Core Metrics to Manage Modern Process

Project management metrics are very necessary and essential for implementing practical and sustainable project management practices and processes in an organization. These metrics enable us to improve our understanding by simply removing uncertainty so that we can form well-informed decisions. These metrics are key to improving how projects are managed and even delivered. Metrics help in estimating cost and schedule for completion along with increasing accuracy over time. 

Advantages of Core Metrics to Manage Modern Process

• Project management metrics help us to measure or calculate and understand the maturity of the organization.
• They help in managing projects and resources in a more effective way.
• It also helps demonstrate year-over-year improvements in project management maturity.
• With respect to time, they provide insight into how processes and products are developing gradually.

Steps of Choosing Metrics for Managing Modern Process

Every business or organization needs unique metrics that can align and add value to its target or goal. The following are steps to choose metrics :

1. First, knowing and understanding the main purpose target, or goal of the project of work is essential.
2. Secondly, to determine and identify critical factors that are needed to be fulfilled for success and to achieve goals.
3. Thirdly, to take critical factors for the project of the program and determine how to measure its completion.

Metrics for Core Metrics to Manage Modern Process

Nowadays, several metrics are available that help in managing modern processes. A total of seven core metrics are available that are essential and vital for all software projects. These seven metrics are categorised into two categories: management indicators and quality indicators. Out of seven, three of them are management indicators and the rest of them are quality indicators. All of these metrics generally have two dimensions: static value which is used as an objective and dynamic trend which is used to manage the main achievement of that particular objective. These metrics are simply based upon common sense and experience regarding the field with both successful and unsuccessful metrics programs. Metrics that are generally related to costs simply prove the value of the team.

1. Burndown/Burnup Charts: Graphical depictions of the amount of work left in a sprint or project at any given time, either as burndown or burnup. These graphs give a clear picture of how much work has been done in relation to finishing the scheduled tasks and meeting deadlines.
2. Defect Density: Usually expressed as faults per thousand lines of code (KLOC), this is the quantity of flaws or defects found per unit of code. Defect density is useful in determining areas that need to be improved and in evaluating the overall quality of the codebase.
3. Deployment Frequency: The regularity with which new features or modifications are rolled out to production or staging environments is known as the deployment frequency. A well-developed and effective deployment pipeline is indicated by a high deployment frequency, which facilitates continuous delivery and a quicker time to market.
4. Customer satisfaction: It refers to the opinions expressed by stakeholders or end users on the usability, functionality, and quality of the product. User feedback, Net Promoter Score (NPS), and customer satisfaction surveys can all offer insightful data on how well the development process is going.
5. Work in Progress (WIP) Limits: The most work items that can be completed concurrently at any one time throughout a development process stage, such as development, testing, or review. WIP limitations facilitate the avoidance of bottlenecks, enhance workflow, and preserve concentration on finishing tasks.
6. Code Churn: The rate at which code is added, changed, or removed from the codebase over time is known as code churn. Increased technical debt and decreased productivity can result from instability or frequent changes in requirements, which can be shown by high code churn.
7. Management Indicators : Metrics that are given below must be interpreted to serve as indicators. They might indicate a problem or issue, minor perturbation, or simply change that is generally being managed. Metrics are given below :
   • Work and progress – Work that is performed over a given period. Planning about iteration means to determine and discuss planning the next cycle, phase, or iteration.
   • Budgeted cost and expenditure – Cost that is incurred over a given period of time. Its Financial insight means to understand the implications regarding financial decisions that are made today.
   • Staffing team dynamics – Personnel changes occurred over a given period of time. Its resource plan means to allocate and utilize resources simply to achieve the highest efficiency of these resources.
8. Quality Indicators : Quality indicators are Key Performance Indicators (KPI) that are very critical during the realisation of a project. These indicators need to be monitored carefully in order to confirm and ensure that the team is working or performing proper tasks. Metrics are given below :
   • Change traffic and stability – Change of traffic and stability over a given period of time. Planning about iteration means determining and discussing planning the next cycle, phase, or iteration. They also indicate convergence schedule which means to indicate convergence points in the schedule where two to more activities come together and explain dependencies of successor activity.
   • Breakage and modularity – Average breakage and modularity per change over a given period of time. There is convergence, software scrap and to indicate the quality of software.
   • Rework and adaptability – Average rework per change over a given period of time. There is convergence, software scrap and to indicate the quality of software.
   • Meantime between failure (MTBF) and maturity – Rate of defect over a given period of time. This is to indicate the quality of software, and test coverage simply to measure and calculate the amount of testing performed by a set of tests.