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.

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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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.

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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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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8 Best Practices To Reduce Technical Debt

When past actions in software development return to haunt you…

Is your business being bogged down by technical debt? Let’s look at measures that you can take to reduce it and scale your operations without the weight pulling you back. 

 

Work with a flexible architecture.

Right from the word go, you want to use architecture whose design is malleable, especially with the rapid rate of software evolution witnessed today. Going with an architecture that keeps calling for too much refactoring, or whose design won’t accommodate future changes will leave you with costly technical debt. Use scalable architecture that allows you to modify or add new features in future releases. While on this, complex features required in the final product should be discussed at the planning stage, that way simplified solutions that will be easier to implement can be identified, as this will lead to less technical debt in the long run. 

 

The Deal with Refactoring 

This is basically cleaning up the code structure without changing its behaviour. With the updates, patches, and new functionalities that are added to the systems and applications, each change comes with the threat of more technical debt. Additionally, organisations are increasingly moving their IT infrastructure from on-premises facilities to colocation data centres and deploying them on the cloud. In such scenarios, some workarounds are often needed to enable the systems to function in the new environments, which they hadn’t been initially developed to accommodate. Here, you will need to take some time to refactor the existing system regularly, streamlining the code and optimizing its performance – and this will be key to pay down the tech debt. When working with a flexible architecture from the start, the amount of work that goes into this will be reduced, meaning there’ll be less tech debt involved. 

 

Run discovery tests

Discovery testing essentially takes place even before a line of code is written for the system or application. This takes place at the product definition stage, where human insight software is used to understand the needs of the customer and is particularly helpful in setting priorities for the development work that will be carried out. It gives your business the opportunity to minimize the technical debt by allowing customers to give you a roadmap of the most pertinent features desired from the product. 

 

Routine code review

Getting a fresh look at the product or application from different sets of eyes in the development team will improve the quality of the code, thus reducing technical debt. There’s a catch though – this should be planned in a convenient way that doesn’t end up becoming a burden for the developers. Here are suggestions:

Break down pull requests

Instead of having complex pull requests where numerous changes in the code are introduced at a go, have this broken down into smaller manageable pull requests, each with a brief title and description about it. This will be easier for the code reviewer to analyse. 

● Define preferred coding practices

Documenting the preferred coding style will result in cleaner code, meaning the developers will focus their effort on reviewing the code itself, not losing time on code format debates.

 

Test automation

Relying only on scheduled manual testing opens you up to the risk of technical debt accruing rapidly, and not having sufficient resources to deal with the accumulated problems when they are identified. Automated testing on the other hand enables issues to be uncovered quicker, and with more precision. For instance, you can have automated unit tests that look at the functioning of the individual components of a system, or regression testing where the focus is on whether the code changes that have been implemented have affected related components of the system. However, establishing and maintaining automated testing will require quite some effort – making it more feasible for the long-term projects.

 

Keep a repository that tracks changes made

Do you have a record of changes made in the software? Keeping one in a repository that is accessible by the development team will make it easy to pin-point problems at their source. For instance, when software is being migrated to a new environment, or legacy software is in the process of being modernised, you will want to have an accurate record of changes that are being introduced, that way if there is an undesired impact on the system this it will be easier to zero-down on the cause.

 

Bring non-technical stakeholders on board

Does this conversation sound familiar?

Development Team: “We need to refactor the messy code quickly”

Product Team: “We have no idea what you are saying”

On one hand, you have the management or product team defining the product requirements, creating a project roadmap, and setting its milestones. On the other hand, there’s the software development/engineering that’s primarily focused on the product functionality, technical operations and clearing the backlog in code fixes. Poor communication between the two teams is actually a leading cause of technical debt.

For you to take concrete steps in managing your technical debt, the decision-makers in the organisation should understand its significance, and the necessity of reducing it. Explain to them how the debt occurred and why steps need to be taken to pay it down – but you can’t just bombard them with tech phrases and expect them to follow your thought process. 

So how do you go about it? Reframe the issues involved with the technical debt and explain the business value or impact of the code changes. Basically, the development team should approach it from a business point of view, and educate the management or production team about the cost of the technical debt. This can include aspects such as expenses in changing the code, salaries for the software engineers especially when the development team will need to be increased due to the workload piling up, as well as the revenue that is lost when the technical debt is allowed to spiral. 

The goal here is to show the management or production team how issues like failing to properly define the product requirements will slow down future software development, or how rushing the code will affect the next releases. That way, there will be better collaboration between the teams involved in the project. 

 

Allocate time and resources specifically for reducing technical debt

With management understanding that working with low-quality code is just like incurring financial debt and it will slow down product development, insist on setting time to deal with the debt. 

For instance, when it comes to the timing of application releases, meetings can be conducted to review short- and longer-term priorities. These meetings – where the development team and product team or management are brought together, the developers point out the software issues that should be resolved as a priority as they may create more technical debt. Management then ensures that budgets and plans are put in place to explicitly deal with those ongoing maintenance costs.

 

Retire old platforms

While most of the resources are going into developing new applications and improving the systems being used, the organisation should also focus on retiring the old applications, libraries, platforms, and the code modules. It’s recommended that you factor this into the application release plans, complete with the dates, processes and costs for the systems involved. 

 

Total overhaul

When the cost and effort of dealing with the technical debt far outweighs the benefits, then you may have to replace the entire system. At this tipping point, you’re not getting value from the technical debt, and it has become a painful issue that’s causing your organisation lots of difficulties. For instance, you may be dealing with legacy software where fixing it to support future developments has simply become too complicated. The patches available may only resolve specific issues with the system, and still leave you with lots of technical debt. Here, the best way out is to replace the system in its entirety. 

 

Final thoughts

Every software company has some level of tech debt. Just like financial debt, it is useful when properly managed, and a problem when ignored or allowed to spiral out of control. It’s a tradeoff between design/development actions and business goals. By taking measures to pay down your organization’s debt and address its interest as it accrues, you will avoid situations where short term solutions undermine your long-term goals. This is also key to enable your business to transition to using complex IT solutions easier, and even make the migration between data centres much smoother. These 8 measures will enable you to manage your technical debt better to prevent it from being the bottleneck that stifles your growth.

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