How did your improvement help the organization achieve its goals?
EPAM has been rated at CMMI®-DEV Maturity Level 5 and currently conventional, linear methodologies are in use for resource planning. The company’s goal is to maintain continuous improvements in our processes and improve accuracy of our predictions. EPAM has piloted Artificial Neural Networks and Deep Learning methodologies in a number of projects as these can deal with non-linearity more effectively than traditional regression analysis if the data has nonlinear dependencies. Deep Learning methods truly represent the third generation of neural networks.
How did adoption or use of the CMMI contribute to the improvement?
EPAM has been rated at CMMI®-DEV Maturity Level 5. Adopting Artificial Neural Networks and Deep Learning represents our approach for the continuous improvement resulting increasing stability and capability in our processes. Our improved methodologies and tools can serve as best practices to a wider community committed to CMMI’s principles.
Why should this implementation be considered successful?
As described above, Artificial Neural Networks and Deep Learning methodologies improved process performance. The tool has helped pilot teams perform quantitative project management by better predicting future sprint results thus providing lower risk in resource planning. Artificial Neural Networks and Deep Learning methodologies support the company’s long-term corporate goals:
- Keep EPAM’s rates competitive with industry benchmarks
- Maintain high quality service delivery
- Maintain effective delivery workforce and sets directions for skill development
- Long term relationship with our customers by providing efficient services to them
Vladimir Savin is a Doctor in Computer Science, Power Engineering with Data Science experience. He previously worked as a Process Manager in ScienceSoft, a Quality Director in SemiTech, an Expert in Galaktika Corporation, a Project Manager in Client-Server Programs Ltd., a Senior Research Officer in Belarus Scientific Research Heat Engineering Institute.
All companies (branch office) are in Minsk, Belarus.
- Data Science
- Operations Research
- Deep Learning
- Machine Learning
- R programming
- Six Sigma
- Lean Six Sigma
- Software Engineering (C++, SQL, PL/1)
- Technical writing Past projects: During 2010-2017