More thoughts on Systems Thinking, Complexity, Chaos and New Community Paradigms

The previous post was a fairly abstract article on applying the logistic equation, from the course Dynamical Systems and Chaos by ComplexityExplorer to New Community Paradigm system structures generally, regarding Causal Loop Diagrams of the currently under construction Community Advocacy patterns specifically. This is taking a satellite distant perspective but still with the possibility for an in-depth inquiry into the parameters of a system. It was more a matter of questions than answers and while jumping to conclusions was hopefully avoided, speculations were stretched. The abstraction, unavoidably, continues.

One conclusion reached that should be viable and understandable but not necessarily fully realized is that systems can, sans mitigating factors and based on deterministic function, exhibit stable and periodic behavior that is both constant and consistent. If it can’t be established and maintained over time, then it is not a system. If it is an established system then it is likely to develop some resiliency to drastic external or internal change. This would mean fundamentally changing a system, particularly an entrenched system would require far more energy than is often appreciated.

Another conclusion, far less intuitive, even cognitively dissonant but just as viable, is that a deterministic function can result in a random output sequence. The alternative to a deterministic function is stochastic, the same input does not always result in the same output. There is some element of chance producing a random result, similar to what happens with a fair coin toss sequence. The behavioral orbits are unstable and aperiodic.

What we have then is a deterministic, rule-based system, that once past a region of undetermined predictability, behaves unpredictably despite being a deterministic system. A system in which the function has the property of being deterministic but the qualities of its output are random.

The Complexity course teaches that it is important to distinguish between the properties of a process or a system that generates an outcome, the cause, and the properties of that outcome, the effect, especially in the long term.

The course demonstrates step by step that the logistic equation with r=4 [where r multiplies x(1-x)] is as random as a fair coin toss series. A statistical test would be unable to distinguish between the results produced by the logistic equation and that produced by a random coin toss.

The idea is that a deterministic dynamical system, is capable of producing random, or another way of saying it is chaotic behavior, regardless of how close the system is to the annihilation population {(1-x) where x is between 0 and 1}. Keeping in mind, we often don’t have any idea what is the annihilation population, just that by mathematical logic that there is one. This is applied in a relatively simple sense to a finite population, consisting of similar elements or units that die off or are eliminated and must be propagated to maintain or to increase that population and will be eradicated if not, over a limited number of time periods.

This is a result of the logistic equation that has been proven by mathematics exactly and rigorously. It can be proven, or deduced, from first principles. The claim has been rigorously established. It is not merely a computer or an experimental result.

The long-term behavior of an aperiodic or chaotic orbit depends very sensitively on its initial conditions. The idea is that a dynamical system featuring the phenomenon known as "sensitive dependence on initial conditions," or SDIC or more popularly as the "Butterfly Effect,” can with even extremely small differences in initial conditions result in a difference that can grow to become exceedingly large. This idea applies to numerous dynamical systems, not just iterated functions. It also has a more formal mathematical definition which is provided in the course.

To predict the behavior of a system with sensitive dependence requires knowing the initial condition with impossible accuracy. An example used in the course demonstrates that a difference of nanometers can result in very different results in a few time steps.

The course provides one example of tremendously improving the precision of a measured number to 15.00000001 when in truth the actual number is still 15.0 but the prediction still becomes worthless after a relatively few more time steps. To help visualize this degree of sensitivity, 15 meters is about as tall as a 5-story building, while 0.00000001 or about 10 nanometers is about 1,000 times smaller than a single red blood cell, 10 times larger than a single glucose molecule.

Something 15 meters versus 15 meters + 10 glucose molecules then will exhibit completely different behavior after just a few more time steps. Practically speaking, the difference between 15.0 and 15.00000001 isn’t simply a matter of not having good enough measuring instruments. A very small error in the initial condition grows extremely rapidly meaning long term prediction and even medium term prediction are impossible. More accurate measurements can lead to more accurate and longer term predictions but we have to work exceedingly harder to get only slightly better results. It is r, the growth factor, that makes the significant difference, not x.

The course has us imagine one version of a path of a hurricane hitting New York City, and another version hitting North Carolina based on the tiny difference of the flapping of a butterflies wings. Phenomena such as this though are essentially unpredictable because one can never measure something like this in a manner in which values are this accurate or are even physically meaningful. The course quotes James Gleick from his book, Chaos, who explains that:

‘Its like giving an extra shuffle to a deck of already well-shuffled cards. You know that it will change your luck, but there's no way of knowing how it will change it.’
Even computers are limited by finite precision and having to round off numbers can't calculate the true orbit with we thought we were dealing. The orbit a computer gives us is never the actual true orbit for a particular initial condition. The course explains that the computed orbit "shadows" the other true orbit, also known as the "shadowing lemma.”

