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

When I want to research skills in the Analyst platform I want to do that in a report on skills, right now I have to back into the skills data I want by running reports on programs or job postings.

As a user, I need more information about skills and your only skill-specific workflow only shows me what skills have increased or decreased over a certain timeframe.

• As a user, I want to understand the relationship between occupations and skills more robustly. I want insight not only into what skills are being requested, but which ones are most important to learn to enter or advance in a given occupation.

• As a user, I want to know what skills increase the salary of an occupation, so I can direct training toward high-value skills.

• As a program developer, I want to understand what skills will be in demand in 2 years, in addition to the skills in demand today.

• Tell me everything about a skill, in a traditional Analyst way

• Given a program I’m teaching, what are the most important skills that I should be teaching to align with a range of occupations as potential outcomes?

• Given a skill, tell me how much more hirable I am in the workforce?

Learner/earner-focused:

• Given a skill that I’m learning, help me understand what else to learn to get the job I want

Value to Customers & Users

• Decreased research time:

  • Making sense of lists of “frequently requested” skills is challenging when creating a program, understanding an occupation, or comparing different roles. The top skills are very often repeated, and don’t provide insight into the true importance of a skill to a job. D/D/N skills provide this insight

  • There is no single place to view a skill, and understand its place in the labor market. Today, Analyst would require running several reports to truly understand what value skills bring to a range of occupations. This shortens that time in the tool

• Better decision making: Similar to above, but:

  • DDN skills help customers understand the skills to teach together for target occupations. Rather than a list of 40 skills, they provide true insight into the skills the define a role, helping hone in on the needed roles (perhaps for microcredentials?). Similar targeting can be done for distinguishing skills to help move students/employees ahead within occupations

  • Understanding salary boosting skills enables customers to more quickly see which skills to highlight/target in training. For employers, they can get a sense of which skills are truly necessary for a role vs are “nice to have” skills

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Conducting research around skills can be difficult because users have to use job posting-focused reports to try and get that information. It is not intuitive to a new user where or how to answer skill questions and often times they have to take parts from several different job posting reports to answer the questions they have.

Additionally, customers do not have a way of understanding the importance of a skill to an occupation beyond recall. A more robust understanding will enable customers to make more strategic decisions about what skills to focus on/recruit for/etc.

Value to Lightcast

• We continue to make skills a huge focus of our marketing materials but do not have a dedicated skills section in our primary research tool. When an existing or potential customer sees information we publish around skills there should be an easy way for them to duplicate that in our primary research tool.

• The addition of skill-specific workflows could be incorporated into new sale opportunities and also help with existing Analyst renewals.

• Integration related: Labor Insight customers had workflows related to skills that were popular; while they have not yet been a hindrance to integration, bringing these back will make customers continue to see the increased value of the merged product

• Delivery of value added models: The models team developed these models at the request of Analyst and API teams. Finish the job.

Target User Role/Client/Client Category

New or existing customers from all three different Analyst BU’s, for example:

• Academic Program developers, to understand what skills to focus on within occupations

• Career Counselors, to help students/job seekers understanding what skills to develop

• Talent Acquisition Specialists, to understand which skills to focus on in recruiting for a role while cutting through the noise of the many skills listed

Delivery Mechanism

Analyst Platform, through both (a) enhancements to existing reports, and (b) additional new reports.

• occupations reports that provide defining, distinguishing, necessary skills views, not just recall rate

• occupations reports that reference booster skills to show where a skill brings more value

• skills reports that show the relationship between skills (demand, hierarchy, similar skills, top occupations)

Success Criteria & Metrics

Users will have a clear path and direct answers for skill-related searches.

Successful adoption should result in a drop in job posting and to a lesser extent program reports since we believe users are often coming to these reports to find out more about skills and not job postings or programs.

Target usage should ~2.5 - 5% of Job Posting Analytics and Job Posting Table report usage for each vertical.
-This would but the skills reports in the top 10 in terms of overall usage for each vertical.

Aspects that are out of scope (of this phase)

Any new or additional skills metadata. We are only planning on using skill data we already have or that is planned to be in place by the end of the year.

Solution Description

Early UX (wireframes or mockups)

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Non-Functional Attributes & Usage Projections

Dependencies

These dependencies are all expected in Q4 2022:

• API delivering D/D/N Model

• API delivering Skill Boosters

• Skill-Skill similarity API

• Open

  

  Classification API (for skill hierarchy)

May be able to consolidate some of these dependencies into using the Occupational benchmark API

Legal and Ethical Considerations

No

High-Level Rollout Strategies

• In advance of rollout brief marketing on feature and use case to evaluate if we should prepare marketing collateral around the new use case and functionality.

• Initial rollout to internal Customer Success and Sales teams in Education to prepare them on how to train or communicate this to existing users and how to pitch this to potential customers.

• The feature will be released for all users across all BU’s.

  • Coordinate the release of the feature with a Pendo announcement that will include a short video communicating what the feature is and how we would recommend using it.

  • Will also check with Customer Success and see if this is something they think should get included in the next webinar after the feature release.

• Monitor feature usage and any feedback from users.

Risks

There is always risk when adding additional reports that they will clutter the tool and make it more confusing and harder to use rather than more simple and easier to use.

Introducing new models could lead to confusion for both internal and internal users. We will need to make sure we add these new models in an easy to understand and digest manner. We will also need supporting KB articles and training to make sure sales and CS understand the models when selling or supporting.

I think the risk to call out here is that introducing multiple models together could lead to some data confusion. For example, what if a skill comes back as both defining and a salary booster for an occupation? (It shouldn’t, but we’ll want to clarify with models)

Open Questions

Users have made it clear that skills research can be difficult to conduct but we need to finalize the workflows that will be most beneficial to users across all verticals. I plan to finalize this through user interviews over the next several months.

Need to be able to pull skill projections with a bulk endpoint, rather than calling the api once for each skill. What is the timeline for getting that added? @Michael Griebling (Deactivated)

Where does the Salary Premium metric come from? @Michael Griebling (Deactivated)

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.