UK

United Kingdom · Sustainability · Lead (8-12 years)

Lead ESG Data Analyst / ESG Reporting Specialist

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

See how AI is changing this job, and get the full read by email.

Start my free Automation Fluency module

As a Lead ESG Data Analyst / ESG Reporting Specialist, a good place to start on Prompt Engineering & LLM Integration is Planning Automation Across a Department, a free Future Fluency module at Level 5. You'd practise working out what in your department's work could be automated, what should not be, and what to recommend.

Free to start, no card.

Keep this job description

Where should we send it?

One email: what AI is changing in this job, the new skills it asks for, where it leads, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

Your employer, or 'self-employed'

Leading a team? Try this with up to five of them for 14 days, free.

  • Experience bandLead (8-12 years)
  • Direct reports3-8 reports
  • Reports toESG Data & Reporting Manager
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as ESG Reporting Lead · Senior ESG Data Lead · Sustainability Data Programme Manager

Built on 43,079 real UK job descriptions we analysed · grounded in what real qualifications cover

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 2 of 5 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 2 of 5 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 5 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 1 of 5 standards
Level 6 Certificate in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 5 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Data-led Decision Making Level 6 Award in Data-led Decision Making
Apply the Concepts of Data Science to Computer Engineering NOCN Level 5 Diploma in Computer Engineering (Information Technology and Data Science)

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Automation Fluency building AI into how work runs
Frontier Fluency the next wave, beyond mainstream AI
Your Plan Illustration

Built for Lead ESG Data Analyst / ESG Reporting Specialist

4 units that map to this job, from the qualifications that cover it.

  1. Introduction to Data Science and Big Data NCC Education Limited · covers 2 of 5 standards Level 5
  2. Data Analytics Pearson Education Ltd · covers 2 of 5 standards Level 5
  3. Data-led Decision Making Institute of Sales Professionals · covers 1 of 5 standards Level 6
  4. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 5 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Lead ESG Data Analyst / ESG Reporting Specialist?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Prompt Engineering & LLM Integration
  • Advanced Data Governance & Lineage Automation
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Lead ESG Data Analyst / ESG Reporting Specialist plan as you set up, starting with the free Automation Fluency module. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

Ready to pay? Subscribe for £70 a month

Keep this read. One email with what AI is changing in this job, the new skills it asks for and where to start free. Nothing else follows unless you confirm your address.

3What this role really is

A Lead ESG Data Analyst manages the ESG reporting process for a major framework, from data collection to final presentation.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

ESG Data Platforms (e.g., MSCI ESG Research, Sustainalytics, EcoVadis) Expert

Configuring data collection campaigns, analysing rating agency methodologies, managing supplier portals, and extracting detailed benchmarks.

Reporting & GRC Platforms (e.g., Workiva Wdesk, OneTrust ESG) Advanced

Designing and building new data models and reporting templates, configuring assurance workflows, and managing audit trails within these platforms.

Python (pandas, NumPy) Expert

Automating the cleansing and transformation of large, unstructured ESG datasets, building custom calculation engines, and creating data pipelines.

SQL Expert

Writing complex queries to pull and join data from various enterprise systems (ERPs, HRIS) for ESG reporting, optimising data extraction processes.

Power BI / Tableau Expert

Designing and building complex, interactive dashboards for business unit leaders and senior management to track ESG KPIs, ensuring data storytelling is clear and impactful.

Confluence / Notion Advanced

Developing and maintaining comprehensive data methodologies, data dictionaries, process documentation, and project knowledge bases for the team.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Data Collection Methodology Follows established procedures; escalates any deviation to supervisor. Proposes improvements to existing methodologies for routine data sets; seeks manager approval for significant changes. Designs and implements new data collection methodologies for complex or novel data requirements; consults manager on strategic impact.
Data Validation & Quality Rules Applies predefined validation rules; flags anomalies to supervisor. Identifies gaps in existing validation rules and proposes enhancements; implements approved changes. Develops and implements comprehensive data validation frameworks for specific workstreams; makes recommendations on critical data quality thresholds.
Team Work Allocation & Prioritisation Receives assigned tasks and prioritises based on supervisor's guidance. Manages own task prioritisation within project scope; flags conflicts to manager. Prioritises workstreams and allocates tasks to mentees; consults manager on resource conflicts across projects.
Budget Approval (Project Specific) No independent budget authority; all expenses must be approved by supervisor. Can approve minor expenses (e.g., software licences up to £500) within project budget, with manager oversight. Can approve project-related expenses up to £5K; consults Director for anything higher.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Audit Readiness Score
The percentage of ESG data points that are fully documented, traceable, and verifiable to external audit standards.
Target · Achieve 95%+ 'audit-ready' data points for all material disclosures.

