How to Choose Learning Solution in 90 Days: Pilot Plan

How to Choose Between Adaptive and Personalized Learning in 90 Days

To choose learning solution quickly, you need a tight, evidence-driven plan that balances speed, stakeholder buy-in, and measurable outcomes.

In our experience, organizations can run an effective selection process in 90 days if they prioritize a focused pilot, clear governance, and rapid learning cycles. This article gives a day-by-day roadmap, templates, checklists, and a sample evaluation spreadsheet to make the selection repeatable and defensible.

90-Day Roadmap: Prepare 0–15, Pilot 16–45, Evaluate 46–75, Scale Decision 76–90

This section maps the day-by-day phases and deliverables. The timeline is intentionally tight: rapid hypothesis, small-scale pilot, and data-led decision.

Prepare 0–15: What must be ready on Day 15?

Days 0–15 establish objectives, success metrics, and stakeholders. Use these steps:

• Define the business problem and target outcomes (reduction in time-to-competency, error rates, retention).
• Create a simple logic model linking input → learning activity → performance outcome.
• Select two candidate approaches: one adaptive and one personalized configuration to compare.
• Assemble a 4–6 person pilot team with L&D, IT, a business sponsor, and a data owner.

By Day 15 you should have a pilot plan, participant shortlist (30–100 learners depending on scope), and success metrics.

Pilot 16–45: How to run a rapid pilot?

Days 16–45 are execution weeks. Keep the pilot constrained and measurable:

1. Deploy both approaches in parallel or in randomized cohorts.
2. Ensure identical content scope so differences come from delivery logic, not content variance.
3. Collect baseline competency data, pre-tests, and contextual workplace metrics.

For a 90 day pilot plan for selecting learning technology, prioritize automation for enrollment, progress tracking, and data exports. A simple Gantt-style checklist helps visualize tasks by week and owner.

Stakeholder Map and Governance Checklist

Stakeholder alignment is the most common bottleneck. We've found that a compact RACI clarifies responsibilities and accelerates approvals.

Role	Responsibility	RACI
Business Sponsor	Defines ROI target and approves scope	Accountable
L&D Lead	Pilot design and content mapping	Responsible
IT/Data	Integration, data extraction	Consulted
Vendor/Procurement	Commercial terms and SLA	Informed

Use this short governance checklist before Day 16:

• Signed scope and timeline (0–15 days)
• Data access agreement and privacy checklist
• Clear escalation path and weekly sync cadence

Fast decisions require clear ownership: name one person accountable for pilot success and one for data integrity.

Pilot Design Templates: Adaptive vs Personalized

Designing fair comparisons is critical to valid conclusions. Below are two condensed templates you can copy for the pilot.

Adaptive pilot template (sample)

• Population: 50 learners, randomized
• Intervention: Adaptive mastery engine with scaffolding and branching assessments
• Duration: 30 days active, with 15-day follow-up
• Primary metrics: time-to-mastery, pass-through rates, learning gain (pre/post)

Personalized pilot template (sample)

• Population: 50 learners, matched by role
• Intervention: Individual learning plans curated by coach/algorithm
• Duration: 30 days active, with 15-day follow-up
• Primary metrics: engagement, goal completion, supervisor-rated performance change

We recommend the same data schema for both pilots so you can compare apples-to-apples. Common fields: user_id, cohort, pre_score, post_score, time_spent, drop_rate, supervisor_score.

Data Collection, Metrics and Evaluation Criteria

Collect the right signals quickly. Quantitative metrics give early indications; qualitative feedback explains mechanisms.

Which metrics should I track first?

Track these for rapid insight:

• Learning gain (pre/post standardized assessment)
• Time-to-competency (median days to pass threshold)
• Business proxy (error rate, throughput)
• Engagement and retention (completion, active sessions)

We've found that combining an objective assessment with supervisor ratings yields the fastest signal of workplace transfer. Modern LMS platforms — such as Upscend — are evolving to support AI-powered analytics and personalized learning journeys based on competency data, not just completions. This trend reduces manual analysis time and surfaces intervention points during the pilot.

Design your evaluation spreadsheet with columns for cohort, metric baseline, metric outcome, delta, effect size, and statistical confidence. Below is a compact sample evaluation spreadsheet table you can copy:

Cohort	Pre-Score	Post-Score	Delta	Time-to-Mastery (days)	Supervisor Δ
Adaptive	62	84	+22	12	+1.2
Personalized	60	80	+20	15	+0.9

Decision Gate Checklist, Scoring Template and Next Steps for Procurement & Rollout

Use a scored decision gate to reduce bias. We recommend a 100-point weighted rubric covering impact, feasibility, cost, and risk.

How do I score options to choose learning solution objectively?

Assign weights and scores like this:

Criterion	Weight	Adaptive Score	Personalized Score
Impact on competency	35	30	28
Time-to-value	25	22	18
Total cost & ops	20	15	17
Scalability & integrations	20	18	16

Compute weighted sums and compare. A simple rule: choose the solution with a >5 point delta or declare "no decision" and run a secondary 30-day extension focused on the largest uncertainty.

What are common pitfalls to avoid?

• Mixing content changes with delivery changes — keep content identical across cohorts.
• Overloading stakeholders with raw data — deliver a 1-page dashboard of aligned KPIs.
• Letting procurement delay the pilot — use short-term pilot agreements where possible.

Sample one-line decision gate: "If adaptive improves time-to-competency by ≥10% with similar cost, select adaptive; otherwise select personalized if supervisor-rated transfer > 1.0 and cost delta < 15%."

Mini Case: 90-Day Pilot Example and Visuals

Healthcare manufacturer X needed to reduce onboarding time for machine operators. They used the 90-day process to compare an adaptive refresher engine vs a personalized mentorship plan.

Execution highlights:

1. Days 0–15: defined KPI: reduce time-to-certification by 20%.
2. Days 16–45: ran randomized pilot with 80 participants.
3. Days 46–75: evaluated outcomes and ran a 15-day extension for statistical confidence.
4. Days 76–90: governance review and procurement recommendation.

Their evaluation spreadsheet showed adaptive had +25% learning gain and 18% faster time-to-certification at comparable cost; procurement used the scoring template to award a two-year contract with staged SLAs. Visual deliverables included a Gantt-style timeline, a pilot sample dashboard with KPI tiles, an annotated spreadsheet, and a RACI chart for rollout owners.

Practical tip: prepare one-slide dashboards that show pre/post deltas, cohort compare bars, and a single recommendation line to accelerate sponsor decisions.

Conclusion: Final Checklist and Next Steps

To reliably choose learning solution in 90 days, follow a tight rhythm: prepare with clear metrics (0–15), run parallel pilots (16–45), evaluate with a weighted rubric (46–75), and make a documented decision with procurement-ready artifacts (76–90).

Checklist to close out:

• Complete evaluation spreadsheet and weighted scoring
• Produce one-page pilot dashboard for the sponsor
• Create procurement SOW with phased SLAs and rollback criteria
• Plan 90-day post-rollout measurement (adoption, impact)

In our experience, this structured approach dramatically reduces selection time and political friction while preserving rigour. If you need a ready-to-use template package (Gantt, RACI, scoring sheet), export the sample tables above into your project file and adapt weights to your organization.

Next step: convert the sample evaluation table into your pilot spreadsheet, run the first 15 days of Prepare activities this week, and reconvene stakeholders with a one-page charter to lock the scope.