Gap assessmentBusiness Process MappingKPIsData CollectionData-Driven Decision MakingData visualization toolsData storytellingData analysis toolsStatistical process control (SPC)ISO 9001: 2015LeanDesign of Experiments (DOE)
Data-Driven Decision Making (DDDM) Specialization
Make better organizational decisions. Improve the bottom line by viewing issues from a data perspective
Offered By
University at Buffalo
The State University of New York
Data-Driven Decision Making (DDDM) SpecializationUniversity at BuffaloWhat you will learn
Identify gaps in data collection processes needed to drive improvements
Compare and contrast data analysis and visualization tools for generating metrics dashboards
Define techniques to validate performance metrics and data integrity
Prepare and present multiple examples of data-driven decision making
Skills you will gain
About this Specialization
This specialization explains why it is important to leverage data when contemplating organizational choices, and supplies the tools at the heart of data-driven decision making (DDDM). The three-course series explores how technology enables the collection and organization of unprecedented amounts of data, and how to dissect that data to gain powerful insights. Course topics include analyzing process maps for driving improvement, software for maximizing data analysis, statistical process control, creating metrics dashboards and translating data stories, and the connection between operations technology metrics and organizational performance. Content touches on leadership’s role in instituting an internet of things (IoT) strategy in manufacturing and service environments. Lessons feature case studies highlighting ROI achieved through DDDM, and the cultural changes required for success.
To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=Oi4mmeSWcVc&list=PLQvThJe-IglyYljMrdqwfsDzk56ncfoLx&index=11.
Applied Learning Project
Each course concludes with a project whereby learners apply DDDM theory to real-world scenarios, while concurrently considering implications for their own organizations. Projects may lead to measurable improvements in quality, cost, efficiency, operational flexibility, capital investments, time-to-market, customer satisfaction, or other key performance indicators.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations.
Approximately 3 months to complete
Suggested pace of 3 hours/week
English
Subtitles: English
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations.
Approximately 3 months to complete
Suggested pace of 3 hours/week
English
Subtitles: English
There are 3 Courses in this Specialization
Data-Driven Process Improvement
8 ratings
By the end of this course, learners are empowered to implement data-driven process improvement objectives at their organization. The course covers: the business case for IoT (Internet of Things), the strategic importance of aligning operations and performance goals, best practices for collecting data, and facilitating a process mapping activity to visualize and analyze a process’s flow of materials and information. Learners are prepared to focus efforts around business needs, evaluate what the organization should measure, discern between different types of IoT data and collect key performance indicators (KPIs) using IoT technology. Learners have the opportunity to implement process improvement objectives in a mock scenario and consider how the knowledge can be transferred to their own organizational contexts.
Data Analysis and Visualization
8 ratings
By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story.
Applied Analytics and Data for Decision Making
By the end of this course, learners are prepared to identify and test the best solutions for improving performance and integrating concepts from operational excellence methodologies for optimum data-driven decision making. The course begins with a focus on deciphering the root cause of problems through a variety of tools before determining and assessing best-fit solutions. Learners discover how to apply ISO, Lean and Six Sigma in the pursuit of aligning organizational operations data with performance standards. Hospitality, manufacturing and e-commerce case studies help illustrate how to build data literacy while ensuring privacy and data ethics measures are in place.
Offered by
University at Buffalo
The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs.
The State University of New York
The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe.
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