How to Create a Sustainability Dashboard in Looker

Building a sustainability dashboard helps you turn abstract goals like "going green" into concrete, measurable actions. This guide will walk you through the process of creating a powerful sustainability dashboard in Looker, from defining your key metrics to building the final interactive report.

Why a Sustainability Dashboard Matters

Monitoring sustainability isn’t just about feeling good, it’s a strategic business move. A well-built dashboard gives you a centralized view of your environmental impact, transforming complex data from utility bills, supply chain reports, and operational logs into clear insights. It helps you answer vital questions:

• Are our energy-saving initiatives actually working?

• Which of our facilities has the highest carbon footprint?

• How are we tracking against our waste reduction goals for the year?

• Can we pinpoint inefficiencies in our water usage?

More than just a reporting tool, a sustainability dashboard helps you improve operational efficiency, reduce costs, strengthen your brand's reputation, and stay ahead of evolving regulatory requirements. It moves your ESG (Environmental, Social, and Governance) efforts from a vague promise to a data-driven strategy.

Step 1: Plan Your Dashboard by Defining Key Metrics

Before you ever open Looker, you need a clear plan. The most effective dashboards are designed to answer specific questions. Start by bringing your stakeholders together - operations, finance, marketing - and deciding what a successful sustainability program looks like and what you need to measure.

Common Sustainability KPIs to Track

Your specific metrics will depend on your industry and goals, but most sustainability dashboards include a mix of the following Key Performance Indicators (KPIs):

• Energy Consumption: Total electricity (in kWh), natural gas, or other fuel consumed over time. You might segment this by location, department, or production line.

• Greenhouse Gas (GHG) Emissions: This is often the centerpiece. It’s typically broken down into scopes:

  • Scope 1: Direct emissions from sources you own or control (e.g., company vehicles, on-site fuel combustion).

  • Scope 2: Indirect emissions from purchased electricity, steam, heating, or cooling.

  • Scope 3: All other indirect emissions in your value chain (e.g., business travel, supply chain logistics, employee commutes). This is often the most complex to track but offers huge opportunities for impact.

• Water Usage: Total water consumed (in gallons or cubic meters), often trended over time and compared across different sites.

• Waste Management: The total amount of waste generated versus the amount recycled, composted, or reused. The goal is to track your diversion rate - the percentage of waste you keep out of landfills.

• Renewable Energy Use: The percentage of your energy consumption that comes from renewable sources like solar or wind.

Instead of just listing metrics, frame them as questions: "What is our month-over-month trend in energy consumption?" is more actionable than just "Energy."

Step 2: Collect and Prepare Your Sustainability Data

Sustainability data rarely lives in one convenient place. You'll need to gather it from a variety of sources and prepare it for analysis in Looker. This is often the most challenging part of the process.

Identify and Centralize Your Data Sources

Your ESG data might be scattered across sources like:

• Uploaded utility bills (electricity, gas, water)

• Spreadsheets from facility managers

• Data from IoT (Internet of Things) sensors on machinery

• Fuel expense reports from your accounting software

• Reports from logistics partners and other suppliers (for Scope 3)

• Employee surveys for commute data

Looker works by reading data from a SQL database or data warehouse (like Google BigQuery, Snowflake, or Amazon Redshift). This means you first need to consolidate your scattered data into a single, clean "source of truth". You might set up automated data pipelines using ETL tools (e.g., Fivetran, Stitch) to pull data from various sources into your warehouse. For many companies, this step involves some manual data entry into a structured format like a Google Sheet, which is then connected to the warehouse.

The goal is a clean, queryable table. For example, a table for energy usage might have columns like location_id, date, utility_type, usage_kwh, and cost_usd.

Step 3: Model Your Data with LookML

Looker's real power comes from its modeling layer, LookML. Instead of writing complex SQL queries for every chart, you use LookML to define your business logic once. This creates a reusable, reliable foundation for everyone in your company to explore data.

Think of LookML as creating a custom "dictionary" for your data. You define your metrics (the things you want to measure, called measures) and your attributes (the things you want to group by, called dimensions).

