Why Fast is Not Alway Good
All corporate functions receive shocks from the market, the economy, the pandemic, and new technologies. New technologies, especially, create a buzz and come with great promise but little maturity. AI and Chatbots are good recent examples.
Why are some recruitment functions able to use these technologies well? And why do many other functions falter and fail to incorporate them successfully?
If we think about change as a multilevel process, with some levels changing faster than others, we can pose answers to these questions.
Recruiting and other functions comprise separate components or layers that operate differently and have different speeds of change. Each layer is also, to a degree, independent of the other layers, but each layer impacts the other, and they all influence each other.
For example, the demand for talent influences sourcing, sourcing influences the recruiter’s ability to present a candidate, and the technology they use can slow or speed up that process. A recruiter’s influence, persuasion skills, and ability to assess a candidate also impact speed and quality.
Fast layers (technology implementations) initiate change; slower layers (structure and culture) remember and absorb the shock. Fast is fleeting, but get things moving; slow lasts longer and puts the changes into action. Fast is usually smaller and is moderated by slower and bigger layers beneath it, which gives consistency and strength.
We pay the most attention to the fast, but the lower and slower layers have the sustaining power. Without the lower layers, there is rapid but unsustainable change. In these cases, the function cannot absorb the shock and falls apart.
Look at a typical recruitment function comprising at least five layers.
Layer #1: Demand for Talent
The first is the demand for talent. It is the direct response to market drivers and powerfully influences all the other layers. The second layer, which responds to the demand for talent, is often technology. In recruitment, it includes AI, chatbots, and all the tools that aid in finding and hiring talent. The third and fourth layers are the structure and the underlying corporate and talent culture that comprise the function. The final layer is the overall resilience and strength of the industry.
Layer #2: Technology
Talent demands often influence recruitment leaders greatly, and technology promises quick solutions. Frequently, a disproportionate number of resources are focused on acquiring and implementing technology to service the demand and to compete with competitors. Today, it is all about artificial intelligence and Chatbots that promise to speed up and improve the ability to find, screen, and engage candidates. As is often the case, the technology does not live up to its promise, costs more, and takes longer to implement than planned. When this happens, disillusionment follows.
Layer #3: Structure & Culture
However, the layers of demand and technology push the function into new thinking and stimulate change. If unchecked, they can lead to failure. Still, if the overall structure of the function is solid, there is enough stability to absorb the initial excitement over the promise of the technology. This structure and maturity can help the function slowly learn how to use the technology and how best to incorporate it into the work process. This is why having an effective structure, good processes, and a stable and well-articulated talent culture are essential to long-term success.
Layer #4: Resilience
Structure and culture are the restraining forces, pushing back against the change layers of demand and technology. These layers change slowly and provide stability, absorbing the shocks of change. Underlying all the layers is the overall industry and function maturity and resilience.
Example
Let’s give an example of these layers in action.
A large recruiting function in a global company is facing a demand for increasingly hard-to-fill software engineers. The sourcers are working overtime to locate top talent and attract it to the company. Because of the demand pressure and need for speed, they turn to AI and other technology to help them source, assess, and engage top performers.
The tools they use are new. Many are barely out of beta testing and may not work as well as advertised. They spend inordinate amounts of time learning to use the software. Sometimes, the software may deliver exceptional results, but at other times, it may not. There will be bugs and implementation issues that take time to solve and remove the sourcers and recruiters from finding and assessing the candidates they need.
In extreme cases, more and more time and effort are spent trying to use the tools, and things begin to get out of control. Hiring managers are unhappy, the time to fill goes up, and candidate engagement goes down.
But suppose the function’s overall structure is stable and built on corporate values. Suppose there are good policies and processes to compensate for errors or issues from using the new software. In that case, the function will adapt to the technology, use it better, continue providing suitable candidates, and remain on track.
The structure is like the bones in your body, giving strength and shape. Values and talent philosophy guide behavior and how to respond.
However, if the underlying structure is weak or disorganized, or if the function is moving away from the company’s fundamental values, the entire function may fail. In this case, the culture and structure provide the continuity and integrity to grow with the new software and slowly incorporate it into their work.
This model also provides a way to understand why change efforts are often unsuccessful. Revolutions are rarely successful unless they build on existing structures and cultures. When changes are made at the superficial top layers without giving the structure time to absorb, the change will be short-lived or lead to failure. It is essential to understand that change takes time to filter into the structure and get incorporated into a modified way of doing things. Evolution is a more successful practice. The changes need to be aligned with the organization’s underlying culture, as well.
As a leader creates or builds a function, large or small, it is helpful to keep this model in mind. When introducing AI or any new software or practices, allow time for filtering and the structure and other layers to adapt to the new. Adopt slowly and allow for a learning curve. Moving quickly is often touted as necessary for survival, but in reality, rapid change most often leads to collapse. Quick is not always good.
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