March 2, 2021 By Wendy Wick 4 min read

The COVID-19 pandemic permanently altered the recruiting process, just as it has done with many aspects of business. Organizations that continue to use pre-pandemic recruiting processes are apt to struggle to find talented candidates and to encounter decreased productivity throughout the recruiting and hiring process, especially when compared with competitors.

As remote work and virtual tools are expected to remain the norm for the foreseeable future, hiring managers and candidates need the flexibility to adjust the when, where and how of the recruiting process to align with what works best for both parties. Instead of a rigid process that requires in-person interviews and in-office work locations, flexibility, digital channels and adaptability must move to the core of the process.

Intelligent workflows

Organizations are increasingly altering their recruitment efforts by creating intelligent workflows, which are processes created combining artificial intelligence, predictive analytics and automation to fully understand both the hiring community and the candidate community. By assigning work based on work effort, organizations can provide different levels of service at the right point in time in the hiring process. The results are a positive experience for the candidate and the right hire for the organization.

Additionally, intelligent workflows help organizations prioritize their recruiting needs. Although each open position is the most important priority to the individual hiring manager, not all open positions are equal in terms of business value and impact. By using intelligent workflows to evaluate the relative importance of open positions, organizations can determine the level of effort that needs to be applied to fill each position. Companies then maximize the return on investment (ROI) on their recruiting efforts based on the business value each successful hire brings to the organization.

With the IBM platform, organizations leverage the cloud and technology-agnostic infrastructure required to provide the next-level recruiting experience needed to remain competitive. Because IBM provides the technology, organizations do not have to shift their current investment or infrastructure strategy. IBM partners with organizations to bring digital technology, such as AI, automation and chatbots, to the business’s current systems using an API, which means a much higher ROI.

Improving personalization through automation

Automation sits at the core of redefining the recruiting process, especially in terms of defining the candidate experience. However, successfully implementing automation remains one of the top challenges for many organizations. Automation is especially crucial in terms of speed of engaging candidates — and keeping them engaged throughout the entire process. Even with higher unemployment rates, top candidates are in high demand and competition to hire is fiercely competitive. Organizations that do not automate the process to a degree that both entices and meets the candidates where they are, are likely to see top recruits accept offers with competitors.

Many HR professionals mistakenly assume automation means using technology to schedule interviews or conduct video interviews. However, talent acquisition automation encompasses a much broader concept and process of using AI to manage the entire process while providing the most efficient and personalized experience for both recruiters and candidates.

Here are three use cases of automation in recruiting:

  • Balancing workloads. If multiple employees in the recruiting process are out of the office on the same day, the manager can use automated workload balancing to determine how to redistribute the work to accomplish the goals for the day.
  • Identifying common candidate roadblocks. Automation can determine decision points where candidates drop out of the process while scheduling the in-person interview. Using AI, the systems can help predict the drop-offs and propose alternative processes to bypass the roadblocks.
  • Flagging specific stalled candidates. Candidates often become stalled somewhere in the process, either because someone in the organization did not get back to the candidate or the candidate has not taken their next step. With automation, employees are assigned to reach out to candidates to keep the potential hires moving through the recruiting process.

Aligning the experience with segmentation

Intelligent workflows also provide organizations with the ability to segment candidate pools and decide how to modify the experience based on the candidates’ expectation and needs. Additionally, positions that are harder to fill may require a higher-cost strategy for recruitment. By using segmentation, organizations can use automation to design the recruitment experience based on candidate availability, work effort and experience.

With segmentation, HR leaders have access to real-time information that provides them with a full picture of their labor and talent pools. Segmentation also allows for a more conscious approach to diversity, inclusion and equity. Instead of having to wait for historical data and react to changes that have already occurred, recruiters can create and change experiences to open doors for candidates in ways previously not possible.

Before the shift to remote working became a necessity for most businesses, an IBM client shifted from a center-based employment model to a co-location model, which meant that 40% of their employees would work virtually. However, many employees in contact center positions preferred working on-site. As attrition occurred, the organization used segmentation to determine talent availability and then virtually managed the recruiting process through texting, self-scheduling and video interviews. Because so many of the organization’s employees did not want to make the move to working remotely, the organization added a touch point to personalize the process and encourage top talent to remain in the pipeline. As the organization was informed by data of the shift in preferences, they were able to manage the process and improve their hiring success.

Building the flexibility to handle future shifts

By using technology to build intelligent workflows that create a personalized and flexible recruiting process, organizations not only position themselves to competitively recruit top candidates post-COVID, but they also build the processes needed to quickly adapt to new changes in the talent pool and candidate expectations. Instead of simply creating a new recruiting process, intelligent workflows build the foundation organizations need in both the short- and long-term future to continually adjust the recruiting experience based on new data.

Learn more about how IBM Services can help transform your talent strategy.

Was this article helpful?
YesNo

More from Business transformation

Putting AI to work in finance: Using generative AI for transformational change

2 min read - Finance leaders are no strangers to the complexities and challenges that come with driving business growth. From navigating the intricacies of enterprise-wide digitization to adapting to shifting customer spending habits, the responsibilities of a CFO have never been more multifaceted. Amidst this complexity lies an opportunity. CFOs can harness the transformative power of generative AI (gen AI) to revolutionize finance operations and unlock new levels of efficiency, accuracy and insights. Generative AI is a game-changing technology that promises to reshape…

IBM and AWS: Driving the next-gen SAP transformation  

5 min read - SAP is the epicenter of business operations for companies around the world. In fact, 77% of the world’s transactional revenue touches an SAP system, and 92% of the Forbes Global 2000 companies use SAP, according to Frost & Sullivan.   Global challenges related to profitability, supply chains and sustainability are creating economic uncertainty for many companies. Modernizing SAP systems and embracing cloud environments like AWS can provide these companies with a real-time view of their business operations, fueling growth and increasing…

Re-evaluating data management in the generative AI age

4 min read - Generative AI has altered the tech industry by introducing new data risks, such as sensitive data leakage through large language models (LLMs), and driving an increase in requirements from regulatory bodies and governments. To navigate this environment successfully, it is important for organizations to look at the core principles of data management. And ensure that they are using a sound approach to augment large language models with enterprise/non-public data. A good place to start is refreshing the way organizations govern…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters