I’ve had the pleasure over the last few weeks of having in-depth chats with several women who are top-notch strategic thinkers and have leadership roles in business and nonprofit organizations. Total contact high.
And this has been dovetailing with my LITA Board almost-a-year retrospective thoughts. Because you know I can’t find something interesting without totally obsessing over it until I understand it frontwards backwards and sideways, right?
And in the meantime I’ve checked out a book on nonprofit financial sustainability, which turned out to have a sticker in it saying it had been placed there by an ALA program on financial literacy, which is surely a sign. The book’s giving me a specific technique for analyzing nonprofit budgets, so I’m testing it out on LITA’s.
The tool is a matrix map – basically, put all your budget lines on a chart of impact vs profitability and see what happens. This gives you four quadrants:
- High impact, profitable (winning)
- High impact liabilities (labors of love: worth doing if you can subsidize them)
- Low impact, high profit (the things you do to subsidize your labors of love)
- Low impact liabilities (why are you doing these?)
Then you represent all those activities with circles scaled to their expense.
The book also gives 7 criteria you can use for determining impact that it claims to have tested (not clear how, but I’m also not done reading) with real-world organizations. It says using more than 4 tends to be unhelpful, so pick the up-to-four that make most sense for your organization; assign each activity a 1-4 score on each criterion; and total them up for your impact estimate. (You can weight them if you like, but that’s a whole other level of complexity I didn’t get into.) I picked the 4 I think are most relevant to LITA and did a back-of-the-envelope impact analysis:
- Mission alignment (I can compare with the mission statement)
- Effectiveness of execution (I think this is really important but I have no way of evaluating it)
- Scale of impact (I assigned a 4 for thousands of people reached per year, a 3 for hundreds, and so forth)
- Community building (I totally just made this number up on instinct)
(The other criteria it suggested are depth of impact on participants; leverage (how much does it increase the impact of your other activities); and filling an important gap in your competitive space. I found these both less interesting and harder to gauge – I think they’d need a lot more data to do right. Your mileage may vary!)
I made graphs! (Impact and profitability normalized so they run -1 to 1, obvs.) These are based on FY2013 year-end data (aka “the most recent completed fiscal year”) – actual as-realized expenses and revenues. Sorry about the overflow on the legend – couldn’t figure out how to fix that.
Here’s what we do:
Here’s another version without Forum (which is so much bigger of an expense than everything else that it makes them hard to see; and apparently I normalized them to different axes, whoops):
Well now, that’s interesting.
I’d love to have some people argue with me – did I pick the wrong criteria from that set? Estimate their values wrongly? Is this entirely the wrong analytical frame? Go for it. Tell me why :)
I also think there’s a hugely important caveat with this entire analysis, which is that our budget docs report staff expenses as a single line item, rather than breaking them out by time spent on each activities. This is important because it means every profitability estimate is an overestimate; not one of those lines accounts for the staff time it takes to make those things happen. This is especially relevant for Forum, which looks like a net profit, but clearly takes a great deal of staff effort (it’s a huge undertaking!) and may therefore be a net loss. That doesn’t mean it’s not worth doing – it reaches hundreds of attendees, who by all reports I’ve heard think well of it, and it’s a great opportunity for us to showcase our members’ accomplishments and help them advance their career goals. But not accounting for staff time does cloud the strategic analysis.
What do you think?