There is no doubt that generative AI will revolutionize how we work.
Whether you are looking to generate text easily that you can use for your go to market motions, create unique and stunning images, or even create new music derived from existing artists, generative AI can work its magic to help you get more done, faster.
What is incredibly powerful about generative AI is that the interface to communicate with these models is incredibly simple and accessible to anyone: a simple chat prompt.
This means that all you need to do is express what you want in plain language, and the system will output what you want, nearly instantly.
Beyond content creation, there are other profound and impactful opportunities for generative AI.
We believe that generative AI can and will forever impact performance management and feedback with hyper-personalized, real time coaching.
This type of performance management can help teams build more self awareness and raise the bar for performance.
The modern performance review system dates all the way back to the 19th century where the military used performance reviews to rank soldiers. With so many soldiers and a need to understand who the highest and lowest performing members were, the crude initial system helped the military gain insight into their ranks, but the system certainly didn't help the military better develop their soldiers.
This system was adapted and shaped through the 19th and 20th century, eventually leading behavioral scientist Aubrey Daniels to coin the phrase "performance management." The phrase was used to describe a method for managing both behavior and results. These combination of these two critical elements are known as performance.
Daniels' insight was an important one: performance is not just about results, but it's also not just about behavior. The combination of both the results generated and the behaviors displayed are the best way to frame and understand an individual's contribution to a team (or school, community group, sports team, or any other group where people work together towards a common outcome).
This all sounds good on paper, but once you get into the implementation details, this simple model turns out to be very difficult to execute properly for three key reasons. First, managers often don't have a complete view into a team member's contribution. Second, the administrative burden of the performance management process consumes so much time and energy that it can only be done sporadically. Finally, performance management is often backwards looking and lacks any practical action or next steps to enable continuing employee development.
Even the best intentioned managers can only spend so much time engaging in and monitoring their team members' behaviors and performance. Managers always have competing priorities and after often required to deliver work product in addition to building and managing their team. The very nature of this relationship means that managers will only see a thin slice of the overall behaviors and results for any given individual on their team.
While it's true that very seasoned managers may be excellent at judging performance through a thin slice of data, it's most often insufficient to truly understand performance and impact. This often leads to managers suffering biases when it comes to measuring and judging the performance of their team, namely recency bias and the open box bias.
During performance reviews, the recency bias can often pop up as a real issue. I don't know about you, but I can't even remember what I had for lunch a month ago, let alone a complete list of all my projects and accomplishments over the last quarter, half year, or year. This means that when you sit down to review and communicate the work you have done, or if you are a manager thinking back about the work that your team has done, it can be incredibly difficult to paint a full picture of the work accomplished.
This leads to too heavy of a focus on work that has been done recently, which is easier to recall and judge. However, this is unfair to the team because a formal performance review should account for all the work done over the review period, not just what is most recent. If the review only includes the work that is most recent, this can create an unfair review because it doesn't encompass the full body of work. If a team member's work isn't fully acknowledged or recognized, many will feel dejected and begin to disengage from work, creating a culture with a lack of true engagement.
In addition to the recency bias, many performance reviews have standard form fields like "what were your top accomplishments" that cater to every employee in every role. This is a huge miss and it puts all the onus on the employee to come up with answers to a vague and poorly formed prompt. This impacts the managers full view of performance because the answers we get are only as good as the questions that we ask. When the questions are junk, managers are left with a very incomplete view of performance.
Over time, there has been tremendous innovation in various workflow processes across organizations to reduce administrative burdens and increase focus on work that has a major impact on the organization's goals.
However, when it comes to performance management processes, the administrative burden is significant. When reviews are isolated to happen during specific "review periods," as it is with most companies that have formal performance review processes, the work required by both the manager and the team can impact productivity for weeks at a time.
This impact to productivity is felt in the immediate term with teams left distracted from their core work, but the impact can continue long after the review period is closed due to the fallout. Often times, managers struggle to deliver meaningful feedback and, in many cases, this can lead to employees feeling less motivated than they were feeling before the review took place. This can create a major negative impact on productivity and engagement, costing the team significantly.
Every performance review process should consider what actions team members can take to improve their results for the next review period. However, often times, these actions are completely missing from the performance review process. Sometimes this is due to simple oversight by the manager, but often times it can be due to the fact that development plans have not been clearly articulated or established by the company.
The issue that arises here is that even for team members who are hungry to learn and grow, there is very little that they can do to improve their performance. This can lead to people feeling dejected and hopeless, which is a huge contributor to a lack of engagement with their team and work.
The people will the strongest desire to learn, grow, and development themselves need access to great resources to help them develop. Without a proper set of materials or training at the ready, many managers are caught flat footed and are missing out on great development opportunities that will create trust and engagement from their team.
AI's natural strengths may present an interesting opportunity to forever change the way that the performance management process works at organizations. While LLMs and chat interfaces have created an explosion of activity in the space, it is still too early to be able to fully understand their impact on business and teams. However, there are some clear opportunities that may be enabled by this technology.
The more data available to a manager or people operations team, the better the decisions that can be made. If a manager had a 100% objective view of all the work completed, the quality of that work, and the behaviors displayed, it would be relatively easy to complete a performance review.
Instead of relying on memory and other artifacts of completed work, an AI system could help everyone align on the reality of performance by connecting to critical systems used daily by team members. AI could easily recap the work performed, identify trends, blockers, and opportunities, and provide a rich, data-driven analysis of output.
As discussed above, performance reviews can easily take days, if not weeks, of time to complete for an organization, crushing productivity during the process. While it is critical to have a performance review process in place, the cost of administering the process can often outweigh the value created.
AI could potentially significantly reduce the administrative burden of the performance review process by automating the creation and summarization of performance results. This elimination of administrative time could allow HR teams and managers more time to develop career training and employee development opportunities, which could have a massive impact on employee retention and engagement.
It is said that the difference between special forces and general military is the quality and intensity of the training. The same can be said for any other profession: in order to rise to the top, elite individuals must obsesses of getting the right training and development to improve their outcomes. However, creating these materials can be incredibly time consuming and difficult to execute. Further, because everyone has a different learning style and a different base skill set, general training and development materials, meant to cater to the broadest possible group of team members, can often feel too generic and downright cheesy.
AI, and generative AI specifically, can solve this problem by automatically generating hyper-personalized training materials for each individual based on their position, development goals, historic performance, and learning styles. This could accelerate engagement in training and development, leading to a higher performance and more engaged workforce.
While nobody can predict exactly what will happen now that this powerful new technology has become widely available, it is fair to assume that AI will have a profound impact on many areas of our work lives. We believe that there is a massive opportunity to re-think performance management and change the way that people understand themselves and their work using this new technology. If you want to learn more about our perspective on AI and the future of work, schedule a demo to connect.
.png){kind=small}
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
.png){kind=small}
