Free Download Data-Based Decision Making for Managers Practical AnalyticsPublished 1/2026
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Language: English |
Duration: 1h 45m |
Size: 3.14 GB
Use data (not guesswork) to set KPIs/OKRs, read dashboards, run tests, and build a culture of evidence-based decisions.
Define objectives and translate them into measurable questions, metrics, and KPIs.
Apply a 6-step data-driven decision cycle and validate outcomes with feedback loops.
Choose and interpret descriptive, diagnostic, predictive, and prescriptive analytics.
Read dashboards/visuals critically and communicate insights with clear data storytelling.
Use frameworks like OKRs, Balanced Scorecard, A/B testing, and PDCA/DMAIC.
Identify bias, bad KPIs, and data-quality issues that lead to wrong decisions.
RequirementsThere are no pre-requisites for this course
DescriptionCompanies are drowning in dashboards, reports, and "insights", yet many managers feel less confident, not more. Here's the opportunity: research consistently shows that organizations that use data effectively outperform their peers-one MIT study found data-driven firms are about 5-6% more productive and profitable, and McKinsey reports data-driven companies are far more likely to be profitable.In other words, using data well isn't a "nice to have." It's a competitive advantage.But data-based decision making doesn't mean ignoring experience or "letting the numbers decide." It means combining judgment with evidence: defining the right question, using the right data, interpreting results correctly, and validating outcomes so you improve with every decision.That's exactly what this course is designed to help you do.In this course, you'll learn how to:- Define data-based decision making (and what it is NOT)- Turn goals into measurable questions, metrics, and KPIs that drive the right behavior- Follow a repeatable decision process: define → collect → analyze → interpret → act → validate- Understand structured vs. unstructured vs. "big data," and when each matters- Use the analytics ladder: descriptive, diagnostic, predictive, and prescriptive analytics- Make sense of dashboards and visualizations-and communicate insights with clarity- Apply practical frameworks: Balanced Scorecard, OKRs, KPI dashboards, A/B testing, PDCA/DMAIC- Build a data-driven culture (trust, literacy, experimentation, and shared definitions)- Spot common traps: correlation vs. causation, confirmation bias, and "garbage in, garbage out"- Navigate modern challenges: AI/augmented analytics, ethics, privacy, governance, and biasYou'll also see real-world case studies from companies like Amazon, Netflix, Spotify, and Walmart-so you can model what works and avoid what doesn't.This is a practical, manager-friendly course. You won't need coding skills or advanced math. You'll learn how to think clearly with data, ask better questions, and make decisions you can defend-whether you're working with Excel, BI dashboards, or an analytics team.If you're ready to stop guessing, reduce risk, and lead with more confidence, this course will give you the toolkit and habits to make data-based decision making part of your daily work.
Who this course is forManagers and team leads who make operational or strategic decisions
Business professionals who want to use data with more confidence
Product, marketing, sales, and customer success leaders
Operations, supply chain, and service delivery managers
HR and people leaders making hiring and performance decisions
Entrepreneurs and small business owners who need practical analytics
Analysts or aspiring analysts who want stronger decision frameworks
Anyone working with dashboards, KPIs, reports, or performance metrics
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