Articulating the Intricacies of our Problem and Solution Space
Ethan Kang, Teddy Smith, Pedro Dal Bo, Manav Shah, Justin Hopf
After developing our system map several weeks ago, the next step was to better understand our problem space and get a better grasp on where we wanted to work specifically within the field of improving agriculture while fighting climate change.
With this in mind, we set out with a focus on how the agriculture industry could be improved to minimize its impact on the global ecosystem, namely its impact on climate change. This mentality was supported by our assumption that this was the best solution avenue to tackle the global issue of climate change, leading to our initial explorations into potential solutions, whether it be a physical device, digital application, campaign, or educational program, as well as trying to work out potential stakeholders to interview regarding our product, such as farmers, public servants, and those on the business side of the agriculture industry.
How Our Problem Space has Changed
We spoke to several professors and researchers at Georgia Tech in the field of sustainable agriculture, and to our surprise, they shared a common belief that the most pressing issue within the intersection of climate change and agriculture was water usage in a climate-change impacted ecosystem. Although this fell in line with our belief that climate change would impact the agriculture industry, we realized that our approach to this problem space may not have been the best. They all echoed a similar point in how climate change would have wide effects on the availability of water worldwide. Furthermore, they discussed how optimizing water usage was relatively uncharted territory and has been proven to be just as vital to improving yields. With this insight, our team decided the best path forward laid in a problem area pivot towards a focus on water usage efficiency, as its importance is critical to the sustainability of agriculture and has a great deal of flexibility in terms of what kind of solutions we can develop.
Problem Space Overview
As climate change continues to impact our ecosystem, the availability of our natural resources are threatened. The agricultural industry is a key player within this development, sitting at both ends of the cause-effect relationship. Agriculture has a huge dependence on water, making up nearly 70% to 80% of global water usage. With this, as water supplies are threatened, agriculture is therefore threatened and by extension, global food security.
Furthermore, based on a supply-demand relationship, as water becomes more scarce, water prices are likely to rise, despite water being a natural resource. Small-scale farmers are likely to be the most vulnerable to this economic impact, with already diminishing profit margins on their crops which are already seeing increasing vulnerability with harsher weather patterns.
With this problem space in mind, our goal is to consider current water systems used in agriculture and develop innovations to reduce unnecessary waste of water, while still delivering the optimal amount of water to keep the farms thriving through a changing environment. This is our main goal, this is our challenge: to help agriculture thrive under any climate, and through any challenge.
In order to facilitate the thought process of our solution space, as advised through our Grand Challenges class, our goal was to develop multiple models based on the Lean Canvas methodology. However, because the variation between our various potential solutions shared a similarity in their target audience and methodology, namely farmers and focusing on water usage efficiency, respectively, we created one Lean Canvas model that was all-encompassing of our potential solutions.
Understanding the Lean Canvas Model
The Lean Canvas model is specifically designed to help layout all the different components essential to starting a business or creating a product and understanding the central business models. By brainstorming each of these different sections, we can delve into a deep understanding of the underlying causes and implications of our problem space. Furthermore, we can identify the most pressing components of the problem and focus much more closely on how to best go about tailoring a potential solution based upon the needs of specific groups affected and other business metrics.
Problem
This section is one of the most important aspects to consider when evaluating a problem space and considering various solutions. Many startups that fail often do so due to a lack of understanding of their problem, spending unnecessary time, money, and resources on fixing a problem that doesn’t exist. With a complete and thorough understanding of the problem, it is possible to best allocate efforts towards developing a targeted and specific solution with real impact.
Existing Alternatives
In order to not develop a solution that already exists, or develop a solution that is not as effective as another existing solution, it is important to perform research on other alternatives in this problem area.
Customer Segments
This section focuses on who we’re trying to work with and help. Who are the users that are willing to use our product?
Early Adopters
Based on our customer segments, what characteristics are shared by our “ideal” customers who would likely be our early adopters.
Unique Value Proposition
This is the “hook” that compels an otherwise unaware audience into a potential customer.
High Level Concept
What is a relatable analogy that is a simpler explanation of our potential solution?
Solution
This is the development of our potential solutions based on the information gathered above. By developing the thought process behind the above solutions, it is now possible to brainstorm potential solutions with a strong understanding of the problem space, existing alternatives, and so on.
Channels
How can we connect to our customers?
Revenue Streams
Similar to the customer segments, this is an understanding of where our income would come from.
Cost Structure
What are the fixed and variable costs necessary for the creation of our product?
Key Metrics
These are the quantifiable metrics that allow for the evaluation of the success of our product.
With these aspects of the Lean Canvas methodology considered, our Lean Canvas is developed below.
Lean Canvas Analysis
After the construction of our Lean Canvas model, three important focus areas begin to emerge within our business model:: the problem area, the potential customers, and the solution area. The complete understanding of these areas are critical as they provide the foundation for our future solutions, and fallacies in our thought processes regarding these areas could be highly consequential for future stages of the developmental process.
Problem Hypothesis
Problem statements are simple statements highlighting what we want to achieve, with whom, where/when and with which intended outcome?
Farmers are striving to adapt to changing environmental conditions in a climate change affected world, we believe that improving water efficiency will improve agricultural resilience and increase crop yield amidst the current climate crisis, in turn helping farmers strive in the changing landscape.
Customer Hypothesis
To define the customer need, we need to use Customer Jobs-to-be-done identifying the customers underlying need and using their own voice.
As a small farmer, I want to be able to increase my crop output even though my region has currently been getting less rain than usual. My goal is to get the highest yield from the amount of water I already have.
