No More Dashboards

Why data dumping grounds don’t drive impact. (And what's better.)

We’re a data startup that hates “Dashboards” — that’s because what we care about is business impact.

Here’s why Dashboards fail to drive impact, what’s better, and why moving past the “Dashboard” will transform your business’s relationship with data, decision making, and execution.

The problem

One of the major frustrations with data tools (including “self-serve” data tools) is that most people still don’t really look at data that much.

Today, most dashboards represent wasted effort — no matter how many great “Dashboards” your team creates, most Dashboards sit idle, and then accumulate over time sucking up data resources to maintain them. We often see companies with tens, hundreds, or (at the enterprise end) thousands of dashboards. Most of these were requested by some exec, took hours or days to build, but then never got traction (they were reviewed with a passing glance, or maybe not at all). Even though they sit idle, your dead dashboards have a real cost. Over time, startups accumulate lots of confusing and conflicting dashboards & metrics, which either break or require expensive maintenance work to preserve (on the off chance someone needs them). Duplication muddies the waters when someone actually wants an answer. And stakeholders don’t really know how to interpret most dashboards — including because they lack context and narrative.

The core problem with most dashboards is they don’t map onto anyone’s workflow. The term Dashboard doesn’t really imply how the data will be used. That’s reflective of a deeper problem around how most dashboards are conceived. Often, dashboards are built in response to a request that focuses on the “what” — a list of metrics. What’s missing is a clear path that connects the dashboard with the operational workflows that drive business impact. There’s often a hope with dashboards that “if you build it the execs/ops will come”. But they don’t (at least not without a clear trigger).

When important data signal gets missed, it’s common to blame the team (”they don’t get data”) — but the real issue is this void between “Dashboards” and the operational workflow.

You can dramatically increase the impact of your data investment & the team’s decision making by tying data work into the operational workflow. The best way to do this is to connect data with specific, triggered moments when it’s natural for the team to look at data — and to create accountability around results via reporting.

What’s better

We propose replacing “Dashboards” with 4 categories of Data Documents — anchored on how they fit into your company’s day-to-day. Any time you introduce a new Data Document, you should bucket it into one of these 4 categories. This simple exercise will help you get more from your data investment because it forces the upfront work to figure out how data work ties into your team’s workflows and drives business impact.

Basically:

  • “Scheduled” = your company’s heartbeat. You should automatically review “scheduled” data docs at a regular cadence (e.g. daily/weekly/monthly/quarterly). These keep your team on track, and learning/executing quickly.

  • Ad hoc = answer targeted questions, as needed. Scheduled reviews often lead to questions that require ad hoc analysis to answer (”why is this number down?”). Or questions may otherwise arise as part of day-to-day prioritization and execution (”is this a big enough opportunity?”).

Here’s a more detailed view of the same thing:

* “Control Panel” isn’t an industry standard term. But we like it as a way of orienting the data views you look at regularly around the action you want to take off of the data.

** For sake of completeness, teams also consume data via “alerting” — which is is when data is proactively pushed out. Alerting can similarly be either scheduled or in response to a specific trigger. We’ll go deeper into alerting in a future article. )


How to get to a post-Dashboard (more impact) world

There’s no time like the present to better integrate data into your operational workflow. Whether you’re starting for scratch or have a ton of legacy work, you can start small and build up. We can help. And in the end it’ll be worth the effort. Here’s what you’ll get:

  • Better leadership at every level. Owners are looking at the right numbers at the right cadence, and have what they need to act on those numbers readily available.

  • Better company-wide execution. Teams execute better since they’re more accountable and better at information sharing.

  • Better decisions. The team is more informed and it’s easy to self-serve answers when questions arise.

  • More efficient data work. Data work focused on outputs that are actually used, with lower maintenance cost.

Daydream is the best place to connect data with operations & business impact. Most BI tools really only support single player use cases, are designed around data visualization vs. business impact & operational workflows, have terrible organization, feel technical, and don’t support context or collaboration. Daydream (in contrast):

  • Brings data into your team’s operational workflows — and makes it easy to collaborate

  • Feels lightweight, user friendly, and easy to use — while being packed with power

  • Can work as a standalone BI tool - or co-exist with your existing tool, as you bring in the “living” data that powers your operational day-to-day

  • Comes with expert support that’ll make it easy for you to get more from your data

We at Daydream can help you along your journey — or to design your data workspace intelligently from the start. Want to have a quick chat or to see an example of how this works in practice? We’re always happy to help. Just book some time here.

No More Dashboards

Why data dumping grounds don’t drive impact. (And what's better.)

