How AEC Firms Are Using Data Solutions to Unlock Hidden Project Insights

Key Concepts

Data journey, data visualization, PowerBI, data management, data strategy, physical system audits, PLC's, SCADA systems, historians, data lakes, data blind spots, cyber security, KPIs, data integration, interoperability, crash data analysis, PMO, single source of truth, data cleansing, data collection, data security, power users.

Backgrounds of Aaron Shelley and Scott Posey

• Aaron Shelley: Started in help desk at AOL, transitioned to business intelligence after discovering a passion for data analysis and reporting. Experience with Tableau, Click, and currently PowerBI. Focuses on transforming large datasets into user-friendly information for answering questions.
• Scott Posey: Electrical engineering background, moved into control systems and automation, particularly in the power industry. Passionate about collecting and visualizing data for client operations and utilities.

Choosing the Right Data Management and Visualization Solutions

• Main Point: A custom solution is needed for each client, depending on where they are in their "data journey."
• Key Considerations:
  • Client's Current State: Are they using Excel, or are they already using a data visualization platform?
  • Meeting Clients Where They Are: Avoid forcing clients into uncomfortable situations or platforms they can't adapt to.
  • Incremental Progress: Focus on helping clients take the next step, even if it's just improving their Excel usage.
• Example: A client using Excel for all data management might benefit from a free database as a single source of truth.
• Quote (Scott Posey): "We try to meet people where they are and not force them into, you know, uncomfortable situations... I want to make sure that, you know, we meet meet people where they are in their data journey and kind of help them to the next step rather than getting them to the finish line before they're ready."

Physical System Audits

• Main Point: A physical system audit is critical for understanding the data being collected and ensuring its quality.
• Key Aspects:
  • Instrumentation Review: Are you collecting the right data in the right locations?
  • System Updates: Are PLC's and SCADA systems up-to-date enough to convey the right data?
  • Data Cleansing: Understanding how data can be sorted and moved to visualize more easily.
• Purpose: To set up the base of the pyramid for successful data visualization.

Common Data Blind Spots

• Main Point: Identifying and addressing data blind spots is crucial for effective data management.
• Common Issues:
  • Excel Files on Hard Drives: Lack of centralized data, especially for critical monthly reports.
  • Unknown Data Sources: Assumptions about data origins can lead to inefficient processes.
• Solution: Thoroughly interview stakeholders to understand all data sources and processes upfront.
• Value of Expertise: Experienced teams can identify common pitfalls and ask the right questions early in the project.

Pitfalls in Implementing New Data Tools

• Main Point: Organizations often underestimate the time and effort required for successful data tool implementation.
• Common Pitfalls:
  • Unrealistic Expectations: Thinking the process will be quick and easy.
  • Lack of Planning: Not understanding the groundwork required to collect and process data properly.
• Solution: Develop a realistic plan with appropriate capital budgeting and stakeholder communication.
• Quote (Aaron Shelley): "...people think that they can get to the end answer extremely quickly. They don't realize what what it takes to get there... it is a journey and it's an there's an opportunity to really define the process uh but that takes time."

Data Integration

• Main Point: Integrating data from different systems can improve outcomes, even if the systems don't natively interoperate.
• Example: Utility company using a new tool that didn't integrate with their financial system (SAP).
• Solution:
  • Archiving Process: Create a database to archive data from the new tool daily.
  • Unique Identifier: Use a unique identifier to align the archived data with financial data.
  • Dashboard Visualization: Display the integrated data on a dashboard for real-time project tracking against budget.
• Key Takeaway: Data can be surfaced in any way desired, regardless of the tool's limitations.

Cyber Security

• Main Point: Centralizing data increases the risk of cyber attacks, requiring robust security policies.
• Key Considerations:
  • Connectivity: Data collection involves connecting systems, creating potential vulnerabilities.
  • IT Department Collaboration: Implement secure practices that align with the client's IT security policies.
  • Balancing Security and Convenience: Avoid sacrificing security for ease of access.
• Expert Guidance: Seek expertise to implement secure data collection and management practices.

Crash Data Analysis in the Transportation Sector

• Main Point: Data visualization can provide valuable insights for improving road safety.
• Project Overview: Analyzing multi-year crash data from different states.
• Process:
  • Data Cleaning and Standardization: Uniforming data from different sources.
  • Mapping and Filtering: Visualizing crash data on a map and filtering by factors like time of day, visibility, and age.
  • Identifying Outliers: Pinpointing intersections with high crash rates due to specific factors.
• Outcome: Providing transportation departments with a starting point for road work and safety improvements.
• Key Takeaway: Data visualization helps subject matter experts easily view and interpret data to make informed decisions.

Balancing Budget Limits and KPIs

• Main Point: Aligning data infrastructure and visualization tool choices with business objectives and budgetary constraints.
• Approach:
  • Staged Implementation: Break down the project into smaller, manageable stages.
  • Prioritization: Focus on tasks that align with the client's goals and budget.
  • Right-Sizing: Tailor the project to the client's capabilities and resources.

Advice for Starting the Data Journey

• Main Point: Start small, focus on tangible results, and find power users to evangelize the benefits of data visualization.
• Key Recommendations:
  • Avoid All-or-Nothing Approach: Don't try to implement a comprehensive solution from the start.
  • Focus on Tangible Results: Solve specific issues with data to demonstrate value.
  • Empower Power Users: Identify individuals who can effectively use and promote data visualization tools.
  • Start with Free Tools: Utilize free versions of tools like PowerBI to experiment and learn.
• Quote (Scott Posey): "You don't need a Lamborghini when when like a Nissan Sentra would would be just fine for your organization... start small... find your power users... and then just you know provide for them and and go on from there."

Synthesis/Conclusion

The key to successful data management and visualization lies in understanding the client's current state, setting realistic expectations, and focusing on incremental progress. A physical system audit is crucial for ensuring data quality, while addressing data blind spots and implementing robust cyber security policies are essential for protecting data. By aligning data infrastructure and visualization tool choices with business objectives and budgetary constraints, organizations can unlock the power of data to drive better decision-making and improve outcomes. Starting small, focusing on tangible results, and empowering power users are key to a successful data journey.