Can We Feed Ourselves? Ulupono Initiative Investigates Hawaii Food Production with Systems Thinking

Among his goals for Hawaii, Governor David Ige hopes to double locally produced food. Like government leaders around the world, Ige is eyeing economic, environmental, and health benefits – better markets for local producers, less shipping and distribution, and greater access to fresh, rather than processed, products.

Doubling food production within the confines of any geopolitical border is a challenge. Hawaii’s particular constraints include mountainous island counties separated by stretches of Pacific Ocean. “Hawaii has a great climate but farming is limited to valleys,” says Kyle Datta, General Partner, Ulupono Initiative. “When plantations went into decline, so did the agricultural infrastructure they left behind. Agriculture also requires a lot of water and labor. Even with technology, supplies of both are limited here.”

Applying Systems Thinking

Ulupono Initiative, an impact investment firm dedicated to improving the quality of life for Hawaii residents, is taking a Systems Thinking approach to the state’s agricultural ambitions. “Everyone at Ulupono is trained in Systems Thinking,” says Datta. “We’re deeply immersed in the concepts.”

When you Google ‘systems thinking’, isee systems always comes up first

Datta and his colleagues knew that even before any model was built, they would need to collect data to drive simulations. “We had built a systems map based on work done by Seeds of Change but couldn’t quantify anything,” says Datta. “The state Department of Agriculture had geographic information system (GIS) and other data, but it took about five years and some commissioned studies to collect propriety datasets of market, consumer, resource, and economic information.”

With data in hand, Datta sought out the model building skills Ulupono needed but lacked. To get the systems model-building help needed to examine the complexities of Hawaii’s animal and vegetable food production, understand constraints better, and identify leverage points, Ulupono turned to isee systems. “When you Google ‘systems thinking’, isee systems always comes up first,” says Datta.

The model was built on-time and on-budget and led to discoveries that have impacted our initiative’s strategic direction

Datta found that Ulupono and isee systems shared a similar design-test-validate approach to Systems Thinking and model building. “The engagement felt like a peer-to-peer dialog. Karim Chichakly from isee systems had to come up to speed on the farm-to-plate chains for vegetables, fruit, and animal products and he brought us up the model design curve – how do we avoid unnecessary loops and avoid the danger of digging too far down. Karim built a model that identifies system constraints and leverage points and helps us discover how to get from A to B.”

Working together, Ulupono Initiative staff and Karim built a model that utilized collected data to yield several critical insights. “It was a great experience,” says Datta. “The model was built on-time and on-budget and led to discoveries that have impacted our initiative’s strategic direction.”

Essential Discoveries

One way to double the amount of food produced in Hawaii could be to double the amount of agriculture in Hawaii. The model quickly pointed out it wouldn’t be that simple. Conventional agricultural methods are not likely to double production. “Growers need to apply precise, technical approaches to avoid the system’s fundamental constraints,” says Datta. “For example, growing lettuce in greenhouses requires more capital, but avoids land and water constraints. A ranch that actively manages grazing will yield more protein than one that practices traditional foraging.”

The model helped us realize that we can’t be ideological in our decision making

The model also pointed out areas where agricultural goals compete. For example, should animal feed be imported to free up limited valley acreage for vegetable crops, or grown locally to reduce shipping costs and build that portion of the local agricultural market? “The model helped us realize that we can’t be ideological in our decision making,” says Datta. “We have to practically balance inputs to get increases.”

Along with natural land and water resources, governmental regulations also present systemic constraints. The federal Food Safety and Modernization Act went into effect in April 2017 and aims to prevent rather than correct food contamination. “If the Act’s requirements take out half of our farmers, we’ll have a significant loss in food production,” says Datta. “But losses really depend on who replaces the growers that the Act impacts. Replacement by larger, lower cost growers would hit the system less than replacement by smaller, higher price growers.”

Increasing or decreasing the amount of time it takes to get a permit makes a big difference in the amount of food produced

Hawaii growers are required to attain permits and that process can take years. The permit barrier to new growers constrains the state’s agricultural capacity. “The model shows us that increasing or decreasing the amount of time it takes to get a permit makes a big difference in the amount of food produced,” says Datta.

Government limits on immigrant labor also impact agricultural capacity. “Hawaii depends on immigrant labor,” says Datta. “If the number of immigrants allowed to work here is reduced, the state will not be able to meet its goals, even when new technology is applied.”

Ulupono Initiative plans to use modelling insights to work with state government officials. “We’ll also use the model in our specific conversations with growers,” said Datta. “It will help us talk about what can be done to move toward goals, what should be done, and what won’t work.”

The model isee systems created and the questions we’re asking apply to just about any agricultural system in a defined geography

“Systems Thinking models are really good for gaining a shared point of view,” says Datta. “We built the model first and foremost to inform ourselves but now that the core code is in place, we have a tool that will help others with the same desire to discover Hawaii’s agricultural system’s leverage points and constraints.”

