3 Big Problems With Your Talent Analytics
Tackle your data challenges with a fresh approach, by looking at people and roles from the perspective of skills.
Every function in every organization is turning to analytics to make better decisions and support business goals. HR teams are also using analytics – that is, gleaning insights from increasing quantities of increasingly diverse data.
With talent analytics and applied AI solutions, you can understand your existing and potential workforce, to make the right decisions when it comes to attracting, engaging, and retaining the best candidates, and to think more holistically about hiring, training, and management.
For HR to become the strategic partner it should be within your business, they need to not only invest in talent analytics capabilities, but also ensure the insights are applied correctly to create the right impact in the organization. And there are a few major roadblocks to that aim.
1. Your talent data lives in too many different places.
HR data lives in lots of different systems that don’t speak to each other. The problem is not unique to the HR department: most companies face an issue with gleaning insights from data that is sitting in hundreds of different places. However, HR is often low on the list, and the data is unstructured, subjective and as messy as the real-life humans it represents.
With information about your employees living in an applicant tracking system, various training platforms and HR databases, you are unlikely to easily garner a fulsome understanding of the people working for you. Bringing these data sets together is not only costly, it is time consuming, and often the insights are out of date before you can really grab them. The data is not useable.
More data doesn’t always mean greater insight. Once you’ve collected data surrounding your workforce (and potential workforce), you need your analytics to point you towards what to do next. Who do you need to hire, to move, to promote?
One big issue companies face is that data is not normalized: it isn’t in a single ‘language’ that allows you to spot patterns, gaps and opportunities across for different job roles and different categories of talent.
2. Your data is focused on the past, not the future.
Analytics is often about taking in and processing historical data, and analyzing that data to identify trends, patterns, and root causes.
When it comes to the always-changing talent landscape, it’s easy to get stuck looking at old information: the skills people had when they joined your company, or the information candidates shared at the time of application.
For companies trying to prepare your workforce for the future (changes in demand, the most sought after skills, digital transformation), it’s crucial to not only have an up-to-date picture of what’s going on in your company, and beyond, but also map out a path for the future.
Getting a 360-degree view of talent
Your talent analytics is only as strong as the questions you are asking it. HR departments often want to know the top sources for new candidates, or the average time taken to hire someone. Today’s People teams really need to understand who their biggest flight risks are, what can be done to make top talent stay, and how they can move the needle on DE&I.
Answering those bigger questions means thinking differently about your data. We believe you need to look at talent through the lens of skills and qualities, rather than work experience and job titles.
Step one is coming up with a job architecture, based on skills, that works for your business. Going beyond basic classification, this infrastructure of tasks and projects within the organization will include levels, role naming conventions, grades, the criteria for career movement, and of course compensation. Of particular importance is career paths: as companies struggle with retention, you need to have a job architecture that is transparent and shows people the career paths open to them, and what skills they need in order to grow.
“Effective job architecture reflects future talent needs, motivates behaviors that support the organization’s business strategies, and communicates a consistent language of work for employees.” Deloitte
At Beamery, we recommend using a Knowledge Graph to map this information. We also recommend thinking of roles through the lens of skills: our Universal Skills Platform could help.
The next step is understanding your people. People are more than just a fixed job role: they have capabilities, aspirations and potential; they have skills that are frequently overlooked in traditional organizational design. In fact, as we explained in our recent webinar, this more flexible way of understanding people and roles leads to more people doing the right work in the right moment, with the right tools. Data and analytics can help.
A clear picture of your global talent pool helps you identify skills gaps, look at internal mobility and upskilling opportunities, and help people (who might be close to leaving) fulfill their potential or find more meaning in their work.
In fact, if you can pull in skills data from your whole talent pipeline – candidates and alumni as well as employees – you will find you make huge gains when it comes to hiring, retention, engagement and development.
Taking data to the next level
Our clients also find it helpful to enhance their talent data with external sources, and bring in third-party insights related to the wider job market. This gives them useful benchmarks, and high quality data (in decent quantities) to analyze in a meaningful way.
From there, predictive applied AI will enable you to understand what skills you need to hire now and in the future. Discover how you can build a diverse team that will attract the next generation of workers, who is most likely to leave (and how to retain them), and what to do in various future scenarios.
Beamery Talent Analytics helps you get answers to the questions that matter regarding your talent. Get better insights across the candidate journey, understand how to retain and grow talent, by unifying internal and external talent data and tracking sentiment, and predict the future of your workforce, to stay ahead of the competition.