help them _______ (insert your passionate thing here). If later you found out that it was a commissioned fundraiser who earned $990 parting you and your $1,000, you who likely not be very happy that only $10 went to (insert your passionate thing here). With just a slight change in the scenario, would you feel any better if there was no commissioned fundraiser but after the new data analysis technology that sought you out as a potential donor was paid for, the net result of your donation was that $990 went to the technology provider and staff time on the project and $10 went to (insert your passionate thing here)?

But it is still a positive return on investment for the charity. The data that was analyzed/shared/extrapolate etc.  suggested that you would give and you did.  In fact, it is the same ROI of the one   scenario above in the for-profit business examples. The 1% ROI was fine in the for-profit model but apparently not here.  Of course those are exaggerated numbers and everyone reading this likely already understands  the importance of infrastructure costs and how these need the support of donors. I get it too and that is not what I am at issue with here.

The big questions to leave you with are ….

•    When you are looking at a new expenditure for analyzing or sharing or extrapolating data for the sole purpose of raising more donations, what ROI is acceptable to your organization?
•    Perhaps more importantly, what would be acceptable to the donors making the new donations?
•    If the donors knew the portion of their donation that went into the analyzing / sharing / extrapolation of data that was spent getting them to consider donating, would they still have given?
•    Where do new infrastructure costs related solely to getting more donations cross the line?