Work To Be Done

Ensuring the accuracy of the data is paramount. Inaccurate data can lead to flawed conclusions and ineffective decision-making. For the SkillScape product, inaccurate data can result in biased or unfair recommendations/assumptions, which can harm underrepresented groups.

This is why an collaboration amongst teams has been assembled between Community Applied Research, Analyst Team Yellow, and Models to verify the accuracy of the data.

• Data Validation: Statistical methods and validation techniques to check the consistency and accuracy of the data with applied research team.

• Data Source Assessment: Assess the credibility and reliability of data sources, and consider diversifying sources to cross-verify information.

• Data Cleaning: Remove duplicates, outliers, and erroneous entries from your dataset to improve data quality.

• Ethical Considerations: Ensure that data collection and processing align with ethical standards, privacy regulations, and DEI principles.

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 assessing SkillScape reports, I want to easily understand which occupations are over and undersupplied, so I can develop the right programs, target correct initiatives, etc

 When preparing for a major economic development investment, I want to understand the projected supply of candidates to fill necessary roles so I can partner regionally to build the pipeline of talent needed to fulfill the goals. I want to assess current plans/educational pipeline to determine where I am likely short of the target so I can properly invest to build the correct workforce.

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?

• Data accuracy for the SkillScape product MVP

• Users and stakeholders must trust the data and insights provided by product. If data is not verified, it may lead to skepticism and reduced confidence in the system, hindering its adoption and impact.

• Unverified data can introduce biases, inaccuracies, or disparities that counteract the very goals of SkillScape. Ensuring data accuracy is vital for maintaining fairness throughout the talent diversification process.

• Verifying data helps you comply with data privacy regulations and ethical guidelines, protecting individuals' rights and privacy.

• Relying on unverified data poses risks, such as legal liabilities, reputation damage, or financial losses. Verification helps mitigate these risks by ensuring data integrity.

Definition of Done

• Re-working the model to address feedback

• Pressure test pipes and data to foster long term success

Value to Lightcast

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

• Pressure test data to be used within other product

• Accurately display Supply & Demand data

• Cross collaboration amongst teams

Target User Role/Client/Client Category

Who are we building this for?

• Analyst customers (see above)

• API customers

Delivery Mechanism

How will users receive the value?

• APIs

• Snowflake

Future: Analyst

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?

• we are able to provide specialized occupation level supply/demand ratios at the MSA level

• Improvements in quality of S/D estimates through analysis and evaluation, and get to an MVP stage

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

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.