Energy Audit – clearly clear?

An energy audit is an examination of an energy system to ensure that energy is being used efficiently. It is the inspection, survey and analysis of energy flows for energy conservation in a building. Energy audits can be conducted by building managers who examine the energy account of an energy system, checks the way energy is used in its various components, checks for areas of inefficiency or where less energy can be used, and identifies the means for improvement.

An energy audit is often used to identify cost effective ways to improve the comfort and efficiency of buildings. In addition, homes/ enterprises may qualify for energy efficiency grants from central government. Energy audits seek to prioritise the energy uses from the greatest to least cost effective opportunities for energy savings.

An energy audit is an effective energy management tool. By identifying and implementing improvements as identified, savings can be achieved not only on energy bills, but also equipment will be able to attain a longer life under efficient operation. All these mean actual dollar savings.

An energy audit has to be conducted by a competent person with adequate technical knowledge on building services installations, after which he/she comes up with a report recommending plans on the Energy Management Opportunities (EMO) for energy saving.

An energy audit culminates to a written report. This could show energy use for a given time period (for example a year) and the impact of any suggested improvements per year. Energy audit reports are then used to identify cost effective ways to improve the comfort and efficiency of buildings. The energy audit report therefore gives management an understanding of the energy consumption scenario and energy saving plans formulation.
Energy audit reports should always translate into action. No matter how well articulated, the energy management objectives are afterall, an energy audit (EMOs), all the effort will be futile if no action is taken. The link between the audit and action is the audit report. It is therefore important for the audit reports to be understandable for all the target audiences/ readers, all of whom may have diverse needs, hence the reason why they should be clear, concise and comprehensible.

What are the do?s and don’ts when writing energy audit reports?

Avoid technical jargon as much as possible; present information graphically; use different graphics such as pie charts, data tables. Schematics of equipment layouts and digital photos tend to make EMO reports less dry. Some of the energy audit software?s come in handy in the generation of such graphs and charts.
The climax of it all is the recommendations, which should be made very fascinating.

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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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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

Energy Cooperation Mechanisms in the EU

While the original mission of the European Union was to bring countries together to prevent future wars, this has spun out into a variety of other cooperative mechanisms its founders may never have dreamed of. Take energy for example, where the European Energy Directive puts energy cooperation mechanisms in place to help member states achieve the collective goal.

This inter-connectivity is essential because countries have different opportunities. For example, some may easily meet their renewable targets with an abundance of suitable rivers, while others may have a more regular supply of sunshine. To capitalise on these opportunities the EU created an internal energy market to make it easier for countries to work together and achieve their goals in cost-effective ways. The three major mechanisms are

  • Joint Projects
  • Statistical Transfers
  • Joint Support Schemes

Joint Projects

The simplest form is where two member states co-fund a power generation, heating or cooling scheme and share the benefits. This could be anything from a hydro project on their common border to co-developing bio-fuel technology. They do not necessarily share the benefits, but they do share the renewable energy credits that flow from it.

An EU country may also enter into a joint project with a non-EU nation, and claim a portion of the credit, provided the project generates electricity and this physically flows into the union.

Statistical Transfers

A statistical transfer occurs when one member state has an abundance of renewable energy opportunities such that it can readily meet its targets, and has surplus credits it wishes to exchange for cash. It ?sells? these through the EU accounting system to a country willing to pay for the assistance.

This aspect of the cooperative mechanism provides an incentive for member states to exceed their targets. It also controls costs, because the receiver has the opportunity to avoid more expensive capital outlays.

Joint Support Schemes

In the case of joint support schemes, two or more member countries combine efforts to encourage renewable energy / heating / cooling systems in their respective territories. This concept is not yet fully explored. It might for example include common feed-in tariffs / premiums or common certificate trading and quota systems.

Conclusion

A common thread runs through these three cooperative mechanisms and there are close interlinks. The question in ecoVaro?s mind is the extent to which the system will evolve from statistical support systems, towards full open engagement.

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