Background

We connected with a client who was looking for a temporary data analyst to fill in while they grew and hired a permanent replacement. Snowpack has provided analyst coverage for the team from August ‘23 to present day. This client is a leading SaaS platform in the compliance space with a suite of products that take a comprehensive approach to IT compliance. The company has grown extremely quickly and most recently completed a Series B round in 2023 for $150M.

Problem

In organizations that grow as quickly as our client’s, new employees entering the company into new roles, or roles that have been empty for a while, find that their swim lanes take time to be defined (or re-defined). With new roles, it can be difficult to define responsibilities properly until someone is actually sitting in the position, ramped up, and doing the work. In the case of existing roles that sit empty, work that should be completed either falls to the wayside, or has to be covered by the remaining members of the team, causing a strain on resourcing. With lead-times for hiring technical talent being longer than the average, this strain represents a challenge to a team that aims to excel in a high growth environment like the one we have here. 

Solution

Snowpack provided analytics support to the client on an hourly basis. The contractor was assigned to fill in the role and contribute to the team until such time a replacement was hired. In this case, the nature of the work was BI focused–examples of the type of work done by the contractor are:

1. Contributing to large scale projects, such as a redesign of financial data models.

2. Driving metric development and weekly executive reporting for key strategic initiatives.

3. Conducting ad-hoc analysis on the user journey and supporting other analysts on the team in their analyses.

The contractor filled in for a period of 7 months starting in August 2023, and was available day-to-day to cover additional responsibilities that came up during high demand periods.

Advantages of filling a temporary gap in staffing with a contractor

1. Minimal ramping time

When projects are clearly scoped and defined, contractors can ramp much more quickly due to the narrower nature of project-based work vs. management of an entire analytics discipline or practice. 

2. Autonomy

The expectation is not to handhold, but to provide the information the contractor needs to succeed. This translates to not having to explain key foundational concepts. 

3. Awareness of industry best practices when approaching a particular data product.

The contractor is already familiar and experienced with key statistical techniques and their standard applications to analysis. Furthermore, applying those techniques across a variety of clients gives them insight into which practices are most effective to solve a particular problem. Snowpack in particular has a wealth of experience effectively implementing similar projects with our clients. 

4. Ability to establish key responsibilities and workflows for the role prior to hiring a FTE.

Several of the reporting assets generated by the contractor are actively maintained and reviewed on a regular basis. The process for continuing to develop these resources, and workflows required to maintain these resources are clearly documented and defined–ready for handoff upon hiring the FTE. This helps the new hire hit the ground running by providing at least some clearly defined responsibilities as guardrails when they join the organization. 

5. Flexibility of hourly billing.

Depending on the workload and demand of the team, management was able to flex the number of hours requested in a given week or month–allowing them to invest hours during periods of high demand and saving money when additional bandwidth wasn’t required. 

Cost Savings 

Snowpack was able to generate a 50.5% savings rate vs. the cost of a full-time employee working during the equivalent period, with most of those savings coming from the lower-demand period from October - December of last year. The ability to scale contributions directly as needed by the client was instrumental in providing incremental value over an FTE.

The chart above shows the amount Snowpack billed to the client vs. the amount they would have paid in salary for the same period for a full-time employee (est. 40hrs/week). Numbers are obfuscated to preserve privacy. 

The projects delivered during this period would have required ~500 hours to complete. 

Without a contractor, either those hours would have been re-distributed to the existing team members, or the projects in question would have been paused until a later time, thereby limiting the overall impact the team was able to have on the organization.

Conclusion

For half the cost of a full-time employee, the client’s data team was able to continue to deliver additional support for the GTM and product organizations with limited disruption to their existing backlog of work or redistribution of responsibilities across the team. 

While hiring a new manager to fill the vacant position on the team, the client was able to ensure that business-critical work did not slip through the cracks, and prevented other team members from becoming bogged down with tasks that sat outside of their realm of responsibility. All of this was done on a flexible, per-hour basis that fluctuated depending on the needs of the business, a  key advantage Snowpack is able to offer in a contractor capacity.

We hope you enjoyed this case study–If you have questions, or your organization would benefit from assistance in building and scaling your data team, we’d love to hear from you! Shoot us an email at [email protected]