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.

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Sources of Carbon Emissions

Exchange of carbon dioxide among the atmosphere, land surface and oceans is performed by humans, animals, plants and even microorganisms. With this, they are the ones responsible for both producing and absorbing carbon in the environment. Nature?s cycle of CO2 emission and removal was once balanced, however, the Industrial Revolution began and the carbon cycle started to go wrong. The fact is that human activities substantially contributed to the addition of CO2 in the atmosphere.

According to statistics gathered by the Department of Energy and Climate Change, carbon dioxide comprises 82% of UK?s greenhouse gas emissions in 2012. This makes carbon dioxide the main greenhouse gas contributing to the pollution and subsequent climate change in UK.

Types of Carbon Emissions

There are two types of carbon emissions ? direct and indirect. It is easier to measure the direct emissions of carbon dioxide, which includes the electricity and gas people use in their homes, the petrol burned in cars, distance of flights taken and other carbon emissions people are personally responsible for. Various tools are already available to measure direct emissions each day.

Indirect emissions, on the other hand, include the processes involved in manufacturing food and products and transporting them to users? doors. It is a bit difficult to accurately measure the amount of indirect emission.

Sources of Carbon Emissions

The sources of carbon emissions refer to the sectors of end-users that directly emit them. They include the energy, transport, business, residential, agriculture, waste management, industrial processes and public sectors. Let’s learn how these sources contribute carbon emissions to the environment.

Energy Supply

The power stations that burn coal, oil or gas to generate electricity hold the largest portion of the total carbon emissions. The carbon dioxide is emitted from boilers at the bottom of the chimney. The electricity, produced from the fossil fuel combustion, emits carbon as it is supplied to homes, commercial establishments and other energy users.

Transport

The second largest carbon-emitting source is the transport sector. This results from the fuels burned in diesel and petrol to propel cars, railways, shipping vehicles, aircraft support vehicles and aviation, transporting people and products from one place to another. The longer the distance travelled, the more fuel is used and the more carbon is emitted.

Business

This comprises carbon emissions from combustion in the industrial and commercial sectors, off-road machinery, air conditioning and refrigeration.

Residential

Heating houses and using electricity in the house, produce carbon dioxide. The same holds true to cooking and using garden machinery at home.

Agriculture

The agricultural sector also produces carbon dioxide from soils, livestock, immovable combustion sources and other machinery associated with agricultural activities.

Waste Management

Disposing of wastes to landfill sites, burning them and treating waste water also emit carbon dioxide and contributes to global warming.

Industrial Processes

The factories that manufacture and process products and food also release CO2 , especially those factories that manufacture steel and iron.

Public

Public sector buildings that generate power from fuel combustion also add to the list of carbon emission sources, from heating to other public energy needs.

Everybody needs energy and people burn fossil fuels to create it. Knowing how our energy use affects the environment, as a whole, enables us to take a step ahead towards achieving better climate.

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What Kanban can do for Call Centre Response Times

When a Toyota industrial engineer named Taiichi Ohno was investigating ways to optimise production material stocks in 1953, it struck him that supermarkets already had the key. Their customers purchased food and groceries on a just-in-time basis, because they trusted continuity of supply. This enabled stores to predict demand, and ensure their suppliers kept the shelves full.

The Kanban system that Taiichi Ohno implemented included a labelling system. His Kanban tickets recorded details of the factory order, the delivery destination, and the process intended for the materials. Since then, Ohno?s system has helped in many other applications, especially where customer demand may be unpredictable.

Optimising Workflow in Call Centres
Optimising workflow in call centres involves aiming to have an agent pick up an incoming call within a few rings and deal with it effectively. Were this to be the case we would truly have a just-in-time business, in which operators arrived and left their stations according to customer demand. For this to be possible, we would need to standardise performance across the call centre team. Moving optimistically in that direction we would should do these three things:

  • Make our call centre operation nimble
  • Reduce the average time to handle calls
  • Decide an average time to answer callers

When we have done that, we are in a position to apply these norms to fluctuating call frequencies, and introduce ?kanbanned? call centre operators.

Making Call Centre Operations Nimble
The best place to start is to ask the operators and support staff what they think. Back in the 1960?s Robert Townsend of Avis Cars famously said, ?ask the people ? they know where the wheels are squeaking? and that is as true as ever.

  1. Begin by asking technical support about downtime frequencies, duration, and causes. Given the cost of labour and frustrated callers, we should have the fastest and most reliable telecoms and computer equipment we can find.
  1. Then invest in training and retraining operators, and making sure the pop-up screens are valuable, valid, and useful. They cannot do their job without this information, and it must be at least as tech-savvy as their average callers are.
  1. Finally, spruce up the call centre with more than a lick of paint to awaken a sense of enthusiasm and pride. Find time for occasional team builds and fun during breaks. Tele-operators have a difficult job. Make theirs fun!

Reducing Average Time to Handle Calls
Average length of contact is probably our most important metric. We should beware of shortening this at the cost of quality of interaction. To calculate it, use this formula:

Total Work Time + Total Hold Time + Total Post Call Time

Divided By

Total Calls Handled in that Period

Share recordings of great calls that highlight how your best operators work. Encourage role-play during training sessions so people learn by doing. Publish your average call-handling time statistics. Encourage individual operators to track how they are doing against these numbers. Make sure your customer information is up to date. While they must confirm core data, limit this so your operators can get down to their job sooner.

Decide a Target Time to Answer Calls
You should know what is possible in a matter of a few weeks. Do not attempt to go too tight on this one. It is better to build in say 10% slack that you can always trim in future. Once you have decided this, you can implement your Kanban system.

Introducing Kanban in Your Call Centre Operation
Monitor your rate of incoming calls through your contact centre, and adjust your operator-demand metric on an ongoing basis. Use this to calculate your over / under demand factor. Every operator should know the value on this Kanban ticket. It will tell them whether to speed up a little, or slow down a bit so they deliver the effort the call rate demands. It will also advise the supervisor when to call up reserves.

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EcoVaro ? ESOS Solution on a Cloud

The UK?s Energy Saving Opportunity Scheme ? and all others in the EU stable – is bound to generate huge quantities of data beyond the reach of processing on standalone computers. This leaves some companies in the mandatory sector between a rock and a hard place. They already have to divert scarce talent to draft compliance reports. Now they face purchasing equipment with big data processing power.

The more astute are turning to cloud computing solutions like EcoVaro in increasing numbers. They are also keen to benefit from remote secure backup. .

Increasing migration to public clouds has caused a growth in niche big data consultants. EcoVaro is one of these. We want to do more than simply open up a port and leave you to become familiar with our technology. We service a growing group of companies who want us to analyse their energy usage reports, and isolate the main demand drivers so they know where to start saving.

We are consumer-centric energy consultants with the emphasis on corporates and sme?s. We offer more than just big data processing facilities. We also help set up your dashboard and are full of practical ideas you can use to start trimming energy costs right away. So please treat us as your affordable energy partner who really wants to help.

Finally, contact EcoVaro for a discussion.

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