Telemetry and the Survival of the Human Species

Without moisture, plants die. Without fodder, the animal food chain collapses. This is why climate change is the greatest threat humankind faces. Crop management needs timely information regarding ambient conditions, and also in the soil itself. In dry areas, online knowledge of trends in rainfall, sunlight, wind speed, leaf moisture, air temperature, relative humidity and solar radiation are indicators of soil stress that can be deadly for plants, and everything that relies on them.

As climate change bites, the need to find solutions accelerates. Drones swoop across to monitor ambient conditions, while probes sunk into plants and the earth in which they grow transmit information to big data repositories for feedback to administrators. In Australia, a remarkable cattle farmer is applying the same approach to his herds.

Nuffield scholar Rob Cook has always been on the edgy side of things. He lost his mobility in a helicopter crash in 2008 patrolling farmland but that has not deterred him. If anything, it has freed his mind to explore the potential that telemetry offers farmers in Australia. He shared this potential with the young beef producers in Roma Australia recently, and here is a summary what he said.

Being wheelchair bound he had to shift from herding with cattle dogs to a more scientific approach. He bought a farm 230 miles / 370 kilometres inland from Brisbane in a warm, temperate climate with significant rainfall even in the driest months. He uses observant software that reports on critical issues like water levels indicating animal consumption, and supplementary water flows from a central irrigation channel.

He also monitors fodder sources for dryer months, and moisture levels in food stocks. Rob is committed to making every blade of grass count. ?We even have the ability to take a photo of the cattle when they are taking a drink of water,? he explains, and that provides valuable information regarding tick and fly infestation and overall condition.

None of this would be possible for Rob Cook without telemetry, which is the process of collecting data at remote points and transmitting it to receiving equipment for analysis. Independent farmers do not have equipment to fund these analytic resources on their own, and use big data resources in a cloud to obtain reports. ecoVaro is on top of current trends. Please speak to us when you need independent advice.

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How Armstrong World Industries is going Cradle-to-Cradle

The Cradle-to-Cradle concept holds that human effort must be biometric, in other words enrich the environment within which it functions as opposed to breaking it down. This means manufacturing must be holistic in the sense that everything is reusable and nothing is destroyed. Armstrong World Industries was the first global mineral ceiling tile manufacturer to achieve Cradle-to-Cradle certification. We decided to take a closer look at how they achieved this.

Armstrong Worldwide Industries has five plants in the UK alone. These produce an annual turnover of ?2.7 billion. They have been making ceilings for more than 150 years. Fifteen years ago and way ahead of the curve it started recycling, and has maintained a policy of not charging contractors for waste ever since. Along the way, it developed a product that can be re-used indefinitely.

The Challenge

Going green must also be commercially sustainable. In Armstrong?s case, it faced a rise in landfill tax from ?8 per tonne per year to ?80 per tonne per year. This turned the financial cost of waste from a nuisance to a threat. It calculated that recycling one tonne of ceiling materials would:

  • Eliminate 456kg of CO2 equivalents by saving 1,390 kWh of electricity
  • Preserve 11 tons of virgin material and save 1,892 gallons of potable water

They hoped to extend their own recycling project by asking demolition and strip-out contractors to join it, so they could reprocess their scrap as new batches of tiles too.

The Achievement

As things stand today, an Armstrong ceiling tile now contains an average of 82% recycled content. Indeed, if they could find more ceilings to recycle this could reach 100%. In the past two years alone, Armstrong Worldwide Industries UK has saved 130,399m? of greenfield from landfill, being the equivalent of 520 skips that would otherwise have cost contractors over ?88,000 to dispose of.

The Broader Context

Armstrong Worldwide Industries is a global leader in water management, and is bent on minimising its reliance on fossil for energy. It has implemented online measurement systems that feed data to its corporate environmental, health and safety system. This empowers it to produce reports, track corrective actions and measure progress towards its overall goal of being carbon neutral.

Next time you sit beneath an Armstrong Worldwide Industries panelled ceiling, spare a thought for how much ecoVaro consumption analytics could contribute to your bottom line (and how it would feel to be lighter on carbon too).

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The Better Way of Applying Benford’s Law for Fraud Detection

Applying Benford’s Law on large collections of data is an effective way of detecting fraud. In this article, we?ll introduce you to Benford’s Law, talk about how auditors are employing it in fraud detection, and introduce you to a more effective way of integrating it into an IT solution.

Benford’s Law in a nutshell

Benford’s Law states that certain data sets – including certain accounting numbers – exhibit a non-uniform distribution of first digits. Simply put, if you gather all the first digits (e.g. 8 is the first digit of ?814 and 1 is the first digit of ?1768) of all the numbers that make up one of these data sets, the smallest digits will appear more frequently than the larger ones.