For our Scope 1 emissions, every kWh of electricity or litre of fuel can be traced back to an invoice or meter reading with a clear calculation methodology, achieving a 98% audit-ready score for that section.

Reporting Cycle Time Reduction
The number of days taken from the close of the reporting period to the final sign-off of the annual sustainability report.
Target · Reduce the reporting cycle time by 20% compared to the previous year, targeting a 6-week turnaround.

Last year, it took 10 weeks to get the report signed off. This year, by streamlining data collection and review, we aim to complete it in 8 weeks.

Data Quality Index
A composite score reflecting data completeness, consistency, and accuracy across key ESG metrics.
Target · Maintain a Data Quality Index score of 4.0 out of 5.0 or higher.

Our Q2 review showed that 90% of our supplier diversity data was complete and consistent, with only minor discrepancies, contributing to a 4.2 DQI for that quarter.

Process Automation Impact
The number of hours saved through the implementation of automated data collection, cleansing, or reporting processes.
Target · Deliver a minimum of 200 hours of manual effort savings annually across the team.

By automating the extraction of utility bill data using Python scripts, the team saved roughly 50 hours per quarter, totalling 200 hours for the year.

Stakeholder Engagement & Influence
How effectively you engage internal and external stakeholders to secure necessary data, build consensus on reporting approaches, and influence data quality improvements.
  • Regular positive feedback from Finance, IT, and operational leads on collaboration. Proactively sought out for advice on new data requirements. Successful resolution of data disputes with minimal escalation. External auditors commend the clarity of data lineage and documentation.
Team Development & Mentorship
Your ability to lead, mentor, and develop your direct reports, fostering a culture of accuracy, continuous improvement, and professional growth.
  • Direct reports meet their performance goals and show clear progression in their skills. Positive feedback in 1-to-1s and performance reviews about your guidance. Successful onboarding of new team members who quickly become productive. You're seen as a go-to person for technical and process advice.
Reporting Framework Expertise
Your depth of knowledge and ability to interpret, apply, and adapt to evolving ESG reporting frameworks (e.g., CSRD, GRI, SASB, TCFD).
  • Proactively identifying upcoming regulatory changes and their impact. Successfully guiding the organisation through new reporting requirements. Developing clear internal guidance and training for the team on framework specifics. You're the person others come to with tricky interpretation questions.
Data Governance Maturity
How well you design and implement robust data governance practices for ESG data, ensuring its integrity, security, and accessibility.
  • Clear data ownership defined for all material ESG metrics. Comprehensive data dictionaries and metadata are maintained. Regular data quality checks are scheduled and acted upon. Collaboration with IT to integrate ESG data into enterprise data governance frameworks.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Building Robust Systems

You get a real kick out of designing a new data collection template that actually works, or automating a manual process that saves your team hours. You love seeing a messy process become a slick, repeatable system.

Spending a week designing a new supplier data intake form that automatically validates entries and flags errors, then seeing your team use it effortlessly.

Solving Complex Data Puzzles

You thrive on the challenge of taking disparate, unstructured data from multiple sources and turning it into a coherent, accurate, and auditable dataset. The 'Scope 3 nightmare' is your kind of challenge.

Successfully integrating two different ERP systems' energy data into a single, consistent format for GHG reporting, despite initial data discrepancies.

Seeing Direct Impact

You're motivated by knowing your meticulous work directly contributes to the company's reputation, improves our ESG ratings, and helps secure responsible investment. You see the link between your data and the bigger picture.