As a large farming conglomerate, I want to be able to minimize my water expenses, yet get the same amount of crop yield or higher.
Solution Hypothesis
A Customer Value Proposition articulates the company’s offer of value to the customer. We use it to frame our value offering before we build solutions.
In a world of increasing water scarcity, our product will help optimize water usage patterns to reduce operational costs, thus increasing agricultural yield within the area of production output.
Understanding our Riskiest Assumptions
Breaking our hypothesis down to smaller bets allows you to co-create with your customers increasing your speed and volume of learning
Following the development of our key hypothesis, the next step was to understand the assumptions we were making and bring them to light. This is critical in the {brainstorming/development} process due to the implications of basing our solution space on assumptions that are not necessarily valid. For many of these assumptions, if they turn out to be false, then the specific consumer will have no need for our product.
This process involved taking our developed hypotheses and breaking them down into smaller sections, asking ourselves the question, “What has to be true for our hypothesis to be true?”
With this in mind, our team developed the following assumptions:
- Farmers are wanting to change the way they use their water
- Farmers want to have a higher crop yield
- Farmers are already aware of their water usage and can quantify how much they are using
- Farmers/corporations do not have a water surplus
- The area of interest is not negatively affected by climate change or is receiving more rainfall as a result of climate change.
- Improving water efficiency will diminish water expenses.
Prioritizing Assumptions
Riskiest assumptions testing moves your learning from being
extrinsic to your customer interactions to being a part of them. You co-create your solutions with the customer in real-time.
Once a list of key assumptions were generated, we needed to prioritize each of them based on their criticality — how important they are to the development of our solution.
We prioritized assumptions based on how much it would impact our ability to provide our product to the consumer if the assumption was false. For instance, if the first ranked assumption is proven to be false, then the consumer will have no need for our product. For the other five assumptions, if they are proven to be false, our product will still be viable but it may be significantly harder to justify it to our customer.
Our problem space assumptions were prioritized as follows:
Assumption #1: Farmers are wanting to change the way they use their water
- If farmers are against changing their water usage then there is no need for our product based around changing water usage.
Assumption #2: The area of interest is not negatively affected by climate change or is receiving more rainfall as a result of climate change.
- If this is the case, then the farmers/corporations will be less likely to adopt our product and change their policy. Our product will still provide value so there is still room for them to adopt it in order to increase yield.
Assumption #3: Farmers/corporations do not have a water surplus
- Farmers/corporations with a water surplus are less likely to care about their water usage. Our product is still viable because we would still be able to optimize the water usage when they have a surplus, so long as they are willing to give the project a chance.
Assumption #4: Farmers want to have a higher crop yield
- Farmers may only produce a specific amount of crops and improving their yield may leave them with an excess which they cannot get rid of. Our product can still help by helping them produce a specific amount while using fewer resources.
Assumption #5: Farmers are already aware of their water usage and can quantify how much they are using
- Quantifying water usage allows us to specifically target areas within the operation as a whole.
Assumption #6: Improving water efficiency will diminish water expenses.
- Consumers will be less likely to adopt the product if it increases expenses, however the product will come in the form of an investment which can boost profits in the long run.
Turning Our Assumptions Into Experiments
The final step is to test our assumptions through a testable methodology with a measurable outcome. This is made possible through the thought process of the following statement: “If we do A then B will happen.”
Assumption #1: Farmers are wanting to change the way they use their water
We will survey random sample of local farmers to see if water is truly a major issue to them.
- If this is not a major concern, we will need to get scientific data to support this.
Assumption #2: The area of interest is not negatively affected by climate change or is receiving more rainfall as a result of climate change
We are going to analyze rainfall patterns in farming areas and predict future behavior, using this information to discuss with climate experts about how excess rainfall may be impacting farming.
- Surveying climate experts in the region to determine the effect that climate change has had will help us estimate what level of involvement/implementation is required.
Assumption #3: Farmers/Corporations do not have a water surplus
We will ask companies/farmers whether they have a water surplus.
- Depending on their answer, it will either confirm or deny our assumption which will dictate our plan of attack.
Assumption #4: Farmers want to have a higher crop yield
Find out how water usage improve crop yield from researchers.
- This will be achieved by comparing the water used to crop output. We will need to determine what is the least amount of water that can give the same amount of crop. This can determine this by analyzing data available or collecting our own.
Assumption #5: Farmers are already aware of their water usage and can quantify how much they are using
We will need to talk to farmers to better understand how they measure the water they use.
Assumption #6: Improving water efficiency will diminish water expenses
This will be tested by comparing expenses of improving water system (buying our product) to remaining on old water usage system.
Conclusion
Over the course of this semester, we started with surface-level understanding of the intersection of climate change and agriculture, to developing a further understanding of the intricacies within these areas, as well as the underlying problems and groups affected. The creation of the systems map to identify the connections between different components of our problem space opened the door to discover potential solution areas. After conducting interviews with experts with a desire to discover unique insights provided by their knowledgeability, these conversations ended up resulting in our team’s pivot towards focusing specifically on water usage efficiency in agricultural production. Since then, we have fleshed out the essential components to understanding our problem in a business sense through the use of a Lean Canvas model, which specifically allowed us consider the product-solution relationship within a business model, as well as specific business metrics and components. Consequently, we have now developed a strong solution space and a detailed business model for this problem space, and are well-poised to begin next semester with a clear idea of how to begin designing the most-effective product solution that can best mitigate water usage inefficiencies in agriculture.
