Top 10 Disadvantages of Spreadsheets

Fraudulent manipulations in company Excel files have already resulted in Billion-Dollar losses. The main underlying reason behind this spreadsheet vulnerability is the inherent lack of controls, which makes it so easy to alter either formulas, values, or dependencies without being detected.


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Disadvantages of Spreadsheets

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1. Vulnerable to Fraud

Of all the spreadsheet disadvantages listed here, this is perhaps the most damaging. Fraudulent manipulations in company Excel files have already resulted in Billion-Dollar losses. The main underlying reason behind this spreadsheet vulnerability is the inherent lack of controls, which makes it so easy to alter either formulas, values, or dependencies without being detected.

2. Susceptible to trivial human errors

While fraud will always be a threat to spreadsheet systems, there is a more significant threat that should make you seriously consider getting rid of these outdated systems. And that is its extreme susceptibility to even trivial human errors. Missed negative signs and misaligned rows may sound harmless.

But when they damage investor confidence or cause a considerable loss of opportunity amounting to millions of dollars (Are we serious? Google up ?spreadsheet horror stories? to find out), you should understand that it?s time to move on to better alternatives.

3. Difficult to troubleshoot or test

So how about testing spreadsheets to mitigate the risks of items 1 and 2? Good luck. Spreadsheets just aren?t built for that. It?s not uncommon to have interrelated spreadsheet data scattered across different folders, workstations, offices, or even geographical locations.

Worse, even if you are able pinpoint the locations of every related file, tracing the logic of formulas from one related cell to another can take ages. It?s pretty obvious now how you?ll also encounter a similar problem when troubleshooting questionable data.

4. Obstructive to regulatory compliance

Combine items 1, 2, and 3, and what do you get? A big headache impacting regulatory compliance. There are number of regulations that have a serious impact on the use of spreadsheets.

Some of the many regulations that impact spreadsheet systems include:

And to think it looks like regulatory bodies are just getting warmed up. Over the last two decades, we’ve seen a surge in regulations that directly affect spreadsheet-based systems. Now, you tell me that you haven?t wished there was a better way to beat regulatory compliance deadlines. Well, if you?re still using spreadsheets, then there certainly is a better way.

5. Unfit for agile business practices

We’re now in an age when major changes are shaping and reshaping the business landscape. Mergers and Acquisitions, Management Buyouts, earthquakes, tsunamis, hurricanes, uprisings, climate change, new technologies, and so on. If your business is not agile enough to adapt to such changes, it could easily be left behind or even face extinction.

Spreadsheets are normally created by individuals who have not the slightest know-how regarding software documentation. In the end, spreadsheet files become highly personalised user developed applications. So when it?s time for a new person to take over as part of a large scale business change, the newcomer may have to start from scratch.

Read further about Implementing Large-Scale Business Change

 

6. Not designed for collaborative work

Planning, forecasting, budgeting, and reporting are all collaborative activities. In other words, plans, forecasts, budgets, and reports typically require information from different individuals belonging to different departments. In addition, the final documents are a result of multiple exchanges of data, ideas, and files.

Now, if your company?s offices are scattered throughout the country or if certain team members are separated by large distances, the only way to exchange data stored in spreadsheets is through email.

Experience will tell you that such a method of exchange is susceptible to duplicate and even erroneous data. Team members will tend to find it hard to keep track of similar files going back and forth, and sometimes even end up sending the wrong version.

7. Hard to consolidate

When it comes to simple data entry and quick ad hoc data analysis tasks, spreadsheets are highly favoured by end users. This has made them one of the most ubiquitous office tools on the planet. But as a consequence, data in spreadsheet-based systems are distributed throughout the organisation.

So when it’s time to generate reports, you’ll really have to go through a slow consolidation process. In most cases, end users would have to collect data from different files, summarise them, and submit the same to their department heads through emails, portable storage media (e.g. CDs or USB flash-drives), or by copying to a commonly shared network folder.

Department heads would have to undergo a similar process before submitting them to their own superiors. This has to go on until all the information reaches their organisation’s top decision makers. Throughout the entire consolidation process, data is subjected to numerous error-prone activities such as copy-pasting, cell entry, and range specification.

8. Incapable of supporting quick decision making

In a spreadsheet-based environment, extracting data from different departments, consolidating them, and summarising the information so that it could aid the company’s top brass in making sound decisions can be very time consuming.

And because we know how susceptible spreadsheets are to errors, everyone involved in the information processing has to be ultra careful to keep the integrity of the data intact. Hence it would be prudent to enforce double-checking as much as possible.

This extra but necessary exercise can further delay the process. So, when the final information arrives at the hands of the top executive, he may not have much time to work with. (Read about Business Intelligence)

9. Unsuited for business continuity

As mentioned earlier, data in spreadsheet systems are never kept in a single place. In fact, it’s the exact opposite. The worse thing about it is that they’re always in the hands of non-IT personnel, who are understandably not familiar with storage and backup best practices.