Receiving positive feedback from investors or auditors on the quality of our sustainability report, knowing your team's efforts made that happen.

What frustrates people
  • Spreadsheet Archaeology: Inheriting a labyrinth of interconnected Excel files with broken links and no documentation, which holds the entire company's historical ESG data.
  • The 'Garbage In, Gospel Out' Problem: Spending 80% of your time cleaning messy, inconsistent, and incomplete data from hundreds of sources, only to have the final, heavily-caveated numbers presented as absolute fact in the annual report.
  • Data Gatekeeper Fatigue: Constantly chasing down busy operational managers and suppliers who view your data requests as a bureaucratic annoyance and a low priority.
  • Regulation Whiplash: A new reporting standard or regulation (like CSRD) is announced, rendering months of work on your old process obsolete. You have to start over.
  • The 'Make It Green' Pressure: Facing subtle (or not-so-subtle) pressure from management to interpret data in a way that tells a more favourable story, bordering on greenwashing.
  • Audit Trail Anxiety: The low-grade, persistent fear that an auditor will ask you to justify a number from 18 months ago and you won't be able to find the source email or spreadsheet.
  • Explaining Scope 3 to Executives: The pain of trying to explain the complex, estimate-heavy nature of supply chain emissions to a leadership team that just wants a single, simple, and preferably low number.
What this role does not give you
  • A static, predictable work environment – regulations and data sources are always changing.
  • Complete control over all data inputs – you'll always be reliant on others for raw data.
  • Instant gratification – building robust data systems takes time and persistence.
  • A role where you only analyse data; you'll spend a lot of time on process design and stakeholder management.

8Who you work with

This role is absolutely central to our ESG transparency and accountability. You'll directly shape our public sustainability narrative, ensuring our disclosures are accurate and robust. Your work underpins our ESG ratings, investor relations, and compliance with increasingly stringent regulations. Get it right, and we build trust and attract capital; get it wrong, and we face significant reputational and financial risks.

Inside the business
  • ESG Data & Reporting Manager
  • Head of Sustainability
  • Finance Leadership (CFO, Financial Controller)
  • IT & Data Governance Teams
  • Legal & Compliance
  • Operational Site Managers (for data collection)
Outside the business
  • External ESG Auditors (e.g., Big Four firms)
  • ESG Rating Agencies (MSCI, Sustainalytics)
  • Regulatory Bodies (e.g., FCA, EU Commission)
  • Key Suppliers and Value Chain Partners

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven experience (8-12 years) in ESG data management, sustainability reporting, or a closely related data analysis field.
  • Demonstrable experience leading projects or small teams, including mentoring junior colleagues.
  • Expert-level proficiency in at least one major ESG reporting framework (e.g., GRI, SASB, TCFD, or CSRD).
  • Advanced data manipulation skills using Python (pandas) and SQL, capable of handling large, complex datasets.
  • Experience with data visualisation tools (Power BI or Tableau) for creating executive-level dashboards.
  • A track record of successfully engaging diverse stakeholders to achieve data collection goals.
  • Strong understanding of data governance principles and their practical application.

10What to practise next

Where the job is going, and what to do about it starting this week.

Predictive ESG Analytics & Scenario Modelling

Important within 18 months – regulators and investors are increasingly asking 'what if?'. We'll need to move beyond historical reporting to forecasting future ESG risks and opportunities.

Time Series Forecasting (e.g., for emissions) · Monte Carlo Simulations (for climate risk) · Machine Learning for Anomaly Detection · Integration with Financial Modelling

  • This quarter: Take an online course on time series analysis or predictive modelling.
  • Next quarter: Identify one ESG metric (e.g., waste generation) and build a simple predictive model for it.
  • Month 6: Research tools and methodologies for climate scenario analysis (e.g., TCFD recommendations).
  • Month 9: Collaborate with the Finance team to understand how ESG predictions could be integrated into their models.

Quick win: Start by identifying key external drivers (e.g., economic growth, energy prices) that might influence our ESG performance and brainstorm how they could be incorporated into simple forecasts.

