Talent Transform: Improve Normalization
Created Date | Feb 1, 2023 |
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Target PI | PI 2 |
Target Release | |
Jira Epic | |
Document Status | Hold Draft Review Committed At RISK |
Epic Owner | @Marla Santos |
Stakeholder | @Mark.Hanson |
Engineering Team(s) Involved | Talent Transform |
PART 1
Customer/User Job-to-be-Done or Problem
The Scope of the user problem should be narrowed to the scope you are planning to solve in this phase of work. There may be other aspects you are aware of and plan to solve in the future. For now, put those in the Out of Scope section.
When [user situation/context/mindset], I want to [user need/goal], so I can [expected result/outcome].
When I create or edit a role in Talent Transform (whether uploaded or manually), I want the automated mappings for Title, SOC, and LOT Specialized Occupation to be driven by all or as much of the information provided with the role so that I can assure that the classifications are the best fit, which then provides the correct comparisons and skill suggestions
Value to Customers & Users
In the JTBD framework, these are the “pains” and “gains” your solution will address. Other ways to think about it: What’s the rationale for doing this work? Why is it a high priority problem for your customers and how will our solution add value?
Lightcast Job Title mapping not just driven off only job title field (and corresponding SOC code)
Decrease in the need to manually update and verify role mappings, especially for those with thousands of roles (time and effort saved)
Reduced need and wait time for consulting to check over roles
Value to Lightcast
Sometimes we do things for our own benefit. List those reasons here.
Improved confidence in Talent Transform product to provide the best automated mappings
Target User Role/Client/Client Category
Who are we building this for?
Clients with Talent Transform
Delivery Mechanism
How will users receive the value?
Built directly in Talent Transform as users create and edit roles
Success Criteria & Metrics
How will you know you’ve completed the epic? How will you know if you’ve successfully addressed this problem? What usage goals do you have for these new features? How will you measure them?
Reduction in events for changed mappings by an actual person
Aspects that are out of scope (of this phase)
What is explicitly not a part of this epic? List things that have been discussed but will not be included. Things you imagine in a phase 2, etc.
PART 2
Solution Description
Early UX (wireframes or mockups)
<FigmaLink>
Non-Functional Attributes & Usage Projections
Consider performance characteristics, privacy/security implications, localization requirements, mobile requirements, accessibility requirements
Dependencies
Is there any work that must precede this? Feature work? Ops work?
Legal and Ethical Considerations
Just answer yes or no.
High-Level Rollout Strategies
Initial rollout to [internal employees|sales demos|1-2 specific beta customers|all customers]
If specific beta customers, will it be for a specific survey launch date or report availability date
How will this guide the rollout of individual stories in the epic?
The rollout strategy should be discussed with CS, Marketing, and Sales.
How long we would tolerate having a “partial rollout” -- rolled out to some customers but not all
Risks
Focus on risks unique to this feature, not overall delivery/execution risks.
Open Questions
What are you still looking to resolve?
Complete with Engineering Teams
Effort Size Estimate |
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Estimated Costs
Direct Financial Costs
Are there direct costs that this feature entails? Dataset acquisition, server purchasing, software licenses, etc.?
Team Effort
Each team involved should give a general t-shirt size estimate of their work involved. As the epic proceeds, they can add a link to the Jira epic/issue associated with their portion of this work.
Team | Effort Estimate (T-shirt sizes) | Jira Link |
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