Engineering Analytics9 Best Practices of Software Development Life Cycle (SDLC)

Avya Chaudhary · 2023-01-10

Poor estimates and poor management has led to many product development failures. A streamlined software development life cycle does more than just keep teams aligned and track work progress. It improves the engineering team's efficiency and highlights gaps in the existing workflows. You can deliver a quality product with lesser resource utilization and production time with the help of a truly optimized SDLC. 

SDLC ensures a data-driven approach focused on business goals. The manager can plan and use risk management to avoid security threats and post-launch requests. Maximizing security and functionality is the focal point of SDLC achieved by incorporating standardization and integration to enhance dev processes. 

But what exactly is the software development life cycle? Let us look at SDLC basics and unravel its best practices.

What is SDLC (Software Development Life Cycle)? 

Defining SDLC and why do we need it?

SDLC (software development life cycle) is a methodology for building high-quality products with seamless workflows and consists of  seven phases, namely: ideation, requirements, design, development, testing, deployment, and maintenance.

In each phase, a certain level of standardization increases the work process's effectiveness. 

But, why do we need to focus so much on SDLC when we can simply go by sprints and product delivery? 

  • SDLC begins by specifying the requirements and defining the goals clearly. Sometimes, developers tend to deviate from the core project goal as they feel overwhelmedwith multiple ideas. The SDLC methodology helps them achieve business goals without much divergences.
  • SDLC means a faster process as it involves standardization. This saves developers’ time by removing unnecessary friction. This standardization is applicable even for security checks and code reviews. It eliminates back and forth requests and security inspections post-launch or post-delivery.
  • SDLC focuses on optimum resource utilization. It starts by analyzing the requirements and puts forward the resources required. This improves the planning process and saves costs.
  • The process ensures high-quality deliverables by deploying an SOP and integrating security checks within the workflow. It minimizes the feedback or loopholes at the end of the sprint cycle, which leads to delays. 
  • SDLC means proper planning, optimum resource allocation, and fewer security risks. All these factors enhance customer satisfaction due to faster and more secure product delivery.
  • SDLC prioritizes security by integrating various measures within the development process such as code review, threat modeling, penetration testing, etc. These lead to better code context, quality, and consistency as the developer tests and deploys code simultaneously. As a result, your team delivers a secure solution. Also, security threats after delivery are much more complex due to the involvement of other users and multiple integrations.
  • SDLC highlights repetitive loopholes or security threats in the development process. Also, a standard security framework builds trust amongst the users. 

Therefore, SDLC solves many different challenges in the software development process. But, even after employing SDLC, companies might not leverage it due to poor management strategies. Let us look at some best practices to improve SDLC.

How to Improve SDLC: 9 Best Practices

Software Development Life Cycle Best Practices

SDLC is a strategic approach to software development that is iterative and structured. However, managers can not use it to its full potential due to errors in time estimates and inefficient task allocation. Here are 9 actionable steps to improve your software development life cycle (SDLC).

Workflow Management

Poor work management is one of the reasons that SDLC does not improve productivity and performance. Inefficient task allocation, lack of work progress, and improper planning disturb the dev workflow. Managers can look into the metrics such as cycle time, velocity, DevOps performance, check-in submissions, product backlog, sprint health metrics, etc. These give a better picture to plan and assign sprints accordingly. 

Clear Scope of Work 

SDLC begins with ideation and studying requirements. An ambiguous scope of work will negatively impact developer productivity. You should include:

  1. Deliverables
  2. Timeline
  3. Milestones
  4. Reports 

    It will avoid  duplication of work, code churn, and increased dev fatigue. Also, scope creep can change project direction and  hamper project clarity. Scope creep is a situation where the client demands more deliverables as discussed before. So, to save resources and the developer’s well-being, having a clear scope of work is non-negotiable.

Documentation

Documentation is making a written record of project related details including deliverables, deadlines, resources, and others with the motive to unify and organize project information. It is vital for engineering teams as it keeps teams aligned, eliminates the chances of scope creep, and lessens iteration rounds. 

The manager should opt for detailed documentation and keep updating to leverage it efficiently. Async tools will help them with transparent communication amongst team and other stakeholders. 

Security risks should have a place in the documentation as well. Every new security threat with proper documentation allows the teams to save time in case of recurring errors, and helps for future reference. 

