Most recruiting functions are thinking about or are in the process of implementing recruitment technology. There is no question that adopting and implementing technology is the key to recruiting success. Those that are successful at this will attract and hire the best people and improve their organization’s profits.
Recruitment Process Automation (RPA) is often considered the way to automate recruiting. It is usually focused on buying off-the-shelf software that automates or augments such processes as posting jobs, recommending job description language, parsing resumes, screening candidates against predetermined criteria, scheduling interviews, video interviewing, and inputting data. However as useful as this is it is not enough. The tools are not “smart” in that they rely on simple algorithms or follow a set of predetermined rules. They do not learn or utilize local data sources. A more powerful and effective method is to adopt Intelligent Automation (IA).
Recruitment Process Automation vs. Intelligent Automation
Intelligent Automation is far more powerful because it combines process mapping and redesign with artificial intelligence and data analytics. By using data analytics combined with artificial intelligence, IA can develop profiles of the most successful employees and use these to recommend candidates. IA can create intelligent chatbots, assess personality and skills, and match them to jobs. Overall IA will lower costs, vastly improve productivity, and make remote recruiting more successful. It provides information about candidates in greater depth than can be done in any other way.
Unfortunately, many recruiting functions that have adopted RPA think this is the end of their automation journey. Many have bought applications that promise to automate parts of what they do but have not seen much success. Often million-dollar investments spent developing websites, acquiring applicant tracking systems, purchasing various apps for sourcing, screening, or candidate engagement have not given a fair return on the investment. They still need the same number of recruiters, and the workload is not less. Candidate quality is no better than it was before they had the software. Stumbling in technology implementation is not new, but there are ways to improve the chances of success.
80% Optimization
The most crucial step is to move beyond simple RPA and invest time and energy in understanding, defining, and simplifying the processes before implementing technology.
The first rule is that you cannot automate the manual systems you are currently using by duplicating them or replacing them with technology. This is the flaw with RPA.
People processes are often not translatable into software processes. People do things sequentially that a computer does in parallel. People need time to complete actions that computers do instantly, and so forth. Off-the-shelf software that uses somewhat customized algorithms is very good at automating routine, administrative tasks that are rule-based.
Understanding the skills your organization needs or assessing candidates for those skills requires much more. Intelligent automation helps to provide depth and deeper understanding.
First of All, Map What You Are Doing
Before buying any software or implementing any technology, we need to take the recruiting process apart and look at it with fresh eyes. This is zero-basing the process or re-inventing it from scratch in re-engineering terms. You should ask: How would I put this function together if I could stray from the usual and do anything I wanted? What could you eliminate, modify, or do differently – even without technology – to make the process as efficient as it could be.
This is the core of process improvement and refinement and should precede any effort to add technology. After you have designed a new process flow that considers automation, you can make changes with confidence that they will work.
Map out the way you are doing things. To learn how to do this optimally, it would be wise to study business process mapping. A good book on this topic is The Basics of Process Mapping by Robert Damelio, or get the delightfully simple book by Dianne Galloway, Mapping Work Processes. This YouTube video is an excellent introduction. Process mapping is a powerful tool and a way to get your arms around what looks like chaos. Once the current steps are identified, it is logical to make the process better by eliminating redundancies, integrating efforts, or simplifying the administrivia. After this first step, you can look at whether you have the right structure or the right tools and base your decisions on how things work.
Four As of Intelligent Automation
It may be helpful to chart what you do using the four As framework. Take each step of your process and assess whether it could entirely or partially be automated, augmented, wholly abandoned, or whether it would be best for it to continue to be done by a recruiter.
Automate
This is the realm of RPA. Decide which steps or processes can be done faster, with fewer mistakes, or more economically with software. As mentioned above, many simple tasks such as scheduling interviews can be completely automated.
Augment
Decide which steps or processes could be aided or done faster or with higher quality if a recruiter had more information or a recommendation assisted by a tool or application. An example might be the use of a chatbot …….
Abandon
Perhaps the most challenging part of this is to decide what to stop doing or do less than you are currently doing. For example, to eliminate the number of interviews or reduce the number of approvals. Every process flow has redundant or unneeded steps that can be removed without affecting the quality of the work.
As It Is
And then decide what software can not do or is best to be done by a recruiter. Even then, perhaps you can still make improvements by tweaking a step or assigning it to someone else. For example, train a hiring manager to make offers or conduct onboarding.
The chart below is an example of how you might think about this. I encourage you to create one of these for your function. In this example, at least 43% of the time could be saved by automating parts of what you do, and another 29% could be augmented. So roughly 80% of your time could be freed up to do more value-added activities such as marketing, influencing, or coaching.
Compromise - Choosing the Technology that is 80% Right
Choosing the right software or application is often not as difficult as we think. If we know exactly what we need, it is generally a straightforward process to determine whether or not various products have the required functions. You will find that no single product will be able to do everything you want. The art of choosing technology is to go for solutions with the most reliable and cheapest blend of critical features. Always choose the simplest tool to do what you need to get done. This minimizes costs, simplifies installation, and shortens the learning curve. My rule is to choose whatever product meets roughly 80% of your needs. Do not require or expect a product to do everything you think it should – you may be wrong, and you may find that it limits you as you learn how to use the technology effectively.
Tweak, Modify and Change - Continuous Improvement
None of us is good enough to architect a system on paper that will be flawless. Most of our processes – even, or perhaps especially, new ones – are filled with bugs and overlooked errors. The best strategy is to accept upfront that any new technology will require a back-and-forth process of tweaking the process to accommodate the technology and the technology to meet the requirements of the process. This constant process of minor improvement and change will evolve your processes.
Data is key to IA
The only way to make changes that will result in higher efficiency and quality is to tap into the data in your ATS, HRIS, and any other systems in your organization. All intelligent automation is based on algorithms that assess or communicate with candidates. These are only as good as the data they learn from.
By integrating process improvement with technology and accessing data, the recruiting function can become a significant asset to the organization. It can move far beyond the relatively administrative activities it now does based on unfounded assumptions and limited data.
Adopting technology is a process, and seeing any result requires careful thought and constant monitoring. Algorithms need to be monitored and modified frequently, and data must be adequate. RPA is limited because simply buying a purported solution and sticking it into your current process will undoubtedly fail.
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Thank you for sharing this, Kevin. I always enjoy reading your views on TA. I've been thinking a lot lately about what you said here:
"we need to take the recruiting process apart and look at it with fresh eyes. This is zero-basing the process or re-inventing it from scratch in re-engineering terms."
As we accelerate deeper and faster into the knowledge economy, right now seems to be the perfect time/place to be doing what you stated above. I call it "first principles recruiting/TA". Using your premise for intelligent automation, first principles recruiting is an honest and earnest approach to TA because it begins from the bottom and moves (reasons) upward, unlike top-down recruiting where lots of tech ended up destroying the best of what humans (employers and talent) have to offer, especially in terms of their ingenuity and creative powers to make recruiting really come alive!