11Staying current once you are in

What people here do to keep up
  • Regularly attend webinars and conferences on ESG reporting, data governance, and emerging regulations (e.g., those hosted by GRI, SASB, IFRS, or industry bodies).
  • Participate in online courses or workshops focused on advanced Python/SQL for data manipulation, or new data visualisation techniques.
  • Actively engage with industry peer groups or professional networks to share best practices and learn from others tackling similar ESG data challenges.
  • Read academic papers and thought leadership pieces on the future of ESG data, AI in sustainability, and integrated reporting.
  • Take a course on change management or leadership skills, particularly focused on influencing without direct authority.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration

Critical within 6 months – honestly, this is already happening. Competitors are using large language models (LLMs) to draft report sections in minutes that used to take hours. Analysts who figure this out will outproduce peers significantly, and as a Lead, you'll need to guide your team.

  • Context Windows & Token Limits
  • Temperature Settings for Different Tasks
  • RAG (Retrieval-Augmented Generation) Architectures
  • Output Validation & Hallucination Detection
  • Prompt Chaining for Complex Analysis

Advanced Data Governance & Lineage Automation

Important within 12 months – with CSRD, audit requirements are getting much tougher. Manual data lineage tracking won't cut it. We need automated, verifiable trails.

  • Metadata Management Tools
  • Automated Data Quality Monitoring
  • Blockchain for Data Veracity
  • Data Stewardship Programmes

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • ESG Reporting Frameworks (GRI, SASB, TCFD, CSRD)
  • GHG Protocol & Carbon Accounting (Scopes 1, 2, 3)
  • Materiality Assessment (Financial & Double Materiality)
  • Data Validation & Assurance Readiness
  • ESG Rating Agency Analysis
  • Supply Chain Data Management

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    From Senior ESG Data Analyst

    3-5 years as a Senior Analyst

    Skills to master

    • Moving from owning specific workstreams to managing entire reporting frameworks, developing leadership skills, and gaining experience in external audit management.

    You're ready to move on when

    • Consistently delivers high-quality, audit-ready data for complex workstreams.
    • Has informally mentored junior colleagues and shown initiative in process improvement.
    • Can confidently present data insights and defend methodologies to senior internal stakeholders.
    • Has a strong grasp of multiple ESG reporting frameworks and their interdependencies.
  2. 2

    From Data Scientist / Senior Data Analyst (with ESG exposure)

    5-7 years in a data science role, plus 2-3 years with ESG focus

    Skills to master

    • Deepening knowledge of specific ESG reporting frameworks and regulations, understanding the nuances of non-financial data assurance, and developing stakeholder management skills in a sustainability context.

    You're ready to move on when

    • Demonstrates expert technical data skills (Python, SQL, visualisation).
    • Has actively sought out and delivered projects with an ESG or sustainability focus.
    • Shows a keen interest in regulatory compliance and data governance.
    • Can translate complex technical concepts into business-friendly language.
  3. 3

    From Financial Reporting Specialist (with ESG interest)

    6-8 years in financial reporting, plus 1-2 years transitioning to ESG

    Skills to master

    • Adapting financial reporting rigour to non-financial ESG data, learning specific ESG frameworks and methodologies (e.g., GHG Protocol), and understanding the unique challenges of collecting qualitative and estimated data.

    You're ready to move on when

    • Has a strong background in audit-ready reporting and data integrity.
    • Demonstrates a clear understanding of the parallels and differences between financial and non-financial reporting.
    • Is actively pursuing ESG-specific certifications or training.
    • Shows a proactive interest in the evolving regulatory landscape for sustainability.

15Where this role leads

The long view: This role can lead to work such as Director of ESG and Sustainability or Head of Data Governance, overseeing wider strategy or enterprise-wide data quality.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Lead ESG Data Analyst / ESG Reporting Specialist is actually changing.

Where it leads

Roles this leads to

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Introduction to Data Science and Big Data, worked against Lead ESG Data Analyst / ESG Reporting Specialist.

