Saving Energy Step 1 ? Implementing a Management System

There has been much hype down the years regarding whether management is art or science. Thankfully, where people are concerned the pendulum has swung away from standard times in sweatshops in the west. However, when it comes to measuring physical things like harvest per square meter and the amount of energy consumed there is no substitute for scientific measurement, and this implies a system.

Managing energy cost and consumption down is like any other strategy. American engineer / statistician / management consultant W. Edwards Demming may have passed on in 1993. However he was as right as ever when he said:

  1. When people and organizations focus primarily on quality, this tends to increase and costs fall over time.
  1. However, when people and organizations focus primarily on costs, costs tend to rise and quality declines over time.

Demming believed that 90% of organizational problems arise from systems we put in place ourselves. This can be because we are so accustomed to them that we fail to notice when they are no longer relevant. The currently prevailing laissez faire towards energy is a case in point. What is managed improves and what is not, deteriorates. We know this. Let us take a look at how to apply this principle to energy management.

First, you need to get the subject out the closet and talk about it. How often do you do this is your boardroom, and how does energy rank against other priorities? Good governance is about taking up a position and following through on it. Here is a handy checklist you may like to use.

  • Do we use a consistent language when we talk about energy? Is it electricity, or carbon emitted (or are we merely fretting over cost).
  • How well engaged are we as a company? Looking up and down and across the organization are there points where responsibility stops.
  • How well have we defined accountability? Do we agree on key performance areas and how to report on them.
  • Are we measuring energy use at each point of the business? When did we last challenge the assumption that ?we’re doing okay?.
  • Have we articulated our belief that quality is endless improvement, or are we simply chasing targets because someone says we should.

A management system is a program of policies, processes and methods to ensure achievement of goals. The next blog focuses on tools and techniques that support this effort.

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New Focus on Monitoring Soil

There is nothing new about monitoring soil in arid conditions. South Africa and Israel have been doing it for decades. However climate change has increased its urgency as the world comes to terms with pressure on the food chain. Denizon decided to explore trends at the macro first world level and the micro third world one.

In America, the Coordinated National Soil Moisture Network is going ahead with plans to create a database of federal and state monitoring networks and numerical modelling techniques, with an eye on soil-moisture database integration. This is a component of the National Drought Resilience Partnership that slots into Barrack Obama?s Climate Action Plan.

This far-reaching program reaches into every corner of American life to address the twin scourges of droughts and inundation, and the agency director has called it ?probably ?… one of the most innovative inter-agency tools on the planet?. The pilot project involving remote moisture sensing and satellite observation targets Oklahoma, North Texas and surrounding areas.

Africa has similar needs but lacks America?s financial muscle. Princeton University ecohydrologist Kelly Caylor is bridging the gap in Kenya and Zambia by using cell phone technology to transmit ecodata collected by low-cost ?pulsepods?.

He deploys the pods about the size of smoke alarms to measure plants and their environment.?Aspects include soil moisture to estimate how much water they are using, and sunlight to approximate the rate of photosynthesis. Each pod holds seven to eight sensors, can operate on or above the ground, and transmits the data via sms.

While the system is working well at academic level, there is more to do before the information is useful to subsistence rural farmers living from hand to mouth. The raw data stream requires interpretation and the analysis must come through trusted channels most likely to be the government and tribal chiefs. Kelly Caylor cites the example of a sick child. The temperature reading has no use until a trusted source interprets it.

He has a vision of climate-smart agriculture where tradition gives way to global warming. He involves local farmers in his research by enrolling them when he places pods, and asking them to sms weekly weather reports to him that he correlates with the sensor data. As trust builds, he hopes to help them choose more climate-friendly crops and learn how to reallocate labour as seasons change.

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.

 

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