S7E158: Planning Projects: Past, Present & Future with Micah Piippo
S7E158: Planning Projects: Past, Present & Future with Micah Piippo

S7E158: Planning Projects: Past, Present & Future with Micah Piippo

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<p>In this week’s pod, we were joined by Micah Piippo to discuss Planning Projects: Past, Present &amp; Future.</p> <p>Micah has spent the last 14 years in Project Controls. While he&#39;s performed a wide variety of roles, his passion and main focus is Planning and Scheduling. During his career he&#39;s tore down nuclear facilities, built large ferries, built data centers all over the world and more recently is helping Intel deliver state of the art fab capabilities.</p> <p>In December 2022, Micah started writing his Zero Float newsletter. In the newsletter Micah explores his favorite topics that he doesn&#39;t see getting enough attention.</p> <p>The main topics we discussed on the podcast were as follows:</p> <ul> <li>Whilst there are certifications available for schedulers. There is no degree programme that would allow students to learn the fundamentals of construction management, people management, how to use data and learning the project ecosystem. Most planners simply fall into the role</li> <li>The consequence of the lack of certification is a lack of respect for the skills that a good planner can bring to the organization by utilizing their experience</li> <li>A top level planner should have a breadth of experience as well as strong communication skills when dealing upwards and sideways within an organization</li> <li>Technology can help planners and project managers by having finite and usable as-built data</li> <li>Automated capture has helped companies to better define progress and productivity on projects. This was previously a highly subjective area</li> <li>There is a danger that Machine Learning / AI does not capture some of the politics around project schedules. This may affect the quality of data in future</li> <li>There is no mandate for government funded projects to share data despite being funded by taxpayers. This hampers the level of data available to be harnessed by machine learning technology</li> </ul> <p>Here are links to some of the topics we discussed:</p> <ul> <li>Probl

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