We’re a data startup that hates “Dashboards” — that’s because what we care about is business impact.

Here’s why Dashboards fail to drive impact, what’s better, and why moving past the “Dashboard” will transform your business’s relationship with data, decision making, and execution.

The problem

One of the major frustrations with data tools (including “self-serve” data tools) is that most people still don’t really look at data that much.

Today, most dashboards represent wasted effort — no matter how many great “Dashboards” your team creates, most Dashboards sit idle, and then accumulate over time sucking up data resources to maintain them. We often see companies with tens, hundreds, or (at the enterprise end) thousands of dashboards. Most of these were requested by some exec, took hours or days to build, but then never got traction (they were reviewed with a passing glance, or maybe not at all). Even though they sit idle, your dead dashboards have a real cost. Over time, startups accumulate lots of confusing and conflicting dashboards & metrics, which either break or require expensive maintenance work to preserve (on the off chance someone needs them). Duplication muddies the waters when someone actually wants an answer. And stakeholders don’t really know how to interpret most dashboards — including because they lack context and narrative.

The core problem with most dashboards is they don’t map onto anyone’s workflow. The term Dashboard doesn’t really imply how the data will be used. That’s reflective of a deeper problem around how most dashboards are conceived. Often, dashboards are built in response to a request that focuses on the “what” — a list of metrics. What’s missing is a clear path that connects the dashboard with the operational workflows that drive business impact. There’s often a hope with dashboards that “if you build it the execs/ops will come”. But they don’t (at least not without a clear trigger).

When important data signal gets missed, it’s common to blame the team (”they don’t get data”) — but the real issue is this void between “Dashboards” and the operational workflow.

You can dramatically increase the impact of your data investment & the team’s decision making by tying data work into the operational workflow. The best way to do this is to connect data with specific, triggered moments when it’s natural for the team to look at data — and to create accountability around results via reporting.

What’s better

We propose replacing “Dashboards” with 4 categories of Data Documents — anchored on how they fit into your company’s day-to-day. Any time you introduce a new Data Document, you should bucket it into one of these 4 categories. This simple exercise will help you get more from your data investment because it forces the upfront work to figure out how data work ties into your team’s workflows and drives business impact.

Basically:

  • “Scheduled” = your company’s heartbeat. You should automatically review “scheduled” data docs at a regular cadence (e.g. daily/weekly/monthly/quarterly). These keep your team on track, and learning/executing quickly.

  • Ad hoc = answer targeted questions, as needed. Scheduled reviews often lead to questions that require ad hoc analysis to answer (”why is this number down?”). Or questions may otherwise arise as part of day-to-day prioritization and execution (”is this a big enough opportunity?”).

Here’s a more detailed view of the same thing:

* “Control Panel” isn’t an industry standard term. But we like it as a way of orienting the data views you look at regularly around the action you want to take off of the data.

** For sake of completeness, teams also consume data via “alerting” — which is is when data is proactively pushed out. Alerting can similarly be either scheduled or in response to a specific trigger. We’ll go deeper into alerting in a future article. )


How to get to a post-Dashboard (more impact) world

There’s no time like the present to better integrate data into your operational workflow. Whether you’re starting for scratch or have a ton of legacy work, you can start small and build up. We can help. And in the end it’ll be worth the effort. Here’s what you’ll get:

  • Better leadership at every level. Owners are looking at the right numbers at the right cadence, and have what they need to act on those numbers readily available.

  • Better company-wide execution. Teams execute better since they’re more accountable and better at information sharing.

  • Better decisions. The team is more informed and it’s easy to self-serve answers when questions arise.

  • More efficient data work. Data work focused on outputs that are actually used, with lower maintenance cost.

Daydream is the best place to connect data with operations & business impact. Most BI tools really only support single player use cases, are designed around data visualization vs. business impact & operational workflows, have terrible organization, feel technical, and don’t support context or collaboration. Daydream (in contrast):

  • Brings data into your team’s operational workflows — and makes it easy to collaborate

  • Feels lightweight, user friendly, and easy to use — while being packed with power

  • Can work as a standalone BI tool - or co-exist with your existing tool, as you bring in the “living” data that powers your operational day-to-day

  • Comes with expert support that’ll make it easy for you to get more from your data

We at Daydream can help you along your journey — or to design your data workspace intelligently from the start. Want to have a quick chat or to see an example of how this works in practice? We’re always happy to help. Just book some time here.

Today’s a pretty good day to run things (even) better.

⚡️ Start Free Trial

Today’s a pretty good day to run things (even) better.

⚡️ Start Free Trial

Today’s a pretty good day to run things (even) better.

⚡️ Start Free Trial