How to ship faster? Tips to reduce waiting times

Product teams have long theorized concepts of velocity and agility to enhance their speed of delivery to users. As someone who (too?) often likes to draw comparisons between Product and Data teams, I find myself wondering – can these frameworks be applied to data teams?

To be honest, over time, my conviction has grown that while the framework certainly holds importance, the "waiting time" between working times arguably matters even more. I defined waiting time as the time needed to start a project, the time needed to hear back from a stakeholder after delivery, the time needed to fix a bug, the time spent building something that was not needed. And from my experience, there are 3 things you can act upon to reduce waiting time:

1. Preparation — The art of understanding the context and discerning what we need
2. Collaboration — The art of aligning all stakeholders in a timely manner
3. Decision-making — The art of quickly addressing complex questions.

About preparation

In the world of data, preparation involves more than just identifying the tasks to be accomplished. It's about understanding the roots and relevance of each request.

When clarity seems elusive, ask more questions. It’s essential to comprehend the why behind the what.

That understanding will help you decide between implementing a comprehensive and costly to build (and maintain) dashboard, or executing a quick-and-dirty, "coin de table" analysis that has known limits but may offer a quicker turnaround.

About collaboration

A slow feedback loop, whether it spans days or even just a few hours, can be a significant setback in velocity. If you've implemented something that isn't used or tested promptly, it can create future challenges and give the impression of a sluggish process.

Collaboration is about working together; but it's about working on it synchronously. It’s about ensuring the right people are engaged on the right topic at the right time. I am not saying async work does not work (obviously as we're async first ourselves) but in that scenario the synchronicity will come from the process and how much it is trusted.

About decision-making

At its core, business intelligence exists to expedite decision-making for the business. However, the concept extends beyond just the major decisions – it also applies to the myriad of smaller choices that help build the case to answer bigger questions. Preparation and collaboration are crucial ensuring empowerment for the data analysts, scientists, and engineers in the process. Any step of the way, they will need both the context and the confidence so they can enable a faster and more effective decision-making.

"The journey to the bigger answers is often paved with many small, but wise, decisions." — says me on June 20th, 2023*. You need to make those decisions fast.

Velocity is about making things go faster (obviously) but actually making it happens relies on how smooth the process is running. Time is most of the time lost at the frontiers between tasks and teams.

Prepare more. Collaborate better. Make small decisions faster.

Ah, one more thing. You can also bring velocity during work time ("hard skills"): reusing existing work might then be the easiest path. At Husprey, we're announcing our now-production ready Query History, our public beta for Variables and will soon be announcing our AI assist product so reusing previous work is always easier. Get in touch with us if you want to try it out.