A Sample Summer Project: Transaction Diligence and Impact Measurement
Featuring Natasha Sakraney, Fellow - Achieve Partners
This past summer, I had the pleasure of working with Achieve Partners as a summer associate through the Mosaic Fellow program. In this piece, I’ll take a bit more of an in-depth look at the main project I worked on this summer, some example workstreams, and how I learned to think about impact metrics as a part of a live deal team.
I was incredibly lucky that about a week before my internship started, the Achieve team had signed a Letter of Intent (LOI) with Cloud for Good, a Salesforce implementation and consulting firm that serves nonprofits and higher education clients. We kicked off a 60-day diligence process, and I hopped on the deal team comprised of Corinne Spears (our fearless VP), Ryan Craig, and Ayesha Khan. My goal was to learn the ropes of a live private equity deal process and find a way to contribute meaningfully as a new team member.
My work entailed supporting the team’s detailed diligence process to validate the financial attractiveness of the investment and alignment with our impact goals. Two workstreams that I’ll discuss here were 1) assessing the market & competitive landscape and 2) building a mini model on top of the deal model to analyze the financial and job creation impact of a last mile training program at Cloud for Good. Additionally, I built a post-close cash forecast and supported customer diligence calls. I also had the pleasure of attending a management meeting in person with Tal Frankfurt, Cloud for Good’s CEO, and our deal team, a rare treat after remote work.
Market and Competitive Landscape Work
To ensure the financial viability of the investment, our deal team conducted detailed business diligence. I helped by building out a classic market and competitive landscape analysis, which was very much in my wheelhouse given my consulting background. In this analysis, we deconstructed the size and growth of all relevant sectors, mapped out a long list of competitors and their offerings, and validated the hypothesis of a skills gap existing in the Salesforce ecosystem. In order for Achieve’s impact thesis to work, we had to ensure that 1) there was actually a talent gap in the Salesforce ecosystem and 2) there was a demand for Salesforce talent in the market from current and potential Cloud for Good customers.
Last Mile Training (LMT) and Impact Analysis Work
Achieve’s impact goal for the recently launched $180M Workforce fund is tied to job creation. The fund aims to place 100,000 Americans into well-paying jobs over the life-cycle of the fund. We do this by building last mile training pathways, affectionately called LMT by the Achieve team. LMT creates a program to home-grow talent through an apprenticeship model within portfolio companies. This talent creation drives profitable growth for the portfolio company and contributes to the impact goal by creating paths to well-paying jobs by upskilling participating apprentices.
Before closing a transaction, the Achieve team wants to make sure an LMT program will actually be successful at scale and be useful to the company. Therefore, after validating the existing of a skills gap in the Salesforce ecosystem from our market research, we moved into the fleshing out the potential design of a last mile training talent program. The idea was that Cloud for Good would benefit from an apprenticeship program that would sustainably train talent and place talent into Salesforce related roles, such as Salesforce Administrator or a Data Specialist who can support Salesforce implementations. One of the theories behind this model is called Hire Train Deploy, which you can read more about here, in a Forbes article by Ryan Craig, one of Achieve’s co-founders and the MD on this deal. The design of these programs ensures that apprentices are fully paid while they train, which is critical for ensuring equity and making sure we can recruit diverse talent.
One piece of work I helped with for LMT was building out a summary “mini model” of last mile training financials (from revenue down to EBITDA) as well as operating metrics (number of apprentice cohorts per year, number of apprentices per cohort, utilization, hours, bill rates, pay rates, etc). This analysis tied to the deal model and could flex based on different scenarios, allowing for a full five-year view of how last mile training might scale and how many people we could upskill through the program. This analysis helped validate the feasibility of launching a last mile training program at Cloud for Good during the diligence process. Post close, this helped facilitate the start of the conversation with Tal and his team about what LMT program design would be best suited for Cloud for Good’s talent needs.
Talent for Good:
With some lucky timing for me, the deal closed in the last week of my internship and was announced shortly thereafter. Since close, the Achieve and Cloud for Good teams have been working tirelessly to launch a 2-year apprenticeship program called Talent for Good. You can read more about the launch of this program here in a piece by Tal Frankfurt. The first apprentices will start in Talent for Good in 2022, and I could not be more excited to see the incredible work Cloud for Good accomplishes under Tal’s leadership.
Now that the deal is closed, I’m thrilled to share my summer experience publicly in order to give prospective fellows a flavor of what an example summer project might feel like. I’m incredibly grateful for the time and effort the Achieve team put into creating a meaningful experience for me as an intern, and I would be happy to chat with other budding impact investors interested in the Mosaic Fellow program about my experience.