Learning & Innovation Research Manager| Project Management Institute (PMI)Spain
Data quality and quantity is particularly important as we think about leveraging AI on projects. Considerations include the diversity and comprehensiveness of the data that is available to us.
Have you ever encountered unexpected challenges or pitfalls while using data in your projects? How did you navigate the situation and find a resolution? Saving Changes...
The way I would navigate unexpected data challenges as a project manager, assess the situation by understanding the nature of the issue. Communicate with the team and stakeholders. Gather information to fill in the gaps. Brainstorm for potential solutions. Identify the risks associated and develop a plan for contingencies. Seek support for expert assistance. Adapt to adjust, by being flexible in my approach to new obstacles. Keep track of the actions taken to resolve. Document lesson learned. Continuous improvement. Saving Changes...
My first approach to unexpected data challenges is to remain calm, in order to control the reaction. It is natural phenomenon for problems to arise unexpectedly. In one of those instances, we had a team that understood we were looking for the root cause, not blame. We put emphasis on lessons learned therefore issues like these were met with open collaboration to pounce on root cause, look for solution, be transparent with stake holders, revert to our already prepared recovery plan to get the project back on track, and finally review to ensure this solution does not spawn into another failure.
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1 reply by Patricia Hays
Jan 25, 2025 5:25 PM
Patricia Hays
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I greatly appreciated your approach to stay calm and to manage the reaction. Virtually anything can be managed and is an opportunity to learn and adapt. Assessing the situation and finding solutions, such as managing quality input and uniformity can help alleviate false misses or garbage out responses.
My first approach to unexpected data challenges is to remain calm, in order to control the reaction. It is natural phenomenon for problems to arise unexpectedly. In one of those instances, we had a team that understood we were looking for the root cause, not blame. We put emphasis on lessons learned therefore issues like these were met with open collaboration to pounce on root cause, look for solution, be transparent with stake holders, revert to our already prepared recovery plan to get the project back on track, and finally review to ensure this solution does not spawn into another failure.
I greatly appreciated your approach to stay calm and to manage the reaction. Virtually anything can be managed and is an opportunity to learn and adapt. Assessing the situation and finding solutions, such as managing quality input and uniformity can help alleviate false misses or garbage out responses. Saving Changes...
Anonymous
We identify the nature of the challenge, underlying cause, and rally the applicable resources to course-correct as quickly as possible to avoid delays in the project. Saving Changes...
Anonymous
I do not have any experience with this at this time. Saving Changes...
The data we use for Generative AI tools sometimes lacks accuracy because the data we collected previously was intended only for rough reference, not for use with Generative AI. As a result, we’ve realized how important data accuracy is at this stage.
Because of this, even if we encounter some data conflicts, we don’t worry too much for now. Our priority is for our team to learn how to use the Generative AI tool effectively. Moving forward, we aim to collect and register accurate data for our future projects.
Saving Changes...
John NjorogeProject Management| Equity Group HoldingsSabaki/ Athi river, Kenya
Hi Claudia,
i have incurred intentionally manipulated data to try and sway a project to one stake holders scope.
the requirements were gathered but documented on a perspective bias.
the mitigation was to to have the confidentiality , integrity and accesibility of the data restored by having the requirement gathering process output being analysed by a third person and also having citations to the actual surveys and business case being done when validating the scope of the project and on sprint review to keep the scope valid.. Saving Changes...
Michael MooreNoneAiken, South Carolina, United States
Data quality in health care organizations may have many different meanings and understandings. Current Procedural Terminology (CPT) codes are used for medical, surgical, and diagnostic services. However, different hospitals, clinics, or health care organizations may have different policies or practices regarding the use of these codes for the same or similar treatments or combinations of treatments or services. Hence, there are data management challenges, particularly with historical data. Narrowly defining the type of data may serve better the purpose. For example, physicians may value as sufficient a patient’s most recent (months to two years) medical data in order to provide timely testing, evaluation, or current medical services or treatments. Medical record data prior to two years may or may not have less value depending on the diagnosis or medical condition regarding current services or treatment. GenAI which complies medical records data for millions of patients may be better applied regarding specific medical conditions and treatments (i.e., CPT codes) within the previous two years. GenAI regarding medical evidence and research may be better applied by compiling and synthesizing thousands of published clinical studies in order to suggest potential combined [physiological] treatments rather than a single pharmacological intervention. Saving Changes...
Anonymous
During a project restart, it came to light the primary field in a data set should be a secondary field. After an analysis of the scope of this problem we found out the accounting department had a heavy lift processing payroll every week. But more interestingly, there was another platform upgrade that was wrestling with the same data issue. A data project was initiated to review and adjust the data structure so the data was easier to implement, utilize and manage across platforms. Saving Changes...
Christina DietrichCustomer Project Manager| Nokia of North AmericaSeattle, Wa, United States
Jan 13, 2024 3:47 AM
Replying to Nikita Jha
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In my previous project, the objective was to reduce obsolescence for database technologies across the globe aka many regions. The timeframe for communication with immense amount of data took two weeks cycle for response and plan of action. However the data kept growing as many assets were not listed in a particular region as API failed to retrieve information at the right time. Hence I took that region as a subset project with dedicated resources and fast tracked to bring the region at par with other regions. It was immensely challenging but at the end it was rewarding in terms of achievement and stakeholders appreciation.
I haven't encountered challenges myself due to not yet using GenAI in my projects, so appreciate getting to ready the insightful responses and learn from my peers. Saving Changes...
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