An Example LookML View

Let's say you have a database table called utility_bills. You'd create a LookML "view" file to define how Looker should interpret it. It might look something like this:

view: utility_bills { sql_table_name: public.utility_bills ,,

dimension: bill_id { primary_key: yes type: number sql: ${TABLE}.bill_id ,, }

dimension_group: bill_date { type: time timeframes: [raw, date, week, month, quarter, year] sql: ${TABLE}.bill_date ,, }

dimension: facility_name { type: string sql: ${TABLE}.facility_name ,, }

dimension: utility_type { type: string sql: ${TABLE}.utility_type ,, # e.g., 'Electricity' or 'Natural Gas' }

measure: total_energy_kwh { type: sum sql: ${TABLE}.usage_kwh ,, value_format_name: decimal_0 }

measure: total_cost_usd { type: sum sql: ${TABLE}.cost_usd ,, value_format_name: usd_0 } }

Here, we’ve defined:

• Dimensions: bill_date, facility_name, and utility_type. These are the fields you can use to filter or group your data.

• Measures: total_energy_kwh and total_cost_usd. These are the aggregations (sum, average, count) that you want to calculate.

Defining this once makes it incredibly easy for anyone - technical or not - to build accurate reports without having to know SQL.

Step 4: Build Your Dashboard Visualizations

With your data prepared and your LookML model in place, building visualizations becomes a straightforward, and even fun, process.

First, Ask Questions with Explores

In Looker, you start creating reports in the “Explore” section. This is an intuitive interface where you can mix and match dimensions and measures from your LookML model to build your first queries. On the left, you'll see a list of available fields (like 'Facility Name' and 'Total Energy kWh'). You simply click the dimensions and measures you want to see, and Looker automatically writes the SQL query and displays the data.

Create Individual Visualizations (Looks)

For each metric you want to track, create a dedicated visualization or "Look". Here are a few examples for your sustainability dashboard:

Chart 1: Total Energy Consumption Over Time

• Goal: See your energy usage trend month-over-month.

• Process: In an Explore, select the bill_date dimension (filtered to 'Month') and the total_energy_kwh measure. Change the visualization type to a line chart. This will instantly show a chart of your energy use over time. Save this chart as a new Look called "Monthly Energy Consumption."

Chart 2: GHG Emissions by Scope

• Goal: Understand the source of your emissions.

• Process: Assuming you have a table with your emissions data, select the emission_scope dimension (e.g., 'Scope 1', 'Scope 2', 'Scope 3') and the total_ghg_emissions measure. Choose a pie chart or donut chart. This provides a clear, at-a-glance view of your biggest emission sources. Save it as "GHG Emissions Breakdown."

Chart 3: Waste Diversion Rate by Location

• Goal: Compare recycling performance across different offices or facilities.

• Process: Select the facility_name dimension and a measure you’ve created in LookML for Waste Diversion Rate %. Use a bar chart to easily compare performance. To make it more insightful, you can add a reference line representing your company-wide goal.

Step 5: Assemble and Customize Your Dashboard

Once you have a collection of Looks, it's time to pull them together into a cohesive dashboard.

Create a new dashboard and simply add your saved Looks to it. You can drag and drop them to arrange the layout, resizing tiles to emphasize the most important KPIs. A good layout guides the viewer's eye from a high-level overview (total emissions) down to more granular details (performance by site).

Add Filters for Interactivity

A static report is good, but an interactive dashboard is great. Add a few key dashboard filters to make it truly useful. The most common filters for a sustainability dashboard are:

• Date Range: Allow users to view data for "Last Quarter," "Last 12 Months," or a custom timeframe.

• Facility / Location: Let a specific site manager see data just for their facility.

• Utility Type: Enable drilling down to see just electricity or just natural gas consumption.

Filters empower your team to answer their own follow-up questions without needing to create a new report for every request.

Final Thoughts

Creating a Looker sustainability dashboard follows a clear path: plan your metrics, consolidate your data, model it with LookML, and then build your visualizations. By centralizing this data, you empower every team to make smarter decisions that improve both your bottom line and your environmental impact.

While Looker is a fantastic tool for companies with data teams, the initial setup - from building data pipelines to writing LookML - can be a heavy lift. We built Graphed because we believe getting insights shouldn't require a data engineering degree. By connecting your sources with one-click integrations and then using simple, natural language to ask questions, you can create real-time operational and marketing dashboards in seconds, not weeks.