Chaos, like the logistic equation, can then be defined in a mathematical sense. A dynamical system is "chaotic" if the following four criteria are met:

1. A dynamical system has to be deterministic, iterated functions and differential equations are certainly deterministic. A dynamical system is just a deterministic rule, if one knows the rule and one knows (with infinite precision) the initial condition, then the trajectory is unique, it's determined. 
2. The system's orbits are bounded, unable to reach infinity. The logistic equation’s orbits start between zero and one and stay between zero and one. 
3. The orbits also have to be aperiodic, they never repeat and they never follow the exact same path twice. They don't go into a cycle. It is a requirement that the orbits be bounded that eliminates the possibility of orbits going off to infinity. If we then have bounded orbits that are aperiodic then they are confined to stay in a unit interval and yet never repeat. 
4. Has sensitive dependence on initial conditions, as again was demonstrated with r=4 for the logistic equation. 

This, in one sense, extends the George Box principle, "All models are wrong, some models are useful" as discussed in Sailing Complex and Wicked Seas with Icebergs (Systems Thinking). Not only wrong in being incomplete copies or maps of reality but as in being limited perspectives, especially one's own. Wicked problems can be analogous to sailing through a massive storm on the sea. The system surrounding the ship can be overwhelming to the system on the ship so people end up arranging deck chairs.

It also though provides a more in-depth understanding despite an inability to reach infinitely fine precision. For myself, having a mathematical foundation as a basis for understanding provides a great deal of confidence but confidence that can check itself. Not to predict where the storm will turn but the confidence to navigate the best possible course.

As Prof. Feldman advises, we sometimes have to invert our thinking about things with starting with an equation because we don't get handed equations, we get handed life and sometimes we can turn it into data. We can't assume that the world is made up of things that are either orderly or things that are random and that these are separate. That we are wrong in thinking that maybe they get jumbled together but they are separate things and need different types of explanation and requiring different means of managing seems reasonable.

One can get disorder from an orderly system, one can get deterministic randomness. We need then need to think about determinism and randomness in a completely different way that in a sense they are two sides of the same coin. They are not complete opposites and we need to think about them completely differently. The relationship between randomness and order is more subtle than we might have thought.

Modeling the Last Mile to Feed the Homeless part 6

This is the last post in this series examining relevant systems in developing an abstract financial model for the very real purpose of feeding the homeless. We have reached a particularly abstract juncture because our focus now is primarily on an unrealized future.  The difficulty with effectively putting a financial model together, so that it works within the parameters of a particular enterprise, at least on paper, has hopefully been conveyed. Making the actual enterprise a reality is even harder. It is, however, not the only path, good or bad, forward.

A number of times throughout this series the concept of ABCD or Asset Based Community Development has been referred to. Now I do not really know that much about ABCD in-depth having only started to learn so I am only referring to generalities. These would though be intentionally bottom up, community generated approaches. Jo illustrated examples of homeless working with her. In these cases, there is no scaling, simply direct assistance with the resources the community can muster. Faith-based organizations have used an ABCD approach before in addressing homelessness. Even institutions like libraries look to use an ABCD approach to assist their clientele, like the Denver Public Library working with homeless teenagers. 

In the last post, questions arose in determining scenarios for scaling the operational units from 1 to 3 units and perhaps beyond. Is it better to buy short buses or long buses and is it better to use 36 months or 60 months for the term of the financing and in what combination? The decision could add up to $0.80 per meal but could also create greater impact. 

The extended service food bus could help different organizations find people that could be helped further. The goal would be to move individuals from streets or camps to shelters to supportive housing options and back into the community. This would likely require a more Collective Impact effort supported by a backbone organization of which the “Last Mile Mobile Food and (now) Community” program might be a spearhead. Likely, we would need a bigger bus, raising the question whether it is actually possible to design a long bus which could handle both food delivery and additional services. A larger question is whether a more focused approach could make a long-term difference for some of the homeless or would a far less focused approach help more people if only temporarily.

                                                                                                   

This could mean getting as much value into each visit as possible to maximize impact. If more services were donated then it would provide more bang for the buck. One could perhaps supply personal hygiene items or even showers which are seen as very important, the homeless referring to toilet paper as "white gold”. There could also be community health interventions including ABCD approaches to community health through organizations such as the Commonwealth Fund, World Health Innovation Summit and other alternative community health approaches which could be explored and developed.

At the start, we said that all models are wrong but they can be useful. One reason they are wrong is models don’t reflect continually changing on the ground or granular reality. The RV to be donated for food delivery is now in use as a residence for two pregnant homeless women.

Models are also wrong because they never fully reflect the entire set of systems involved. One system we have not examined up to this point is the political one, or perhaps closer to the mark is the political reality. This last January, the mayor of Portland established “safe sleeping” meaning that homeless, sleeping in a doorway, would not be woken up by authorities to move to another location. This has now been rescinded. The mayor is also having major sweeps done around town with 72 hours notice, expecting everyone to pack up and move on but without giving options where to go and sometimes taking everything they have. The supporting advocacy groups are now extremely busy trying to find housing for hundreds of people or at least some place for them to pitch their tents and be safe.

