Spreadsheet Fraud

To any company executive or business owner, the mere possibility of fraud can be enough to send alarm bells ringing – for good reason. In a prolonged recession, the last thing investors would want to discover is a huge, gaping hole where supposedly a neat profit should have been. Also to find out that such loss was brought about by deliberately falsified accounting and poor spreadsheet controls only makes the situation even more regrettable.

Why?

Because these losses would not have occurred had there been a stronger risk management program in place and more stringent quality control on critical data to begin with.

But given the nature of a spreadsheet system i.e. its sheer flexibility and easy accessibility, plus the fact that they were never intended to be enterprise-level tools, there are no hard and fast rules for auditing spreadsheets. Also because of the lack of internal controls for end user computing (EUC) applications, in this case spreadsheets, you can’t expect these systems to yield consistently accurate results.

In fact, most managers assume that major spreadsheet errors should result in figures that are blatantly out of touch with how things stand in the real world, making these errors easily detectable.

Well they assumed wrong. You’ll find cases where the losses ran to millions of dollars without anyone being the wiser.

In instances of fraud, the problem becomes more complicated as these errors are deliberately hidden and cleverly disguised, perhaps one erroneous cell at a time. Even if these cover-ups started out with smaller figures that may have had negligible impact on a company?s operation, the cumulative costs of these ?insignificant? errors multiply exponentially as the spreadsheets are reused and utilised as bases for other related reports.

While there is no generally accepted definition of the term ?spreadsheet fraud?, its quite easy to identify one when a case crops up. Fraud arising from spreadsheets are typically characterised by:

Fallacious inputs – correct figures are deliberately replaced with false values.

Erroneous outputs owing to data alteration – hyperlinks are linking to the wrong spreadsheets or cells; use of macros or special lines of code which are understandable only to the person who developed the code.

Concealment of critical information – can be done with easy ?tweaks? such as hidden rows and columns, using the same colour for both the font and the background, or hard coding additional values into a cell.

There is nothing really highly-sophisticated or technical in any of these methodologies. But without internal spreadsheet controls in place, it would take a discerning eye and a thorough review to catch the inconsistencies contained in a spreadsheet fraught with errors. Also, if these errors are knowingly placed there, the chances of finding them are close to nil.

Learn more about our server application solutions and discover a better way to protect your company from spreadsheet fraud.

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Why Predictive Maintenance is More Profitable than Reactive Maintenance

Regular maintenance is needed to keep the equipment in your facility operating normally. All machinery has a design lifespan, and your goal is to extend this as long as possible, while maintaining optimal production levels. How you go about the maintenance matters, from routine checks to repairing the damaged component parts?all before the whole unit needs to be tossed away and a new one purchased and installed. Here, we will break down the different approaches used, and show you why more industries and businesses are turning to proactive maintenance modes as opposed to the traditional reactive approaches for their?field service operations.?

Reactive Maintenance: A wait and see game

Here, you basically wait for a problem to occur, then fix it. It’s also commonly referred to as a “Run-to-Failure” approach, where you operate the machines and systems until they break. Repairs are then carried out, restoring it to operational condition.?

At face value, it appears cost-effective, but the reality on the ground is far much different. Sure, when the equipment is new, you can expect minimal cases of maintenance. During this time, there?ll be money saved. However, as time progresses there?ll be increased wear, making reliance on a reactive maintenance approach a costly endeavour. The breakdowns are more frequent, and inconsistent as well. Unplanned expenses increase operational costs, and there will be lost productivity during the periods in which the affected machinery won’t be in operation.?

While reactive maintenance makes sense when you’re changing a faulty light bulb at home, things are more complicated when it comes to dealing with machinery in industries, or for those managing multiple residential and commercial properties. For the light bulb, it’s easier to replace it, and failure doesn’t have a ripple effect on the rest of the structures in the household. For industries, each time there is equipment failure, you end up with downtime, production can grind to a halt, and there will be increased environmental risks during equipment start-up and shutdown. If spare parts are not readily available, there will be logistical hurdles as you rush the shipping to get the component parts to the facility. Add this to overworked clients in a bit to complete the repair and to make up for lost hours and delayed customer orders.

