Last week I attended the Talent Analytics Leadership Roundtable hosted by Northwestern University and co-sponsored by Sears Holdings Corporation. The event included over 20 talent analytics thought leaders from companies in high tech, retail, financial services, manufacturing, and service industries – a veritable Dream Team of analytics brainpower.
The discussion revolved around how organizations are deriving value from talent analytics, their use of methods, models and technologies, and trends for the future.
Here is a recap of a few key themes from the discussion.
1. Predictive retention models: Coming to a desktop near you.
With their advanced analytics capabilities, most of the roundtable participants have built their own predictive retention models and are using these to understand and help prevent turnover. But these models will soon be available to the masses. Solution providers big and small have jumped into this space with pre-packaged solutions: Oracle, Workday, SuccessFactors, Visier, Evolv, just to name a few. In the near future, these models will be available to thousands of organizations. The question is: are HR and business leaders ready?
If the models are constructed well, they can be extremely beneficial to organizations in uncovering potential problem areas and helping organizations identify targeted initiatives to help mitigate turnover.
But HR needs to be able to validate these models over time and within targeted employee segments. One Fortune 100 company I talked with recently, for example, said that its model was very accurate for individual contributor and manager-level roles, but totally fell apart for senior leadership roles. HR needs an advanced analytics capability to be able to assess the accuracy of these models.
In addition, some organizations worry about disclosing the predicting turnover scores for individuals, as managers may not use this information appropriately. If a manager can only send one of two high potentials to a development event, for example, perhaps she will send the individual with a lower predicted turnover score, figuring that to send the one with high predicted attrition would be a waste of money (and eventually the attrition becomes a self-fulfilling prophecy).
For these reasons, HR leaders will need to decide who has access to these models and how they are used. Both HRBPs and managers will need training on how to use the information in the models, and new talent initiatives may need to be created given the different factors related to risk.
The use of predictive retention models is an exciting step forward for analytics, but HR needs to get ahead of the game to make sure they serve their purpose.
2. Continuous performance feedback replaces the dreaded annual performance appraisal.
We’ve been saying for more than three years that the annual performance appraisal is dead (or should be.) For many of the participants at the roundtable, this goal has become a reality. These organizations have moved past the static, once a year performance process in favor of more continuous feedback. This approach includes regular feedback check-ins with the manager (typically two to four times per year) plus ongoing feedback from peers (sometimes called “crowdsourced” performance feedback). While these organizations are enabling broader, more immediate feedback from a variety of sources, they still emphasize the importance of managers and employees having conversations about performance. In other words, peer feedback does not completely replace managers, but rather supplements and supports manager-to-employee conversations.
At Sears Holdings Corporation, for example, employees have a digital cloud-based application they can access anytime on their computer or smart phones to request and give feedback to anyone else on the platform. The tool provides a view into how they are achieving results and how they are demonstrating capabilities and living the culture. The feedback goes directly to the employee and the manager has full visibility to all feedback an employee receives, helping both quickly identify what worked well and where they can improve. The new platform was specifically designed to structure feedback in the most effective way possible and create a growth mindset, facilitating continuous improvement. Launched three months ago, the new feedback tool is catching on, with over 10,000 feedback submissions in the first months of deployment.
This is the future of performance feedback. Companies that are still stuck in the once-a-year review cycles would be wise to rethink now how they conduct their performance process.
3. An overhaul in employee engagement measurement.
In a similar vein, the annual employee engagement survey process is due for an overhaul, and many leading organizations have moved past the static process in favor of continual measurement. Similar to the performance review issue, why wait for a once-a-year reading on the engagement levels of your employees? If you have a problem, most of your high performers will have left by the time you analyze the survey results.
Instead, organizations with advanced analytics capabilities are continually monitoring employee engagement by analyzing employee postings on internal discussion sites and communities. IBM, for example, has an initiative underway to use sentiment analysis of internal postings to monitor engagement on a regular basis. By augmenting their traditional survey approach with ongoing monitoring of engagement, the company can get a better handle of issues as they arise and take prompt action.
These are exciting trends but a big change for many companies. HR needs to be at the forefront, advocating for these ideas and paving the way for these changes. That will require a savvy analytics capability, a great deal of change management to gain buy-in, and development initiatives to upskill HR and business staff to appropriately glean insights from data.
4. Prepare to address privacy and ethical issues around analytics.
Analytics offers so much promise, but it also brings up a number of ethical questions and privacy concerns. From the example cited earlier (what if managers start discriminating against employees with high predicted attrition scores?) to organizations wanting to scrape employee comments off external sites , ethical questions – as well as legal ones – abound. These are even more prevalent in Europe, where the legal standards on data are higher. Even something as seemingly simple as analyzing diversity data can be fraught with legal concerns.
Analytics leaders need to be thinking about these issues now and establishing partnerships with their legal teams to address these concerns. Even if an initiative is “legal” it can raise concerns among employees that will cause a backlash. Just because data can be collected and analyzed, that doesn’t mean it should be. Analytics leaders will need to tread a fine line and decide what is appropriate for their organizations. The more transparent they can be about the purposes of the research and how it will be used, the more acceptance and support may be gained among employees – and the press. (For more insights on this issue, check out this article.)