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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Why Spreadsheets can send the Pillars of Solvency II Crashing Down


Solvency II is now fast approaching and while it may provide added protection to policy holders, its impact on the insurance industry is not all a bed of roses. Expect insurance companies to restructure, increase manpower, and raise spending on actuarial operations and risk management initiatives. Those that cannot, will have to go. But what have spreadsheets got to do with all these?

Well, spreadsheets aren’t really the main casts in this blockbuster of a regulatory exercise but they certainly have a significant supporting role to play. Pillar I of Solvency II, which calls for improved supervision on internal control, risk management, and corporate governance, and Pillar II, which tackles supervisory reporting and public disclosure of financial and other relevant information, both affect systems that have high-reliance on spreadsheets.

A little background about spreadsheets might help.

Who needs an IT solution when you can have spreadsheets?

Everyone in any organisation just love spreadsheets; from the office clerk to the CEO. Because they’re so easy to use (not to mention they’re a staple in office computers), people employ them for processing numbers and as an all-around tool for planning, forecasting, reporting, complex modelling, market data analysis, and so on. They make such tasks faster and easier. Really?

You probably haven’t heard of spreadsheet hell

Unfortunately, spreadsheets do have certain shortcomings. Due to their inherent structure and lack of controls, it is so easy to commit simple errors like an accidental copy paste, an omission of a negative sign, an incorrect data input, or an unintentional deletion. Such shortcomings may seem harmless until your shareholders discover a multi-million discrepancy in your financial report.

And because spreadsheet errors can go undetected for a long time, they are constant targets of fraudsters. In other words, spreadsheets are high risk applications.

Solvency II Impact on Spreadsheet-based Financial and IT Systems

Regulations like Solvency II, are aimed at reducing risks to manageable levels. Basically, Solvency II is a risk-based system wherein a company?s capital requirements will depend on its measured riskiness. If companies want to avoid facing onerous capital requirements, they have to comply.

The three pillars of Solvency II have to be in place. Now, since spreadsheets (also known as User Developed Applications or UDAs) are high-risk applications with weak control features and prone to produce inaccurate reports, companies will have a lot of work to do to establish Pillars II and III.

There are at least 8 articles that impact spreadsheets in the directive. Article 82, for example, which requires firms to ensure a high level of data quality and accuracy, strikes at the very core of spreadsheets? weakness.

A whitepaper by Raymond Panko entitled ?Spreadsheets and Sarbanes-Oxley: Regulations, Risks, and Control Frameworks? mentioned that 94% of audited real world operational spreadsheets that were included in his study were found to have errors and that an average of 5.2% of all cells in the audited spreadsheets had errors.

Furthermore, many articles in the directive call for the enforcement of better documentation. This is one thing that’s very tedious and almost unrealistic to do with spreadsheets because just about anyone uses them. Besides, with different ‘versions? of the same data existing in different workstations throughout the organisation, it would be extremely difficult to keep track of them all.

Because of spreadsheets you now need an IT solution

It is clear that, with the growing number of regulations and the mounting complexity of tasks needed for compliance, spreadsheets no longer belong in this era. What you need is a server-based solution that allows for seamless collaboration, data reliability, data consistency, increased security, automatic consolidation, and all the other features that make regulation compliance more doable.

One important ingredient for achieving Solvency II compliance is sound data risk management. Sad to say, the ubiquitous spreadsheet will only expose your data to more risks.

More Spreadsheet Blogs


Spreadsheet Risks in Banks


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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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Everybody knows about rugby union scrums. For our purposes, perhaps it is best to view them as mini projects where the goal is to get the ball back to the fly-half no matter what the opposition does. Some scrums are set pieces where players follow planned manoeuvres. Loose / rolling scrums develop on the fly where the team responds as best according to the situation. If that sounds to you like software project management then read on, because there are more similarities?.

Isn’t Scrum Project Management the Same as Agile?

No it’s not, because Scrum is disinterested in customer liaison or project planning, although the team members may be happy to receive the accolades following success. In the same way that rugby players let somebody else decide the rules and arrange the fixtures, a software Scrum team just wants the action.

Scrum does however align closely ? dare I say interchangeably with Agile?s sprints. Stripping it of all the other stages frees the observer up to analyse it more closely in the context of a rough and tumble project, where every morning can begin with a backlog of revised requirements to back fit.

The 3 Main Phases of a Scrum

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Phase 2 – Sprint Towards the Goal. The team separates to allow each member to complete their individual lines of code. Little or no discussion is needed as this stage.

Phase 3 – Review Meeting. At the end of each working day, the team reconvenes to walk down what has been achieved, and check the interconnected functionality.

The 3 Main Phases of a Scrum ? Conclusions and Thoughts

Scrum is a great way to liberate a competent project team from unnecessary constraints that liberate creativity. The question you need to ask yourself as manager is, are you comfortable enough to watch proceedings from the side lines without rushing onto the field to grab the ball.

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What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

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