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.

JTBD1: When looking at local talent, I want to understand what graduates from local schools (in recent years) are staying/leaving, so I can target efforts to retain needed talent.

JTBD2: When looking at IRS migration data, I want to understand more broadly the way individuals are migrating. What states are they moving to? What Metropolitan areas? And then what counties? (Covered in https://economicmodeling.atlassian.net/wiki/spaces/DPM/pages/2486075512 )

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?

• IRS Migration data is (a) 2 years old, (b) has limited detail in the data. However, customers like this information.

• IRS Migration data is currently only displayed at county-to-county. This is far too specific for providing a broad understanding

• Community consulting has sold this community-wide education migration data directly

Value to Lightcast

Sometimes we do things for our own benefit. List those reasons here. 

• MSA to MSA migration data is sold to our customers by one of our competitors. We can provide this easily.

• Enhances our use of profile data

• Provides data for consulting to use more easily

• Enables us to distinguish ourselves in terms of migration

Target User Role/Client/Client Category

Who are we building this for?

• Community-based organizations

• Regional governments and partners

Delivery Mechanism

How will users receive the value?

• Via Analyst platform

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?

• Overall usage of migration will increase by 20%

• Consulting clients (ie Virginia) will begin to use this rather than contacting consulting

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.

• Migration based on skill/occupation/etc

• Broader professional migration data which needs to be taken into context with IRS data

Solution Description

Early UX (wireframes or mockups)

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Non-Functional Attributes & Usage Projections

Consider performance characteristics, privacy/security implications, required copy translations (mostly surveys), mobile requirements, accessibility requirements

• Same privacy concerns as any profile-based data. Possible to get to individuals

Dependencies

Is there any work that must precede this? Feature work? Ops work? 

• Data parts of https://economicmodeling.atlassian.net/wiki/spaces/DPM/pages/2486141701 :Need to have graduation year associated with program and school exposed in data and API

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. 

• There is a slight chance of overlap with AO 2.0 needs. Goal is to stay focused on regional migration without ability to delve into individual institutions and their alumni in order to not step on Alumni Outcomes 2.0 business case.

We need to remain clear that profile data is used for 3 distinct use cases, with distinct customer utility and revenue implications

1. Profile Analytics:

   1. Delivery Mechanism: Analyst Platform for users who select.

   2. Goal: expand to all users

   3. What it is: Profile Analytics provides a proxy for supply data. Users of Profile Analytics can explore the scope of talent within their region, including what occupations people work in, what skills they have, where they went to school. Should be used in conjunction with demand data from postings and LMI to provide a full picture of a local labor market. Can be used for:

      1. sourcing talent

      2. assessing regional talent gaps

   4. Base data set: Profiles segmented by location of individual

2. Regional Educational Migration:

   1. Delivery Mechanism: Analyst Platform

   2. Goal: All Community users accessing it

   3. What it is: Regional Educational Migration is a dataset that enables communities to understand (a) what graduating talent they are losing to other regions/gaining from other regions, (b) view the aggregate profiles of who is moving. This data is used for making strategies on how to best increase the local talent supply - by targeting regions to recruit from, and by understanding what local talent should be targeted for retention strategies.

   4. Base data set: Profiles segmented by location of education institution attended.

3. Alumni Outcomes

   1. Delivery Mechanism: Analyst Platform and Consulting deliveries (prior to AO 2.0)

   2. Goal: Turn into ARR for education customers

   3. What it is: See broader AO 2.0 documentation, but short version: ability to track graduates of an individual institution for marketing, alumni relations, etc.

   4. Base data set: Profiles segmented by specific institution with matching provided to those specific institutions

Estimated Costs

Likely engineering will need to help with this section. “I’m not sure” is acceptable here.

I’m not sure. Generally:

• The data exists on the data, so estimate is low lift for the data team

• A lot of reuse of packets/visuals for Analyst team.

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.

Open Questions

What are you still looking to resolve?