“Mathematical and logical truths are true of an ability to connect ideas outside of our senses” – Thomas Cagley. A small glimpse from this thought-provoking class on setting smart goals for testers. A session that answers some unbounded questions like; do we need to set goals? If so, how are they attainable? What are heuristics, and are they good or bad or both? Let’s dive in to know.
Our guests on this episode:
They are two intelligent personas from the testing industry. Our first presenter is Thomas Cagley, President at Tom Cagley & Associates. Apart from his ravishing career, Thomas is also an author, blogger, and podcaster. You can listen to him speaking on how to set smart goals for testers.
Next is Mr. Prashanth Hegde, QA Lead at MoEngage Inc.Prashanth is a passionate tester and an earnest writer with several published blogs in different magazines. He would be emphasizing on the Heuristics – how our minds work. He’ll explain to us how.
Show Notes
[3.18]
How many goals do you currently have? (current 3 top goals).
[8.44]
What goals are you pursuing?
[10.36]
Typical organizational goals are cross-code.
[11.33]
Targeting goals for testers.
[14.23]
One or the other is bad.
[16.17]
Big hairy audacious goal: unsmart?
[17.49]
Specific, measurable, attainable, realistic time-bound goals.
[20.47]
Bad, unclear, and smart goals.
[23.26]
Focus areas while selecting or setting goals.
[23.37]
Systematic problems with goal and goal setting.
[27.27]
Goals checklists.
[39.58]
Some tips for sharing some to include smarter goals in OKRs.
[47.32]
Thinking fast and thinking slow.
[50.13]
What are heuristics? (Mental shortcuts)
[55.45]
Goldilock, too big, too small, and just right.
[59.38]
Develop your own heuristics.
[1.03.46]
The seven principles of software testing.
[1.04.02]
Mnemonics – a memory aid.
[1.04.47]
Popular heuristics using mnemonics.
[1.05.40]
Beware heuristics can lead to cognitive, stereotypes, and prejudice.
[1.09.47]
Anchoring bias.
[1.11.44]
The gambler’s fallacy, premature closure, the bandwagon effect, similarity bias, confirmation bias, and authoritative bias.
