How we manage risk in IT projects
Our time-tested work processes fight for your project’s success.
The problem: between a third to a half of IT projects fail—that includes everything from multi-million dollar outright failures, to overruns of timeline or budget, to projects failing to deliver what they set out to do, to adoption failures by customers or employees.
In our 20+ years, we’ve built hundreds of projects. Many came to us broken—and we’ve had a few fail in our care, too. From these experiences, we created a unique work approach that is focused on managing risk. It fosters software quality, asks critical questions early on, cultivates team happiness, and provides the highest likelyhood of project success.
Four ways we see projects fail
Bellyflops are the obvious ones. The software or hardware systems don’t work, and that’s discovered at the end of a long and expensive process. Surprise!
Often we see the wrong tool for the job, where an organization is committed to a software solution that doesn’t fit anymore, hasn’t been implemented well, or is causing increasingly expensive workarounds.
Even more often, we see untested solutions for unclear goals. In these cases, tactics have already been determined—perhaps by committee, an RFP process, or by poaching features from competitors. The tactics aren’t tested with the audience who will use them, and the bigger ‘why’ question isn’t asked. Sometimes we see variations on this, like fear of launching and feature addiction, where just one more feature will make everything perfect.
The most complicated case is failure to adopt—even if the product works correctly, the audience doesn’t find it useful enough.
How we fight against project risk
Nobody wants a project to fail. We’ve learned how to cultivate successes—and avoid surprises—by validating solutions with design sprints, real-customer testing, and validated product roadmaps. We uncover problems early, using integration prototypes, real-content fitting, and iterative UX/UI design. Finally, we create quality software by working in iterative sprint-driven cycles, supported by extensive tests, and deployed using automated DevOps.