If you’re managing a talent acquisition program and an executive says to you, “Put a report together that shows me how successful your program is,” you might start to panic. What data do you use to show you’ve achieved success? And how do you define that success in the first place?
Dan Anderson, founder and CEO of Adaptalytics, will show you how to handle this situation in an interactive learning lab, Measuring Program Success in the Absence of Data, at the TalentBlend conference April 27-28 in Washington, D.C. TalentBlend is designed for professionals who build, optimize and innovate talent acquisition programs, systems, tools, and practices.
He will also be a presenter on March 8 at 3 p.m. Eastern in the Talent Acquisition Program Management (TAPM) Academy Hangout — an interactive live chat — organized by Meritage Talent Solutions.
Define What Success Looks Like First
It’s easy to be intimidated by data, especially if it’s not something easily accessible like databases in PeopleSoft or Taleo.
For many talent acquisition program managers, Anderson says, “Their project is so unique, there’s not a system to support it. So they don’t have the data to show they achieved a goal.”
While Anderson refers to himself as a data wizard, that doesn’t fully explain what he does. First he helps his clients define what success looks like and then he gets them to agree what metrics will validate it. At that point, he works backward to determine what data is needed to support that metric.
In your case, defining success means getting managers and executives on board and agreeing on a particular definition. And that means asking them a lot of tough questions, which might be intimidating.
For example, take an internship program. Is success measured by how many interns you hire from the CEO’s alma mater? Or is it defined by how many interns convert to employees or how many interns have engineering degrees?
“You have to know that if you don’t define success very well up front, there will be lot problems down the road,” Anderson says. “Once you define it, you have to make sure that everyone agrees on what metrics will validate it. Once you define it and it’s validated, then and only then can you collect the correct data. And in doing so, you’ve saved yourself so much work, because you know what data matters, and what data doesn’t matter.”
That allows you to say no to managers who keep asking for reports that don’t support the goal.
“They want to lead where the group is going and they want to do their own thing,” Anderson says. “And you have to say, ‘No, that’s not what the group wants. The group has all agreed that success is defined by this. Therefore, what you just asked for, you’re not going to get that. That doesn’t align with what we all agreed is success.’ ”
The Hunt for Data
Sometimes the data can take some time to collect. But if it supports your goal, then it’s time well spent. It means you’re going down the right path.
Anderson gave an example of a project he worked on for a FORTUNE 500 company a few years back. Managers would go into the HR system to submit employee changes on their own. Because they didn’t understand the system well, they consistently chose the wrong fields to enter the information, and then spent two weeks emailing back and forth with HR to correct the problem. Finally, it was decided that only HR should submit these changes. That prompted executive leadership to ask, “Has this process change been a success?”
If the data you need isn’t in a database, you have to devise your own system. Anderson, who worked with TalentBlend organizer Moe Hutt at SAIC, said she had created her own tracking system for the internship program in Excel, because the data she needed wasn’t collected in the HR system.
“The enterprise solution for that data set was on Moe’s desktop,” he laughed. “And that’s OK. For these types of things, that’s what you have to do. But know the right way to manage these files and don’t have multiple versions of the truth. Have definitions of what data should be captured and how often.”
What You’ll Learn at TalentBlend…and a Special Preview
Anderson’s learning lab at Talent Blend will focus primarily on how to define success, not how to become a data scientist. You’ll learn what questions to ask executives, how to define the metrics you need to collect, how to prioritize them, what sourcing you might need, and how to report that data consistently and basic data management practices.
“Sometimes you have to fight to define success,” Anderson said, “but that’s going to save you a lot of heartache. When you have that figured out, it eliminates the daily fires you deal with in many cases. It also helps you argue for the policies and procedures that align with your program.”
To learn more about Dan Anderson’s approach to measuring success in the absence of data, register to attend TalentBlend, a conference featuring industry practitioners and leaders who will transform the way you think about talent acquisition programs, operations and projects.
Also, get a preview of his learning lab by attending the Talent Acquisition Program Management (TAPM) Academy Hangout on March 8 at 3 p.m. Eastern. Register today!
View Dan Anderson’s LinkedIn profile.