The political force motivating this change in policy is known as Safe & Livable Portland, who assert that the “safe sleep” policy or homeless camps would not solve the problem of homelessness and, “…resulted in violence, unhealthy conditions, and pain and suffering for our most vulnerable residents."  The sincerity of this outlook though might be questioned by some closer to the situation. 

Other cities have taken a different approach. In Seattle, youth voted through participatory budgeting to spend $300,000 out of a $700,000 budget, on programs to address homelessness. This also though may have its own limitations, as to whether the programs being developed will actually effectively impact homelessness? It depends on the overall attitude held by those in power. In Los Angeles, the LAPD ordered officers to show 'compassion and empathy' to homeless people. The institutional system for helping the homeless though can be very bureaucratic.

Using a true community based ABCD approach could make developed systems more resilient, helping to protect it hopefully from entrenched institutional system’s political arbitrariness or overcomplicated bureaucracy.

At least for now, this turn of events has undone any further progress regarding the current efforts. It didn’t stop all efforts, though, just the path they were taking. Jo is currently looking at getting a 1987 Mercedes truck with a little over 14,000 miles on it for food deliveries. In this political environment will it be possible to get the resources to scale the enterprise? Are there other pathways that could be taken?

One idea we had discussed was an expansion of the Church delivery of homemade meals. There is a community food-sharing system out there. Unfortunately, it is currently illegal.

“There are lots of people out there that love to cook. Maybe I need an application that helps people find camps that need food and coordinates delivery.”  - Jo

Jo wondered how the laws affect people who are not selling the meal just delivering it. Another option could be working more closely with the Farmers Markets. 

The issue is that both add to the number of pick up points for food delivery. This is not necessarily an immediate problem as long as one has enough willing volunteers. However, there could be a point at which such a system is not able to respond adequately to the need and a more efficient system needs to be put in place. 

Another idea raised was working in low-income districts trying to get ahead of those who might become homeless. Although the idea had some merit, feeding the homeless for this assignment was seen as already a huge undertaking.

Rents across the board have gotten so high that most minimum wage people can no longer afford to rent. But it is also the people who have good income just too much debt. They get evicted and then can't find anywhere else to rent. - Jo

Another idea was providing the homeless with their own form of community currency which would have a better exchange rate than standard currency.  

The community currency idea is in the vein of the Farmers Markets, though it may not work with all homeless types. There are differences with the Farmers Markets program which seems to be absorbing the economic cost of doing and assumedly has a rationale for taking such an action. My idea was community-based backed by Social Impact Bonds, combining both to make it go further. There would have to be a great deal of community support. The community currency could only be used within the community with specific vendors. Community banks or something similar would also have to be involved. Selected vendors would accept the community currency and be reimbursed from a dedicated fund in standard currency. A Kumu map was created exploring the concept.

Social Impact Bonds also are known as "Pay for Success" have been used in Massachusetts to address the issue of chronic homelessness through the Home & Healthy for Good (HHG) low-threshold housing initiative. HHG has demonstrated that treatment of often traumatic and under-treated health conditions besetting chronically homeless individuals was better after a person gained a basic level of stabilization provided by permanent housing. HHG also demonstrated significant cost savings to the Commonwealth and successfully housed those often considered the hardest to serve. Whether it would be possible to obtain similar type funding or perhaps an extension of such funding is an open question? 

The inclusion of community currency doesn't really change the short term transaction costs but long term, at least potentially, could help tie the homeless back into the community through economic transactions. At some hopeful point in the future, those individuals become members of the community again, although only if they can find adequate housing. A final solution will be able to address challenges of a wicked nature, addressing not only the systemic processes and structures but the mental models associated with the problem as well. Whatever the configuration, it will likely be a model that helps us understand it. 

Modeling the Last Mile to Feed the Homeless part 5

Over the last four posts, we have discussed the challenges of feeding the unsheltered homeless and have devised means of addressing those challenges through a proposed social enterprise.  This social enterprise follows a systematic financial model that is very similar to one that could be used by entrepreneurs in establishing a start-up for-profit business. We can now go deeper into the workings the Financial Model though this will not be an attempt to capture all of the details of the course. For that, I strongly recommend taking the course which being free can be expected to be a good return on investment. 

The external customer or beneficiary for our enterprise is the unsheltered homeless who require a different delivery or business model than those living in shelters or those who are low and very low income but not homeless. 

Among some of the constraints to serving the targeted beneficiaries are how much food can be carried and delivered within a defined distance and period of time-based on the equipment and available personnel. It also needs to be recognized that the homeless still have choices they can or have to make, like any client, which could impact the success of the venture. 