For field service companies, more time ends up being spent. After all, there?s the need of knowing which parts needed to be attended to, where they are, and when the servicing is required. Even when you have a planned-out schedule, emergency repairs that are required will force you to immediately make changes. These ramps up the cots, affecting your operations and leading to higher bills for your client. These inconveniences have contributed to the increased reliance on?field service management platforms that leverage on data analytics and IoT to reduce the repair costs, optimise maintenance schedules, and?reduce unnecessary downtimes?for the clients.

Waiting for the machinery to break down actually shortens the lifespan of the unit, leading to more replacements being required. Since the machinery is expected to get damaged much sooner, you also need to have a large inventory of spare parts. What’s more, the damages that result will be likely to necessitate more extensive repairs that would have been needed if the machinery had not been run to failure.?

Pros of reactive maintenance

  1. Less staff required.
  2. Less time is spent on preparation.

Cons of reactive maintenance

  1. Increased downtime during machine failure.
  2. More overtime is taken up when conducting repairs.
  3. Increased expenses for purchasing and storing spare parts.?
  4. Frequent equipment replacement, driving up costs.?

This ?If it ain’t broke, don’t fix it? approach leads to hefty repair and replacement bills. A different maintenance strategy is required to minimise costs. Proactive models come into focus. Before we delve into predictive maintenance, let’s look at the preventive approach.?

Preventive Maintenance: Sticking to a timetable

Here, maintenance tasks are carried out on a planned routine?like how you change your vehicle?s engine oil after hitting a specific number of kilometres. These tasks are planned in intervals, based on specific triggers?like a period of time, or when certain thresholds are recorded by the meters. Lubrication, carrying out filter changes, and the like will result in the equipment operating more efficiently for a longer duration of time. While it doesn’t completely stop catastrophic failures from occurring, it does reduce the number of failures that occur. This translates to capital savings.??

The Middle Ground? Merits And Demerits Of Preventive Maintenance

This periodic checking is a step above the reactive maintenance, given that it increases the lifespan of the asset, and makes it more reliable. It also leads to a reduced downtime, thus positively affecting your company?s productivity. Usually, an 80/20 approach is adopted,?drawing from Pareto’s Principle. This means that by spending 80% of time and effort on planned and preventive maintenance, then reactive maintenance for those unexpected failures that pop up will only occur 20% of the time. Sure, it doesn’t always come to an exact 80/20 ratio, but it does help in directing the maintenance efforts of a company, and reducing the expenses that go into it.?

Note that there will need to be a significant investment?especially of time, in order to plan a preventive maintenance strategy, plus the preparation and delegation of tasks. However, the efforts are more cost effective than waiting for your systems and machinery to fail in order to conduct repairs. In fact, according to the US Dept. of Energy, a company can save between 12-18 % when using a preventive maintenance approach compared to reactive maintenance.

While it is better than the purely reactive approach, there are still drawbacks to this process. For instance, asset failure will still be likely to occur, and there will be the aspect of time and resource wastage when performing unneeded maintenance, especially when technicians have to travel to different sites out in the field. There is also the risk of incidental damage to machine components when the unneeded checks and repairs are being carried out, leading to extra costs being incurred.

We can now up the ante with predictive maintenance. Let’s look at what it has to offer:

Predictive Maintenance: See it before it happens

This builds on preventive maintenance, using data analytics to smooth the process, reduce wastage, and make it more cost effective. Here, the maintenance is conducted by relying on trends observed using data collected from the equipment in question, such as through vibration analysis, energy consumption, oil analysis and thermal imaging. This data is then taken through predictive algorithms that show trends and point out when the equipment will need maintenance. You get to see unhealthy trends like excessive vibration of the equipment, decreasing fuel efficiency, lubrication degradation, and their impact on your production capacities. Before the conditions breach the predetermined parameters of the equipment’s normal operating standards, the affected equipment is repaired or the damaged components replaced.??

