Why data quality will define your MHHS settlement success

The UK energy market is undergoing a once-in-a-generation transformation with Market-wide Half-Hourly Settlement (MHHS).

For energy suppliers, MHHS promises a more flexible, efficient, and customer-centric system but it also brings immediate operational challenges that must be tackled head-on.

One of the big questions on everyone’s mind is: can 100% settlement at four months really be achieved? The short answer is it depends on how prepared your organisation is, particularly around data quality and settlement processes.

Data Quality- The key to settlement success

When it comes to MHHS, good data quality is non-negotiable. But what does this actually mean in practice?

Good data quality:

• Effective meter reading strategies that minimise the need for estimated consumption
• Proactive resolution of read and settlement-related exceptions
• Strong, up-to-date customer data to maximise contact success for reads and smart meter installs
• High smart meter penetration with fast resolution of non comms issues
• Strong read and settlement performance, with current R2 performance approaching 100%

Poor data quality:

• Ineffective meter reading strategies, weak exception management, and closed loop control frameworks that don’t escalate to achieve the required outcome
• Missing customer information preventing contact for meter reads or smart installs
• Low smart meter penetration and/or high proportion of non-communicating meters
• Sub-90% R2 settlement performance that indicates an over reliance on backstop controls to achieve target

The benefits of good data quality in MHHS

Having robust data quality is more than a compliance tick-box, it directly impacts your ability to achieve timely settlement:

• Smoother migration: Reduces friction and exceptions when transitioning to MHHS
• Mitigation of settlement risk at go-live: Limits errors that could delay settlement and negatively impact performance
• Smarter forecasting and trading: Reliable read data underpins accurate demand forecasts, reducing imbalance charges and enabling more efficient hedging strategies - directly lowering wholesale cost-to-serve
• Supplier–DSO collaboration: Richer data flows mean suppliers can better align with DSO flexibility markets, opening up new revenue streams and creating synergies between operational efficiency and market innovation
• Customer segmentation and targeted support: Enables precise interventions for customers who need assistance

Practical steps to improve data quality 

• Clear reads and settlement backlogs: Ensure all outstanding meter reads and settlement items are resolved to provide a clean starting point for MHHS
• Data cleansing: Identify critical data items and proactively cleanse them ahead of migration to avoid errors downstream
• Implement proactive controls and monitoring: Introduce early warning systems to detect exceptions or issues before they impact settlement
• Enhance exception management: Address data exceptions promptly to prevent them from escalating and causing wider settlement issues
• Prioritise automation early: With initial spikes in exception handling, automated workflows and intelligent triage systems can help control costs and improve efficiency
• Strengthen third-party management: Ensure suppliers and partners adhere to agreed service levels and maintain high-quality data provision
• Invest in staff training and upskilling: Equip teams with the knowledge and skills required to handle MHHS processes and data effectively
• Invest in analytics capabilities: MHHS data only delivers value if the organisation can interpret it effectively - build teams capable of transforming data into actionable insights

How to assess where you stand

If you want to know which bucket your organisation falls into, start by comparing your R2 and RF settlement performance - it’s one of the clearest indicators of how prepared you are for 100% settlement at four months.

Under MHHS, the settlement timeline is being shortened from 14 months to just 4. This means there will be no additional settlement runs after the new four-month RF point, so any inaccuracies in your settled volumes won’t be corrected later.

In other words, if your R2 and RF figures don’t align closely now, you could end up overpaying for energy that you’d normally recover between R2 and RF. Read more about this risk in our previous article.

If you’re looking for support with interpreting performance or improving data quality processes, our MHHS Readiness Assessment can help. Recently, we helped a supplier to identify ~£75m in potential annual settlement risk, leading to practical recommendations for improved settlement performance. 

Contact Kevin Scott or Jon Vincent if you’d like to know more.