Partnership Design in Social Enterprise at MIT’s D-Lab

Late last summer I ran an online Partnership Design workshop with 2 agribusiness social entrepreneurs from Kenya, Peter Mumo (Founder of Expressions Global) and Dysmus Kisilu (Founder of Solar Freeze). In this post, I’ll take you through the process of how a pay-as-you-go irrigation service (Expressions Global) could collaborate with a cooled storage service provider (Solar Freeze). A collaboration which appeared ready to go, but actually wasn’t quite there yet. 

Partnership context
Peter, and Dysmus met as part of the Massachusetts Institute of Technology D-lab project on inclusive partnerships, which is a year-long learning lab on the topic of Co-Designing Inclusive Partnership Models. 

When Peter, and Dysmus were introduced to the Partnership Canvas during the first session as part of the learning lab, they were inspired to collaborate with their 2 companies, Expressions Global (EG), and Solar Freeze (SF). 

They were aiming for the same customer segments, smallholder farmers, and both companies could benefit from connecting their services. More, high-quality produce in stable supply from better irrigation, and trusty cold storage would mean more interest from well-paying (export) traders, and thus more interest from prospective smallholder farmer clients.

A few months after the initial workshop where Peter, and Dysmus met, I checked in on their progress together with Saïda Benhayoune, who is Program Director at MIT D-labs. We proposed an online workshop to apply the Partnership Design process, in order to analyse the current status of their collaboration, identify next steps, and put the Partnership Design tooling to the test at the same time. 

Approach to an online partnership design workshop
Because our aspiring partnering entrepreneurs were based in Kenya, and Saïda was in Boston, and I myself in The Netherlands, we needed to a workshop setup that could operate remotely. 

We chose to use miro.com as a virtual whiteboard, which was accessible to all. We used Skype as a means for talking.

Despite the often tricky internet connection with Kenya, the combination of both tech platforms worked wonderfully for the 3 hours of discussion we had together. Especially the miro board provided a very interactive, and immersive way for virtual collaboration.

During our call, we went through all the steps of the Partnership Design process (see visual below, which can be explored in more detail here). The results themselves are discussed in the next section of this blog.

Partnership Design Expressions Global - Solar Freeze
Output from the remote Partnership Design session between Expressions Global, and Solar Freeze in Kenya. (click here to explore the full virtual board)

The Partnership Design Process

-Understand-

We started discussing both partners’s business models, using the business model canvas. From there we looked at current priorities, and challenges to both businesses. 

For EG the main challenge is to find an well-paying market outlet for the farmers that use their irrigation technology. Without a well-paying market, like a higher-end domestic, or  export market, farmers are less inclined to invest in their crops with irrigation. 

SF is looking to expand their presence in the market, building new units, and connecting with new farmer groups who would use storage for their fresh products. 

-Intent-

Next we explored both partners’ intent to collaborate; why do they need help from a partner to to achieve their priorities?

EG is in need of cold storage capacity in the supply chain of their farmers. That is key to access high-end markets, as it keeps produce fresh during shipment. However, investing in their own cold storage would be expensive, and it would detract from their core business, which is irrigation. It would be better to work with a partner that is specialised in storage facilities.

SF is in need for new farmers to collaborate with. But building those relationships is hard. It would make more sense to collaborate with an organisation that already has those relationships in place.

So it turned out, both EG, and SF have matching priorities, and also need collaboration to achieve them. EG needs cold storage, and access to higher-end marktes, which SF can offer. And from its end, SF needs access to organised farmers, which EG can offer. This is a solid basis for delving further into the design of their partnership.

-Design & Compare-

Using the Partnership Canvas we started discussing the setup of the collaboration. For EG it was clear what value the partnership needed to create. A cold storage unit, on site, near the farmers that they work with. 

One of the key assets that SF needed to realise the construction of their cooling unit was to have land available to place the unit. Peter said that through EG’s relationship with local landowners this could easily be arranged. Also this relationship could provide for security. Operationally it seemed possible to place a functional cooling unit.

The remaining question now was how SF could tie relationships with farmers, so that they would start using the cooling storage facility. Both Dysmus and Peter explained how farmers need to improve their production practice to meet the higher production standards, and how training of farmers was key. 

For that reason they thought that it would be appropriate to design a joint training for export markets for farmers, where Peter’s standard training on Good Agricultural Practices could be combined with a Post-Harvest Management content based on Dysmus’ experience. This training could be a way for SF to acquire new farmer-customers for the storage unit.

The Created Value form the partnership is labelled with yellow on the whiteboard

-Evaluate-

Now that the design for the collaboration was made apparent with the Partnership Canvas, we looked at the big questions that needed to be answered for the collaboration’s business case; the hypotheses behind the partnership (those are labeled in red on our whiteboard). 

For EG, the big question was whether the cold storage unit in combination with the training would lead farmers to dedicate more acreage to high quality (exportable) crops, and supply the (stable) volumes of that product . The needed increase in acreage, and productivity could be achieved through the EG’s irrigation service, which would mean more revenue for the business. Also, Peter expected that EG would be able to generate more revenue from commissions, as an intermediary in the trade between farmers, and exporters. 

SF had questions about how the training would influence utilisation rates of the storage units. The training would need to lead to new numbers of farmers that would use the unit, and an increase in the volume of product that they would store. This would impact revenue growth from the storage service.

These were questions about conversion from the farmer training to paying customers for storage on the one hand, and then on the other hand about productivity, and volumes of product that these customers would actually store in the cooling unit.  

Conclusion
The case for partnering turned out to be clear. The assumptions were reasonable, and if they were to be true, both business would benefit from the collaboration. 

