Spreadsheet Woes – Burden in SOX Compliance and Other Regulations

End User Computing (EUC) or end User Developed Application (UDA) systems like spreadsheets used to be ideal ad-hoc solutions for data processing and financial reporting. But those days are long gone.

Today, due to regulations like the:

  • Sarbanes-Oxley (SOX) Act,
  • Dodd-Frank Act,
  • IFRS (International Financial Reporting Standards),
  • E.U. Data Protection Directive,
  • Basel II,
  • NAIC Model Audit Rules,
  • FAS 157,
  • yes, there?s more ? and counting

a company can be bogged down when it tries to comply with such regulations while maintaining spreadsheet-reliant financial and information systems.

In an age where regulatory compliance have become part of the norm, companies need to enforce more stringent control measures like version control, access control, testing, reconciliation, and many others, in order to pass audits and to ensure that their spreadsheets are giving them only accurate and reliable information.

Now, the problem is, these control measures aren’t exactly tailor-made for a spreadsheet environment. While yes, it is possible to set up a spreadsheet and EUC control environment that utilises best practices, this is a potentially expensive, laborious, and time-consuming exercise, and even then, the system will still not be as foolproof or efficient as the regulations call for.

Testing and reconciliation alone can cost a significant amount of time and money to be effective:

  1. It requires multiple testers who need to test spreadsheets down to the cell level.
  2. Testers will have to deal with terribly disorganized and complicated spreadsheet systems that typically involve single cells being fed information by other cells in other sheets, which in turn may be found in other workbooks, or in another folder.
  3. Each month, an organisation may have new spreadsheets with new links, new macros, new formulas, new locations, and hence new objects to test.
  4. Spreadsheets rarely come with any kind of supporting documentation and version control, further hampering the verification process.
  5. Because Windows won’t allow you to open two Excel files with the same name simultaneously and because a succession of monthly-revised spreadsheets separated by mere folders but still bearing the same name is common in spreadsheet systems, it would be difficult to compare one spreadsheet with any of its older versions.

But testing and reconciliation are just two of the many activities that make regulatory compliance terribly tedious for a spreadsheet-reliant organisation. Therefore, the sheer intricacy of spreadsheet systems make examining and maintaining them next to impossible.

On the other hand, you can’t afford not to take these regulations seriously. Non-compliance with regulatory mandates can have dire consequences, not the least of which is the loss of investor confidence. And when investors start to doubt the management’s capability, customers will start to walk away too. Now that is a loss your competitors will only be too happy to gain.

Learn more about our server application solutions and discover a better way to comply with regulations.

More Spreadsheet Blogs


Spreadsheet Risks in Banks


Top 10 Disadvantages of Spreadsheets


Disadvantages of Spreadsheets – obstacles to compliance in the Healthcare Industry


How Internal Auditors can win the War against Spreadsheet Fraud


Spreadsheet Reporting – No Room in your company in an age of Business Intelligence


Still looking for a Way to Consolidate Excel Spreadsheets?


Disadvantages of Spreadsheets


Spreadsheet woes – ill equipped for an Agile Business Environment


Spreadsheet Fraud


Spreadsheet Woes – Limited features for easy adoption of a control framework


Spreadsheet woes – Burden in SOX Compliance and other Regulations


Spreadsheet Risk Issues


Server Application Solutions – Don’t let Spreadsheets hold your Business back


Why Spreadsheets can send the pillars of Solvency II crashing down

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A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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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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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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