Knowledge Management and Peer Learning in a Community

Context: First year Master project – February 2018

Client: Herenboeren Wilhelminapark

Description of the challenges and solution

Poster summarizing the project

In a HerenBoeren farm, the owners – 150 families – are also the consumers, therefore eliminating the middle men and revolutionizing the supply chain. Members have a word over what and how it is grown. In 2018 the “herenboeren” had access to seasonal vegetables, meat (beef, pork) and eggs (chicken). The farm is located in Boxtel and more are in development in Weert, Rotterdam, Ede, etc.

The project facilitated the learning that takes place between the members of the community. It consisted of a digital platform which allows the users to share knowledge of tips and recipes. The sharing leads to a stronger community and a more meaningful experience. Users are presented with a personalized homepage which recommends relevant tips and recipes. The content is seasonal and based on the patterns in the family history.

This is valuable because the members take the food directly from the farm, which is not something the modern human is used to. It requires a set of skills to clean, store and cook the vegetables and meat. 

Process Overview

Starting from the Co-founder’s description of the community and it’s challenges, I conducted wide need finding research among the users through: safaris, observations, and interviews.

The data was analyzed into insights and placed on an Journey Map – which would be later validated with the users. The next steps consisted of framing a challenge (which was not previously articulated by the founder) and testing it’s perceived usefulness with members of the community through a rapid click-through prototype.


The attempt to complement the physical user journey with a digital one was validated, resulting in a later iteration involving members of the community as designers, engineers and content creators. The solution enabled knowledge sharing of recipes and tips through a live, high-fidelity prototype.

The resulting work is in production, serving real users, with the usual administration, maintenance and continuous tinkering challenges that come with the real world.


Storytelling Video – Iteration 1

Project outcome

A digital journey that complements the physical one:

Letting community members learn from each through relevant recipes.

The users include:

  • those who mostly consume recipes,
  • amateur and professional recipe creators and
  • the moderators


Below you can find the front page of the high fidelity prototype (implemented in the real world with real people). For example, on a Saturday, it is showing:

  • first the relevant Tips: when returning home with the groceries, the user sees tips on how to clean and store the vegetables
  • followed by Recipes: based on historical preferences and the tastes of the family

Homepage – Implemented with real users (built using WP Ultimate Recipe with custom CSS)

Starting point

The initial challenges we first discussed with the Co-founder were wide and multiple, among which: problems with planning the crops and harvest; educating other farmers on other farms of how to run a farm. After the initial user research using contextual interviews and shadowing, a set of frustrations became clear. The members had an unmet need of avoiding waste and improvising better with what nature provided in terms of seasonal vegetables. They also wanted to have a stronger feeling of belonging to the community.

User Journey starting every week on Saturday

It is important to note that the founders or the management board were not fully aware of all these issues (in red), which were only discovered during my initial research observations and proposing an initial prototype.

These issues would later become the defining characteristics of a new design, which had impact over the Value Proposition of the farm, and over the Strategy / Market in which it is active – starting the move

>> from a farm which sells products on a subscription basis with a community membership

>>>> to a service which offers a communal cooking and eating experience, a learning and confidence-building experience, and a feeling of being part of a (food) tribe.

User Research

The Research consisted of observation at the farm (tens of people), shadowing 1 user at home, informal discussions with many members who are either designers or operational excellence professionals and about 5 contextual interviews.

Picking up the products at the farm on Saturday

Fridge storage after the products are cleaned

Room temperature storage after vegetables are cleaned


After the initial discovery, the direction was chosen to be:

To facilitate the learning that takes place between the members of the community by building a platform which allows the users to share knowledge of tips and recipes. 

This is valuable because the members take the food directly from the farm, which is not something the modern man is used to. It requires a set of skills to properly clean, store and cook the vegetables and meat. These skills are very contextual and procedural (learned by doing, not reading or seeing), and so it matters to have a touchpoint at home where dynamic information is easily accessible, as opposed to having educational discussions only on Saturday at the farm.

The members wish to avoid waste and improvise with what nature provides in terms of seasonal vegetables. They also wish to have a stronger community, and the knowledge sharing helps in accomplishing those goals.

The challenges that could only be enumerated after the first Co-Reflections

As is often the case, the challenges above became clear only after the first iteration was presented for user evaluation in the form of a rapid prototype (Adobe XD mockup); paired with an experience flow in order to stimulate co-reflection.


Rapid Prototype – Iteration 1

Ideation was helped by the use of tools like: scenarios, storytelling, which slowly led to functionality, wireframes and a click-through prototype.


Homepage – Iteration 1 using Hellofresh recipes and Adobe XD

Sometimes a bit of acting out can do wonders for the process and getting unstuck. Below you can see a set of tangible figurines which were useful in acting out and storytelling for ideation purposes; as well as for presentation through an animated video.


User Testing is not described on this page. Following sessions using the first prototype, I discovered a group of people within the community (led by Paul) who were aiming to achieve the same goal, and we joined forces. Therefore, this work was indeed desired, and realized in a collaborative manner.

Iteration 2 is currently running live in the real world with real people contributing and using it. It is different from iteration 1 in that it is of higher fidelity and more precise in the features it offers.

Machine Learning

The Machine Learning algorithm was prototyped in order to make possible the “recommender” behind the platform. One of the limitations for the content moderator was that they had to manually propose a selection of content – while maintaining a high level of engagement, relevance and the “new”-factor. Using an algorithm enabled us to offload that responsibility, and paved the path toward a personalized experience.

Visitors during Demo Day had the opportunity to tangibly act out the algorithm and pretend to be in the mind of the computer. The prediction becomes more relevant in time, while being able to adjust with changing patterns. (for the technical people: Bayes was used)

Acting out the machine learning algorithm in a tangible way


In retrospect, my role as a designer became to express what the members wanted in the first place when they joined the community.

The end result was strengthening the connection between members, and helping them organize and problem solve in this decentralized organization. They have been doing it before I arrived, and would continue to do so after I left.

I would like to thank Boudewijn (Co-Founder) for allowing me to apply Design in the real world, and Paul (Active member) for accelerating the speed at which we prototyped and experimented.

Credits: the featured photo on the project thumbnail – source