The financial model, according to the course, also represents an internal customer. 

The financial model is the voice of your “internal customer” whose needs need to be met just the same as your external customers. 

It is this “internal customer,” or donors who use the model for decision making, that must be convinced of the project’s financial sustainability and sometimes potential scalability to fund the entirety or substantial portion of a nonprofit enterprise. While there is potentially strong external demand for our proposed enterprise no expectation can be had of the enterprise being grown or even maintained based on a future revenue stream because it does not exist.

However, even if we cannot depend upon a future revenue stream, we will undoubtedly be facing future operational costs. After some experimenting and sticker shock as to the costs of running such an operation, we came up with admittedly rough estimates. We were not preparing for an audit, simply making some sense of the parameters of our enterprise. It was fully recognized that all of the numbers would have to be tested in the real world and adjusted accordingly, perhaps even to the point at which the model would break down.

The costs reflected were for human resources, equipment, leases and operations. Constraints brought on through such costs had us reconsider our transactions per month based on the estimate of what one bus with three people could accomplish based on a set criteria. That criteria could range from quickly passing packages out to those in nearest proximity to endeavoring to make some form of connection to establish relationships for future interventions. The criteria I chose leaned closer to the later.    

I calculated 3 salespersons (with one being supervisor/driver) for each Operational Unit, running scenarios for one, two and three buses. The human personnel costs were based on 2016 Oregon minimum wage plus 25% benefits. A premium for a supervisor for each truck was provided at 10% higher. 

We operationalized the cost of the buses mentioned in the third post by depreciating their cost. We then calculated costs related to running a Home Office. Whether this would be necessary could be a question but for purposes of the course, we went ahead. It might seem to make little sense with just one bus but there could still be a need for a place of operations, e.g., to park the bus when not in use, and for coordination. 

A Territory Manager was set 40% higher than the main workers. We placed the general operating costs under this category. The cost of buses and refrigerators and their depreciation was researched from the web as was the lease for commercial property in Portland, Oregon.  Other costs were based on rough estimates or percentage factors. 

The need for a head office became greater with a greater number of buses but we were also able to lower the cost per Operational Unit or cost per meal package while increasing the number of transactions. Scaling up from one operational unit with three people to three operational units and nine people and proportional support staff did make a difference. The estimated cost per meal was $3.88 for 3 trucks, $4.63 for 2 trucks and $8.29 for one truck. It was still presumed that the food was free and we inevitably missed costs so this was still an abstract model. It was felt to be a good beginning.

The next step involved going even further into abstract and speculative calculations. An entrepreneur who creates a new business that has the capacity to grow into multiple outlets must not only generate enough demand for their product or service so as to maintain the current level of operations but also generate enough to invest for future growth. Some growth might come from new investors or loans but there will still be new revenue to demonstrate internally generated growth to justify it. External sources are likely to be doled out based on performance.

The nonprofit has to ask for such investment in advance and then prove that it is a worthwhile risk for future investment. This may not seem logical as how does one determine the level of risk the enterprise entails? While concerns of profit may not come into play, any money lost or wasted could have been used for other beneficial purposes. The risk premium for our enterprise was set at a total of 95% reflecting a Required Rate of Return/Rate of Investment that was, in reality, being covered by the donors. How this risk could be spread out could be determined by the length of the investment period, 36 months or 60 months or time before sought after results were obtained and the type of bus that was to be purchased, long or short. We ran scenarios using all of the combined criteria.   

The final calculation was to determine a price point for our product, the meal package. We did not make a final decision on what the meal package would be or what it would consist of. Jo leaned towards providing healthy burritos as it could be carried, easy to distribute and minimal need for clean up. I stayed with free food from the pantries though did not fully consider what that might involve. Whichever, there would though be associated costs we had not added in yet.                                                                            

Financial modeling is again done iteratively, finding the sweet spot matching up product and price with consumers needs at a cost allowing the venture to be financially sustainable. This is true even when the product is being provided for free because of other life costs are borne by recipients such as the homeless. If they don’t believe that they can depend upon delivery of the product or feel diminished by it for some reason then they will not use it. Also if the monetary cost is too high then donors may look for lower hanging fruit to put their money towards. 

This means non-profits often encounter a large gap between the price required for profitability, or in the case of non-profits the level of supportable financing required to sustain and scale up a social enterprise, and the price they believe consumers (the course says or, I am going to say and) donors will pay for the product. This is a natural tension inherent within the challenges that social issues present. 

Ask yourself what you think would be the absolute maximum a customer would pay for the product or service you have in mind, and what would be the ideal price (i.e., the lowest) that you think would easily attract customers. Then pick a few prices that fall within this range. 

Social entrepreneurs inevitably have to experiment then with different models or scenarios making tradeoffs to bring the equation into balance. 

