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INFORMATION TECHNOLOGY & BUSINESS PROCESS RE-ENGINEERING
FACT: The $7 trillion per year Construction Industry ranks 87th globally, among Industries in the adoption of Technology.
Overall, on a global scale, the Construction Industry is showing growing awareness of the role of Information Technology (IT) as a key tool which can be used to improve competitiveness in construction and the need to develop appropriate solutions. The reality is that managing information technology in large enterprises is complex. However, we have found that the root causes of dissatisfaction with return on IT lie primarily in organization and business issues, not technology. At KarpeDium we are strong proponents of process-driven IT as a management process that uses functional priorities to improve the effectiveness of your IT investments.
The need for IT enabled AEC Organization
Construction today is too complex, with terabytes of information and data created during any one project. Accurate information is the lifeblood of construction and enables constituents to gather, analyze and produce the insight for decision making and profitability. Being the most information intensive industry, where decisions are called everyday during project life cycle, the amount of information created here is enormous even for a small-sized construction project.
We assist businesses in the construction sector, to streamline and re-engineer their processes with the help of modern IT tools (Hardware & Software) to improve productivity and attain quality gains. At KarpeDium we have developed a program/project delivery framework that is enabled by flexible IT architecture and SAS (SOFTWARE AS A SERVICE) tools over the web.
Our best practices combined with a flexible yet sustainable IT infrastructure has contributed to increased process capability and allows for the ability to manage multiple resources across geographic and cultural boundaries.
We assist in:
IT STRATEGIC PLAN
IT IMPLEMENTATION
BUSINESS WORK FLOW
MANAGEMENT TOOLS
PERFORMANCE ANALYTICS
PROCESS AND DATA MODELING
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