The performance management process can be a source of frustration and wasted time for many businesses. A 2014 Deloitte University study found that 58% of companies surveyed believed their performance reviews were a waste of time. This sentiment has not improved in the years since.
In response, Deloitte and other major companies, including Accenture, Adobe, GE, Goldman Sachs, IBM, Microsoft, and SAP, had at the time abandoned traditional annual performance reviews in favor of more effective approaches. At the time, data from Towers Watson shows that 14% of companies have already eliminated performance ratings, with an additional 24% considering doing the same.
These are large, enterprise companies making the switch to new performance management methods. These are well-established businesses that carefully consider and test new programs before fully implementing them. These companies discovered that alternative methods can provide more valuable insights into employee performance and that the resources and time dedicated to performance reviews can be better allocated elsewhere.
While there are many arguments for abandoning traditional performance reviews, the increased velocity of employee performance metrics for employees is a key factor to consider. By collecting and analyzing data in a more timely manner, businesses can make faster and more informed decisions about their employees to drive the performance of the company.
Data velocity is one of the 3Vs of Big Data. The other two are X and Y. The concept of data velocity refers to the speed at which data is collected and analyzed.
Traditionally, HR data has been collected at a relatively slow pace, with annual performance reviews being a common example. But this slow process means that data collected can quickly become incomplete, outdated, and subject to biases (recency), making it less useful for informed decision-making. For performance management, higher velocity data would mean multiple data points throughout the year instead of one annual performance review.
But to increase the velocity of HR data, companies may need to adopt new technologies and approaches that enable more frequent and efficient data collection and analysis. Traditional systems that handled annual performance reviews may not make the transition to a higher velocity approach. This might include the use of specialized systems for check-ins and pulse surveys or working with HR tech startups that specialize in real-time performance management.
If you look closely at any of the companies that have dropped annual performance reviews, they aren't actually eliminating performance management or even the review process. Instead, they’ve adopted technologies that enable them to switch to a high-velocity alternative.
Think about your FitBit or smartwatch if you have one. If it only told you once a year how many steps you’d taken, it wouldn't give you much insight into how to change your habits. The critical piece of that technology is the velocity of the data collection. That enables you to know when you've been sitting too long reading HR analytics articles and that you should get up and take a walk.
When you can collect higher velocity data, the time gaps between data points shrink, which then lets a learning algorithm better understand the data. When an algorithm can make sense of your data across time, that's when you can start to make predictions or better segment the employee population.
The use of higher velocity data in HR can greatly improve the accuracy and effectiveness of employee performance analytics. By collecting data at a faster rate, businesses can better understand how performance metrics for employees change over time and identify trends and patterns faster throughout the year. This can lead to more informed decision-making and the ability to make predictions or segment the employee population. While these approaches may involve significant changes, they can ultimately provide more valuable insights into employee performance and drive business success.
The lack of progress in increasing the velocity of HR data collection and analysis can be attributed to the challenges of changing established practices and the difficulties of collecting data from employees. Not to mention that HR departments are stretched to their limits in terms of data collection and may not have the resources, tools, or capacity to gather data at a faster pace without technological support.
Without the right technology, it’s difficult to implement a high-velocity performance management system that can provide accurate, timely insights into employee performance. Traditional methods are not sufficient for statistically sound, bias-free analysis (some companies are still recommending post-it notes in a drawer to record employee achievements). In order to effectively collect and analyze work performance data in real-time, HR departments need access to digital technologies specifically designed for this purpose.
This can be frustrating for HR professionals who are eager to adopt modern, data-driven approaches to performance management. But as new technologies are developed and made available, it’ll be easier for HR departments to implement high-velocity performance management systems that drive business success and improve employee performance.
"As we strive to improve performance management"
"In our efforts to harness the power of HR data"
"As we move towards more data-driven approaches to performance management"
"In our pursuit of high-velocity HR data"
"As we continue to evolve our performance management strategies"
As the field of HR evolves and the demand for high-velocity data increases, companies have seemingly three options: build their own technology in-house, purchase a solution from a vendor, or risk falling behind.
But with One Model, companies have a fourth option: build+. They get the benefits of starting with a robust system as well as the ability to customize and make the solution fit their needs 100%.
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