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.
Duplicate RequirementsRepeated requirements, in terms of content and context, are detected using the latest NLP libraries.
Ambiguous RequirementsAmbiguous requirements are compared with the industry standards and users are contacted for more inputs.
Major FunctionalitiesThese are detected based on the keywords interface, reports, transactions, displays, and data storage.
Parent-Child RelationshipsThe relationships between variables are analyzed based on hierarchy levels.
- 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.
CONSISTENT HIGH-QUALITY RESULTS
- Top-notch developers
- Dedicated quality assurance personnel
- Adherence to QA best practices
- Agile development process
COST-EFFECTIVE SOLUTIONS WITHIN BUDGET
- No surprises
- Efficient operations
- Good coding practices
- Expertise in latest technologies
PREDICTABLE RESULTS ADHERING TO DEADLINES
- Transparent project management
- Warranty-assured deliverables
- Carefully defined project plans
- Staffed to handle unexpected challenges