Predictive Analytics: Building the Infrastructure
As companies are beginning to turn their focus from reporting on historical performance to predicting what should happen, organizations are being created whose sole purpose is to run HR analytical analyses. However, companies struggle with how many resources to put in the organization, what types of resources are needed to ensure success, and the scope of services the organization should provide. In order to recruit the right resources that can navigate the different channels in the enterprise and cultivate collaboration, the analytics group needs to have a clear definition and message of what it is and what it is trying to accomplish.
Here are a few questions to ask when establishing, or improving, your HR analytics function:
ScottMadden shares our recommendations about governance and competencies below.
ScottMadden believes that when a new HR analytics function is established, an interdisciplinary governance structure should be considered. Data analytics is a cross-functional discipline requiring reach and coordination between finance, operations, sales, HR information system, IT, and other HR centers of expertise. So, while the organization may sit in HR, interdisciplinary governance and integration with other functions will ensure data elements are consistent and systems are integrated appropriately.
In addition, the analytics group may be the data scientists with keen insight into organizing and mining data and building statistical models, but to be effective, the group must collaborate across business lines to identify relevant business questions and deliver results in a way that leaders can understand and use them. Let’s take a deeper dive into the competencies of an analytics function.
Competencies for the Analytics Group
While one key to an effective analytics function is collaboration across business lines, success also comes in the careful composition of your team. Competencies differ between those who:
- Ask the strategic business questions
- Know where the data are stored and how to retrieve them
- Analyze and interpret data
- Present the findings to leadership
A strong team is a balance of data scientists, software engineers, subject matter experts related to the business question or hypothesis, and strategists who build the story to engage stakeholders, drive buy-in, and transform results into meaningful and impactful initiatives.
Of course, it’s easy to make a list of your analytics “dream team,” but it’s a bit more difficult to source the talent. Numerous clients have been struggling to attract and hire the “right” resources. Part of the problem may be that the composition and number of resources on a dream team may not be static. What you need may be different from another company or change from year to year based on the industry, company size, organizational needs, and data infrastructure. This is why it is critical to meet with and interview business leaders annually to uncover the critical business challenges prior to hiring Ph.D. statisticians and business intelligence experts. These business challenges become the framework for the analytics group’s annual strategic goals, guide the group when prioritizing requested analyses, and provide insight into the required talent pool for the group’s success.
Taking the time to strengthen your analytics group’s infrastructure is time well spent if your group is able to hit the ground running and providing value to your corporation within the first six months. With a little bit of foresight and thought leadership, your “dream team” will win the prize for adding value to the organization.
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