Transactions at steady were lowered to that used in the other modules to reflect limited capacity and desire to focus help rather than maximize output. So the only change in variables is the type of buses being used and the loan period. 

The lowest price point chosen for each scenario was that which covered Single Transaction Costs and Operational Unit Whole Costs. There was not practical reason to go higher than this as clients are not making reimbursements and donors want the greatest efficiencies.  

Next Part 6 

Modeling the Last Mile to Feed the Homeless part 4

Creating a sustainable and scalable enterprise to feed unsheltered homeless has proven itself to be embroiled in a number of complex systems, food distribution, transportation, and others as demonstrated by the last three posts. We devised our Operational Unit or means of delivering the food, a Mobile Food Bus in the last post but we still need a targeted market to pursue and to make the enterprise’s operations sustainable and hopefully scalable. 

Practically speaking, for a start-up operation, three meals a day is a lot of meals. Jo could readily come up with three camps of 25 to 30 people per camp very close to each other, with some smaller camps in close proximity.  So, she initially thought to provide 200 to 300 meals a day plus groceries in this limited areas plus small camps and any street people that show up to start. 

This seemed to be doable based on our targeted market scenarios. However, it would be only a small percentage of the potential total population to be served. It still needs to be determined whether or not the enterprise could be grown or scaled to serve a far larger number of unsheltered homeless. From an ABCD perspective, it might also be asserted that it should be determined that such an enterprise would not be turned into a bureaucratic form of control diminishing the self-worth of individuals in exchange for sustenance.

Different business models can fulfill different sets of needs so it is necessary to determine what needs we are attempting to fulfill then determine what product fulfills those needs within that business model or delivery system for which we can create a sustainable financial model. This is an iterative process that goes back and forth.

What the nonprofit should understand is the constraints and inefficiencies of the systems (invariably plural) it is working within and then determining whether it can devise financially sustainable ways that can be scaled to overcome them which then drive the numbers in the financial model. 

Nonprofit organizations, however, can impose their own constraints or inefficiencies by too quickly becoming too product-centric or specific service-centric and not paying enough attention to the business model or systematic means of delivering the product or service. 

Two important variables that can determine a social enterprise’s potential are the operational unit’s “reach” and its “penetration rate.” Reach is the number of potential customers or beneficiaries that the operational unit can access (before competition or other alternatives) and penetration rate is the percent of those customers that the venture would eventually serve over time (after competition or other alternatives). This is part of the bounding of the operational unit. It forces constraints to avoid what were termed in the first post as unrealizable idealism. To be more precise goals that are unrealizable within the constraints of available resources and time. We were not going to feed all the homeless in Oregon. A purpose of the financial model is to grow available resources to meet the ostensibly unrealizable goals over time.

The geographic size of the potential target market in question was first set at 431 square miles but Jo decided to limit that to an area of approximately 289 square miles, east of I-5. The total population number was set at 1,887 from the homeless census. The potential target of our operation, the proportion which could be reached, was estimated initially at ninety percent because the homeless census was able to ascertain where approximately ninety percent of the unsheltered homeless were situated. However, just because we know where they are or were at doesn’t mean we truly have the potential to reach them so we also did other scenarios at lower percentages. 

Next was a matter of estimating our operation’s level of penetration, going into a geographic area, finding the targeted population and serving them. The last mile and routing challenges discussed in previous posts would very likely limit effective penetration. This gave us the total population x potential targeted percentage x penetration. Again we ran different scenarios using limited targeted levels to reflect likely limitations in operations. We didn't want to start out promising too much.

Then it was a matter of determining our venture's potential market share or the proportion of our potential target we could serve out of all the other alternative offerings in the area such as soup kitchens and food delivery by churches. This we did set high, again at ninety percent fairly confident if we could get the food to the homeless then they would use our services. This then gave us total population x potential target percentage x penetration x market share which equaled our Operational Unit's customer/beneficiary base or how many served at steady state. 

The ventures proposed through the course were all modeled at a future point in time when “at-scale,” meaning covering the entire targeted geographic area and operating at “steady-state,” defined as having matured, with revenues and costs holding constant. Again, this is a wrong or an unreal model but still useful as it allows the social entrepreneur to see the potential financial viability of the enterprise over an extended and forward looking period of time. If the numbers don’t work in the model, they are not all that likely to work in reality. 

The Operational Unit's beneficiary base at steady state is based on the Operational Unit's monthly beneficiary transaction rate at steady state which is determined by your product's service's intended frequency of use daily.

What a transaction is for a nonprofit is the point of exchange with beneficiaries or clients for a product or service. The size of our customer unit was set at one, as in one food package, multiplied if needed by the number in a family or group. The initial frequency of use was set at once a day.

The client load of an individual salesperson each month depends upon the number of days in a month available for conducting transactions and the number of transactions that can be performed each day. 