“The model isee systems created and the questions we’re asking apply to just about any agricultural system in a defined geography,” says Datta. “People everywhere are asking ‘Can we feed ourselves? What will it cost? Will people buy what is produced? At what price?’ Those questions are the same everywhere.”

About Ulupono Initiative: Ulupono Initiative is a Hawaii-focused impact investing firm that uses for-profit, non-profit and social investments to improve the quality of life for island residents in four areas: locally produced food, clean, renewable energy, and waste and water management.

To learn more about Ulupono Initiative, visit www.ulupono.com.

African Leaders Embrace Systems Thinking Approach to Problem Solving

An anesthesiologist from Uganda who is passionate about reducing maternal and infant mortality rates. An occupational therapist from Botswana, hoping to improve rehabilitation services for car accident victims. A research clinician from Kenya focused on acute HIV infection detection and prevention. A food safety expert from Nigeria intent on ensuring farm to fork food reliability.

Modeling is important to the types of problems they want to solve

Those are just four of the 25 professionals who spent six weeks at Ohio State University (OSU) as part of The Mandela Washington Fellowship for Young African Leaders Institute (YALI). Another 975 YALI participants attended programs offered by universities across the United States. Highly educated and professionally experienced, the 1,000 member 2016 YALI class was selected from 40,000 applications.

A major component of the OSU program was taught by Rudy Hightower, CEO, Hightower and Hightower LLC, PhD Candidate, Ohio State University and Cara Clark, his Senior Research Assistant. They focused on applying System Thinking to the complex issues participants faced in their day to day work. “Modeling is important to the types of problems they want to solve,” says Clark.

Organizations that are employing Stella... really impressed the group. It got them excited

Hightower and Clark used lectures and hands-on instruction to move every participant from paper-based mental models to fully functioning models built with Stella. “System Thinking, modeling and simulation were new to every one of our participants,” says Hightower. “We started with an introduction to non-linear modeling and how it’s being used for decision-making. We showed a slide with logos from well-known companies and organizations that are employing Stella and that really impressed the group. It got them excited.”

Stella is easy to learn and easy to teach, I knew students wouldn’t be fighting the software as they built their models

Barry Richmond’s Introduction to Systems Thinking guided the group through basic concepts that were applied in presented systems, including a basic population model. During independent working sessions, participants began to develop and build their own models. “First they defined stocks and flows related to their research topics, then built running models, and then developed interactive, decision making interfaces,” says Clark.

“Every participant was impressive, really smart,” says Hightower. “They came in on Sunday, worked late, argued with one another to schedule extra one-on-one sessions. The YALI Fellows all watched Chris Soderquist (isee systems training partner and consultant) videos to get ideas and extra help. They wanted to be sure they could bring their work home and present it. It was inspiring to see how fast they went from zero to hero.”

First introduced to Stella by his PhD advisor in 2011, Hightower was familiar with the software’s ease of use. “Stella is easy to learn and easy to teach,” he says. “I knew students wouldn’t be fighting the software as they built their models. Students intuitively clicked and dragged to automatically connect stocks and flows. We helped them put buttons on their graphs so that they could run their models and see results.”

Once their models were working, participants wanted to test them with real data. “Dr. James Kumwenda from Malawi actually called home to get data on the distribution of malarial drugs in his country,” says Clark. “There’s a high rate of drug theft in Malawi. Dr. Kumwenda came to the YALI program hoping to find ways to increase accountability for stocks. He left with a running system dynamics model that will be presented to government officials.”

Seeing how the system could work was like turning on a light. Without Stella, she would have been dead in the water

Another participant, Dr. Isabella Epiu, a NIH Global Health Fellow from Uganda with a Masters in Medicine, was also concerned with access to needed medicine. Her modeling efforts were aimed at anesthesia supplies. “Using her model, she could make a small increase in supply flow or decrease waste and see how each change would build anesthesia stock levels,” says Hightower. “Dr. Epiu found that simultaneously addressing inflows and outflows made the biggest impact. Seeing how the system could work was like turning on a light. Without Stella, she would have been dead in the water.”

Poor access to critical medical supplies and care was a concern for Dr. Enque Endeshaw too. A physician and licensed psychiatrist from Ethiopia, Dr. Endeshaw is engaged in increasing access to mental health care services for resident and refugee populations throughout Ethiopia. With a population of nearly 100 million people, Ethiopia has only ~160 psychiatrists. “Enque brought her model home and with her new Stella Architect license and is continuing to build upon her model while working on a research paper she hopes to present at the 2017 System Dynamics Conference in Cambridge,” says Hightower. “We’re emailing and Skyping back and forth to continue to support her and help her gain confidence so she can improve and present her findings.”

Dr. Endeshaw is just one of the many participants who have stayed in touch with Hightower and Clark. “We forged a lot of friendships and have been in touch over email, Facebook, and Skype,” says Clark. “We’ve even helped several participants get Stella Architect licenses.”

