A digital agriculture leader wanted to reduce operational friction, track and provide data lineage, and improve data quality for internal users of their data pipeline.
- Persona research
- Story mapping workshops
- Technical discovery and recommendations
- Plan and begin implementation of the solution
- Comprehensive personas and journey maps documented crucial pain points for users interacting with the existing system
- Comprehensive story map and roadmap drove the vision for delivery and implementation
- Story mapping with users increased engagement with the problem, organizational alignment, and decreased cross- department communication silos
The Challenge: Disconnected Users
Customer obsession has been a prevalent buzzword in the last decade – and the data has backed up the important role it plays in a company’s success. But what if your customer uses a back-end system? The traditional ways to practice customer obsession are challenging to apply. A digital agriculture leader based in the midwest faced just this problem. Their flagship product uses field and machine data, fed by a data pipeline, to help farmers make better, more informed decisions about their crops. Internally, the organization faced challenges maintaining the pipeline due to evolving complexity, difficulties with navigation, and siloed knowledge. They sought ways to reduce frustrations for those interacting with the pipeline and provide data lineage to increase efficiency.
Our Process: Human-Centered Design Agile
Employing our HCDAgile approach, we worked closely with the digital agriculture company to first understand and then solve the right problems for these internal users. This started by conducting qualitative interviews with all key stakeholders. These initial interviews helped us to understand the organizational structure and leadership’s view of the problem. From there, the team began deep dives into the existing code and architecture, while simultaneously conducting user interviews with engineers and scientists to understand the existing system and evaluate the experience of supporting or interacting with it. The technical and human-centered discovery work offered a holistic perspective on their challenges and guided further technical exploration and meaningful follow-ups with users, stakeholders, and technical contributors.
In the technical deep dives, we worked closely with key architects at the digital farming company to consider technical solutions alongside industry best practices. Together, we matched those possible solutions to the needs of their current infrastructure to ensure a sustainable outcome that fits with the existing system and skill-set.
Overall, the team interviewed more than 50 individuals, including product support, growers, scientists, database administrators, regulatory managers, software engineers, IT managers, data scientists, QA, architects, and others. From all of these interviews, we identified three key personas, mapped their experiences with the existing data pipeline in as-is journey maps, as well as how we predicted those experiences to change following implementation of the MVP solution. The problems we solve for our clients are complex, and the as-is and to-be journey maps communicate our understanding of the depth of a challenge and set the expectation for how an MVP solution will or will not make a difference to a users’ experience.
Additionally, we facilitated micro-story mapping sessions, which provided users and stakeholders with the opportunity to engage with the problem and collaboratively explore solutions. These sessions enabled us to fully capture the challenges and opportunities at hand and facilitate alignment around potential solutions.
Our teams took all of that information gathered and applied it to a collective story mapping session to give visibility to stakeholders across the board. From there, we scoped it down to the most critical problems to fix, validated with all stakeholders, and then developed solutions for those key problems.
The Outcomes: Uniting in a Comprehensive Solution
The HCDAgile process had several key business outcomes for the digital agriculture company:
Understanding and identification of most crucial challenges
We developed and delivered personas and journey maps following user interviews. These HCD artifacts, along with the developers’ participation in our discovery process, enabled them to better understand the technical challenges and how they were experienced by end users, enabling them to build for those specific purposes and needs. Personas and journey maps not only identify existing challenges but also help the project team stay focused on those challenges as the driving force behind the solution.
For example, user interviews helped redefine and prioritize the architecture. In the first phase of architecture priorities, the initial priority turned out to be inconsequential to users which led to re-prioritizing and adjusting the architecture to more accurately reflect user needs.
Bridging internal communication gaps
The process helped break down communication silos across the organization’s teams to surface previously undiscovered issues and grow visibility among stakeholders and users. Journey maps – as is and to be – helped demonstrate the opportunity for improvement and set expectations for how the solution could impact users’ work experiences. Working in lockstep, we established a productive, collaborative relationship with the existing client teams to complement and accelerate their efforts.
Engagement and alignment around a cohesive solution
By facilitating micro story mapping workshops, we creatively engaged stakeholders and end users in a process of knowledge sharing around the challenge and solution ideation. A comprehensive story map fostered alignment on an MVP solution and extensible opportunities along with ownership of the solution for the company’s teams, building buy in, engagement, and sustainability.
Ultimately, we worked with the organization to develop a directed, human-centered solution plan with a strong understanding of users and the flexibility to be Agile and iteratively improve. Future goals in the next phase of the project include improved data quality, scalability, reliability, and availability of the platform along with launching the next generation of services.
Would you like to learn more?
A digital agriculture company needed a way to enable easy adoption and utilization of their data platform for the engineers that use it both internally and externally to access agricultural insights.
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