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The business of sustainability

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Integrating Innovation into EHS Programs:ERM’s Journey

Presented by:Denice Nelson (ERM)

Joint AWMA NYWEA SeminarFebruary 13, 2019

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Technology: 1990’s

Calculations & Data StorageDirections

Photography Laptops and PDAs News and Books

Remote Communication

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Same Technology: Present

Any sufficiently advanced technology is indistinguishable from magic.

- Arthur C. Clarke

Integrating Innovation into EHS Programs: ERM's Journey

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Current Status

Data available Data Used?Integrating Innovation into EHS Programs: ERM's Journey

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500TBFacebook

Of data per day

1 MillionWalmart

Customer transactions per hour

72 HrsYouTube

of video uploaded per minute

5 BnMobiles

People use mobile phones each day

2.5x1018

Quintillion bytes of data every day

DATA• 90% of the world’s data was

created in the last 2 years• Requirement for data storage is

expected to double every 2 years

• 80% of the world’s data are unstructured

How Much Data? BIG DataTraditional Relational Database Management Systems (RDBMS) are not able to manage the volume or type of data we generate today:


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The Future: Bigger Data

Image: http://www.texodroneservices.co.uk/service/hyperspectralIntegrating Innovation into EHS Programs: ERM's Journey

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Digital Maturity – a Corporate View

Digital Maturity Level 1Moving from Analog

L1 Characteristics Isolated Data Sets Pen & Paper Excel Bespoke Reports Reports On Hard Copies/Hard

Drives Lack Of Transparency

INCONSISTENT AND INEFFICIENT

Digital Maturity Level 2Making the Digital Leap

L2 Characteristics Digital Data Collection Single Source Of Truth Speed Up Decision Making

Process (Real Time) Consistent And Efficient

Reporting

RELIABLE AND EFFICIENT

Digital Maturity Level 3Integrating on Digital

L3 Characteristics Connecting Business Data

Sources Data Insights Leading To

Optimization Better Visualization (3D)

Stakeholders Efficient Decision Making Process

INTEGRATED AND INSIGHTFUL

Digital Maturity Level 4Into Data Mining

L4 Characteristics Predictive Analytics Machine Learning For Data

Analysis Automated Decision Making

FORWARD-LOOKING AND PROGRESSIVE

To Artificial Intelligence, Virtual Reality And Beyond


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Role of a Strong Digital Foundation


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Example Data WorkflowField

PlanningData

ReportingData

Assessment

EQuIS

Office

Field Data Collection

Soil Sampling

Indoor Air Sampling

Field

Data Management

EQuIS

Office


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NEXUS by ERM: Groundwater Monitoring

Benefits:

• Field tasks clearly defined

• Real time review of field data

• Field data immediately uploaded into EQUIS


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ArcGIS Collector: Excavation Tracking

Benefits:

• Real-time information on

• Excavation Extent

• Photos of impacted material, piping, concrete vaults, etc

• Connects project and field teams in real-time

• Allows for efficient discussions on troubleshooting, construction issues, etc.


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Leveraging data means modernizing work flows and processes

Field samples Lab

EDD / ReportExcel

Report

Reporting

Visualization ANALYSIS

Long-term DataStorage

DATABASE

Data queriesStatistical analysis

ReportsExceedances

Regulatory Comparisons

GISGraphicsModeling

Transferable databaseInformation sharing

Manual data work flows are error prone Move toward an Integrated Data Practice


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Establishing an insights road map for Power ClientsBegin with the end in mind

Client Challenge:

Establish a groundwater monitoring program for all coal ash landfills and impoundments

Recommendations Establish a compliant yet flexible decision framework and

implement these with the right digital tools

Employ data analytics at key strategic decision points

Carefully consider regulatory timeline and program phases

Program priorities

Data analytics

Data-Driven Decision making


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Controlled, Web-based Access to Database

Automated reporting / screening against UPLS

Sample tracking

Real-time data views


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Automated Analysis and Reporting for Compliance Testing

R Markdown reports executes decision framework

Auto-population of tables, figures and text

Comparisons to regulatory limits (UCLs, UTLs, and UPLs)


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Dynamic Reports

Code in R studio

Document Text

Statistical Code

Reproducible documents with

appealing figures and formatted tables

Text

Tables

Figures


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Benefits of integrated, statistically-driven processFlipping of the 80:20 Ratio

Increased value for CCR clients Compliance with CCR rule

Data-driven, objective decision making

Consistency across client sites

Shift to proactive from reactive analysis

Improved communication and access to data

Increased data security and quality

Effectively manage liabilities

Program priorities

Preliminary analyses

Data-Driven Decision making

Data prep and analysis

Interpretation and strategy

80% Effort spent 20%

20% 80%


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Takeaways

1. Individual and organizational maturity is important to make progress on digital transformation –

We should leverage new technology and software to enhance how we work.

2. Definition of problem statements/hypotheses enable us:

to build workflows and identify the data needed to produce robust solutions

3. Don’t under-estimate the value in good data management:

the reward is being able to work smarter

4. Big data ≠ Big reports –

More data and better integration should provide insight and resolution to problems.

5. Data is a journey.

Its important to start on the right foot and then enjoy the ride!


The business of sustainability

Thank you Denice NelsonPartnerNorth [email protected]+1 612 386 4618Minneapolis, MN

Simon GibbonsTechnical FellowUK & Northern [email protected]+44 7557 540 526Bristol, UK

integrating innovation into ehs programs...integrating innovation into ehs programs: erm's...

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