Project Management Institute

The Power of AI Predictions

Artificial Neural Networks Can Boost the Accuracy of Project Estimates

By Hari Doraisamy, PMP

It is notoriously difficult for project managers to accurately estimate project costs. However, software that uses neural networks can be a powerful solution to this problem.

Artificial neural networks, a type of artificial intelligence (AI), mimic the way neurons in the brain work. They “learn” patterns based on historical data and can then estimate values that depend on several inputs.

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Project managers know that the cost of a project largely depends upon three variables: the number of resources, their cost and the project's length. However, lesser variables, like scope expansion and complexities, could also impact the project's cost. That's where artificial neural networks come in—we can use them to identify potential cost overruns based on data from past projects of similar size and type.

This can allow a project manager to more accurately plan project activities and resources—possibly helping to prevent cost overruns.

Project managers who want to give it a try could use commercial software to create a customized neural network. A good programmer also can develop a computer program to design a neural network.

I designed a neural network and trained it with a data set from 27 different projects. Parameters included project duration, complexity of the project, number of resources and projected cost.

The set also included the actual cost for each of these 27 scenarios. I trained the network using the historical data by iteratively adjusting the weights until the calculated output matched the desired output within tolerance for each training record.

Neural networks have been widely used in science and engineering. Project managers have been slower to adopt them, possibly due to a lack of awareness.

When presented with new data, my neural network was able to estimate the project costs based on the historical information. I tested it with simple sample projects and found it impressively accurate. For more complex projects, the network also did an excellent job of estimating costs, though it was not as accurate as with simple projects.

Neural networks have been widely used in science and engineering. Project managers have been slower to adopt them, possibly due to a lack of awareness. But neural networks have great potential for our profession. And although my experiment focused on project costs, they also could be used to forecast other project data. PM

The future of AI has real possibilities. See page 62

image Hari Doraisamy, PMP, is team lead of mission critical support, SAP, Newtown Square, Pennsylvania, USA.
This material has been reproduced with the permission of the copyright owner. Unauthorized reproduction of this material is strictly prohibited. For permission to reproduce this material, please contact PMI.

JANUARY 2017 PM NETWORK
PM NETWORK JANUARY 2017 WWW.PMI.ORG

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