Scrum Best Practices

agile scrum

Most of the development teams work under a scrum arrangement. The engineering manager should opt for best scrum practices such as asynchronous communication and data-driven workflows. These practices enhance the team collaboration and effort alignment. The managers can track work progress and bring improvements for better quality products. They should look into metrics to set healthy dev workflows and team relationships. It involves activities such as daily stand-ups and sprint retrospectives. These aim at keeping teams in sync and resolving blockers. 

Integration

Opt for CI/CD (continuous integration and continuous deployment) to avoid last-minute hassles of integration. It saves time by reducing the chances of lost code context. This also means deploying tests and code reviews at the development time which gives a secure product. The product delivery comes off with minimum security risks and saves time for developers from complex risks. 

Track Engineering Metrics

Looking at the engineering team's performance is vital for seamless SDLC. The manager should track metrics such as cycle time, DORA metrics, and code review metrics to improve dev velocity and eliminate bottlenecks. Some important metrics to look for are:

  • Cycle Time: How quickly can your team deliver the product from start to finish? The manager needs to aim for a smaller cycle time
  • Deployment Frequency: How often can your team deploy the code? The aim is to release small chunks of code as soon as possible. So, the deployment frequency should be high.

DORA Metrics overview by Hatica
  • Rework Ratio: How many codes need to be rewritten? If the rework ratio is high, it indicates a high churn ratio and leads to lower efficiency.
  • High-Risk Branches: What particular issue branches need the maximum rework? Often certain branches need a lot of rework leading to increased risk and low productivity.
  • Investment Profile: How much time is the dev spending on each task? This could include all the productive and non productive tasks ranging from solving blockers to attending meetings.
  • Context Switching: How often do the devs have to hop from one issue to another due to blockers? Tracking this gives an idea as to how efficient the team is. In case of constant back-forth, teams are considered inefficient.
  • Work-In-Progress Balance: This metric focuses on equal work distribution amongst the team. The manager needs to ensure that the members are not overwhelmed or underloaded.
    As a result, this leads to improved code quality, aligns team effort, increases dev engagement, and enhances DevOps performance.

Collaborative Learning

Collaborative training using the buddy system is an effective way to train developers. This leads to better team relationships and communication. In this system, two members train and work in a pair. The process is faster and more efficient as it enhances productivity and increases job satisfaction. You can track the progress using data and manage accordingly.

Breaking Down the Tasks

Conduct sprint reviews and dev workflow health checks to break tasks into smaller milestones. This helps the manager with better engineering team management. It leads to faster code reviews, better cycle time, and improved PR metrics. This helps enhance SDLC by making the process of testing, deployment, and maintenance easier. However, analyze these metrics regularly to stay updated and modify work allocation whenever required.

Data-Driven Success

Setting the right SDLC requires looking into engineering team metrics and data to get actionable insights. It helps in finding loopholes and enhancing the cycle with the right metrics. Do the sprint reviews, look for bottlenecks, identify DevOps blockers, and plan workflow accordingly. Plan sprints by referring back to sprint retrospective and backlogs review. 

From here on, it is clear that the data of engineering teams is vital to planning and executing an effective SDLC. You need to extract the data such as DORA metrics, team blockers, velocity metrics, and code review visibility. It can be challenging to manually get this as it would interfere with the team workflow and productivity. So, What is a better solution?

Data-Driven Approach to SDLC

SDLC starts with looking at the product requirements and ends with maintenance, after which the loop continues. At all stages, getting the right data can enhance the team's performance and ensure quality product delivery. In addition to this, managing the teams efficiently is a deal breaker. Solution? An engineering analytics platform like Hatica!

Hatica is an engineering management platform that pulls all the work data to give actionable insights. It integrates with your project management tool, communication tool, and software development tool to collect and interpret data, and offers custom dashboards with insights. It tracks bottlenecks in dev processes and provides velocity metrics by giving access to DORA metrics. From basic check-in to burnout tracking, you can align team efforts toward business goals.

Request a demo and explore Hatica further.

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Table of Contents
  • What is SDLC (Software Development Life Cycle)? 
  • How to Improve SDLC: 9 Best Practices
  • Workflow Management
  • Clear Scope of Work 
  • Documentation
  • Scrum Best Practices
  • Integration
  • Track Engineering Metrics
  • Collaborative Learning
  • Breaking Down the Tasks
  • Data-Driven Success
  • Data-Driven Approach to SDLC