By Laura Shores - April 17, 2020
Out of necessity, companies are making a rapid transition to remote work, shifting key processes and systems from in-person to online. While many have the basic hardware and software in place, most have not adopted the best tools to deliver the highest impact from their data teams.
During our recent virtual Fireside Chat, “What’s Remote Got To Do With It?,” we discussed how companies gradually optimize for remote work and why this typically doesn’t happen overnight. Only once they’ve realized the potential of distributed teams do organizations fully adopt practices and tools for working remotely.
In the conversation, Simon Ouderkirk from WordPress.com described it this way, “If modern companies look at the way they’re actually spending their day, on email and phone calls, they’re already working remotely. This is a journey and a spectrum and you’re already on it.”
The gap between our tools and analyst productivity
More than any other part of your organization, data teams need the right tools in order to be productive in remote (or really any) environments. However, the painful truth is that there is a disconnect between analysts’ ideal workflow and the modern BI tools they are using today.
In the same webinar, Tristan Handy from Fishtown Analytics expressed his frustration that normal collaborative tasks simply can’t be done on top of a Tableau workbook. He recommends choosing tools that allow you to adapt those types of workflows.
Tristan said, “I don’t know how to run a data team that uses Excel and Tableau as the first-class tools in a remote-friendly way. It’s just not that easy to do. The way that you produce the work needs to be aligned with the work style that everyone’s using.”
These descriptive BI tools are not only incompatible with analyst workflows, but also leave teams ill-equipped to keep up with the repeated, complex diagnostic inquiries the business is more frequently requesting.
“I don’t know how to run a data team that uses Excel and Tableau as the first-class tools in a remote friendly way. It’s just not that easy to do.” – Tristan Handy
The core issue is that dashboards only present static, surface-level trends on changing metrics, which ultimately inspires more complex, operational questions from the business. Those complex questions are the toughest to answer, and analysts are left with the arduous task of manually weeding through the data in a process that can take hours to weeks.
Sisu: Fast, comprehensive diagnostics built for analyst productivity
Fortunately, faster, more comprehensive diagnostic tools exist. Sisu automates the manual, rote work of data exploration and surfaces the most interesting, useful, and hard-to-find facts in even the most complex data sets. Sisu’s answers are comprehensive, relevant, and interpretable by anyone, which ultimately empowers your analysts to achieve more, faster.
For example, with a dashboard anyone can see that a KPI like average session duration is flat this month. But they can’t answer what’s driving engagement – or harming it. Analysts can get a lot of actionable information from just one fact in Sisu, and have instant visibility into the factors that matter most with granularity that a dashboard could never surface.
Another way Sisu enables analysts to move quickly is by sending real-time notifications when key performance indicators change. Analysts become real-life heroes when they can proactively reach outside the data team with new information, never breaking the link to the data, to keep the business on track.
For example, if you’re tracking differences in viewer behavior week by week, like retention from episode to episode, Sisu can send you proactive notifications as your metrics change and as new trends in the data emerge.
Flexibility is key in remote environments, and Sisu is accessible for teams on any device. Sisu is delivered as a SaaS-based application designed to keep an analyst in the loop, and to ultimately make analysts faster and more efficient.
Finally, no matter how analysts are distributed in your organization they all need to be using the same stack of tools for optimum productivity and alignment. For example, If you have three different teams using three different project management tools this becomes an alignment issue, and agreeing on a tooling stack is essential.
“What you want to do is solve data problems, and you want to do the things that get you fired up. A good stack and set of processes around it is key in both remote and co-located environments.” – Simon Ouderkirk
You can listen to the full virtual Fireside Chat here, and dive deeper into transparency, the importance of documentation, as well as how analyst teams can best collaborate with the rest of the business.