Data is constantly generated, updated, and evaluated in today’s digital world. For software engineers and software development companies such as BairesDev, data is incredibly important as it provides actionable, accurate feedback to help developers understand where there is room for improvement in the software development process and how to make said changes.
Current software development is all about data. From the product itself to its customers and markets, integration, and testing to deployment and runtime, various kinds of data help members of the development team get a full picture of the software that they are developing.
What Exactly is Data-Driven Software Development?
Data-driven development (sometimes referred to as DDD) is a method used for development and service maintenance based on data. Just as the name suggests, data-driven software development uses metric-based key performance indicators (KPIs), objectives, and/or key results (OKRs) to help determine the strategic outcomes of daily work and overall business value for each project.
Metrics provide powerful insight into how the business is successful, where its weakest links are, and allows each person to see how their individual efforts helped contribute to the overall project. In addition to KPIs and OKRs, these metrics commonly include engineering metrics and positive behavior metrics.
The Common Issues
Taking a metrics-focused approach is incredibly beneficial for many organizations. However, there are a few common issues that occur when a company is not following key performance indicators and such, including:
- The development, creation, and deployment phases are sometimes a bit bulky. This is commonly due to a focus on management without listening to the wants and needs of the developers who are actually completing the individual projects. Leadership must play a strong role in a data-driven development team as employees are sometimes intimidated by individual measurements. Leaders have to engage with the development teams to ensure that they do not disengage and to help streamline the process overall.
- Key performance indicators seem overwhelming when a team has an off month, quarter, individual project, or even year. It is sometimes difficult for teams to stay motivated and engaged when their measuring metrics do not reflect the effort that they are putting into their software development work.
- Organizations sometimes struggle with balancing individual KPIs and those of the team as a whole. There must be a fair balance between the two types of metrics to both measure and reward successes while identifying problem areas.
Tips for Successful Data-Driven Development
- Scale key results and experiment with them as necessary. OKRs are not static, unchanging metrics. After tracking for a quarter or after a few projects, these metrics should be reviewed and discussed with all team members. This way, problems are identified before the next project begins, team members get a voice in what is a fair metric, and results are reviewed by the full team. Developers, testers, and all software development team members alike should be encouraged to engage with these numbers and feel that they are serving for the betterment of the team as a whole to be more successful in the future.
- Try to avoid “dirty data,” or data that contains inaccurate, duplicate, inconsistent, incomplete, or other incorrect data. Removal of every piece of dirty data is nearly impossible, therefore strategies to work with this data are required to avoid interference with important metrics. Data management experts can help mitigate these issues by cleansing, validating, replacing, and deleting inaccurate information.
- Make the majority of key performance indicators an accounting function or rolled into the software product as a key management function. Larger organizations with major business divisions may subdivide, but everyone should be held accountable to the same level of measurement.
- Every software development team and leadership should make data quality a top priority throughout the data-driven development process. The process of discovering data is obviously a fundamental and crucial task for this method of development to work. Data profiling and data exploration help those responsible for analyzing the data to investigate the quality and implications of use before it is established as a metric. One of the best ways to improve and ensure high-quality data is being used is by making the data quality cycle a standard part of all data analysis.
- Software development organizations must take the time to find the right engineering metrics tool to track necessary metrics. Leadership must engage with their teams to help understand their work and how an effective tool can help their employees understand the results while getting more done. Software development teams should engage with the engineering metrics and suggest their own ways to use them.
Data-driven software development benefits development providers far beyond just the numbers with an effective process in place from the very beginning. As an organization moves toward a data-driven process, the focus must be on developing quality software products. These metrics help teams see the value that they are delivering in measurable numbers while also helping identify areas for improvement and success.