[100% OFF] Data Storytelling: Turn Data into Decisions and Action [EN]

This course contains the use of artificial intelligence.

The most common fate of a good analysis is that everyone agrees with it and nothing happens.

The numbers were right. The charts were clean. And three weeks later the company is doing exactly what it was doing before.

Why correct analysis does not produce decisions

Because a decision needs something analysis alone does not provide. It needs the finding framed as a problem someone recognises as theirs. It needs a cause that has been tested rather than assumed, since the first plausible explanation is usually wrong and always comfortable. It needs one recommendation rather than nine observations. And it needs to be told to a specific audience in the form that audience can act on, which is almost never the form you did the analysis in.

Analysts learn the first half of this job in training. The second half they usually learn by watching their work get ignored.

How the course runs

Thirty-eight lessons following one arc from data to decision. It starts before the data exists: survey design, question types, scales, the response rate problem, and the report and action plan at the end of a survey cycle.

Then the analysis itself. Segmentation, lifetime value and ROI, journey and funnel analytics, attrition analysis and the mistakes almost everyone makes measuring it, key driver analysis, correlations in Excel, multiple regression with R-square and variance, forecasting with trend lines, and experiments with a proper control group.

Then six lessons on critical thinking, which is where you find out whether your conclusion survives contact with a determined sceptic. Deduction and induction, weak arguments, confirmation bias, anchoring, framing, fact against opinion, and decision models including OODA and Cynefin.

Turning the finding into a decision

Then ten lessons of structured problem solving, and this is the part that changes how your work lands. SCQA for framing. MECE and logic trees for breaking it down. 5 Whys and Ishikawa for the cause. Pareto and the decision matrix for prioritisation. TRIZ, SCAMPER and Six Thinking Hats for generating options. And a script for the session where a group turns your analysis into a choice, including how to handle the person who talks over everyone.

The last six lessons are delivery: audience segmentation, personas, message templates, channel choice, communicating findings nobody wants, and measuring whether the message landed.

Who is teaching this

Mike, the number one HR instructor on Udemy. More than 1.6 million course enrolments, over 150,000 professionals trained, PHRi and SHRM-CP certified, HRCI representative in more than 10 countries. I built the people function of the unicorn Preply and worked at Wargaming, Alfa-Bank and iDeals. The analytics examples run on workforce data, because it is the messiest data in most companies and the methods transfer to anything cleaner.

What is included

• Lifetime access to all course materials

• Active instructor support in the Q&A section

• Udemy Certificate of Completion

• Practical assignments and real business cases

• A section with additional courses, tools and resources

How to take it

Bring a real question you have been asked to answer, and work it through the course section by section rather than watching it end to end first. The methods only stick when they are applied to data you care about. Enrol now and start the first lesson today.