Learning Products for Brokerage

01The strategy

Learning Products for Brokerage

Any Way In.
One Consistent Experience.

Three product tracks. Support in the work. Managers involved.

Dr. Shika Mahdavi
Director, Learning Products interview | Fidelity Brokerage

The shiftFrom service delivery to product ownership

Requests fulfilled one at a timeA managed portfolio of learning products

Courses and workshops firstSupport inside the work first

Completions and attendanceProficiency and business results

Content that ages in placeOwned, reviewed, and retired on schedule

Principle: keep the relationships, standardize the experience.

The operating modelSelect a step to preview

A proposed approach built from conversations with Rachel and Jeff. Select a step to preview how it runs.

02Operating model

A product operating model for a three-person team.

Director

Product owner for the portfolio

Business alignment
Portfolio and roadmap decisions
Stakeholder relationships
Team coaching
Outcome reviews

Designer and architect

Two roles. Assignments to confirm with the team.

Performance discovery
Reuse decisions
Solution and UX design
Prototyping
Evaluation planning

Implementation specialist

Runs releases and records

Release coordination
Resource organization
Review tracking
Adoption reporting

Business partners and experts

Own accuracy and context

Accuracy
Operational context
Source updates
Validation, with compliance involved where appropriate

Portfolio priorities and roadmapDirector, with Rachel
Accept, redirect, defer, or declineTeam, using shared criteria
Design and release of productsLearning team
Content accuracy and sourcesBusiness experts and compliance
Manager practicesJen, with our design support
Enterprise courses and certificatesEnterprise teams; we link and apply

Proposed. Decision rights and measures of success to set with Rachel in the first 30 days.

Build team capability through live work

Open any practice

1Review real requests together

Each week we walk through two or three live requests. What was asked, what the business needs, and what we would recommend. Shared judgment grows from work the team already knows well.

2Practice consulting conversations

Short practice rounds on the hard moments: a leader asks for a course, the cause looks like process, or we need data the partner has not shared. Real phrasing, direct feedback, and I take a turn too.

3Calibrate accept, redirect, and decline decisions

Each of us scores the same request on our own, then we compare. Where we differ, we talk through why. Over time partners get the same answer no matter who they spoke with first.

4Pair on early prototypes

Rough versions go in front of a few users early. I pair with the designer and architect on what to test and what to drop. The craft stays central. The change is reaching a usable draft sooner.

5Build product habits

Each product gets a one-page brief: the user, the problem, the measure of success, and the owner. Product management and UX practices become part of how the team works, not a separate skill set.

6Review evidence of application after launch

A few weeks after a release, we look at whether people used it in the work, what managers saw, and what we would change. It is a learning review for the product, not a review of the person.

Impact scales through choices.Prioritization, reuse, and partner ownership create capacity before any case for headcount.

03Consistent consulting from any entry point

Ask once. Diagnose together. Agree on the next step.

Keep the relationships. Standardize the experience. No new platform required.

Rachel

Melissa

Amanda

Other partner conversations

One shared request record and one consulting approachKept in tools the team already uses

Select a stage to see how it works. Any entry point leads to the same four stages.

AI can

Summarize an approved request or conversation
Extract the desired outcome and audience
Identify missing information
Suggest follow-up questions
Surface related existing resources when approved access permits

People

Verify facts
Diagnose causes
Assess priorities
Agree on ownership
Make commitments

Approved tools and appropriate data handling only. AI works with what it is permitted to access.

04The learning product portfolioProposed tracks

Three tracks built around business priorities.

Four overlapping audiences: Brokerage employees, product and digital teams, Digital Assets teams, and leaders and managers. Managers are an audience and a partner in every track.

Track 1

AI at Work

Partner: Melissa
Audience: Brokerage employees

FoundationsResponsible use, approved tools, and data rules
AppliedRole-based use cases, examples, and prompt guidance
ChampionsPeer practice and shared examples

Proposed outcome
Use approved AI tools effectively in everyday work.

Track 2

Product Excellence

Partner: Amanda
Audience: Product and digital teams

CoreConnect people to existing product management learning where available
CraftPractical UX and research support
ApplicationReview preparation, checklists, and coaching tied to real work

Proposed outcome
Apply product practices to better decisions and reviews.

Track 3

Digital Assets Readiness

Partner: Melissa and relevant business experts
Audience: Digital Assets teams

OnboardRole-based onboarding milestones
RefreshTax season, staking, and product-change refreshers
ExpandNorway and MiCA readiness resources validated by appropriate experts

Proposed outcome
Prepare teams for changing roles, products, and markets.

Manager support, partnered with Jen

Attached to existing manager onboarding and coaching practices. Not another leadership program.

05The knowledge hub and microlearning libraryWithin existing approved tools

Useful at the moment someone needs it.

Delivery order

1Answers and job aids
In the moment, at the task
2Short learning
When explanation is needed
3Practice and coaching
When application is needed
4Live sessions
When interaction warrants the time

Microlearning runs under five minutes and covers one task, decision, or skill. Not every answer is a video or a course.

Design principles

Built around a task
Plain language
Tested with real users before release

Learning hub | prototypeIllustrative content. Owners and review dates are placeholders.

Search by task

Track

Audience

Resource type

6 of 6 resources

06Keep it current and check results

Every resource needs an owner and a reason to stay.

Ownedsource, date, trigger, retire rule

Create or reuse

Search first. Reuse or adapt existing material, including enterprise learning. Build only what is missing, as the smallest useful unit.

Every resource needs

Named ownerA role accountable for accuracy, named before release
Authoritative sourceThe one place the facts come from
Review dateSet by how fast the topic changes
Update triggerThe events that force an early review
Retire ruleWhen it comes down, so old guidance does not linger

Update triggers

Select a trigger to see what happens.

AI roleMay flag possible conflicts or draft updates where approved. A qualified person validates every change before publication.

Business evidence: time to proficiency and operational performance are outcome measures. Hub use, manager coaching activity, and intake speed tell us whether the system is working. Activity alone does not establish performance improvement.

07Roadmap

First 90 days: set the operating model, then prove it with one release.

Actions

Meet each team member one to one
Meet Rachel, Jen, key partners, Line HR, and the enterprise teams
Review existing resources and recent requests
Learn the approved tools and data rules

Outputs

Map of current resources and owners
List of open requests
Short summary of partner priorities

Decisions

Agree on one measurable business problem to start with
Draft ways of working, decision rights, and measures of success with Rachel

What I need to learn first

Where requests come from today
What the team does best
What Client Services learning and the enterprise teams already cover

At day 90

One intake standard in use, whoever takes the request
Portfolio view with a stage, owner, and measure for each product
Decision rights and measures of success agreed
One product released in one track, with manager support
Early evidence reviewed and the next release chosen

The first track is chosen with Rachel based on the business problem we agree on.

Track record, Charles Schwab

25Courses in an award-winning Service and Operations Academy

~25%Faster time to proficiency

15-20%Better frontline operational performance

CoachManager coaching certification and performance scorecards

AIKnowledge hub for performance support

Closing

My first 90 days: understand the work, align the team, and prove the approach with one useful release.