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.

 

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Symbion Pharmacy Services? Definition of Responsibility

A ?symbion? is an organism in a symbiotic (i.e. mutually beneficial) relationship with another one. In the case of Australia?s giant Symbion Pharmacy Services, this means supplying and delivering over-counter Chemmart medicines to more than 3,000 hospital and retail pharmacies, while remaining mindful of its carbon footprint.

In 1999, the company with the tagline ?life matters? and a desire to be seen as ?a good corporate citizen? decided it was time to measure exactly what it was pumping out from 12 facilities and over 200 vehicles. This was a voluntary decision as even now there is still no carbon emissions law in Australia (although no doubt being a ?first mover? will put the company in a competitive position when this inevitably comes).

Symbion decided to install emission detection devices and connect these to a central monitoring system with the intention of managing what these measured. There were two stages to this process. First, Symbion determined its reporting requirements based on one of its larger warehouses. Following that, it established a carbon footprint for each of its wholly owned and managed facilities. This put it in a position to:

  • Analyse total emissions down to a level of detail where it understood the contribution of each source
  • Use big data management tools to identify carbon hotspots for priority remedial action
  • Inform the affected workforce, explain the monitoring system and keep them in the loop
  • Separately manage energy abatement programs such as lighting and delivery routes

The program also had productivity spin-offs in that it focused management attention on the processes behind the emissions that were ripe for material and system improvements. It also provided marketing leverage. Symbion?s customers are in the wellness business, ahead of the curve when it comes to how emissions contribute to chronic illness, and aware of the cost of this in terms of human capital.

EcoVaro could help you manage your throughputs by analysing your data on our cloud-based system. This includes trending your metrics, comparing them to your industry seasonal average, and providing you with a business-like view of how well you are doing.

Our service reduces your reliance on (and the cost of) third party audits, and simplifies the reporting process to your controlling authority. It simply makes more sense to contract your software out this way, and only pay for it when you need it.

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

Lowers cost of analytics

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

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

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

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

So where does the cloud fit into all these?

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

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

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

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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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