1.1 Demand (what companies need—and why they’re not getting it yet)

1) Faster onboarding and shorter Time-to-Productivity

What we need: junior hires moving from “shadowing” to real work in weeks, not months.
Why it’s hard today: long, linear courses don’t fit the workday and don’t translate into action. Leaders are shifting to learning in the flow of work and short, connected bursts that solve immediate problems without derailing execution. learning.linkedin.com

Visual: line chart “Time-to-Productivity — before vs after micro-routes” (8–12 weeks horizon).

2) Evidence of competence (not just “course completed”)

What we need: proof that a person can do a task in context—event-level evidence rolling up to a skill profile and a certificate we can trust.
Why it’s hard today: most LMS track completions and quizzes, not behavioral signals tied to real decisions. The market is moving toward skills-based approaches and measurable outcomes—execs expect learning to drive retention, mobility, and performance, not vanity metrics. learning.linkedin.com

Visual: simple pipeline Event Log → Competency Vector → Verifiable Certificate (QR).

3) Learning that fits the day (micro + in-flow)

What we need: modules in 200–500 words, 1 action, instant feedback—exactly when and where the task appears.
Why it’s hard today: attention is fragmented (email, meetings, chat). L&D is explicitly pivoting to microlearning/nanolearning and in-flow experiences as the default pattern, not an add-on. learning.linkedin.com

Visual: “workday attention heatmap” with micro-learning pulses between meetings.

4) Durable retention (not one-off exposure)

What we need: people to keep knowledge under pressure and across contexts.
Why it’s hard today: big content drops + single-context practice fade quickly. What works: short, frequent re-engagements and context switching (revisiting a topic via a different role/constraint) to make recall automatic. (See LinkedIn WLR guidance on micro-/nano-learning and in-flow repetition trends.) learning.linkedin.com

Visual: 3-step “reinforcement loop” where the same concept reappears in a new micro-case.

5) Scale across domains and roles

What we need: one engine that adapts to EPC, HSE, Operations, PM, Sales Ops—without custom-coding each simulation.
Why it’s hard today: most “simulators” are bespoke and expensive; many LMS/LXP vendors bolt simulations on top of a content warehouse, making route control and behavioral analytics second-class. Enterprises are evaluating platforms under the broader corporate learning technologies category but still struggle to get route-first, data-first architectures. gartner.com+1

Visual: core route graph (nodes/edges) with pluggable content “layers” on top.

6) From compliance to performance

What we need: compliance boxes ticked and observable improvement in capability (speed, accuracy, safety, quality).
Why it’s hard today: legacy stacks optimized for tracking mandatory training, not for capability building in a boundaryless, project-based reality. 2024 Human Capital Trends push organizations toward skills and human performance as the operative currency. image.marketing.deloitte.de Deloitte United Kingdom

Visual: 2×2 “Compliance ↔ Capability” with the desired quadrant = High/High.

7) AI-era upskilling (at hiring speed)

What we need: rapid, repeatable AI-aptitude building—so non-technical roles can use gen-AI tools safely and productively.
Why it’s hard today: employees have already run ahead—75% of knowledge workers use AI at work; leaders say AI skills are becoming a hiring filter, yet most companies haven’t built internal training paths or ROI models. This gap is widening every quarter. Microsoft

Visual: “AI Skills Radar (12–24 months)” with segments like data handling, prompt craft, judgment/controls, safe ops.

What this means for a CFO/CHRO right now

Shift funding to short, connected, in-flow experiences that cut Time-to-Productivity. learning.linkedin.com
Require event-level telemetry → skills profiles → verifiable credentials to justify spend. learning.linkedin.com
Treat AI-aptitude as a horizontal skill and build internal skilling at pace with hiring. Microsoft

Sources you can hand to the board

LinkedIn Workplace Learning Report 2024 — micro/nano-learning, in-flow learning, business outcomes from strong learning cultures. learning.linkedin.com
Microsoft x LinkedIn Work Trend Index 2024 — 75% of knowledge workers use AI at work; leaders’ hiring stance on AI skills. Microsoft
Deloitte Global Human Capital Trends 2024 — boundaryless work and the shift toward human capabilities & skills-based orgs. image.marketing.deloitte.de Deloitte United Kingdom
Gartner market context — where corporate learning technologies sit in the stack (helps explain why most stacks are content-first vs route-/data-first). gartner.com+1