Accelerating Your Sustainability Journey with PwC’s Unified Sustainability Hub on AWS

By Kiran Kumar Ballari and Rama Lankalapalli – AWS
By Jahanzeb Azim, Ankur Goyal, and Karthikeyan Chokappa – PwC Australia

PwC

Organizations are increasingly encountering amplified demands from shareholders, investors, customers, regulators, and activists to exhibit heightened transparency and a genuine commitment to environmental, social, and governance (ESG) matters.

In a recent PwC survey, global investors viewed sustainability as a priority for companies and one that calls for financial discipline and greater transparency. The survey suggests that sustainability outcomes have become too important to investors for companies to treat them as mere add-ons, and lists reductions in greenhouse gas emissions in a company’s own operations and supply chain as one of the top five priorities f or business to deliver against.

By leveraging Amazon Web Services (AWS) cloud infrastructure and PwC’s ESG and data analytics subject matter expertise, PwC Australia (PwC) has developed the Unified Sustainability Hub, a highly customizable accelerator which can help organizations rapidly access and manage their ESG data. The tools available in this accelerator assist organizations track and report Scope 1, 2 and 3 emissions so they can properly analyze and optimize environmental impact.

The prevailing way of dealing with ESG reporting within organizations heavily relies on manual data collection and outdated technologies with siloed interfaces. PwC’s Unified Sustainability Hub takes a different approach and instead provides a balance between acceleration and scalability, by making available PwC templates which connect to dashboards that deliver key insights, simulation capabilities and traceability.

PwC’s Unified Sustainability Hub, together with PwC professional services, can be rapidly deployed to support organizations address their sustainability challenges.

In this post, we will look at PwC’s Unified Sustainability Hub, its architecture, and how it can assist an organization speed up its sustainability transition. PwC is an AWS Premier Tier Services Partner with AWS Competencies in Data and Analytics, DevOps, Security, and more key areas of cloud computing. PwC helps you drive innovation throughout IT and the business to compete in today’s service economy.

Solution Overview

PwC’s Unified Sustainability Hub integrates internal and external stakeholders (decision makers, stakeholders, consumers), processes, and standards to make sustainability a core part of the value chain.

The accelerator leverages data analytics and artificial intelligence (AI) to drive end-to-end sustainability performance tracking and planning. The various configurable components provide an end-to-end accelerator that integrates the data life cycle for an ESG platform.

Figure 1 illustrates PwC’s Unified Sustainability Hub architecture, which establishes a cohesive, governed, and traceable view of sustainability data.

Figure 1 – PwC’s Unified Sustainability Hub capabilities.

PwC’s Unified Sustainability Hub, along with AWS-native technologies, offers a comprehensive suite of capabilities designed to address existing challenges using automated and diverse data sources. Following are the key features delivered by these capabilities:

360–degree view feature: This can centralize an organization’s sustainability data, transforming, unifying, and providing predefined and extensible data models. A holistic approach offers a comprehensive view of sustainability performance across various dimensions.
Intelligent data extraction: Enables extraction from various data sources in different formats, such as PDF, CSV, and SAP. This eliminates the need for manual translation and extraction of different sets of activity data from invoice data (such as electricity bills) across various suppliers with minimal manual supervision.
Scalable carbon accounting: Provides drill-down and traceability capabilities to identify and audit emissions data, right from activity data and emission factors to final emissions outcome.
Managed edge integration: Enables granular data capture, such as your electricity usage at 5-30 mins intervals, allowing for time-series-based analysis and generation of meaningful and actionable insights to improve efficiency and decision making.
Report and analyze: Provides pre-built and self-service analytics that enables data population into reporting templates, providing insights on customers’ sustainability performance.
Generative AI assistant for ESG: This is an intelligent assistant that uses generative AI to provide real-time insights in natural language.
Forecasting and simulation: Assists in running simulation and what-if analysis by exploring various combinations of decarbonization levers, forecasting scenarios and sustainability goals to make informed decisions about organization’s sustainability journey.
Sustainability planning: Enables planning of emission reduction targets to align with organizational sustainability goals and monitor performance against the targets. Implemented by applying statistical inference and business knowledge to data.
Data exchange: Enables integration and exchange of data between various stakeholders to enrich the sustainability ecosystem, including suppliers, customers, and external data exchange platforms. Allows a supplier to share the required data with your organization under the guidance of sustainability experts.

PwC’s Unified Sustainability Hub Architecture

The following high-level architecture diagram covers AWS services provisioned for this accelerator. The architecture is composed of serverless components and AWS managed services. It’s designed with modularity in mind and enables organizations to capitalize on their existing investments while seamlessly incorporating new AWS technologies as they become available.

