Our Services
- Initial Consultation: A quick 1-2 hour discussion where we will help you tease out the shape of your issue and empower you to choose your next steps (includes a short post-consultation summary and report).
- Detailed Consultation & Report: A multi-day consultation (including site visits, if desired) where we will take a deep dive into your systems and processes to help you understand what’s going right, what’s going wrong, and how to fix it. We will produce a detailed report explaining our findings and proposed solutions.
- Bespoke User Guide/Explainer: Struggling with a new technology at work or at home? We will write you your own user guide, personalised to your needs and your priorities.
- Interested? Contact us at heberle@testudyne.com
Our Focus
- We specialise in people-focused design: identifying sources of friction, confusion and waste and helping organisations remove them. Rather than boosting a specific expensive technology, we seek to identify solutions that align with the people who will actually use them, even if it ends up being “low-tech”.
- We prefer to hear the problem in your own words, and, if possible, observe the processes of your organisation as it goes through its day-to-day business. We aim always to be a non-judgemental, sympathetic eye in these situations: if a system is not understood by its users, the flaw lies with the system, not them.
Case Study: Making Cakes Digital
- In consultation with a local sole trader, we identified an accounting and invoicing solution that enabled their cake business meet upcoming Making Tax Digital regulations and advised them on tools to manage their social media presence. Additionally, we suggested modifications to their workspace to help them avoid losing their working sketches in the period between planning a cake and assembling it. Since their workflow was based on physical sketching, we judged that an electronic solution would cause unnecessary disruption compared to an appropriate display and filing system.
Case Study: Local Landmarking
- A not-for-profit was struggling with how to process a large, unlabelled image dataset within the constraints of their limited volunteer base. The local nature of the images, depicting people and places with little to no online presence, made crowdsourcing an inefficient solution and machine learning a non-starter. Instead, we advised them on how to distribute labelling tasks to make the most use of the time of their limited “high local knowledge” volunteers.