BB notes: this is mostly work that we know, but there are extra moving parts because of the scale of the taxonomy changes.

• July 10 due date is the date communicated externally for 2023.3 datarun

• OEWS data is late and will not be part of 2022.2, increasing the pressure that we are not late for 2023.3

• The more we can parallelize some work on field names, etc while the Taxonomy team handles updates to Acme, the better.

PI 4 Definition of Done: Delivery by July 17

• Note: delivery date is one week after published expected delivery date. Plan to communicate new expected date before the start of PI 4.

PART 1

Customer/User Job-to-be-Done or Problem

When using Lightcast data, I want all datasets to use the same industry taxonomy, so I can make appropriate cross references, and make good decisions about the regions, industries, or companies I am comparing.

Value to Customers & Users

Federal statistical agencies use NAICS when publishing statistical data related to the U.S. business economy. Our data needs to align, otherwise clients will be forced to crosswalk from one taxonomy version to another. This is therefore a “need to have”.

Value to Lightcast

See above - Most US clients will regard this as a “need to have”.

Target User Role/Client/Client Category

All US clients who use industry data or access our data using industry specific filters.

Delivery Mechanism

All data delivery channels and apps.

Success Criteria & Metrics

All data outputs reliably using updated NAICS codes to a level of accuracy and precision not lower than current standards.

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)

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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.