A bias for observation
An old Zen parable goes: after studying to be a Zen teacher for many years, a student goes to visit his master. It is raining heavily and, as is customary, the student leaves his clogs and umbrella in the entrance before entering the teacher’s house. The teacher asks, “Did you leave your umbrella to the left or right of your clogs?” Unable to answer, the student goes away to study for six more years.
The takeaway from this parable is that, like the student, our work is incomplete if we are not mindful of the seemingly trivial around us. While this is relevant to anything we do in everyday life, it bears special significance when viewed in the context of creating products that customers can meaningfully interact with, and derive value from.
Andy Raskin has eloquently described how selling potential customers on the promised land can be the single narrative around which to align all stakeholders – internal and external. However, the path to the promised land is long and arduous, and in the pressure cooker environment of a startup, it is often too easy to go all-in on execution on an initial vision – a bias for action.
“We sold customers on a vision, surely we know better?”
Unfortunately not, in many instances. Known more famously from the lean startup methodology as Build-Measure-Learn, constant observation, analysis and fine-tuning is indispensable.
This need for observation manifests itself at various scales, and the learnings span the spectrum of practical to profound. In product design, a commonplace example is to let UX be driven by detailed analysis of data on how users were interacting with solutions. There is an original hypothesis on expected usage, but more often than not, real usage springs surprises that need to be incorporated on an almost continuous basis.
Sometimes the realizations and concomitant benefits are more significant, and relate to a complete change in the narrative and offering of the company – Slack being one of the higher-profile examples of this, where the realization that an internal tool (chat) developed in service of a failing product held value far beyond the product itself.
At LightMetrics, we try to keep getting better at more nuanced observation and analysis, of both our product and our customers. From realizing that the value of the driver and fleet analytics derived from our APIs are best communicated through fully fleshed-out dashboards of our own, to using granular usage metrics to learn what matters most to our users, it has been a gift that keeps on giving. Nothing however has given us more insight than the very old-world strategy of regularly meeting our customers and listening with empathy. Our product roadmap bears witness to this: from our evolution towards smart multi-camera solutions, to the deeply integrated telematics offerings through our partnership with Micronet.
All of this has led to a ton of things for us to execute on for this year, and exciting roles that we cannot wait to fill. If you are a motivated engineer working in Computer Vision, Android, iOS or systems engineering, drop us a note at firstname.lastname@example.org.