Parker Lee · Instructional Design

Five-Phase ID Framework

01
Discover
Verify the problem before designing any solution

Questions I won't skip

  • 01What behavior is missing or wrong — observable, on the job?
  • 02What happens when someone gets it wrong? What's the real cost?
  • 03Who decided this is a training problem — and did anyone push back?
  • 04Can you show me what expert performance looks like, or introduce me to someone who does it well?
  • 05Is the gap in knowledge, skill, or environment — process, tools, management clarity?
  • 06What would change if training worked perfectly? Would you see it in a metric?
  • 07What do learners already know? What's their context coming in?
  • 08What's the real timeline, and is it realistic for the scope being described?

SME action-mapping script

  • →Ask what experts do, not what they know
  • →"Walk me through the last time this went wrong — specifically."
  • →"What would a great performer do at this decision point that a novice wouldn't?"
  • →Push vague answers: "What does that look like on the floor?"

AI + this phase

✓ Can help

  • Draft SME interview questions
  • Pressure-test the brief
  • Flag non-training problems

✕ Can't replace

  • The actual SME conversation
  • Org and culture context
  • Training vs. process judgment
02
Design
Pick the right modality. Structure before building.

Modality decision guide

Rise 360Async, self-paced knowledge transfer — onboarding, compliance, product content. Use when completion tracking matters.
StorylineBranching scenarios, scored simulations, complex interactions. Use when skill practice and realistic consequence matter.
HTML / codeLightweight reference tools, embeddable job aids, sales enablement. Faster, more accessible, easier to update.
BlendedComplex judgment calls, culture-shaping, sensitive topics. If the live debrief is the point, don't async your way out of it.
Job aidPure reference — process steps, checklists, decision trees. Never needs a quiz. If they need to memorize it, it's not a job aid.

Scenario structure

  • →Realistic trigger — not "imagine you are a rep..."
  • →Choices that aren't obviously right or wrong
  • →Realistic consequences — not just "try again"
  • →Debrief that explains, not just reveals the answer

AI + this phase

✓ Can help

  • Scaffold scenario text fast
  • Draft and critique objectives
  • Suggest modality given constraints

✕ Can't replace

  • Knowing your learners' context
  • Culture that makes scenarios real
  • Domain accuracy — SME review required
03
Build
Pre-build discipline prevents expensive rework

Pre-build

  • →Storyboard before opening Storyline or Rise
  • →Content QA with SME before build — not after
  • →Lock final brand assets before building
  • →Scope in writing — verbal agreements disappear

Build cadence

  • →Pilot section first — QA one piece before building everything
  • →Narration: script → record temp → record final
  • →In Storyline: master slides before content slides
  • →Test every branch, especially failure paths

Polish checklist

  • →Read every word aloud — awkward phrasing reveals itself
  • →Test on the device learners actually use
  • →One SME review pass on final content only
  • →Check accessibility: tab order, alt text, contrast

AI + this phase

✓ Can help

  • Draft narration scripts
  • Flag corporate-sounding language
  • Suggest alternatives for awkward phrasing

✕ Can't replace

  • Domain accuracy QA
  • Never skip the SME content review
04
Deliver
Manager prep is the most skipped, most impactful step

Launch sequence

1Pilot with 3–5 real learners — not leadership, not L&D. Track time-on-task and confusion points.
2Adjust based on pilot. Completion time, drop-offs, and qualitative quotes beat survey scores.
3Manager brief before learner launch: what's coming, why it matters, what to reinforce.
4Launch email: one sentence on why this matters to them, not to the company.
5Completion deadline: visible, specific, reasonable. "By end of quarter" is not a deadline.

Manager one-pager

  • →What the training covers (2 sentences max)
  • →3 questions to ask in a 1:1 after completion
  • →What good performance looks like in 30 days

AI + this phase

✓ Can help

  • Draft launch communications
  • Write the manager one-pager
  • Summarize pilot readout data

✕ Can't replace

  • The manager conversation
  • Advocacy from the right sponsor
05
Measure
Evaluation is a design constraint, not an afterthought

Kirkpatrick L1–L4

L1 · ReactionSurvey at end, 3–5 questions. Useful for spotting confusion. Not evidence of effectiveness.
L2 · LearningKnowledge checks in-course. If you're not adjusting design based on failure rates, you're not using L2 data.
L3 · BehaviorObservation or manager report 30–90 days post. Requires manager pre-commitment before launch.
L4 · ResultsBusiness metric change. Only promise if you have a clear, defensible causal path — attribution is almost never clean.

When L3/L4 attribution is credible

  • →You have a pre/post baseline on the metric
  • →You control for confounds: market, leadership, headcount changes
  • →Training was the only meaningful intervention in the window

AI + this phase

✓ Can help

  • Draft L1 survey questions
  • Suggest L3 behavioral indicators
  • Design evaluation canvas with sponsor

✕ Can't replace

  • Collecting the actual data
  • Causal attribution — that's a business call