This article will guide you through how Andela , a company that connects leading technology companies with talented software developers from tech hubs across Africa, went from hiring 3 senior software developers in 60 days to hiring 10 senior software developers in 30 days. At we are driven by people analytics**.** We recognize that hiring doesn’t have to be a mystery — you can gain useful insights through well-organised data. A consistent goal of ours is to hire and support the continent’s top technologists. To accomplish this, we need to build systems that let us know how we are doing, and what we need to do to get better at attracting top talent. In this instance, we needed to increase the number of senior developers within the organization in a short period of time in order to support the learning of the rest of our developer community. People Analytics: Andela In order to hire these top software developers in a short amount of time**,** we built a system using Sheets that we believe people can leverage from. In a 4-part framework we will walk you through this system: Hiring Systems: Google — this section will cover how to use historical data to calculate the likelihood of hiring an applicant within the pipeline. Part I: Defining Hiring Probabilities — this section provides a brief overview of how we integrated Google Sheets with our hiring system. Part II: Tracking Role-Specific Candidate Status — this section will walk you through how to calculate the probability of hiring active applicants. Part III: Calculating Expected Values — this section provides insights on how to calculate probability by desired attributes. Part IV: Making Time-Bound Decisions Part I: Defining Hiring Probabilities from our Applicant Tracking System (-ATS) to understand what percent of candidates at each stage are likely to be hired. We used historical data to understand the likelihood that a given individual would be hired. We round these up to the nearest tenths. We created classes based on the probability of advancing to the next stage. This step — by — step predictive analysis helped with the goal of increasing efficiency in the hiring process. We thought through hiring process changes Part II: Tracking role-specific candidate status using real-time and periodic updates in Google Sheets. We integrated with our ATS Real time updates were done using a Greenhouse add-on — Greenhouse Report Connector — to link Greenhouse reports and Google Sheets. Periodic updates were sent to Google Sheets with Greenhouse candidate exports and formulas. This required manual refreshing/updating of the data. whether role, stack, resumption lead time or any other attribute we wanted to display. We needed to forecast for probability of applicants within different stages in the application pipeline based on their prominent stack and lead time to resume at . We categorized by the most important features, Andela Part III: Calculating Expected Values so we could see how many people under a specific stack were in each stage. We multiplied the probability by the number of candidates by stack. We used that to predict how many people would be hired Part IV: Making time-bound decisions Time to hire, Role to hire, and Number of people likely to be hired. We used these three metrics because we believe they are the most impactful to growing our business. We showed three dimensions: Google Sheets in three dimensions: Use a data validation-drop down menu to let people toggle the third axis. A three dimensional table is used to display data based on three different variables, in our case by application stage, stack and resumption lead time. this was included in our drop down menu and we used the “if & countif -formula” to calculate the current numbers. We included “All Stack” as a dimension: Result: We had hired 3 senior software developers in 60 days prior to these systems. We hired 10 in the 30 days after we implemented these systems. That’s a increase in number of hires, with a 50% decrease in time. Proven increases in efficiency and outcome: 233% if you’re interested in understanding more about how Andela leverages people analytics — leave a comment Join us
