I recently got an email from the university soliciting ideas for efficiency improvements, so it is a good time to document the “kaizen” (continuous improvement) culture in my unit. For context, Arts ISIT has a small software development team, which I belong to. Our mandate is to support the T&L, research, and administration needs of our faculty, by adapting or developing technologies. The requests are diverse, yet ISIT is just a unit within the Faculty of Arts, so our funding is quite limited. That means we need to be efficient. I have never used the term kaizen at work, as we are a long way from being a Toyota story, but I have a belief that if a small team continuously self-reflects on process efficiency and leverages the vast intellectual capital in a university, it can provide top-notch service and create world-class innovations.
A successful case study at Arts ISIT is the CLAS project. CLAS is a video management and interaction system that arose out of the need to apply videos in education in a pedagogy-rooted manner, simplify user experience so that using videos in a course is not a burden, and give students deeper and more varied ways of interacting with videos. Spreading mainly by words of mouth, CLAS now serves 2500 students each year in 3 faculties and satisfies many complex requirements that cannot be met by Youtube or off-the-shelf video systems. CLAS also supports research from Psychology, Education, and Applied Science, and incorporates some of the findings back. The kaizen spirit that is now spreading in my unit can be said to have begun with this project.
The service model of CLAS represents a win-win-win collaboration between researchers, educators, and staff. Researchers see their latest work implemented professionally within a year or two from an initial idea, and limited-scope results from singular studies are aggregated into a complete product suite that may gain critical mass as a whole. Educators benefit from a video system informed by up-to-date research. As staff, I have the opportunity to apply my M.Sc. degree in HCI, received at UBC, to the fullest. Our support staffs also enjoy the boons of in-house product control. Because the development is very close to users, when an instructor has a novel use-case related to videos, our support team can confidently say “Yes, or if not yet, we can discuss how to make it happen.” Thus, the support work for CLAS becomes more intellectually rewarding, with activities like consulting educators on the technology and learning about their pedagogical needs, as opposed to firefighting problems that cannot be resolved internally. Finally, this project and others at ISIT instill in our staff and our users a sense of pride, as we are all contributing to UBC products that could be called “world-class.” After all, various external parties have inquired us if CLAS is commercially available yet (including universities in the Canada, the US, Japan, the UK, Australia, New Zealand, and most notably, the Ministry of Education of Singapore).
In other words, the dev team at Arts ISIT could be seen as the start of something similar to MIT Hyper Studio, Media Lab, and similar research & development groups in other top universities.
A good model still needs good execution, so what are the day-to-day secret ingredients of CLAS?
- Keep team structure flat and task division fluid: In the early stages of CLAS as a production service, I handled nearly all support tasks and communication, despite my official role of programmer analyst. This was not out of an obsession over a technology or a lack of organizational discipline, but completely out of needs. Like in a startup, the person most knowledgeable about a topic at each stage of an endeavour will handle whatever tasks necessary to move the endeavour forward to the next stage until others can take over. As the project matures, division of labour and communication happened fluidly. Our support team began to take over, and now completely own, the support website and user documentation. My manager took over all the project management aspects the moment the abstract visions became clear enough that a scope could be defined and split to milestones and tasks. Our unit has 25 people total, but most importantly, 19 of them are technical support, instructional support, and engineering staff. This makes for a rather “flat” management structure, with the most resources being spent on the productivity drivers. So how do we accomplish the requirement analysis and evaluations of alternative solutions? We leverage the intellectual capital of the university, which is our next best practice…
- Collaborate! Communicate! My academic chair, my manager, myself, and our learning support team routinely reach out to our faculty members, using any channel most convenient for the faculty members to share their thoughts: walk-in consultation, focus group, contact forms, and support email address published in multiple locations. We are flexible and eager to listen, because providing service to faculty members and students is our first priority, not procuring technology for technology’s sake. Our analysis and evaluation function is thus distributed among my manager (finance & resource planning), myself (matching technical constraints and alternatives with functional requirements and usability), and the faculty members themselves (contributing their observations from the trenches, research results, and a first hand account of their needs). The direct communication and flat team structure make this process remarkably fast and effective compared to the big corporate cultures that I used to work in. The startup attitude also inspires a sense of ownership in faculty members and partners, even those outside of Arts. Three other Faculties have independently solicited grants to add functionalities to CLAS, and Faculty of Education in particular even volunteered to create professional orientation videos for the system.
- Intellectuals lead and management manage: As the technical project lead, I have the clearest sense about what is possible now, what is not yet possible, and what can become possible given each architectural choice. I discuss these options openly with my manager. My manager creates the project management scaffolding around my work, but keeping to the abstract requirements instead of dictating the “how”. My manager also lends a set of strategic eyes and ears for risks and funding opportunities, and discusses them openly with me. Management gather the fuel to keep the ship going and look out for rocks and shallows while intellectuals try to navigate the map and steer. We developed trust and respect from this healthy partnership.
- A technology project needs a lead with deep working ability in technology and also in user experience, since this role requires bridging the engineering gap between stakeholders’ needs, expressed in human language, and all the abstraction levels of technology. More generally, you could say that a project about a domain X needs a lead who is both an expert in domain X and in user experience.
- Our support team is also our Quality Assurance team, allowing support staff to become very familiar with each new set of capabilities before those capabilities are released into the production service. In addition, front-line support staffs have an intimate knowledge of how instructors and students think, which inform their testing. Finally, work study students who support our technology learn a variety of useful skills: QA testing process, drafting test cases, user consultation, and articulating about technology.
- Test! Verify! Assume nothing! I test my projects ceaselessly with each incremental change, so that by the time a release reaches QA, it is already virtually problem free. When integrating an external technology, I verify all advertised features, keeping in dialog with our instructional design and support staff or directly with our users, to make sure that use-cases are actually being met *at an adequate quality of user experience*. I insist on a very generous allotment for testing in project time estimates, because an exhaustive verification regiment is crucial to high service quality and also results in a net cost saving. It is much easier to fix a bug in code you just wrote, or an external product you just integrated, than to deal with a trouble ticket about a hasty decision 6 months before. More importantly, a single IT problem or subpar user experience can waste hours of 20, 50, 100 faculty members at a time, negating any hypothetical benefits of short term cost cutting methods.
- Give time for engineering: The CLAS project is characterized by a paradoxical combination of blistering productivity and high quality. A huge number of enhancements are released every term (this is a typical 3-month update), while having a yearly trouble ticket count of less than 5. This is due to my insistence, and my manager’s support, on spending time creating and improving our engineering framework. A few of our pearls:
- There should be a multi-tenancy architecture for every project, big or small: each tenant (virtual instance) should be able to stand on its own physical server or a shared server, yet is completely separate from each other in terms of database, code base, configuration files, database users and passwords, and encryption key. These instances should be so isolated from each other that you can compromise and destroy one instance without any harm to all the others.
- Every project should be version controlled: The repository structure for each project should contain separate areas for core deliverables (code, configuration files, database schema, etc.), implementer’s documentation (technical notes for me and others in the dev team), stakeholders’ reports (drafted by myself after each milestone, improved upon by support team), and user documentation (by the support team).
- Every project should have an automatic, transparent upgrade system in the back-end: this kind of systems pays for itself many times over in productivity increase and reduction of human error. So how transparent are we talking about here? Watch the demo!