Thus, if a major disaster strikes, full data recovery can be very difficult if not impossible. As a consequence, even if the company has financial reserves, the absence of data (e.g. accounts receivable records, customer records, and inventory) to work on can prevent the company from making a quick restart.

10. Scales poorly

As an organisation grows, data in spreadsheet-based systems get more distributed; subsequently compounding the issues outlined above. It is absolutely not advisable for a large organisation to keep using spreadsheets.

 

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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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

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.

How COBIT helps you achieve SOX Compliance

First released way back in 1996, COBIT has already been around for quite a while. One reason why it never took off was because companies were never compelled to use it ? until now. Today, many CEOs and CIOs are finding it to be a vital tool for achieving SOX compliance in IT.

Thanks to SOX, COBIT (Control Objectives for Information and related Technology) is now one of the most widely accepted source of guidance among companies who have IT integrated with their accounting/financial systems. It has also gained general acceptability with third parties and regulators. But how did this happen?

Role of control frameworks in SOX compliance

You see, the Sarbanes-Oxley Act, despite having clearly manifested the urgency of establishing effective internal controls, does not provide a road map for you to follow nor does it specify a yardstick to help you determine whether an acceptable mileage in the right direction has already been achieved.

In other words, if you were a CIO and you wanted to find guidance on what steps you had to take to achieve compliance, you wouldn’t be able to find the answers in the legislation itself.

That can be a big problem. Two of your main SOX compliance obligations as a CEO or CIO is to assume responsibility in establishing internal controls over financial reporting and to certify their effectiveness. After that, the external auditors are supposed to attest to your assertions. Obviously, there has to be a well-defined basis before you can make such assertions and auditors can attest to anything.

In the language of auditors, this ?well-defined basis? is known as a control framework. Simply put, once you certify the presence of adequate internal controls in your organisation, the external auditor will ask, ?What control framework did you use??

Knowing what control framework you employed will help external auditors determine how to proceed with their evaluations and tests. For your part, a control framework can serve as a guide to help you work towards specific objectives for achieving compliance. Both of you can use it as a common reference point before drawing any conclusions regarding your controls.

But there are many control frameworks out there. What should you use?

How SOX, COSO, and COBIT fit together

Fortunately, despite SOX?s silence regarding control frameworks, you aren’t left entirely to your own devices. You could actually take a hint from the SEC and PCAOB, two of the lead organisations responsible for implementing SOX. SEC and PCAOB point to the adoption of any widely accepted control framework.

In this regard, they both highly endorse COSO, a well-established internal control framework formulated by the Committee of Sponsoring Organisations of the Treadway Commission (COSO). Now, I must tell you, if you’re looking specifically for instructions pertaining to IT controls, you won’t find those in COSO either.

Although COSO is the most established control framework for enterprise governance and risk management you’ll ever find (and in fact, it’s what we recommend for your general accounting processes), it lacks many IT-related details. What is therefore needed for your IT processes is a framework that, in addition to being highly aligned with COSO, also provides more detailed considerations for IT.

This is where COBIT fits the bill.

How COBIT can contribute to your regulatory compliance endeavors

COBIT builds upon and adheres with COSO while providing a finer grain of detail focused on IT. You can even find a mapping between COBIT IT processes and COSO components within the COBIT document itself.

Designed with regulatory compliance in mind, COBIT lays down a clear path for developing policies and good practice for IT control, thus enabling you to bridge the gap between control requirements, technical issues, and business risks.

Some of the components you’ll find in COBIT include:

IT control objectives

These are statements defining specific desired results that, as a whole, characterise a well-managed IT process. They come in two forms for each COBIT-defined IT process: a high-level control objective and a number of detailed control objectives. These objectives will enable you to have a sense of direction by telling you exactly what you need to aim for.

Maturity models

These are used as benchmarks that give you a relative measurement stating where your level of management or control over an IT process or high-level control objective stands. It serves as a basis for setting as-is and to-be positions and enables support for gap analysis, which determines what needs to be done to achieve a chosen level. Basically, if a control objective points you to a direction, then its corresponding maturity model tells you how far in that direction you’ve gone.

RACI charts

These charts tell you who (e.g. CEO, CFO, Head of Operations, Head of IT Administration) should be Responsible, Accountable, Consulted, and Informed for each activity.

Goals and Metrics

These are sets of goals along with the corresponding metrics that allow you to measure against those goals. Goals and metrics are defined in three levels: IT goals and metrics, which define what business expects from IT; process goals and metrics, which define what the IT process should deliver to support It’s objectives; and activity goals and metrics, which measure how well the process is performing.

In addition to those, you’ll also find mappings of each process to the information criteria involved, IT resources that need to be leveraged, and the governance focus areas that are affected.

Everything is presented in a logical and manageable structure, so that you can easily draw connections between IT processes and business goals, which will in turn help you decide what appropriate governance and control is needed. Ultimately, COBIT can equip you with the right tools to maintain a cost-benefit balance as you work towards achieving SOX compliance.

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