Basically, maintenance is scheduled before operational or mechanical conditions demand it. Damage to equipment can be prevented by attending to the affected parts after observing a decrease in performance at the onset?instead of waiting for the damage to be extensive?which would have resulted in system failure. Using?data-driven?field service job management software will help you to automate your work and optimise schedules, informing you about possible future failures.

Sensors used record the condition of the equipment in real time. This information is then analysed, showing the current and future operational capabilities of the equipment. System degradation is detected quickly, and steps can be taken to rectify it before further deterioration occurs. This approach optimises operational efficiency. Firstly, it drastically reduces total equipment failure?coming close to eliminating it, extending the lifespan of the machinery and slashing replacement costs. You can have an orderly timetable for your maintenance sessions, and buy the equipment needed for the repairs. Speaking of which, this approach minimises inventory especially with regards to the spare parts, as you will be able to note the specific units needed beforehand and plan for them, instead of casting a wide net and stockpiling spare parts for repairs that may or may not be required. Repair tasks can be more accurately scheduled, minimising time wasted on unneeded maintenance.??

Preventive vs Predictive Maintenance?

How is predictive different from preventive maintenance? For starters, it bases the need for maintenance on the actual condition of the equipment, instead of a predetermined schedule. Take the oil-change on cars for instance. With the preventive model, the oil may be changed after every 5000?7500 km. Here, this change is necessitated because of the runtime. One doesn’t look at the performance capability and actual condition of the oil. It is simply changed because “it is now time to change it“. However, with the predictive maintenance approach, the car owner would ideally analyse the condition of the oil at regular intervals- looking at aspects like its lubrication properties. They would then determine if they can continue using the same oil, and extend the duration required before the next oil change, like by another 3000 kilometres. Perhaps due to the conditions in which the car had been driven, or environmental concerns, the oil may be required to be changed much sooner in order to protect the component parts with fresh new lubricant. In the long run, the car owner will make savings. The US Dept. of Energy report also shows that you get 8-12% more cost savings with the predictive approach compared to relying on preventive maintenance programs. Certainly, it is already far much more effective compared to the reactive model.?

Pros of Predictive Maintenance

  1. Increases the asset lifespan.
  2. Decreases equipment downtime.
  3. Decreases costs on spare parts and labour.
  4. Improves worker safety, which has the welcome benefit of increasing employee morale.
  5. Optimising the operation of the equipment used leads to energy savings.
  6. Increased plant reliability.

Cons of Predictive Maintenance

  1. Initial capital costs included in acquiring and setting up diagnostic equipment.
  2. Investment required in training the employees to effectively use the predictive maintenance technology adopted by the company.

The pros of this approach outweigh the cons.?Independent surveys on industrial average savings?after implementing a predictive maintenance program showed that firms eliminated asset breakdown by 70-75%, boosted production by 20-25%, and reduced maintenance costs by 25-30%. Its ROI was an average of 10 times, making it a worthy investment.

Is the GDPR Good or Bad News for Business

The European Union?s General Data Protection Act (GDPR) is a new data authority coming into force on 25 May 2018. It replaces the current Data Protection Directive 95/46/EC, while extending the remit to include the export of personal data outside the EU. It aims to give EU citizens and residents living there more control over their personal information. It also hopes to make regulatory compliance simpler for participating businesses.

The Broad Implications for Business
The GDPR puts another layer of accountability on businesses falling within its remit. It requires them to implement ?comprehensive but proportionate governance measures? including recording how they make decisions. The long-term goal is to reduce privacy infringements. In the short run, businesses without good governance may find themselves writing new policies and procedures.

Article 5 of the European Union?s General Data Protection Act lays down the following guidelines for managing personal data. This shall be ?
? Processed transparently, fairly, and lawfully
? Acquired for specific, legitimate purposes only
? Adequate, relevant and limited to essentials
? Not used for any other, incompatible purpose
? However it may be archived in the public interest
? Kept up to date with all inaccuracies corrected
? Ring-fenced when the information becomes irrelevant
? Adequately protected against unauthorised access
? Stored in a way that prevents accidental loss
Furthermore, affected businesses shall appoint a ?controller responsible for, and able to demonstrate, compliance with the principles.?

