Data with a heart
Ankita Poddar
Sr. HR Business Partner at Amazon Web Services (AWS) | Blogger | Podcast Creator & Host
What is the biggest grouse of an HR professional? No matter the country, industry or organization, it is always data. Access to reliable data, the means to analyze and draw meaningful inferences may sound like a small request to help run a massive engine, but ask any HR professional and they will likely launch into a heartfelt rant into the endless hurdles one needs to jump to achieve the tiniest glimpse of success. It starts with multiple sources of data ranging from excel sheets to PeopleSoft to Tableau, none of them churning the same numbers. Different numbers are stored at different places and they almost never match. If you have been lucky enough to land with the right data, you now face the challenge of analyzing it. It dawns on you that drawing any form of meaningful inference needs one to move beyond addition, subtraction, multiplication and division. It needs close familiarity with statistical models; models that we never bothered retaining past our college years.
That’s where Heartcount fits right in. Over the past few years I have come across endless offerings that promise to solve your angst with data yet none do it as elegantly as Heartcount does. Focused on your data analysis needs, the portal makes you feel like an expert with numbers irrespective of your familiarity with statistics. My favorite aspect of the product is that it does not attempt to confuse you by overdoing the mathematical models. Heartcount is aware that one does not need to boil the ocean to find meaningful insights. It keeps things simple, easy to navigate and focuses on what’s important. Allow me to introduce you to how Heartcount allows you to flow through the what, why and how of data.
What
The drill down and the smart discovery are everyday basics. Imagine that I am attempting to drill down to the factors that influence attrition (the most common question for HR professionals). The product allows me to do so within seconds. Could a trusty excel sheet with its pivots and graphs allow me to do so? Of course. Would it be as easy? Hardly. Drill-down allows me to play around with multiple combinations to see how a variable or group of variables impact attrition.
Now the sheet I uploaded had up to 81 variables that could impact attrition. It would likely take me up to a week and immense patience to go through all permutations and combinations to figure how different variables tie in (for 50 variables, the total number of two variable combinations is 1,225). Why not let Heartcount do the work for you? Their Smart Discovery feature is by far my favorite of them all. Yes, there are a lot more features that generate greater insight but Smart Discovery takes what every HR professional already does every day and take the pain out of it. It automatically presents the conditions that have maximum impact.
Why
This is where Heartcount begins to do things that we usually ignore. Not only does Heartcount reflect statistically significant drivers at the click of a button, it also does not assume that the user is proficient with variance and p-values. This is where the ‘Explainer’ feature comes in handy. It breaks insights into understandable chunks. This along with difference analysis completes one’s understanding of how the variables interact with each another. The other feature of Difference analysis allows you to compare any two groups e.g. teams with high vs low attrition and understand where they differences come from.
Often most HR professionals depend on a variety of other resources either tools or people to help understand how to influence change. I have been known to say that in the field of HR, managing multivariate regression is a giant leap. I know organizations are far more adept at data than when I first said this, however, for individual HR professionals, the statement continues to be true. What I love about Heartcount and this set of features is the independence that it provides for every HR professional to validate their hypothesis and do more with the data they have available.
How
The last feature that I am going to talk about today is micro segmentation. Micro-segmentation in Heartcount allows for optimization of a select variable by understanding which segments are at maximum risk (in case of attrition) by leveraging the decision tree algorithm. I love this feature (and I realize I am saying this about every single one) because this allows you to deepen your understanding of the available data. You can choose the level of micro segmentation that you want to dive into. This not only allows you to understand which strings to pull to influence outcomes, it also tell you by how much. I have spent hours playing around with this feature and wondered why I have never contemplated something like this before.
I love data democracy; the power of being able to analyze data independently without being dependent on another individual. Products like these empower every individual in the organization to derive meaningful insights at team, business and organizational level. It doesn’t overwhelm nor fall short. Heartcount gracefully does all the hard work and allows you to jump straight to the meaningful insights.
Is Heartcount perfect? Well I can nitpick. The most quoted advantage of Apple products is simplicity and that a user intuitively knows how to navigate the products. I put Heartcount to the same test. I ignored the user manual and jumped straight in. It took me a few hours to be able to navigate through all available features. Thus while the product is intuitive enough for first time users, it isn’t a ten yet.
I recommend taking Heartcount for a test drive. Figure if you enjoy the drive. Unless you try, you will never know. And if in a moment of epiphany you realize that this is the answer you’ve been looking for, don’t forget to return and thank me. Until then, happy exploring.
Resource Manager at Deloitte USI || XIMB-HR
4 年Interesting to know :)