From Penalty to Profit: Why MHHS Turns Data Accuracy into a Board-Level Risk

Under the Market-Wide Half-Hourly Settlement (MHHS) programme, data accuracy is a direct financial risk. According to recent modelling reported by Utility Week, the UK’s largest energy suppliers could face a £21 million annual penalty or reward depending on their data quality performance.

MHHS has elevated data accuracy from a technical metric to a bottom-line issue, so let’s explore why finance teams should take ownership of data governance, and how proactive revenue assurance can turn regulatory risk into competitive advantage.

Data Accuracy: The New Financial Frontier

For years, poor data quality in UK energy retail has been tolerated as a cost of doing business. Manual meter reads, inconsistent agent performance, and fragmented systems meant inaccuracies were inevitable.

MHHS changes that.

Under the new programme, suppliers will be financially incentivised to improve data performance. Those who submit accurate, timely half-hourly data will share in redistribution rewards, while those relying on estimates or missing data will fund the penalties pot.

In effect, MHHS’ smart grid transforms accurate data into a measurable financial lever that can introduce a swing of up to £21 million per year for the largest suppliers, according to analysis by energy data specialist Stark.

For finance leaders, that introduces a new type of exposure: data-driven P&L volatility.

The Scale of the Challenge

The same Utility Week report found that around one-third of UK meters (approximately 11.6 million) are not sending accurate data. That’s a structural weakness baked into the system.

The energy regulator, Stark warns that while the MHHS business case projects £4.5 billion in industry-wide savings, poor data quality, weak enforcement, or tolerance of underperformance could turn that benefit into a net loss.

In short: MHHS rewards precision and punishes inefficiency. And for finance teams, that means every missing or estimated data point is a potential financial liability.

Why This Matters for Financial Controllers

Data accuracy now sits squarely within the remit of finance because it directly impacts margin, cash flow, and audit outcomes. The implications include:

• Revenue volatility: Incorrect or delayed settlement data distorts income recognition and forecasting.
• Increased penalties: Suppliers with poor data performance will pay into redistribution funds, directly reducing profit.
• Audit complexity: Unreconciled variances between operational and financial systems increase audit workloads.
• Reputational risk: Persistent underperformance against MHHS targets may invite regulatory scrutiny.

Suppliers who can quantify and mitigate these risks will play a crucial role in protecting and potentially enhancing company profitability under MHHS.

Turning Compliance Pressure into Opportunity

While many suppliers view MHHS as a compliance burden, it’s better understood as a financial opportunity.

Those who invest early in data integrity and process control stand to benefit from redistribution rewards and improved settlement accuracy. The difference between a £21 million penalty and a £21 million reward isn’t just performance, it’s preparedness.

ESG Consulting Services work with leading suppliers across the UK market to achieve exactly that. Our consultants help finance and operational teams build strong data foundations through:

• Data quality audits – assessing completeness, accuracy, and timeliness of half-hourly data.
• Revenue assurance frameworks – linking technical performance metrics to financial outcomes.
• Cross-functional collaboration – connecting settlements, billing, and finance functions for unified oversight.
• Continuous monitoring – ensuring MHHS readiness through proactive performance tracking.

ESG’s combined technical expertise, and financial insight helps clients not only achieve compliance but convert it into measurable margin improvement.

“ESG’s Consulting Team support Corona Energy with accurate views of monthly financial positions. This information is valuable in detecting and reconciling imbalances and providing a first sight of where settlements focus is required.” – Phil Morton, CFO, Corona Energy

The Real Financial Impact of Poor Data

Let’s quantify the exposure.

• A large supplier could see a £21 million swing between penalty and reward, depending on performance.
• A mid-sized supplier faces a potential difference of £5–8 million.
• Even a small supplier could lose or gain £1–2 million annually.

These figures reflect just one dimension of the impact. Add the hidden costs (manual reconciliation, audit queries, and forecasting errors) and the true financial risk is significantly higher.

Improving data quality not only protects margins but strengthens credibility with regulators, auditors, and investors.

Building Financial Confidence in a Data-Driven Market

As the industry transitions to full MHHS implementation by May 2027, finance leaders have a window to act.

Those who build strong revenue assurance frameworks today will enjoy three core advantages:

• Predictable and more profitable margins through consistent, accurate settlements.
• Audit-ready financials supported by transparent data trails.
• Board confidence grounded in reliable reporting and measurable ROI from data improvement investments.

“Over ten years, the ESG Consultants have become an extension of our internal finance team, and we have developed an extremely collaborative relationship. Year after year, the financial benefits to our business continue to far outweigh the costs of their support.” – Saul Templar, Vice President Commercial Optimisation, SEFE Energy Limited

From Risk to ROI: The Role of ESG Consulting

ESG Consulting Services specialise in helping suppliers understand, quantify, and improve their data performance ahead of regulatory milestones.

Their work with leading UK suppliers has already delivered measurable results: recovering on average 1–2% of annual energy costs, reducing settlement variance, and improving audit outcomes across finance functions.

With MHHS set to heighten the financial consequences of inaccuracy, the case for proactive intervention has never been clearer.

Find Out What’s at Stake For You

If you’re unsure what poor data could be costing your organisation, start with the numbers.

Use our ROI Calculator to estimate your potential financial exposure and discover how much your business could gain by improving data accuracy.

FAQs

How does MHHS change the financial stakes for finance teams?

Under MHHS, data accuracy becomes a direct driver of profit and loss: suppliers submitting accurate, timely half-hourly data share in redistribution rewards, while those relying on estimates or missing data fund the penalties pot. For the largest suppliers, this creates a potential swing of up to £21 million per year, introducing data-driven P&L volatility. Incorrect or delayed settlement data can distort income recognition, forecasting and cash flow.

What should finance teams do now to mitigate risk and capture upside?

Treat data accuracy as a finance-owned priority and build revenue assurance that links technical performance to financial outcomes ahead of full MHHS implementation by May 2027. Practical steps include commissioning data quality audits, establishing revenue assurance frameworks, driving cross-functional oversight across settlements, billing and finance, and implementing continuous monitoring.

Early investment turns compliance pressure into opportunity by improving settlement accuracy and positioning the business for redistribution rewards.

How big could the impact be for our business, and how can we quantify it?

A large supplier faces a £21 million penalty-to-reward swing, a mid-sized supplier £5-8 million, and a small supplier £1-2 million annually, with hidden costs from manual reconciliation, audit queries and forecasting errors amplifying the true risk. With around one-third of UK meters (c.11.6 million) not sending accurate data, exposure is systemic. To size your position, use the ROI Calculator to estimate your potential financial exposure and the gains from improving data accuracy.