UK Government Updates ESOS Guidelines

Britain?s Environment Agency has produced an update to the ESOS guidelines previously published by the Department of Energy and Climate Change. Fortunately for businesses much of it has remained the same. Hence it is only necessary to highlight the changes here.

  1. Participants in joint ventures without a clear majority must assess themselves individually against criteria for participation, and run their own ESOS programs if they comply.
  2. If a party supplying energy to assets held in trust qualifies for ESOS then these assets must be included in its program.
  3. Total energy consumption applies only to assets held on both the 31 December 2014 and 5 December 2015 peg points. This is relevant to the construction industry where sites may exchange hands between the two dates. The definition of ?held? includes borrowed, leased, rented and used.
  4. Energy consumption while travelling by plane or ship is only relevant if either (or both) start and end-points are in the UK. Foreign travel may be voluntarily included at company discretion. The guidelines are silent regarding double counting when travelling to fellow EU states.
  5. The choice of sites to sample is at the discretion of the company and lead assessor. The findings of these audits must be applied across the board, and ?robust explanations? provided in the evidence pack for selection of specific sites. This is a departure from traditional emphasis on random.

The Environment Agency has provided the following checklist of what to keep in the evidence pack

  1. Contact details of participating and responsible undertakings
  2. Details of directors or equivalents who reviewed the assessment
  3. Written confirmation of this by these persons
  4. Contact details of lead assessor and the register they appear on
  5. Written confirmation by the assessor they signed the ESOS off
  6. Calculation of total energy consumption
  7. List of identified areas of significant consumption
  8. Details of audits and methodologies used
  9. Details of energy saving opportunities identified
  10. Details of methods used to address these opportunities / certificates
  11. Contracts covering aggregation or release of group members
  12. If less than twelve months of data used why this was so
  13. Justification for using this lesser time frame
  14. Reasons for including unverifiable data in assessments
  15. Methodology used for arriving at estimates applied
  16. If applicable, why the lead assessor overlooked a consumption profile

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Uncover hidden opportunities with energy data analytics

What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

The application of Data and IT could drive significant cost savings in company-owned buildings and vehicle fleets. Virtual energy audits can be performed by combining energy meter data with other basic data about a building e.g. location, to analyse and identify potential energy savings opportunities. Investment in energy dashboards can further enable companies to have an ongoing look at where energy is being consumed in their buildings, and thus predict ways to reduce usage, not to mention that energy data analytics unlock savings opportunities and help companies to understand their everyday practices and operating requirements in a much more comprehensive manner.

Using energy data analytics can enable an organisation to: determine discrepancies between baseline and actual energy data; benchmark and compare previous performance with actual energy usage. Energy data analytics also help businesses and organisations determine whether or not their Building Management System (BMS) is operating efficiently and hitting the targeted energy usage goals. They can then use this data to investigate areas for improvement or energy efficient upgrades. When energy data analytics are closely monitored, companies tend to operate more efficiently and with better control over relevant BMS data.

The Connection between Big Data and MDM

Master Data is information that is critical to your business. This could include contracts, proprietary information, intellectual capital and a whole lot more besides. Because this often reposes in a variety of different places, you need a master data management / MDM policy to control it. That way, you can link it all together in a single, secure, backed up file.

This Sounds Like Big Data

Not necessarily: big data refers to extremely large data sets that are best stored and analysed on a cloud using big technology, in order to uncover trends, patterns and associations often relating to human behaviour. Of course, if you run a niche restaurant your critical master data might be limited to a few recipes and the books you do not care to show your accountant.

The distinction is largely a question of size: think of your master data as the subset of big data that you already have your mind around. According to John Case of IBM this is probably already in a structured format and available to share. He goes on to present a cogent case for using this as a peg point around which to systematise the rest. This is because the average organisation already has master data recording customers? and prospects? behaviour.

Do I Still Need My Master Data?

Yes you do, because real people created it with the benefit of human insight. Retain it as a separate set. Then compare it with the results of big data processing for even richer insights. Two heads are better that one and that goes for data processing too.

Trends in CRM Big Data

Adding data via location-aware devices like smartphones and tablets is adding a new dimension to customer information. We now know where they were when they made the enquiry or punched in the information. Use this geo-location data to hone the way you interact with customers and service their accounts. Do not phone a customer who makes decisions at work when they are at home.

Does My Master Data Belong on a Cloud?

There are a number of ?ifs? to consider. How comfortable are you with your service provider. What would happen if someone hacked their server? There are many advantages to cloud technology. Denizon knows of solutions you can rely on, and makes sure its clients have contingency plans to protect them at all times.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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  • (+44)(0)20-7193-9751 – UK

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