Two variables that would drive our costs then are the number of monthly sales or “transactions” conducted with beneficiaries or clients, and the “client sales load” of a single salesperson. Even if the beneficiaries are unable to pay, the financial model still treats them as customers or clients. While this may be seen as a matter of respect, it also recognizes their importance to the financial viability of the enterprise. If this is not done, then the systematic approach sought by the financial model is reduced to simply pouring money on to the problem until it runs out. 

Calculating the number of salespeople required for an Operational Unit requires dividing the number of transactions conducted over the course of a month by the "client load," or the average number of transactions a salesperson can perform monthly.

The most conservative first estimate for an operational unit put us at 4,892 transactions per month. Under it, we reached only 40% of the 1,887 unsheltered homeless listed by the census giving us a target market of 755. Our penetration rate was set at a seemingly reasonable 30% with 90% market capture or a steady rate penetration of about 27% which equaled serving 204 beneficiaries. Supplying an average of one meal per day for a 30 day month, and assuming an 80% repurchase rate (as mentioned previously, people move around) put us at the 4,892 transactions per month. Our least conservative estimate put us at 27,513 transactions per month using perhaps possible but idealistic numbers.

We then had who our target market was and how we intended to reach them. We still needed to operationalize how it was going to be done. 

If we simply totaled the miles from base to the food pantries as described by the Food Network map then the distance could be covered in three days at eight hours a day but that does not take into account actually delivering to and feeding people or the complex scheduling of food pick-ups and deliveries which are unlikely to be that efficient. 

For-profits are naturally concerned with sales and margins as defining their means of being financially rewarded or making a profit. A non-profit enterprise usually doesn’t need to be as concerned with sales and margins. It should though understand the total costs required to offer products or services to targeted beneficiaries so that one knows precisely what’s needed in terms of fundraising. 

Even if one could get all volunteers or had real property and equipment donated, one still wants to calculate a cost to demonstrate the enterprise is financially sustainable and, for in-kind matching contributions from major donors which are often a requirement. 

Next Part 5

Modeling the Last Mile to Feed the Homeless part 3

This is the third post on a Financial Model to provide mobile food service to ‘unsheltered’ homeless around Portland, Oregon. The last post gave insights into the Hobson choice homeless advocates have in continuing with temporary fix programs because financially viable long term solutions requiring greater upfront investment don’t have the required support. Also, the challenges homeless advocates face maintaining these temporary but necessary programs. The Financial Model will seek a path making such efforts both financially sustainable and expandable or scalable. These are two separate criteria that must be judged within their own context. While it is obviously good that a beneficial social effort is sustainable that does not alter the immediate need. Further, an inability to scale to assist more people does not make local efforts to meet such needs unhelpful. What the financial model will do is help prevent wasting resources on unviable enterprises and expand them if possible.

Part of developing the Financial model was looking for greater efficiencies in delivering the service. One early idea was to develop an app to address the food distribution challenges discussed in the first two posts. Apps like Cerplus, OkCupid, Leftover Swap and Spoiler Alert, which was built by MIT graduate students, can help individuals and organizations meet food waste reduction goals. There is also a growing awareness by companies like Starbucks which took action after workers fretted over wasted food

"We are affected at a human level when we see something that's perfectly good that could feed needy families going to waste," the Starbucks manager said. 

After a year of research and food safety testing, Starbucks rolled out food-donation pilot programs in Arizona and California.

The food is delivered within hours to food banks and agencies where yogurt parfait may go into children's lunch bags or be served along with Starbucks breakfast sandwiches on a food line.

It also demonstrates the level of the challenge in delivering food to those that are not only without means of sustainable nutrition but also without minimally proper, decent shelter of any type. We are speaking of the inefficiencies of two different systems, first within the food system.

“Food waste happens not because businesses intend to waste the food but because they’re often disconnected from one another and lack a real-time solution,” says Ricky Ashenfelter, co-founder and CEO of Spoiler Alert.

Then the further challenge of serving the unsheltered homeless when even the basic efforts are difficult.

"It takes so much planning," said Al Brislain, CEO of Feeding America San Diego. "All the routes, all the-- you know, making sure the temperature is right, making sure that the food is still nutritious and fresh."

Other efforts, in different parts of the globe, seek to address the food wastage problem but this still does not translate readily into solving the problem of feeding the homeless. Denmark opened WeFood, its first food waste supermarket in the country and perhaps the world, selling produce at prices 30 to 50 percent cheaper than normal supermarkets not just to low-income shoppers but anyone who is concerned about the amount of food waste produced in the country. 

This is still, it can be argued, an inefficient solution as WeFood does nothing to address the underlying cause(s) of the massive amounts of food wasted in the food and service industry which happens because of consumer demand for price competition. The food industry depends upon massive overproduction to remain profitable which WeFood does nothing to address. WeFood helps maintain overproduction through tax incentives created specifically to make surplus supermarkets viable. 

