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HomeBig DataAmazon QuickSight helps TalentReef empower its clients to make extra knowledgeable hiring...

Amazon QuickSight helps TalentReef empower its clients to make extra knowledgeable hiring selections


This put up is co-written with Alexander Plumb, Product Supervisor at Mitratech.

TalentReef, now a part of Mitratech, is a expertise administration platform purpose-built for location-based, high-volume hiring. TalentReef was acquired by Mitratech in August 2022 with the objective to mix TalentReef’s best-in-class methods with Mitratech’s experience, know-how, and international platform to make sure their clients’ hiring wants are serviced higher and sooner than anybody else within the business.

The TalentReef crew are consultants in hourly recruiting, onboarding, and hiring, with the mission to assist its clients have interaction with nice candidates using an clever, easy-to-use single platform. TalentReef differentiates itself from its rivals by not simply constructing options, however creating a whole expertise administration ecosystem on the thought of eliminating friction and making the hiring and onboarding course of as easy and straightforward as potential for his or her clients and candidates.

TalentReef used Amazon QuickSight with the intent of changing their legacy enterprise intelligence (BI) reporting. The crew discovered QuickSight simple to make use of and developed two new dashboards that changed dozens of legacy stories. The response has been overwhelmingly constructive, resulting in the event of two further analytics dashboards, Job Postings and Onboarding, each set to be launched within the first half of 2023.

The next screenshot exhibits the Applicant dashboard, which is used internally by TalentReef Buyer Resolution Managers in addition to externally immediately by clients embedded inside the expertise administration utility. This dashboard supplies fast entry to their clients’ vital metrics. For instance, it exhibits the entire variety of candidates for all of the job postings. It additionally exhibits what number of candidates are current within the system by place.
full TalentReef dashboard

Offering readability to clients for hourly workforce hiring

The warfare for expertise is prime of thoughts for these hiring inside the hourly workforce. Hiring managers are always in search of prime expertise and attempting to grasp the place they got here from, why they’re making use of, and extra. They need to see how their job postings are performing, if there’s a drop in any posting, and alternatives to optimize their course of. TalentReef’s earlier answer wasn’t designed to convey this data, and required guide intervention to extract these hidden insights from a number of stories.

With the brand new dashboards embedded immediately into TalentReef’s buyer view, the event crew is ready to streamline their knowledge ingestion course of to make sure up-to-date knowledge is out there to their clients inside the TalentReef platform. QuickSight options corresponding to forecasts, cross-sheet filtering, and the flexibility to drill into underlying knowledge permits clients to shortly see the worth by completely different lenses.

At any time when a brand new characteristic was rolled out within the earlier answer, it wasn’t potential to gauge the impression it had on candidates and new hires as a result of it required a whole lot of guide work. Growth groups had to supply a uncooked knowledge file to inner customers, upon request, to indicate the worth of the brand new characteristic, and even then it was restricted in how they may present worth. With QuickSight, not solely are they in a position to present the worth of recent options shortly, however they’ll achieve this with out improvement intervention.

Knowledge visualization helps enterprise analysts scale consumer help

The sheer quantity of our datasets made gathering insights a sluggish course of. Not solely that, however datasets weren’t accessible to a large viewers outdoors our crew, corresponding to companions, program managers, product managers, and so forth. Consequently, Enterprise Intelligence Engineers (BIEs) spent a whole lot of time writing advert hoc queries, which then took a very long time to run. When the insights had been prepared, BIEs had been tasked with answering questions by way of guide processes that didn’t scale.

On September 6, 2022, TalentReef launched two new analytics dashboards, Applicant and Rent, that are embedded into their buyer utility. Because the launch, TalentReef has seen utilization improve over 20% and has saved guide inner sources hours of their time placing collectively insights for his or her buyer base throughout QBR calls that now could be accessed immediately from the dashboards. With TalentReef’s earlier software, stories had been unstable and would outing, which required improvement groups to troubleshoot and restore. Since implementing QuickSight, TalentReef has discovered efficiencies for each inner sources in addition to buyer hiring managers, and are assured within the capacity to fulfill the demand of those customers.

