Sometimes Moving Quickly Means Slowing Down
Noteworthy Analytics
- Burn Rate Analysis: Tracking the hours engineers spend against estimates to make informed decisions about change requests, schedules, and project direction.
- Data-Driven Decision Making: Using a data warehouse to target keywords, analyze article performance, and decide on investments to drive subscriber growth.
- Project Reporting: Emphasizing the importance of generating key reports throughout the project to measure success and inform strategic decisions.
Episode Highlights
- ✅ Tracking burn rates helps in making informed decisions about project changes and direction.
- ✅ Data warehouses enable targeted keyword strategies and investment decisions.
- ✅ Key reporting throughout projects ensures measurement of success and strategic adjustments.
Episode Summary
In this episode of the Analytics for Humans podcast, Bryan Mishkin, Chief Technology Officer at Reel Analytics, shares his extensive experience in technology and data analytics. Bryan discusses the pivotal role data plays in decision-making processes, providing examples such as burn rate analysis and data-driven strategies for keyword targeting and investment decisions. He emphasizes the importance of generating key reports throughout a project to measure success and make strategic adjustments. Bryan also highlights challenges in data-driven decision-making, the integration of new technologies, and the potential of AI in transforming business processes. He shares insights on maintaining a solid foundation of people, processes, and technology to ensure effective scaling and success.
Notable Questions and Answers
Q: How does data play a role in decision-making at Reel Analytics?
A: Data provides transparency and guides decisions in an analytical way. For instance, tracking burn rates helps make informed decisions about project changes and schedules, while data warehouses enable targeted keyword strategies and investment decisions.
Q: What are some challenges in data-driven decision-making?
A: People often rely on instincts and may avoid data due to fear of invalidation. Additionally, companies might lack transparency or access to data, leading to decisions based on gut feelings rather than informed analysis.
Q: How do you approach integrating new technologies into existing business processes?
A: Start with small investments to collect data through proofs of concept or A/B testing. Use this information to guide the next steps, ensuring minimal disruption and informed decision-making throughout the integration process.
Q: What impact does AI have on business processes at MIT Sloan Management Review?
A: AI helps automate tasks such as generating article descriptions and extracting SEO keywords, saving significant time and allowing staff to focus on higher-value tasks. This approach complements human efforts, enhancing productivity and efficiency.
Q: How do you ensure a solid foundation before scaling a team?
A: Ensure the right people, processes, and technology are in place before scaling. Address any foundational issues early on, involve the team in decision-making, and maintain transparency to foster engagement and buy-in from team members.
Q: What advice would you give for making data-driven decisions?
A: Understand the types of data available and use AI as a supplement, not a substitute. Reserve the right to adjust decisions as new data emerges, and consider seeking help from partners or experts to enhance decision-making processes.
Q: What has been the most rewarding project or achievement in your career?
A: One of the most rewarding achievements was growing the engineering team at Senior Advisor from 7 to over 30 people without losing a single team member. This involved establishing a solid foundation, ensuring the right people were in place, and fostering a collaborative and supportive environment.
Q: How do you keep a team engaged and motivated during periods of rapid growth?
A: Maintain transparency, involve the team in decision-making, and ensure everyone understands the objectives and the value of their work. Address any foundational issues early and provide clear direction to keep the team focused and engaged.
Q: What key takeaway would you like to share with listeners?
A: Sometimes, moving quickly means slowing down to ensure a solid foundation of people, processes, and technology. This approach minimizes rework, reduces waste, and ultimately allows for faster and more effective progress.
Chapters
00:00 Intro
00:21 Bryan's Background and Experience
01:29 The Role of Data in Decision Making
03:12 Challenges in Data-Driven Decisions
05:35 Integrating New Technologies
08:09 AI and Its Impact
09:16 MIT Sloan Management Review and AI
12:15 Bryan's Career Highlights
14:04 Strategies for Team Growth and Management
21:23 Key Takeaways
#DataAnalytics #BurnRateAnalysis #DecisionMaking #ProjectManagement #AIinBusiness #TechLeadership #DataDrivenDecisions #KeywordStrategy #InvestmentDecisions #ReportingTools