That is, according to Benford’s Law,

1 should comprise roughly 30.1% of all first digits;
2 should be 17.6%;
3 should be 12.5%;
4 should be 9.7%, and so on.

Notice that the 1s (ones) occur far more frequently than the rest. Those who are not familiar with Benford’s Law tend to assume that all digits should be distributed uniformly. So when fraudulent individuals tinker with accounting data, they may end up putting in more 9s or 8s than there actually should be.

Once an accounting data set is found to show a large deviation from this distribution, then auditors move in to make a closer inspection.

Benford’s Law spreadsheets and templates

Because Benford’s Law has been proven to be effective in discovering unnaturally-behaving data sets (such as those manipulated by fraudsters), many auditors have created simple software solutions that apply this law. Most of these solutions, owing to the fact that a large majority of accounting departments use spreadsheets, come in the form of spreadsheet templates.

You can easily find free downloadable spreadsheet templates that apply Benford’s Law as well as simple How-To articles that can help you to implement the law on your own existing spreadsheets. Just Google “Benford’s law template” or “Benford’s law spreadsheet”.

I suggest you try out some of them yourself to get a feel on how they work.

The problem with Benford’s Law when used on spreadsheets

There’s actually another reason why I wanted you to try those spreadsheet templates and How-To’s yourself. I wanted you to see how susceptible these solutions are to trivial errors. Whenever you work on these spreadsheet templates – or your own spreadsheets for that matter – when implementing Benford’s Law, you can commit mistakes when copy-pasting values, specifying ranges, entering formulas, and so on.

Furthermore, some of the data might be located in different spreadsheets, which can likewise by found in different departments and have to be emailed for consolidation. The departments who own this data will have to extract the needed data from their own spreadsheets, transfer them to another spreadsheet, and send them to the person in-charge of consolidation.

These activities can introduce errors as well. That’s why we think that, while Benford’s Law can be an effective tool for detecting fraud, spreadsheet-based working environments can taint the entire fraud detection process.

There?s actually a better IT solution where you can use Benford’s Law.

Why a server-based solution works better

In order to apply Benford’s Law more effectively, you need to use it in an environment that implements better controls than what spreadsheets can offer. What we propose is a server-based system.

In a server-based system, your data is placed in a secure database. People who want to input data or access existing data will have to go through access controls such as login procedures. These systems also have features that log access history so that you can trace who accessed which and when.

If Benford’s Law is integrated into such a system, there would be no need for any error-prone copy-pasting activities because all the data is stored in one place. Thus, fraud detection initiatives can be much faster and more reliable.

You can get more information on this site regarding the disadvantages of spreadsheets. We can also tell you more about the advantages of server application solutions.

User-Friendly RASCI Accountability Matrices

Right now, you’re probably thinking that’s a statement of opposites. Something dreamed up by a consultant to impress, or just to fill a blog page. But wait. What if I taught you to create order in procedural chaos in five minutes flat? ?Would you be interested then?

The first step is to create a story line ?

Let’s imagine five friends decide to row a boat across a river to an island. Mary is in charge and responsible for steering in the right direction. John on the other hand is going to do the rowing, while Sue who once watched a rowing competition will be on hand to give advice. James will sit up front so he can tell Mary when they have arrived. Finally Kevin is going to have a snooze but wants James to wake him up just before they reach the island.

That’s kind of hard to follow, isn’t it ?

Let’s see if we can make some sense of it with a basic RASCI diagram ?

Responsibility Matrix: Rowing to the Island
Activity Responsible Accountable Supportive Consulted Informed
Person John Mary Sue James Kevin
Role Oarsman Captain Consultant Navigator Sleeper

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Now let’s add a simple timeline ?

Responsibility Matrix: Rowing to the Island
? Sue John Mary James Kevin
Gives Direction ? ? A ? ?
Rows the Boat ? R ? ? ?
Provides Advice S ? ? ? ?
Announces Arrival ? ? A C ?
Surfaces From Sleep ? ? ? C I
Ties Boat to Tree ? ? A ? ?

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Things are more complicated in reality ?

Quite correct. Although if I had jumped in at the detail end I might have lost you. Here?s a more serious example.

rasci

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There?s absolutely no necessity for you so examine the diagram in any detail, other to note the method is even more valuable in large, corporate environments. This one is actually a RACI diagram because there are no supportive roles (which is the way the system was originally configured).

Other varieties you may come across include PACSI (perform, accountable, control, suggest, inform), and RACI-VS that adds verifier and signatory to the original mix. There are several more you can look at Wikipedia if you like.

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