Our own United States Congress passed an important piece of tax legislation as part of the 2016 fiscal year omnibus budget to increase food donations and thereby prevent food waste. Businesses that donate could benefit from this federal legislation allowing more businesses to get tax deductions for donating food. The Food Law and Policy Clinic (FLPC) applauded the passage of this portion of the legislation, which provides for a more comprehensive tax incentive policy for food donations. Again, though, this does not readily reach the homeless.

This then can be seen as a version of the Traveling Salesman Problem which could involve perhaps the use of apps in finding the most efficient routes. The term “Last Mile”, which was used in the title of the project, “Last Mile Mobile Food and Community Bus” came from the public transportation sector, based on the idea that it is easier to get a thousand people from point A (Station) to point B  (Station) and back again than it is to get that same thousand people from point B to point B1, B2, B3, and so on for each individual destination. People may be willing to ride a bullet train or light rail but don’t because they can’t cover that last mile to their destination. At this next level of need differences in outcomes can depend upon economic factors. Bullet train riders are often upper income, riding instead of flying, and their businesses often cover the extra costs. Those who are low-income use services which are often undependable, then when they don’t use those services that is used as an excuse to cut them.

Similarly, the unsheltered homeless often cannot cover the last mile to get to the food so the intention is to cover it for them but the difficulty of doing so is comparable to that of public transportation challenge because of multiple changing sources and targets. 

Now we can start building an enterprise to address these challenges. The first step in creating our Financial Model was to “Bound the Operational Unit,” revealing what makes one’s approach uniquely suited as a start-up. This means creating from a “bottom up” perspective of a single “operational unit”.

The operational unit is the smallest self-sustaining component of a larger enterprise responsible for conducting sale or service in a defined territory.  It is what is replicated when one scales or expands. This assumes multiple operational units whose activities need to be coordinated and by which cost savings can be attained through such coordination. While a non-profit's operational unit often does not generate revenue, it is still a basis for calculating donor or grant funding required to cost and effectively serve targeted beneficiaries at scale.

Our venture was urban mobile in nature according to criteria set by the course. Our operational unit was to be a food truck, a fifth wheel, bus, or other large vehicles. This was to be the enterprise's engine (ignore any suggestions of a pun) generating the money not only for its own operations but also for any enterprise-level activities performed from a head office or central office, as well as revenue to continue growing the enterprise to enable it to scale properly.

I found online, a 1998 Chevy Collins Used (short) School Bus, CARB  legal, for $12,500 and a 1991 International Blue Bird School CARB Compliant for sale at $24,500 online which I used as the numerical input for my model. Buses are closer to 10 miles per gallon so they could carry more food but could cost more in fuel delivering it. 

Jo ended up working with a local nonprofit, first looking at the donation of two buses at $45,000 each then working on obtaining an RV to be refitted for this purpose. Technical assistance with the retrofitting is to come from a creative individual with the necessary experience who is currently homeless, again demonstrating an ABCD philosophy of focusing on what is strong rather than what is wrong. 

Under the concept of all models being wrong, we can include nonprofits not being able to select, or which could be modeled, a reality favorable to them as the one they work in. They have to take the resources made available to them and make them work rather than depend upon abstract models of numbers that might add up but don’t have any real substance. The challenge is putting these approaches together in a viable manner. 

Next Part 4

Modeling the Last Mile to Feed the Homeless part 2

This is the second blog post concerning the Financial Modeling for the Social Sector course from Philanthropy University powered by the Berkeley Hass School of Business and there still isn’t anything yet about the financial model itself. We are still defining the boundaries, elements and relationships of the systems with which we are dealing. We still need to better understand this larger environment in which we hope to implement our financially viable and sustainable enterprise to help address the needs of the homeless.

It has been shown that one of the most financially effective and sustainable remedies to address homelessness is providing homes rather than continually providing services which while necessary in the short run do not make a significant enough of an impact to bring about needed change in the long run. Salt Lake City six years ago started a project to provide housing for every homeless person, Austin Tx did something similar, also a study coming out of Calhoun County, Michigan asserted, “The most ironic obstacle to implementing the fundamental solution was the community’s very success in providing temporary shelters and supports.”

However, while building homes may be one of the best remedies for homelessness, lack of a home is not, I will propose, the primary etiology of the detrimental afflictions of homelessness and those afflictions are acute in nature. 

I am going to suggest that it is a lack of community, separation from deeply structured community, from that social relationship network that can be defined as civil society. In exploring those relationships, I came up with a rough cut term, community-less-ness. A weakness of this argument is that the reality of such a social structure can be taken for granted by most of us. In numerous cases, we can make decisions to bypass such relationships but remain, even if only subconsciously, confident that they will be available if we need them. This includes those community relationships that we forge through our economic transactions. This is again a model which does not encompass the truth of homelessness and is wrong, but it could provide what could be considered an important insight.

