Using Data for Business Strategy and Decisions
Learn and discuss the essentials of statistics, “big data” applications and analysis that are vital to making sound business decisions. Explore application examples and case studies. Examine information about scoreboards and dashboards.
Improve your understanding of data essentials by determining bad data and what information needs are necessary to make sound business decisions. Examine ways on how to measure business performance and how to best present data to an audience.
- Essentials of Data: Bad data = bad decisions; structured data; information needs; communicating with data scientists
- Analyzing Data: Statistical basics and probability; descriptive statistics; inferential statistics; cluster analysis; predictive analysis; statistical conclusions
- Making Business Decisions: Application examples; case studies; building your operational data analytics strategy; measuring and monitoring performance; understanding variation as a management tool; scorecards and dashboards.
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Joe Brancaccio is a Process Management Consultant. He has more than 20 years of experience in process management, strategic planning, organizational effectiveness and leadership. Mr. Brancaccio has worked with many Fortune 500 companies and assisted the States of Texas and ... read more
Who Should Attend
- Business analysts
- Systems analysts
- Project managers
- Business team leaders
- Program managers
- Supervisors of business analysts/project managers
Benefits and Learning Outcomes
- Understand bad data and how it leads to bad decisions
- Communicate your needs to data scientists and architects
- Understand descriptive statistics, inferential statistics, predictive analytics and converting statistical conclusions to business decisions
I. Introduction and Overview
- What are business analytics?
- Key questions
- Support structure for success – strategy, people, processes, systems
- Results – what can be achieved?
II. Essentials of Data
- Bad data = bad decisions; how to get “the right stuff”
- Data collection principles
- Avoiding data overload – differentiating “nice to know” from “need to know”
- Communicating with data scientists
- Data deception – manipulation and misinterpretation of averages, percentages, rankings and other basic stats
III. Analyzing Data
- Probability – can we predict the future?
- Types of stats – understand what has happened (descriptive) versus making estimates about what will happen (inferential)
- Predictive analytics
- Understanding variation as a management tool
- Pitfalls of using histograms/bar graphs
- Trend/control charts
- Regression analysis – when and when not to use it
- Finding patterns in data – cluster analysis, stratification and disaggregation
- Decision trees
- Is it all about the data?
- The role of intuition
- Understanding your business
IV. Making Business Decisions
- Converting statistical conclusions to business decisions
- Case studies from various industries
- Scorecards and dashboards
- Application workshops
V. Transforming Classroom into Reality
- Building your operational data analytics strategy
- Barriers to success
- Parting thoughts
This course qualifies you to earn Professional Development Units with the Project Management Institute (PMI). Please contact us to learn how many Professional Development Units you can earn for each PMI credential.
14 CDUs, 14 PDUs, 1.4 CEUs
"Joe was an engaged enthusiastic instructor. He made the material presented in a way that relates to real scenarios!" — Joe Cedzo, Hatco Corporation
"This class content highly met my expectations!" — Sallie Rabe, Children’s Hospital of Wisconsin
All sessions are Face-to-Face unless otherwise noted.