The next picture demonstrates UTM parameters (Urchin Monitoring Modules—a monitoring gadget that helps get actually particular with the site visitors supply). This dashboard permits TalentReef’s buyer base to grasp the place their candidates are coming from, in order that they know the place to speculate their recruitment {dollars} (whether or not the candidates got here from certainly.com, or google.com, and so forth). This embedded dashboard even permits customers to drill additional into their knowledge, understanding the identify, date, location, and extra that the UTM supply is tied to.

UTM Parameters

QuickSight has allowed TalentReef to unlock insights that weren’t beforehand attainable, or very guide to derive, from their earlier reporting software. An instance of this within the following picture is the typical time to assessment an utility. Within the warfare for expertise, minutes could make a distinction between discovering the people wanted to fill a place or letting them slip by the cracks. Such a data provides management benefit to know the place to focus their consideration and assist win the warfare for expertise within the hourly workforce.

Applicants over time

Unlock the ability of applicant and rent knowledge to get insights you by no means had earlier than!

Our clients have been extraordinarily impressed with our QuickSight dashboards as a result of they supply data that was beforehand unavailable, with out guide effort by improvement groups. The interactive nature of the QuickSight dashboards permits TalentReef’s buyer base to dive deeper into the candidates and employed candidates, for instance to grasp from the place an applicant got here from or how an applicant utilized to a job posting.

With QuickSight, not solely can we visualize applicant and rent knowledge in a number of, significant methods for our buyer base, but in addition we will help them see the ROI from further merchandise they’ve added on to the platform. Within the following instance, now we have a wide range of filters that permit shoppers to see if their sponsorship {dollars} are returning profitable hiring purposes, if their add-on of chat apply brings greater utility quantity, if the applicant got here from textual content to use, and extra.

dashboard controls
Applicant report

Innovating sooner with intuitive UI, growing buyer satisfaction

QuickSight permits TalentReef to innovate sooner in response to buyer suggestions. With the intuitive UI and native knowledge lake connections of QuickSight, TalentReef’s product crew is ready to shortly construct visualizations primarily based off the wants and needs of all their clients.

TalentReef’s earlier reporting software required guide efforts from improvement groups. Enhancements and bug fixes required prioritization in opposition to different initiatives and had the next chance of error. With QuickSight, TalentReef was in a position to arrange an information lake that enables dashboards to be constructed and innovated on by the product crew, liberating up improvement sources to proceed on the best precedence. Builders get the information into the information lake, after which the product crew pulls within the knowledge into QuickSight and deploys it as wanted. This has result in greater buyer satisfaction each internally and externally with the short turnaround time.

The suitable individuals with the fitting data

In any sort of HR area, the fitting stage of information entry is essential to be sure you aren’t leaving your self open to compliance points. Our improvement crew developed an answer that is ready to be utilized throughout all QuickSight dashboards utilizing row-level safety on the dataset.

TalentReef’s partnership with QuickSight has enabled us to unlock insights that had been beforehand troublesome or inconceivable to achieve. We’ve allowed our buyer base to know what is occurring and why it’s occurring, and visualize knowledge that’s most impactful and vital to them.

To study extra about how one can embed personalized knowledge visuals, interactive dashboards, and pure language querying into any utility, go to Amazon QuickSight Embedded.


In regards to the Authors

Alexander Plumb is a Product Supervisor at Mitratech. Alexander has been a product chief with over 5 years of expertise resulting in extremely profitable product launches that meet buyer wants.

Bani Sharma is a Sr Options Architect with Amazon Internet Companies (AWS), primarily based out of Denver, Colorado. As a Options Architect, she works with numerous Small and Medium companies, and supplies technical steering and options on AWS. She has an space of depth in Containers and Modernization. Previous to AWS, Bani labored in varied technical roles for a big Telecom supplier Dish Networks and labored as a Senior Developer for HSBC Financial institution Software program improvement.

Brian Klein is a Sr Technical Account Supervisor with Amazon Internet Companies (AWS), serving to digital native companies make the most of AWS providers to carry worth to their organizations. Brian has labored with AWS applied sciences for 9 years, designing and working manufacturing internet-facing workloads, with a concentrate on safety, availability, and resilience whereas demonstrating operational effectivity.



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