AI & ML for Project Cost Estimation

Artificial intelligence and Machine Learning For Faster and Accurate Project Cost Estimation

AI, ML for Project Cost Estimation: An Overview

Speedy and accurate project cost estimation is critical in order to ensure customer satisfaction and repeat business. However, it remains one of the most arduous tasks in software engineering, especially when the projects dealt with are complex, extensive, and in the conceptual stage. The advancements in Artificial Intelligence and Machine Learning technologies are transforming the traditional methodology of software cost estimation into a flexible and intelligent approach. A compelling use case is an intelligent solution to identify and eliminate duplicates, analyze and pin-point ambiguity, and process RFPs in varied formats with minimal human intervention, for efficient and expedited project cost estimation.

Present Day Challenges in Project Cost Estimation

Today, software development cost estimation is performed by comparing known attributes with a reference class of projects, and leverage project managers’ experience in dealing with similar projects in the past. The current methodology can give rise to inaccurate estimates due to the following impediments:

Inability to factor in ambiguous requirements

Optimism bias that sets in due to the assumption of all resources working at maximum productivity

Significant wastage of time and effort in identifying and filtering out duplicate estimates

Padding estimates to make enough room to cover unexpected costs

Skipping key cost-drivers due to pressure from stakeholders to roll out the figures in haste

Dependencies on technological advancements and changing market conditions

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Redefining Software Cost Estimation with Artificial Intelligence and Machine Learning

An intelligent system leveraging AI and ML can be used to overcome the above human errors and arrive at meaningful estimates within limited time frames. The solution empowers project managers to automatically analyze requirements, weigh dependencies, and generate detailed reports, resulting in expedited software cost estimation.

The leading-edge technologies can intelligently identify:

Duplicate Requirements

Repeated requirements, in terms of content and context, are detected using the latest NLP libraries.

Ambiguous Requirements

Ambiguous requirements are compared with the industry standards and users are contacted for more inputs.

Major Functionalities

These are detected based on the keywords interface, reports, transactions, displays, and data storage.

Parent-Child Relationships

The relationships between variables are analyzed based on hierarchy levels.

The requirement analysis report generated by the intelligent system can be further vetted by users and fed as training data for ML, improving the algorithm at every stage. The system identifies and weighs requirements, captures dependencies like the technologies and skill sets of resources involved, and arrives at accurate estimates.

Benefits

Faster project estimation by automating mundane tasks.
Precision improvement by 30 – 40% as compared to traditional methods.
Accurate figures backed by historical data.
Timely estimation of extensive projects that include a plethora of parameters and huge databases.
Automatic identification and weighing of key cost drivers.
Provision to manage ambiguous requirements, including missing values and incomplete databases.
Development of trained algorithms reusable for future estimations.
Ability to generate estimates for documents of varied scope, characteristics, and formats.

How Fingent can help?

Fingent helps you leverage emerging technologies in innovative ways to redefine your business processes. With a dedicated team of engineers who stay abreast of the latest technologies and agile methodology of development, we convert out-of-the-box concepts of our clients into solutions with ease.