Month End Accounting the way it should Be Today

Month end accounting has always been a business critical exercise. Without the balance sheet, income statement, and other financial reports this exercise ultimately produces, management could not make informed decisions to keep the company in the right direction and at the ideal operational speed.

Now, in order to maintain optimal business velocity, month end activities have to be carried out as swiftly and as accurately as possible. Delays will only inhibit managers from reacting and effecting necessary adjustments in time. Inaccurate information, on the other hand, obviously lead to bad decisions.

But that’s not all. Never has the month end close been as demanding as it is today. Regulations like the Sarbanes-Oxley Act, Solvency II, Dodd-Frank Act, and others, which call for more stringent controls and more robust risk management practices, are now forcing companies to find better ways to face the end of the month.

Sticking to old month-end practices while striving to achieve regulation compliance can either cost a company more (if they add manpower) or simply bog it down (if they don’t). Among the worst of these practices is the use of spreadsheets.

These User Developed Applications (UDAs) are very susceptible to errors. (See spreadsheet risks)

What’s more, consolidating data from spreadsheets as well as carrying out reconciliations on them is very time consuming. These activities usually require data from outside sources – i.e. a workstation in a different department, building, or (in the case of really large corporations) geographical locations.

Furthermore, if one of these sources fail, the financial reports won’t be complete. This is not a far-fetched scenario, considering that spreadsheet storage and backup is typically carried out by the average end user. This leaves the spreadsheet data vulnerable to hard disk crashes, virus attacks, and unexpected disasters.

Thus, in order to produce accurate financial reports on time all the time, you need a financial/IT solution that offers optimal provisions for risk management, collaboration, backup, and business continuity. Learn about server-based solutions and discover a better way to carry out month end accounting.

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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.

Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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