Energy prices doubled last year (you probably noticed). Although they are flattening now – that means they are rising more slowly, not going down, they are not going back to historical levels at any time in the future foreseeable future. At the same time regulation around CO2 emissions is getting stronger not weaker, tenders are increasingly likely to require firms to disclose their ESG credentials and consumers, particularly those under 35 are already showing a tendency to select and deselect brands on their perceived environmental friendliness.
All of this means you cannot ignore the impact of rising and high energy prices and the market demand that firms act responsibly regarding their carbon emissions.
For some reason hospitality seems to be a laggard when it comes to implementing sound energy and carbon management process is compared to verticals like retail for example. Why that is we don’t know but we do have a solution and a challenge.
- We believe that our EMMA AI platform can save you tens of thousands of pounds, hundreds of thousands, depending upon your size, from Day1.
- With no capex required
- With no hardware needed
- With no incremental headcount
- With no onerous amount of additional work
- Without having anything cross your firewall, all you need is an email address and a browser.
If you accept the challenge, we’ll prove this in a pilot, across a representative number of your sites and if we can’t credibly demonstrate annual savings way more than what annual license fees would be there will be no charge. Zero, Nada, Zip.
If you always do what you always did then you’ll always get what you always got
Historically firms in hospitality have dealt with energy management by negotiating tariff and to be fair it’s been successful up until a year or so ago. But that no longer applies. You cannot negotiate your way out of rising energy prices by attacking the tariff because it’s the tariff that’s the problem. The only approach is to manage consumption. Any reduction in your energy spend goes directly to your bottom line. Think of what say, a 10 or 15% saving would require in additional sales days to achieve of the impact of a 15% hike on net profit on your P&L. It’s beyond significant and well worth the effort. But you cannot manage waste if you can’t see where it occurs, so job number 1 is to make the invisible, visible.[Sidebar: current estimates are that UK businesses collectively waste 34% of the energy they can see consume].
Energy management firms like us have for years now made managing waste the feature of their systems and we’ve all done it by producing easily understandable graphs from the meter data that every organisation has and pointing out where consumption goes outside of the expected daily curve. The shortcoming in that is addressing the problem often cost more than the problem itself because you need an army of people to look at generic data like that and figure out what and where the problem is before you can address it. Imagine a large complex hotel where the data says, ‘you have spike of energy at 5:00 in the morning’. Where is it? In the kitchen? The fitness centre? In the laundry (if you have one) Data alone is useless, it’s what you do with the data that matters and to make that analysis achievable, even in a well-staffed business, means you need technology rather than people to turn the data into information.[Sidebar: did you know that you, legally own your energy data, not the supplier. They must provide it to you on demand and in as much detail as you need, that means half hourly for businesses of your size]
AI. It’s computing Jim, but not as we know it
EMMA AI is a genuine AI Platform. It uses various machine learning techniques, advanced data pattern recognition and language parsing to read the ‘fingerprint’ of the data that goes through your incoming fiscal metre and from this can determine any anomaly or abnormality in your pattern of energy consumption – and that’s electricity, gas, water, oil, solar, anything that’s metered. EMMA doesn’t have rules. As a true AI application, it learns as it works, and it does that from users providing simple, plain text feedback. Example: if, for example, EMMA sees an anomaly in electricity consumption it will look at the data pattern to determine what it is, lighting looks different from heating which looks different from a malfunction in an AHU etc. Applying its inference engine to its knowledge bank EMMA will then issue a simple work ticket to whoever your nominated resource is; the engineering dept, a fault desk, an external plumber or electrician etc. that says, ‘I saw spike in electricity overnight. It looks to me like you left lighting on where it wasn’t needed this anomaly has cost you £23’. At the same time, it will also issue a simple feedback ticket that asks, ‘Was my suggestion right and if not, what was the cause? And ’What did you do about it’? In this example if the feedback was, ‘It was the car park lights that were left on all night and I reset the timer’ EMMA will bank that data pattern and the next time it appears the platform will not say ‘I think you left the lighting on’, it will say’ I think you left the car park lighting on’ and that’s how AI works. The net result of it is that your existing team get a small number of work tickets which they can easily and quickly action and you fix the problem at source, saving a fortune.
Whilst EMMA is issuing work tickets on a close to real time basis (day +1) it’s also collating the data behind it into whatever reports you want to fit your KPI’s. We firmly believe that the last thing that the world needs is another dashboard. EMMA’s data will go into whatever your regular reporting is however you want it via a simple API. What this does is give you two important benchmarks against which to target performance improvements:
- How much would I save if I performed every day at the best I performed in the past period?
- How much would I save if I performed at the level of the best performing unit in the estate?
Our experience is that this can create a bit of very healthy competition in the team.[Sidebar: We’re saving the BetFRED chain of 1400 betting shops £230,000 a year. It works]
The Deal. Trump would probably call it the best deal in the entire history of the entire universe. Ever.
For starters if you will give us a year’s data (we’ll start with electricity consumption) we’ll run that through the platform and give you an indicative level of savings CO2e reduction that you could make from that. If that excites you, we’ll set up and run a pilot in between 5 and 10% of your sites over a 90-day period to prove definitively the quantum of savings that can be achieved in both cash and CO2e. And if that proves the case that savings would be far more than licence fees, we’ll put you on a best terms contract going forward.
EMMA pricing depends upon the number of sites you have and/or the MWh you consume so we can’t spell out licence fee investment in abstract. It is almost always about 1% of your utility spend and, subject to minimum annual fees of £5,000, we guarantee it will not be more than 2%. Savings produced by EMMA are in the range of 10-15% of spend per utility.[Sidebar: Example: If you’re spending £500,000 on electricity the annual EMMA license fee would be £5,000. Expected savings at 10-15% would be £50k-£75k so net savings £45,000-£70,000]
What must happen now?
If you’re up for this challenge, you need three things:
- Half hourly utility consumption data. That means a smart meter.
- Somone or more who will do something with the work ticket recommendations EMMA sends out. EMMA is an information system, not a control system
- Someone, usually the same person as in #2, who will complete and return the feedback tickets. Finally, just click or call……and start saving a fortune and saving the planet at the same time.
Written by Michael Prager, Non Exec Chair of Optimal Monitoring.