If you read one of my recent posts, “Getting Started with Recruitment Marketing”, you’ll know my thoughts on the importance of analytics in a total recruitment marketing strategy.
And over the past few months, I’ve noticed something that I think is important to the recruiting analytics topic. As an industry, much of our focus on analytics is on the output rather than the input when it comes to data. That’s something I’d like to explore today.
Output vs. Input for Analytics
Today, we are laser-focused on the ultimate deliverables (or output) that are provided in terms of data and the areas that we measure whether it’s time to fill, source of quality or cost per hire.
It makes sense, this is what you use to make strategic decisions and ultimately these metrics are used to evaluate your team’s performance. The result is practitioners, vendors and thought leaders talking about what you need to measure, the dashboards and systems used to provide this real-time data and benchmarking your overall success. And rightfully so, it’s integral to overall strategic improvement.
But in this topic, I don’t hear about the input a whole lot. And when I mention input, it’s around how you capture, store and provide access to the data you capture. While not as sexy as the ultimate deliverables, it’s this process that ensures the integrity of your data, enables you to identify simple & complex relationships between data points and ultimately makes sure those outputs are available to key decision makers in real-time.
In short, it’s the “Garbage In, Garbage Out” philosophy. If your input process of how you capture and store the data is off, the data output on the back end can’t and shouldn’t be trusted in decision making.
So the question is how do we improve our data input?
A Focus on Better Data Inputs
When I talk about analytics the first thing I always fall back to is Trust. You need to ensure you have trust in the way data is captured, trust that all data is talking the same language and trust that your data process is scaleable as more data comes through the door. This is what data input is all about.
When capturing data you need a system and technology that you can trust to do all of the above while providing an easy and robust way to view the output of the data to be used in important decision making. When choosing technology, I recommend understanding how it fits with existing systems you use to capture data. I’d also look at limiting the amount of systems you use to capture your recruitment marketing data with one front-end platform being optimal.
When looking at your data capture and storage process, you can ask the following questions to better understand your data integrity:
1. How many different systems are you using to capture recruitment data?
Most organizations will have an ATS that helps them capture applicant to hire data (the accuracy of which can vary). But it’s on the pre-applicant side (where source, engagement and marketing data is captured) that organizations typically have multiple solutions focused on a single sliver of recruitment marketing (whether it’s mobile, social, job distribution, CRM, etc.) In these scenarios, the answers to the questions below are crucial.
2. Is your data captured in the same manner based on the same criteria?
Here’s a key issue especially when using multiple systems. If your data doesn’t talk the same language, it’s extremely difficult to make any sense of it much less compare it to one another. So we need to ensure that data from our marketing email campaigns, social recruiting efforts, mobile Career Site, etc. are all measured towards the same key criteria in the same way across all the solutions we use. That’s not to say that you don’t capture initiative specific data outside of that for certain initiatives (i.e. Google Analytics for Career Site). But just that the core data captured needs to be seamless with one another.
3. Is your data being captured together?
If you’ve answered the two questions above, you should have a process that uses a few key systems to capture all your data based a certain set of criteria that is the same across all initiatives. That’s a great start.
Now we need to make sure the data is stored in one location. This is integral if you are using multiple systems as you want data centrally available across all initiatives. You don’t want to have to manually combine data every time you want to get a Total view of your recruiting strategy. So a level of integration that gets all your clean data in one place is essential.
4. Do users have full access to your data? In real-time?
This is where input bridges the gap to output. We want to make sure your data is structured and stored in the way to give users full access to slice and dice the data as they see fit. And we want to make sure it’s available in real-time (not a month from now.)
If your data is clean and stored in a data warehouse, it’s just about how your platform provides you access to the data. This is where the glitz and glamour comes in through the form of pretty dashboards and reports. Any good system will make sure to provide you with real-time data in ready to consume reports that display key relationships that can help you make better decisions. It will also provide full access to the data to enable you and your team to make your own custom views of the data for further exploration.
The Ying (Input) and Yang (Output) of Analytics
The fact is both inputs and outputs are extremely important to better more strategic decision making in your recruitment marketing strategy. They are the Ying and Yang of analytics and need to be a key focus as you try to gain insight into your recruiting performance.
To sum it up, we need to ensure that how we capture and store our data is done correctly so we can have full trust in our data all while providing easy to use and powerful ways to consistently experience, interact and learn from this clean data.
In the end, that’s how we improve.