Figure 2 – PwC’s Unified Sustainability Hub technical architecture.

PwC’s Unified Sustainability Hub is built using AWS-native technology and uses the following key services to keep performance and scalability high and running costs low:

Data sources and ingestion layers allow existing internal data and external data such as Scope 1, 2, and 3 emissions data or supplier-specific data to go through their respective ingestion patterns. These are loaded into the data lake environment, which is built using AWS Lake Formation, Amazon Simple Storage Service (Amazon S3), and Amazon Redshift.
Source files are validated and standardized through the best-fit data consumption approach. It’s implemented using AWS Glue, Amazon Kinesis, Amazon AppFlow, and AWS Data Brew.
All the raw data ingestion into the data lake is automated using pattern-driven ingestion methods. Amazon Data Firehose, AWS Glue Streaming, and AWS IoT Core are used to stream data into the data lake.
ESG engine funnels the data into the appropriate streams based on real-time, batch-based, and PDF image processing. AWS Lambda workflows route the incoming files to their specific data pipelines. Amazon Simple Queue Service (SQS)-based processing is applied to add a layer of resiliency to the process flow. Orchestration of data pipelines will be triggered through Amazon Managed Workflows for Apache Airflow.
The semantic layer in Amazon Redshift is built using SQL/stored procedures.
Data exploration channel is used for querying and analyzing data using Amazon Athena for data in the lake. Persona-driven reports are created and consumed by building visualizations and dashboards using Amazon QuickSight.
Simulation models are built using Amazon SageMaker to train and deploy machine learning models from the ESG data sets to run what-if scenarios, advanced heuristics and ML models scenarios that guide carbon consumption decisions.
Generative AI assistant for ESG is the sustainability intelligence assistant that delivers insights in natural language and is built using Amazon SageMaker Jumpstart and Amazon Bedrock.
Common platform services involving environment monitoring, governance, authentication, and observability implemented through Amazon CloudWatch, Amazon Cognito, and AWS CloudTrail.

Key Features

Let’s delve into the standard persona-driven end user workflow and highlight key features of this accelerator:

After successfully logging in, the landing page offers a unified view and allows access to all accelerator features. The sustainability dashboards empower users to analyze sustainability insights based on carbon accounting on activity data by applying various emission factors as applicable for the organization.

Figure 3 – Landing page presenting a single unified view.

The accelerator comes with out-of-the-box pre-built dashboard templates to speed up your sustainability journey.

Figure 4 – Pre-built interactive dashboard templates.

Dashboards show sustainability datasets for Scope 1, 2, and 3, key performance indicators (KPIs), and insights through interactive charts and graphs. You can filter by time, emission factors, industry, business unit, and location, and slice and dice data for detailed analysis. It also provides the ability to run self-service analytics for power users to create their own dashboards.

Figure 5 – Sustainability self-service analytics dashboard.

Generative AI assistant for sustainability uses generative AI on AWS for democratizing sustainability insights. For example, with a simple request – “I am about to meet with our chief sustainability officer, which of my facilities is contributing the highest scope-2 emissions?” – the generative AI assistant provides an insight based on organization’s own sustainability data.
Note that the accuracy of Amazon SageMaker and Amazon Bedrock may vary based on specific use cases and customization levels.

Figure 6 – Generative AI assistant for ESG.

The forecasting and simulation module helps to create configurations of carbon levers to the forecasted emissions data and applies them to simulation modeling. It provides advanced analytics to optimize a decarbonization roadmap by simulating outcomes based on various combinations of growth forecasts, emission reduction targets, decarbonization initiatives, and budget and resource constraints.

Figure 7 – Forecasting and simulation.

This accelerator assists in ensuring carbon accounting is auditable and traceable to activity data. To monitor carbon accounting audit and data quality, select the quality and assurance dashboard from landing page to report lineage across carbon accounting.

Figure 8 – Quality and assurance.

Conclusion

In this post, we explored how PwC’s Unified Sustainability Hub is designed to handle ingestion, storage, transformation, and generation of insights from an organizations ESG data. We also delved into how this accelerator:

Efficiently ingests data from digital assets.
Configures workflows and runs metadata enrichment.
Uses pre-built dashboard templates to facilitate persona-driven outcomes and insights.
Governs access to emissions data.
Utilities automated analysis capabilities native to AWS.

Organizations can use these insights and outcomes to optimize their environmental footprint, support compliance, and assist strategic decision making. Organizations can also use the key insights to assist with meeting compliance and reporting obligations associated with Scope 1, 2, and 3 of carbon emission standards.

To learn how this accelerator can be tailored and integrated into your AWS managed environment for streamlined carbon accounting and compliance reporting, contact the PwC’s Unified Sustainability Hub team.

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