Introduction to Data Science and Big Data Level 5

Applied to your work in Lead ESG Data Analyst / ESG Reporting Specialist

The objective of this unit is to provide learners with a systematic understanding of Data Science and Big Data concepts, including their characteristics and applications. Learners will develop proficiency in data collection, design, and modelling techniques, and will be able to select appropriate tools for data pre-processing and apply analytical techniques to generate insights from data.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

See Your Progress Grow Illustration
Lead ESG Data Analyst / ESG Reporting Specialist
  • ESG Reporting Frameworks (GRI, SASB, TCFD, CSRD)
  • GHG Protocol & Carbon Accounting (Scopes 1, 2, 3)
  • Materiality Assessment (Financial & Double Materiality)
  • Data Validation & Assurance Readiness
  • ESG Rating Agency Analysis
  • Supply Chain Data Management
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Lead ESG Data Analyst / ESG Reporting Specialist is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. ESG Data & Reporting Manager (L5)

    3-5 years in the Lead role

    This is a step up to managing the entire ESG data function, not just specific frameworks. You'll own the overall reporting strategy, manage a larger team (including other Leads), and be the primary face-off with external auditors and senior executives.

    • Enterprise ESG Data Architecture Design
    • Vendor Management & Contract Negotiation (for data platforms)
    • Integrated Reporting Strategy (connecting financial and non-financial data)
    • Advanced Risk Management (ESG data security, regulatory non-compliance)
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, ESG data work can be incredibly manual and time-consuming. But what if you could cut down on the tedious bits and focus on the strategic, impactful stuff? That's where AI comes in. We're not talking about replacing you; we're talking about giving you a seriously powerful co-pilot.

For a Lead ESG Data Analyst, AI isn't just a buzzword; it's a practical tool that can transform how you manage complex reporting frameworks. Imagine automating the grunt work of data extraction, getting instant summaries of dense regulations, or even drafting narrative sections for your reports. This frees you up to do what you do best: ensure data integrity, lead your team, and provide strategic insights.

Automated Data Extraction

Use AI tools (like Microsoft Syntex or custom scripts) to automatically scan and pull key data points (e.g., kWh, litres, metric tonnes) from thousands of unstructured supplier PDFs, utility bills, and invoices. No more manual copy-pasting from endless documents.

Competitor Analysis Accelerator

Feed an AI assistant the sustainability reports of 5-10 key competitors and get a concise summary of their stated goals, key initiatives, and data disclosures for a specific topic like water management or human rights. This saves you days of reading and synthesis.

Regulatory Summariser

When a new, dense regulation like the CSRD is updated, use an AI model to summarise the key changes, identify new disclosure requirements, and compare them against your current reporting. Stay ahead of the curve without drowning in legal text.

First-Draft Narrative Generator

Once your data is validated, feed key themes and last year's report into a generative AI to create a solid first draft of the narrative for a specific section of the annual sustainability report. You'll then refine it with your expert knowledge, saving hours on initial drafting.

Common questions

Common questions

How do you become a Lead ESG Data Analyst / ESG Reporting Specialist?

Common routes in include From Senior ESG Data Analyst (3-5 years as a Senior Analyst), From Data Scientist / Senior Data Analyst (with ESG exposure) (5-7 years in a data science role, plus 2-3 years with ESG focus) and From Financial Reporting Specialist (with ESG interest) (6-8 years in financial reporting, plus 1-2 years transitioning to ESG). Times vary with prior experience.

Where can a Lead ESG Data Analyst / ESG Reporting Specialist progress to?

This role can lead on to ESG Data & Reporting Manager (3-5 years in the Lead role), depending on the skills you build.

What new skills matter most for a Lead ESG Data Analyst / ESG Reporting Specialist?

Increasingly, Prompt Engineering & LLM Integration and Advanced Data Governance & Lineage Automation. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

Three free tools, no account needed. Each one ends with a role, a level and a way in.

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

Or try another one

17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in sustainability

Stay in the field you know and move sideways rather than up.
If you leave this industry

Skills in data management, regulatory compliance and stakeholder engagement apply across industries with ESG reporting requirements, such as financial services, manufacturing and energy. They also suit consulting roles focused on sustainability data.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my free Automation Fluency module What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.