How To Implement Talent Intelligence
Unless you’ve been living under a rock, the chances are that your talent news sources are flooded with articles about talent intelligence. There seems to be yet another talent intelligence how-to article almost every day.
Let’s add another one to the list.
While most talent intelligence gurus correctly identify what it is and what are the benefits of talent intelligence, they fail to address the top pain point of talent management teams, viz, how to implement talent intelligence correctly and reap maximum ROI.
This article is an attempt at filling this crucial knowledge gap.
Because you can read up all you want about talent intelligence, but if you’re not able to implement it successfully across your enterprise talent landscape, then you’ve already lost the talent race.
What is talent intelligence?
In a nutshell, talent intelligence empowers talent management teams with crucial talent data to make informed recruitment and reskilling decisions.
But what is talent data?
Talent data can include anything from your enterprise diversity data to skills templates, compensation metrics, performance reviews, etc. These are data that you have accrued over time from your talent pool.
If leveraged correctly, this data can provide you actionable insights into your talent pool. Using modern analytics solutions, decision–makers can identify where the talent pool is lacking and what can be done to fix it.
Broadly speaking, the power of talent intelligence lies in its ability to incorporate artificial intelligence-powered insights into strategic workforce planning.
Why should your enterprise use talent intelligence?
- Predict the talent ecosystem: AI is now commonplace in applications with predictive capabilities, and for a good reason. Modern talent intelligence tools use AI to forecast the talent ecosystem for a given skill in a given location for a particular time. Given that the world is increasingly moving towards remote work post-COVID-19, the benefits of such forecasting features are obvious.
- Manage your talent acquisition costs: These talent intelligence tools are embedded with terabytes of streaming talent data from all around the internet. This enables them to crunch numbers and predict the talent acquisition cost for an emerging skillset across any geography with a surprising degree of accuracy. In fact, while most companies restrict their hiring pipeline to global metros, insights from talent intelligence platforms like Draup indicate that more hiring should be done from tier 2/ tier 3 cities. Not only does this significantly lower your talent acquisition costs, but also ticks some of the diversity metrics.
- Identify talent gaps and disrupted roles: This is perhaps the most important feature of modern AI-powered talent intelligence platforms like Draup. They can ingest talent data, analyze the broad trends and predict which roles are under threat of disruption from emerging technologies.
It doesn’t just stop there. Draup also provides talent management teams with an end-to-end reskilling solution to help reskill/upskill these jobs.Post-COVID, enterprises have realized the importance of AI-powered talent intelligence to streamline their talent acquisition and management processes.It is evident from the above benefits that talent intelligence helps HR leaders streamline their entire talent pipeline while drastically improving the team’s ROI.
Implementing Talent Intelligence
To empower your talent decisions with AI-powered talent intelligence, you need access to a wide pool of talent data.
Sure, you can leverage applicant tracker tools, CRMs, recruitment portals, LinkedIn etc., for such external talent data. However, such talent data is often incomplete, and in some cases, even inaccurate due to zero vetting.
If you still choose to go this way, then the recommended starting point is to establish a talent intelligence brain desk team within your HR team.
This team would ideally consist of people who not only have a good grasp on the enterprise talent requirements but are also well-versed with modern data scraping and data analysis tools.
Step two is to identify sources to scrape talent data from. Sure, your own talent data can serve as a starting point, but if you want to extend your model to analyze if your talent pool can meet the future requirements, you’re going to know what your competitors are up to.
In other words, you need access to processed, clean talent data vetted by human analysts that can be ingested to extract useful talent predictions.
This is easier said than done.
Several talent intelligence platforms have spun-off with the aim to solve this crucial problem for HR teams.
Draup, for example, leverages artificial intelligence to perform crucial talent intelligence tasks automatically. You are presented with talent data pertaining to niche skills analysis, emerging location talent discovery, competitor talent ecosystem, talent diversity analysis & compensation metrics.
This enables talent management teams & HR leaders to implement talent intelligence strategies into their pipeline easily.
In fact, several global enterprises have leveraged insights from Draup’s artificial intelligence-powered talent intelligence platform to study the talent ecosystem at an emerging location before building an office there.
Draup’s talent intelligence insights also extend to emerging technologies like quantum computing too, using which companies looking to expand into these domains can make informed decisions backed by well-researched data.