It becomes all the more evident in the manner in which we use the problems with our food wastage as a means of addressing the feeding of the needy and the homeless.

Food pantries mainly store non-perishable items for access by needy individuals or families either for free or at very low cost. Food trucks mainly distribute perishable or soon to perish items to food banks and shelters  making food preparation an important component. Feeding the needy though is very different from feeding the homeless, especially those in camps or on the streets.

As said before, although the Portland food distribution system is available to the homeless, it is not necessarily accessible by them. The local pantries will gladly bend over backwards for a person with no address.

“But that homeless person has to figure out a way to get the groceries back to camp or shelter and the street person is limited to what he can carry on a daily basis. It is very limited what kind of healthy ‘walking food’ the pantries carry”. - Jo

Another shortcoming with homeless food distribution then besides a lack of choices is an inability to keep food fresh once it is distributed because it is given in quantities too large to be used in a timely enough manner. 

Currently, as Jo explains, “They don't have much choice in food so they end up with five loaves of bread that go bad before they can use it.”

There is then the issue of transporting the food as most of that food has to be refrigerated and/or cooked.

Jo can plan on hitting each pantry at least once a month, whether they call her or not as they always find groceries for her to take. On any given day one can determine the hours of operation for a given pantry. When Jo put together a list of all the local food outlets, she was thinking that the homeless could use a copy for themselves. That way they would know such things as that there are two pantries that one can only frequent every ninety days. To help out with this, I created an online map of Jo’s Portland Food Network.

The need for multiple pick ups comes from going to all Harvest Shares and Community Baskets and stopping at multiple pantries when the pantries call with food for not less than 50 people. That food goes to waste if they can't figure out a way to distribute elsewhere. 

There is also an entity called Gleaners which provides mostly fruit and vegetables that are not fit for resale as they will have some sort of blemish or a shipment did not arrive in time making Gleaners the beneficiary. That is then free food if one works several hours as a volunteer to help sort the food. 

“I usually bring several homeless to the Gleaners to volunteer and then we fill up my van,” - Jo.

This Financial Model with Jo seeks to further expand food delivery to the camps and street people. In keeping with the philosophy of an ABCD approach, the homeless are part of the solution.

Street people might be nearby for a meal and then not in the area for the next three days or more. They know where the soup kitchens are and usually get one meal a day there. 

Homeless campers usually don't get to soup kitchens unless they are very close. Homeless camps have no refrigeration, and limited cooking facilities. Local churches deliver hot food most of which is nutritious a couple times a week. Some people volunteer to cook a meal for 25 or 30 in their own homes and then deliver them. While it is amazing how many churches walk into a camp and hand out food, it is not consistent. They go to only the camps and not to find people on the streets.

Groceries could include canned goods as they can be stored in camps but street homeless do not want to carry it around. The street homeless like to have "walking food,” stuff like health bars, and fruit roll ups and bags of tiny carrots to put in their pockets to carry around. 

One idea then was to provide carry around food such as a protein bar and raisins as a fruit, maybe a package of healthy chips. The homeless also don't get vitamins.

Jo wanted more than a nutritious meal served at one time, thinking of the meal and also some walking food for later. 

“My thinking is anyone who came up to the window to be served, got a high energy protein bar. A soup with vegetables and fiber in it. (we now have a littering issue with that soup bowl. I wonder if the soups could be served in an edible bread bowl) The bar they can take with them and eat at another time.” 

That way they would at least eating one meal a day other than at the soup kitchens or churches delivering meals, which would be more than they are eating now.  - Jo

There are two other possible sources to acquire food within the Oregon Food system.  SNAP or the Supplemental Nutrition Assistance Program can be seen as a first line of defense in fighting hunger serving 20% of Oregonians, at an average benefit of about $130 per month. Oregon tops nation in food stamps at 20% of its population, compared say to California at 9.7% of its population.  Food stamp usage Is high in Oregon because more eligible Oregonian use the program compared to other states due to large extended efforts to sign people up and in part because of the time Oregon has had taken to recover from the recession. Under the SNAP/Food Stamp Program homelessness have rights but they still need to verify their identity. 

The other possibility is Farmers Markets, many of which accept SNAP benefits as a means of payment. They then use funds to match SNAP clients' purchasing power, dollar-for-dollar, up to $10. This means that SNAP participants could get $20 worth of produce and unprepared foods at a farmers market by spending $10 in benefits. The Double Up Food Bucks program works with participating Farmers' Markets throughout Oregon in matching SNAP benefits up to the $10 at their markets.  This, however, is more helpful to those who are needy but still structurally within the community both economically and socially than it is for the homeless.

Next Part 3