The partnership seemed ready to move into action mode, testing the hypotheses in a pilot project. And an obvious first thing to start with would be the farmers trainings, which could even start before building the cooling units. Implementing the training would answer questions that both EG, and SF were facing. But despite this obvious first step Peter, and Dysmus hadn’t started their joint project yet. 

When digging into the issue, it turned out that Dysmus had made a wrong assumption in his numbers behind SF’s growth. Where initially he thought that SF could finance placement of new cooling units through its own profits, growth actually required external funding. So, SF’s arranging of funding turned out to be a very important missing priority in the partnership discussion, and was the cause for the hold-up. 

This piece of information also increased the importance of utilisation rates for SF’s cooling units, and whether the farmers’ training would actually lead to more farmers signing up, higher productivity of their crops, and more supply to the cooling units. This would be critical for financial viability of SF to bring return on investment of new cooling units.

This additional pressure on the numbers increased the risk to the partnership. Yet even more so, it pointed to the importance of starting of the joint training as that would provide key insights needed to confirm (or invalidate!) the business case in this early stage of the partnerhip. 

We left the conversation there, with a clear next step for Peter, and Dysmus to follow-up on. As for the result of the Partnership Design process, it pointed to the importance that a good preparation by laying out the starting situation of both businesses is critical for achieving momentum in partnering. If information is missing  in this orientation stage, the partnership will likely run into delays.

We’ll be sure to check in again with the EG-SF partnership again soon to see what insights the implementation of the training has brought. 

[PS. Upon reviewing this article, Peter explained that the partnership has run into an additional challenge, namely that exporters demand graded produce. They were assuming that cold storage was their only impediment.

So, despite having the relevant contacts with exporters in place, they still need to work out how to jointly fulfil the exporters’ product, and packaging requirements. The partnership now needs to involve sorting, and packaging facilities, which neither EG nor SF currently has.

Will it be a joint investment? Or will it be assigned as a responsibility to either of the partners individually? What are your thoughts? – Leave them in the comments below 👇]


Interested to learn more about Partnership Design?

You can join the Partnership Design Linkedin group!

Further inquiries? Send an email to: info@partnershipcanvas.com

Understanding appropriate UX requirements for on-boarding farmers to your agtech solution

The world of technology has only recently begun to design services for farmers. But the numbers show that this line of business is already growing rapidly. Investment records are broken every semester.

Underlying this development is the boon of the huge amount of data that a farm now generates. Like every other human being, farmers do book keeping, are active online, and use smartphones. They use such tools to solve problems on the farm, and by doing so, they’re generating data. There is also farm machinery, loaded with sensors generating lots of data. By combining such farm operations data with other data repositories, like open satellite data on water tables, precipitation, and nutrition data from the feed manufacturer, etc, data can be combined into useful applications that can help with farm management.

Despite the opportunity for the developer to build valuable solutions, there are also barriers that significantly obstruct adoption of digital solutions for farm management. An important barrier is created by technology solutions imposing certain implicit requirements regarding a farmer’s level of data saviness, to collect, organize, and distribute data. Even farmers who do understand the value of data management, generally don’t use computer or web-based tools.

The transfer of farm management practice to an online environment, is hardly seamless, and this transfer problem is a problem for many companies and startups that are developing services in this space. More often than not, I see solutions being launched that are at quite a distance from the kind of tech usability that a farmer can muster.

A Thinking Model
A rule of thumb for nailing product design is that you can best meet your farmers where they are. To help position where the farmers you’re targeting are in terms of tech saviness, I’ve developed a model form making farm data personas. This model is presented below.

A model for making farm data persona's
A model for making farm data persona’s

The basic idea is that any farmer, regardless of the technology, has to follow a flow of datamanagement in order to utilize and implement insights drawn from data in the farming practice. This datamanagement flow consists of 4 steps: Data Input, Data Storage/Retrieval, Data Sharing, and Data Analysis.

For each step there are a variety of options available to the farmer to handle their data. These options range from low-tech solutions, like paper-based record keeping, to high-tech solutions, like cloud computing storage, and SaaS for analyzing farm performance. (These can of course be adapted to whatever fits the sliding technology scale that matches your own circumstances.)

Next to profiling farmers according to their tech saviness, this model can also be used to indicate what level your solution currently requires your farmers to be in. By comparing these parameters, you can start to see, and understand the gaps.

Making technology appropriate.
Lets take an example of a solution of herd management for dairy farmers. Say you have an idea for a SaaS analysis solution, to offer online software for dairy herd management, like Farmeron. You will need to figure out a way to connect all the necessary data flows to feed your analytical solution. You want farmers to somehow get their cows to the cloud for analyzing herd performance, and you’re going to need a way to get them to digitize their input.

In the case that your farmers are still working with paper-based recording keeping, which is likely, you’re probably going to have to physically on-board their data. (As stated by Matija Kopic himself, founder of Farmeron)

Once you’ve identified this gap, the question then becomes what intermediate steps you can build into your solution to take farmers up the tech ladder. Can you redesign your product to include a learning curve, which will take your farmers on a journey to comprehend your solution, take control, and eventually make it fully usable?

Sticking with the example of Farmeron, they’re streamlining their person-to-person onboarding service with other support tools to educate farmers, and keep the learning going. This is something they had to configure on the fly whilst already being deeply rooted into their developed solution.

The upshot is that agtech initiatives will likely need to design for the farmer’s learning curve. Adoption for agtech solutions will be slower, and acquisition costs relatively high compared to other tech industries. This is something startups in this space will spend of lot of time on, and their investors will need to provide for the adequate runway.

—–
Thanks to some valuable discussions I’ve had about this model with my colleagues Lan Ge, and Marc-Jeroen Boogaardt at Wageningen University in our Farm Digital project, and also with my dear wife Anne Bruinsma, who happens to be a leading figure in agtech with Hackwerk Advies.