How Predictive Analytics Can Make Talent Development More Effective

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Jul 27, 2018

“Controlled chaos” sounds like an oxymoron. Yet to anyone who works in talent management or talent acquisition, controlled chaos describes daily life. There are too many things to do, too many needs to address, and too much happening at once to really get a handle on it, but somehow you find a way to get it done.

The problem is — and we all know this feeling — it could be a lot better. In an ideal business state, you are able to dedicate the appropriate time and resources to recruiting, hiring, and developing key individual contributors and current and future leaders, and such efforts are carried out systematically. In an ideal business state, you’re ahead of the game and make the best possible talent decisions instead of scrambling to keep up and making unwanted concessions and compromises.

The actual business state, unfortunately, is a lot messier.

To help tame the chaos and tidy up that mess, it’s worth it to make Predictive Analytics an integral part of your talent development strategy. Analytics has already proven its value in talent management by adding consistency to the process, limiting human bias, and identifying organizational talent gaps. But we’ve only just begun to tap into the potential of this tool. Here are three big ways predictive analytics can further support your talent-development objectives:

1. Predictive analytics makes career pathing faster and easier

Using analytics, you can build a model of a successful promotion – what a candidate would need to do to be successful in the role, what traits they should possess, and what top performance looks like in general.

You can use data from your existing strong performers to build a predictive algorithm of success for the person you want to promote. Using your algorithm, you can mine existing database of potential candidates to identify the people who are most likely to be successful in the new role.

2. Predictive analytics allows you to more effectively target and address training needs

Comparing employee potential against your model allows you to quickly identify gaps. Gaps that are shared between several employees can be addressed with training, while gaps that only a few employees have can be addressed with coaching. You will be able to provide concrete data to support your training recommendations, making it easier to negotiate for budget and resources.

Your data-driven approach will enable you to quantify the gains that your company gets from a successful training program, and tie those gains directly to improved performance.

3. Predictive analytics can be used to create a model for performance management

Predictive analytics is the ultimate tool for securing your seat at the table. By pulling in data from multiple sources, you can create a performance management plan that connects directly to the overall corporate strategic plan. And, you will always have data to describe how well individuals and teams are executing on the strategic vision.

To make all of this work, you need good data and an effective tool for analyzing it. One of the most important data sources to start with are personality assessments, provided that the assessment you use has a strong validity and can provide you with trait-based data. Other data sources are important too, such as performance management data and engagement surveys. The more data points you pull in, the greater your predictive power. Look at your existing HR databases to see what information you already have.

To start datamining, you’ll probably want to work with a company that can provide you with analytics software and expertise for using it appropriately. For your part, getting training for yourself and your team in how to use analytics tools, how to identify and collect meaningful data, and how to interpret the results can be an important investment in the future. Analytics is only going to become more widespread and accepted going forward.

Ultimately, the goal of predictive analytics is to provide structure, consistency, greater insight, and improved accuracy to your talent-management strategy. As with anything new, there’s a learning curve (depending on how deeply your organization has gotten involved in analytics so far). However, once you have mastered the tool, you’ll find a lot less gray area and a lot more reliability in the execution of your talent strategy. It won’t be controlled chaos anymore. It will simply be control.

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