Optimizing

I describe Goodwill’s overall objective in general terms as “Maximizing mission-related impact while maintaining a financial position that enhances long term viability.” Of course, such a definition requires that we be able to define mission-related impact. And, despite the use of the word maximizing, the overall challenge is really one of optimizing.

optimize

Many of our management challenges involve finding optimal solutions. For example, how much of our revenue should we spend on General and Administrative expenses (In the not-for-profit world, this is typically referred to as “overhead.”)? Some people believe not-for-profits should minimize G&A. In the long run, that is a recipe for ensuring less than optimal performance, as it results in inadequate value-added support of the high mission impact parts of the organization. Spend too much, though, and there could be legitimate questions about whether the organization is being a good steward of its resources. In this, as is in so many situations, one size does not fit all. Two very important factors in arriving at an optimal percentage are the size and complexity of the organization. In our large, very complex organization, somewhere around 10% of revenue seems to be close to optimal. While to some it might seem counterintuitive, a well-run smaller organization would likely have to spend a larger percentage of its revenue on G&A, as those expenses should not increase at the same rate as revenue.

Another example: One of Goodwill’s historic roles is to provide work for people whose options are limited by disability, criminal history, low education level, or other significant barrier. This is a very important part of our mission and one way we can add unique value in a community. Obviously, then, we want to provide as many jobs as possible for individuals who don’t have many options. However, because retail is the financial backbone of our entire organization, we must have a sufficient number of people with skills that enable us to be competitive and efficient. If we do not have enough people with barriers who have the necessary skills, we must hire others who can fill the gap. In recent years, filling approximately 2/3 of the jobs in donated goods/retail operations with people who have employment barriers has generally seemed to result in an optimal mix.

There’s another optimizing challenge embedded in that example, though, and that is the mix of full-time vs. part-time employees. We have quite a number of employees who for any of a variety of reasons are not able to work full time. However, if we have too few full-time employees, productivity can drop, and that will affect financial performance.

External factors can also have a powerful influence on optimization challenges. For example, the Affordable Care Act has resulted in a large increase in the number of employees who have signed up for coverage under our health plan. While we’re glad more of our employees now have health insurance, this has greatly increased our operating expenses – so much so that we might find it necessary to reprioritize and determine a new optimal mix of operations and services and/or full-time vs. part-time employees that will enable us to continue maximizing mission-related impact while maintaining a financial position that’s good for long term viability.

Nothing is static. Conditions are constantly changing, and we must constantly adapt or suffer the consequences. Optimization issues are always before us, and we’re always striving to find the best balance point – at least until something else changes.

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