Online series provides insights in leveraging data for decision making

BUFFALO, N.Y. – It’s one thing to understand your organization’s level of profitability, but it’s quite another to pinpoint which products or services have the best profit margins or could be prime candidates for a tweak in pricing structure.

That is one potential difference between an organization that pays little attention to leveraging its data, and one that deliberately makes the effort. A new online course series from the University at Buffalo guides learners toward becoming data driven, by teaching them critical concepts of how to harness the wealth of organizational information generated each day.

The three courses of Data-Driven Decision Making (DDDM), produced by the UB Center for Industrial Effectiveness (UB TCIE) in collaboration with Freed Maxick CPAs, focus on how to collect and dissect data analytics to improve the bottom line of an organization, both large and small.  

“An organization that’s more data driven is making more precise changes, identifying opportunities faster, and bringing them to market faster, rather than one relying just on instinct,” says Dan Gerena, principal of the Business Intelligence Practice at Freed Maxick CPAs.

Gerena appears in the series as a special guest sharing his expertise and insights. Otherwise, courses are facilitated by Peter Baumgartner, UB TCIE director of operational excellence; Akshay Sivadas, UB TCIE project engineer; and Brittany O’Dea, senior business intelligence analyst at Delaware North.        

The series examines the convergence of operational technology and information technology, preparing learners to devise and implement a robust data strategy aligned with organizational goals.

“By using actual live data, DDDM provides an enterprise’s management with insights to expand and grow the business by maximizing capital expenditures, optimizing supply chains, and properly utilizing a trained workforce,” says Timothy Leyh, executive director of UB TCIE.

Available on the Coursera platform, the three courses are:

• Data-Driven Process Improvement: introduces the strategic importance of aligning operations and performance goals, current and future state process maps, and collecting key performance indicators using the Internet of Things (IoT) technology
• Data Analysis and Visualization: presents common hurdles that obstruct adoption of a data-driven culture, standard data analysis and visualization software tools, and statistical process control
• Applied Analytics and Data for Decision Making: covers concepts from operational excellence methodologies – including ISO, Lean and Six Sigma – for optimizing data-driven decision making

Material consists of 5- to 10-minute video lesson learning sprints, demos, hands-on exercises, readings and discussions. Each course concludes with a project, with the potential to result in measurable improvements in quality, cost, efficiency, operational flexibility, capital investments, time-to-market, customer satisfaction or other key performance indicators.

Gerena explains that together, the courses help cultivate a DDDM mindset that starts with understanding data in the context of business operations and grasping statistical methods to avoid skewed interpretations.

“Finally, the ability to take data and convert it into information is obviously the goal,” he says. “The larger point is to tell a story – what’s really happening based on what the data is showing.”

Learners may sign up for individual courses or the complete series. There is no charge to “audit” a course, which includes videos, readings, community discussion forums and the ability to view assignments. The fee to gain complete course access – which includes submitting all assignments for feedback or a grade, and the opportunity to earn a certificate for the complete series – is $49 per month.

The Data-Driven Decision Making courses join 22 others created and produced by UB TCIE and available on Coursera. Topics include digital manufacturing and design, blockchain technology, energy, collaborative robot safety, computer vision and solar energy.