Spreadsheet Woes – Limited Features For Easy Adoption of a Control Framework

Like it or not, regulations are here to stay and for a company to comply with them, its IT and financial systems will have to be equipped with a suitable control framework. One common stumbling block to such an implementation is a company?s over-reliance on spreadsheets.

Why is it so difficult to adopt controls for a system that’s reliant on spreadsheets? To understand this, let’s pinpoint some of the strongest, most powerful attributes of these User Developed Applications (UDA).

By nature, spreadsheets are the epitome of simplicity: easy to develop, easily accessible and easily altered. All computers in your workplace will most likely have them and everyone in your organization may be sharing them, making their own versions, and storing them in personal folders.

Sad to say though, these strengths are also control weaknesses and constitute the very reasons why spreadsheets require effective risk management.

Easy to develop. Being easy to develop, most spreadsheet systems are created by non-IT users who have limited knowledge on best control practices. Being constantly under time pressure, these ?developers? may also relegate documentation, security, and data verification to the back burner in favour of coming up with a timely report.

Easy to access. Information in a spreadsheet can be opened by practically anyone within the organization?s network. Who accessed what? And when? If anything goes wrong, it would be difficult to identify the culprit, and the failure to pinpoint responsibility for erroneous data could lead to bigger, more costly mistakes.

Easy to alter. Lastly, if the information is easy to access, then it can also be easily altered, consequently making reports more prone to both accidental errors and fraudulent modifications.

The rise of multimillion dollar scandals due to accidental and intentional spreadsheet errors have prompted regulatory bodies to publish guidelines for mitigating spreadsheet-associated risks. These controls include:

  • Change control
  • Version control
  • Access control
  • Input
  • Security and data integrity
  • Documentation
  • Development life cycle
  • Backup and archiving
  • Logic inspection/Testing
  • Segregation of duties/roles, and procedures
  • Analytics

In theory, these controls should be able to bring down risks considerably. However, because of the inherent nature of spreadsheets, such controls are rarely implemented effectively in the real world.

Take for example Security and Data Integrity. One of the most common causes of spreadsheet error is due to ?hardwiring?. This happens when values are inadvertently entered into a formula cell, naturally changing the logic of the spreadsheet.

As a way of control, cell locking can be applied on the formula cells to prevent users without the proper authority from making any changes. However, when reporting deadlines approach drawing spreadsheets to the forefront of data processing, more people are given access rights to the locked cells. Ironically, it is during these crunch times, when errors are most likely to happen.

Because the built-in features of a spreadsheet support none of the controls mentioned above, some companies are tempted to purchase control-enabling programs for spreadsheets just to continue using them for financial reporting. But although these programs can integrate the required controls, you?d still be interacting with the same complex and outdated interface: the spreadsheets.

Thus, these band-aid solutions may not suffice because the root cause of these problems are the spreadsheets themselves.

Learn more about our server application solutions and discover a better way to implement controls.

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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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Technology and process improvement

Tightening organisational flow to improve productivity and minimise costs is a growing concern for many businesses post the Global Financial Crisis. Businesses can no longer afford to waste time and personnel on inefficient processes. Organisations using either Six Sigma or Lean techniques better manage their existing resources to maximise product out-put. Both of these techniques involve considerable evaluation of current processes.

What is Six Sigma?

Six Sigma is an organisational management strategy that evaluates processes for variation. In the Six Sigma model, variation equates waste. Eliminating variation for customer fulfilment allows a business to better serve the end-user. In this thought model, the only way to streamline processes is to use statistical data. Each part of a process must be carefully recorded and analysed for variation and potential improvements. The heart of the strategy embodied by Six Sigma is mathematical. Every process is subject to mathematical analysis and this allows for the most effective problem solving.

What is a Lean Model?

Lean businesses do not rely on mathematical models for improvement. Instead, the focus is on reducing steps in the customer delivery cycle, which do not add value to the final deliverable. For example, maintaining excess inventory or dealing with shortages would both be examples of waste behaviour. Businesses that operate using Lean strategies have strong cash flow cycles. One of the best and most famous examples of Lean in action is the Toyota Production System (TPS). In this system, not only is inventory minimised, but physical movement for employees also remains sharply controlled. Employees are able to reach everything needed to accomplish their tasks, without leaving the immediate area. By reducing the amount of movement needed to work, companies also remove wasted employee time.