Implementing Accountability and Governance
The UK Information Commissioner?s Office has issued guidelines regarding provisions to assure governance and accountability. These are along the lines of the ?don’t tell me, show me? management approach the office has generally been following. In summary form, a business, and its controller must:
? Implement measures that assist it to ensure demonstrated compliance
? Maintain suitable, relevant records of personal data processing activities
? Appoint a dedicated data protection officer if scale makes this appropriate
? Implement technologies that ensure data protection by design
? Conduct data protection assessments and respond to results timeously

Implementing the General Data Protection Act in Ireland
The Irish Data Protection Commissioner has decided it is unnecessary to incorporate the GDPR into Irish law, since EU regulations have direct effect. The office of the Commissioner is working in tandem with data practitioners, and industry and professional bodies to raise awareness in business through 2017. It has produced a document detailing what it considers the essentials for business compliance. Briefly, these pre-requisites are:
? Ensure awareness among key personnel, and make sure they incorporate the GDPR into their planning
? Conduct an early assessment of quality management gaps, and budget for additional resources needed
? Do an audit of personal data held, to determine the origin, the necessity to hold it, and with whom shared
? Inform internal and external stakeholders of the current status, and your future plans to implement the GDPR
? Examine current procedures in the light of the new directive. Could you ?survive? a challenge from a data subject?
? Determine how you will process requests for access to the data in the future from within and outside your organization
? Assess how you currently obtain customer consent to store their data. Is this “freely given, specific, informed and unambiguous”?
? Find how you handle information from underage people. Do you have systems to verify ages and obtain guardian consent?
? Implement procedures to detect, investigate, and report data breaches to the Data Protection Commissioner within 72 hours
? Implement a culture of always assessing the effect on individual privacy before starting new initiatives

So Is the GDPR Good or Bad for Business
The GDPR should be good news for business customers. Their personal data will be more secure, and they should see their rate of spam marketing come down. The GDPR is also good news for businesses currently investing resources to protect their clients? interests. It could however, be bad news for businesses that have not been focussing on these matters. They may have a high mountain to climb to come in line with the GDPR.
Disclaimer: This article is for information only and not intended as a comprehensive guide.

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Computer Forensics

So you had a customer data security breach last weekend? Do you know you could be held liable in court for failing to implement required security procedures? That’s right. Due to the overwhelming surge in identity theft wherein nearly 20 million Americans have already been affected, most states have enacted laws to curtail this fast rising crime. Therefore, it is important to redefine how your company deals with customer data security.

  • First, you’ll want to know what your obligations are as dictated by law. Some places, for example, require the destruction or deletion of personal data through shredding, erasing, or by rendering them undecipherable.
  • Second, not only do you need to comply with the said requirements, you’ll also have to prove in court that you actually complied if ever a security breach does happen.
  • Third, you need to be aware of your post-breach duties to avoid being dealt additional penalties.

Obviously, such situations now call for individuals who are experts in both the legal and technical aspects regarding data security. Such individuals are practitioners of a relatively new discipline known as computer forensics.

Armed with our computer forensics specialists, we’ll be able to help you deal with the above concerns. As a result, you can be prevented from having to pay fines that can go up to hundreds of thousands of euros.

There are other equally important reasons why you would want to avail of computer forensics services. For example, you’ll need computer forensics specialists because you want to:

  • Catch a person involved in criminal activities such as child porn, stealing of personal data, and destroying intellectual property.
  • Investigate a computer, network, or even a mobile device for clues that may lead to the culprit.
  • Determine the extent and possible causes when you discover your digital data has been damaged.
  • Find and recover damaged, deleted or encrypted data regardless of whether the cause was intentional or not. If the data in question will be used as evidence in a legal action, there are certain procedures that need to be followed during recovery operations to retain the integrity of the data. Computer forensic specialists are highly qualified for such operations.
  • Implement security policies in your organisation. Such policies have to operate within legal bounds if you want to avoid possible sanctions in the future. These policies should also be designed such that future forensic operations can be conducted with a high likelihood of success.

That said, a company that integrates computer forensics into its IT security policies and practices will be better equipped to remedy the situation once data security has already been compromised than a company that doesn’t.

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