The OSU program also introduced YALI program staff from the Department of State to Systems Thinking and Stella. “We had a visitor from the State Department who was amazed to see what the fellows were doing,” says Hightower. “They’re already trying to get us to offer the same program next summer.”

While Hightower isn’t sure if his schedule will permit him to instruct a new group of YALI fellows, he knows he’ll continue applying Systems Thinking and Stella in consulting projects. “isee systems has been so supportive of our System Dynamics teaching and work with Stella,” says Hightower. “When Stella Architect came out, we were like kids in a candy store. Stella really blows other applications out of the water.”

2016 Mandela Washington Fellowship for Young African Leaders – Ohio State University
Participants and their modeling focus:

• Jack Abuli, Kenya – securing farming communities
• Mensah Adika, Niger – best practices for tackling cyclical food crises
• Camus Adoligbe, Benin – establishing non-governmental organization for community development
• Ghislaine Glitho ep Alinsato, Benin – increasing investment in medical equipment, infrastructure, and human resources
• Cosmos Anweh, Nigeria – creating a network of agricultural revolutionists to grow sustainable practices
• Frederick Danso, Ghana – training farmers on post-harvest management
• Abdoulaye Diallo, Guinea – implementing the USAID bilateral Health Service Delivery project
• Enque Endeshaw, Ethiopia – increasing access to mental health services
• Isabella Epiu, Uganda – increasing availability of anesthesia supplies
• Kine Faye, Senegal – developing sustainable rural communities
• Carmen Havyarimana, Burundi – reducing maternal and fetal mortality
• Ehigie Imarhiagbe, Nigeria – pioneering person and institutional excellence in dentistry
• BB Ismail, Nigeria – raising public awareness of food safety to reduce foodborne disease
• Tania Katanga, Democratic Republic of the Congo – promoting financial inclusion and sustainable growth of businesses
• Lady Kgaswane – delivering occupational therapy services to car accident victims
• James Kumwenda, Malawi – reducing theft of malaria medicines
• Hakimu Msombe, Tanzania – enhancing sugar production through small-scale projects that include women and youth
• Beauty Mulenga, Zambia – training for agriculture entrepreneurship and gender mainstreaming
• Grace Mwashigadi, Kenya – preventing disease though education
• Sulani Nyimbili, Zambia – improving the efficiency of disease surveillance and information systems
• Emmanual Odama, Uganda – promoting sustainable, climate-smart agricultural production
• Hija Raphael, Tanzania – supporting small and medium-sized business enterprise growth
• Anatasia Tomson, South Africa – fighting for transgender and LGBTAIA rights
• Coli Tfwala, Swaziland – assisting orphan children and youth and destitute women through business development
• Ubk Ubaka, Nigeria – promoting ethical provision of health care

Learning Environments: Design and Theory Live Online Course

Over the last couple of months, we've offered free webinars that introduce you to some of the mechanics of the new features of Stella. We now invite you to put that gained knowledge to use in our new online course, Learning Environments: Design and Theory. Taught by one of our lead developers, Billy Schoenberg, students will work through the key components of creating effective learning environments. Each class will finish with a designated question and answer session with Billy to help you solidify your learning from the class.

Did you miss out on the previous free webinars on mechanics? Not to worry, we record all of our webinars and you can view them on YouTube or our Webinar page. Recent webinars include, Designing Interfaces with Stella Architect, Creating Engaging Content with Stella Architect and Building Multiplayer Simulations with Stella Architect.

New features in Stella...Are you up to date?

There have been great developments for Stella in 2017! Our new software has been out for over a year now and the new engine has given us a great base to leap forward with our functionality, as well as introduce exciting new features. Here is an overview of some of the features currently available with our latest version 1.4.3:

Multiplayer Games

Create multiplayer games with which players connect from their own browsers and enter their decisions as inputs for the next step of the game. This allows multiple users to interact, make decisions for different roles, and learn from other players' decisions while running the simulation.

Animations

Create sophisticated animations based on SVG graphics files, moving images in response to model variables if desired. Color, size, rotation, position, and text can all be animated.

Data Collection Option

Assign different levels of data collection to your published simulations to learn more about how users are interacting with your models. After purchasing this per-model option, authors can collect run data or page tracking information from a simulation.

Coming in November: Optimization

Optimization allows you to find the set of parameters (constant values) that maximize some measure, or measures, of performance when a model is simulated. For example, suppose that you have a model of a fishery that related the number of days spent fishing each year to the number of fish caught. One question that you could address with such a model would be what number of days fishing will give you the most fish. Spend no days fishing and you won't catch any, but fish too many days and the stock of fish will be depleted. Sensitivity analysis allows you to map out the relationship between days fishing and cumulative catch and use that relationship to find the number of days to spend fishing. Optimization is a way of automating that process and can work with multiple parameters at the same time.

To help you analyze the results of optimization, we’ve added output graph and table formats, including Confidence, Histogram, and Correlation Plots.