Industry Applications for Lean and Six Sigma

Lean businesses reduce the number of steps between order and delivery. The less inventory on hand, the less it costs a business to operate. In industries where it is possible to create to order, Lean thinking offers significant advantages. Lean is best utilised in mature businesses. New companies, operating on a youthful model, may not be able to identify wasteful processes. Six Sigma has shown its value across industries through several evolution’s. Its focus on quality of process makes it a good choice for even brand new businesses. The best use is the combination of the two strategies. With the Lean focus on speed and the Six Sigma focus on quality combined, the two organisational processes create synergy. By itself, Lean does not help create stable, repeating success. Six Sigma does not help increase speed and reduce non value-added behaviours. Combined, these two strategies offer incredible value to every business in cost savings.

Using Technology to Implement Lean Six Sigma

Automation processes represent an opportunity for businesses to implement a combination of both Lean and Six Sigma strategies. Any technology that replaces the need for direct human oversight reduces costs and increases productivity. A few examples of potentially cost saving IT solutions include document scanning, the Internet, and automated workflow systems.

  • Document Scanning – Reducing dependency on paper copies follows both Lean and Six Sigma strategies. It is a Lean addition in that it allows employees to access documents instantly from any physical location. It is Six Sigma compliant in that it allows a reduction on process variation, since there is no bottleneck on the flow of information.
  • The Internet – The automation potential offered by the Internet is limitless. Now, businesses can enter orders, manage logistics and perform customer service activities from anywhere, through a hosted portal. With instant access to corporate processes from anywhere, businesses can manage workflow globally, allowing them to realise cost savings from decentralisation.
  • Automated Work Systems – One of the identified areas of waste in any business is processing time. The faster orders are processed and delivered, the greater the profits for the company and the less the expense per order. When orders sit waiting for attention, they represent lost productivity and waste. Automated work systems monitor workflow and alert users when an item sits longer than normal. These systems can also reroute work to an available employee when the original worker is tied up.

Each of these IT solutions provides a method for businesses to either reduce the number of steps in a process or improve the quality of the process for improved customer service.

Identifying Areas for Lean Six Sigma Implementation

Knowing that improved processes result in improved profits, identifying areas for improvement is the next step. There are several techniques for creating tighter processes with less waste and higher quality. Value Stream Mapping helps business owners and managers identify areas of waste by providing a visual representation of the total process stream. Instead of improving single areas for minimal increases in productivity, VSM shows the entire business structure and flow, allowing management to target each area of slow down for maximum improvement in all areas.

Seeing the areas of waste helps management better determine how processes should work to best obtain the desired outcomes. Adding in automated processes helps with improved process management, when put in place with a complete understanding of current systems and their weaknesses. Start with mapping and gain a bird’s-eye view of the situation, in order to make the changes needed for improvement.

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How Alcoa Canned the Cost of Recycling

Alcoa is one of the world?s largest aluminium smelting and casting multinationals, and involves itself in everything from tin cans, to jet engines to single-forged hulls for combat vehicles. Energy costs represent 26% of the company?s total refining costs, while electricity contributes 27% of primary production outlays. Its Barberton Ohio plant shaved 30% off both energy use and energy cost, after a capital outlay of just $21 million, which for it, is a drop in the bucket.

Aluminium smelting is so expensive that some critics describe the product as ?solid electricity?. In simple terms, the method used is electrolysis whereby current passes through the raw material in order to decompose it into its component chemicals. The cryolite electrolyte heats up to 1,000 degrees C (1,832 degrees F) and converts the aluminium ions into molten metal. This sinks to the bottom of the vat and is collected through a drain. Then they cast it into crude billets plugs, which when cooled can be re-smelted and turned into useful products.

The Alcoa Barberton factory manufactures cast aluminium wheels across approximately 50,000 square feet (4,645 square meters) of plant. It had been sending its scrap to a sister company 800 miles away; who processed it into aluminium billets – before sending them back for Barberton to turn into even more wheels. By building its own recycling plant 60 miles away that was 30% more efficient, the plant halved its energy costs: 50% of this was through process engineering, while the balance came from transportation.

The transport saving followed naturally. The recycling savings came from a state-of-the-art plant that slashed energy costs and reduced greenhouse gas emissions. Interestingly enough, processing recycled aluminium uses just 5% of energy needed to process virgin bauxite ore. Finally, aluminium wheels are 45% lighter than steel, resulting in an energy saving for Alcoa Barberton?s customers too.

The changes helped raise employee awareness of the need to innovate in smaller things too, like scheduling production to increase energy efficiency and making sure to gather every ounce of scrap. The strategic change created 30 new positions and helped secure 350 existing jobs.

The direction that Barberton took in terms of scrap metal recycling was as simple as it was effective. The decision process was equally straightforward. First, measure your energy consumption at each part of the process, then define the alternatives, forecast the benefits, confirm and implement. Of course, you also need to be able to visualise what becomes possible when you break with tradition.

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