John Healy lives on the front lines of the talent supply chain. As VP & Managing Director for Kelly’s Outsourcing & Consulting Group, he designs and delivers data based insights that connect employers and talent with higher engagement and less risk. He heads up Kelly Services R&D function and has the pleasure of engaging with curious clients, candidates, and colleagues eager to explore the possibilities of automation and artificial intelligence.
In this Q&A, Healy discusses how analytics and automation inform decisions within your talent supply chain, as well as why his team is on a mission to simplify the complexities to make dramatic change more consumable and palatable.
RIX: What are the most exciting developments in automation and AI you’re seeing?
JH: With the consumerization of work, we’re really seeing the creativity and entrepreneurial spirit of our industry come into play. Things are happening right now, and it’s fun. We’re past the “chicken little moment” about automation replacing jobs. Yes, many jobs are going to be reconfigured or restructured, but every time there’s been an industrial revolution new jobs have been formed. I’m excited to observe these developments as they’re happening and jump on them early.
RIX: What practical applications are coming into their own?
JH: When you say “automation,” people tend to think of physical robots. But with RPA—robotic process automation—you’re zipping right through rote processes to create efficiencies. Wherever you have standardized and rules-based activity, such as tax filings or data entry, you have an opportunity to take SG&A costs out of the business.
In recruitment, we’re seeing inroads into candidate engagement, particularly with chatbots. When done well, they make the recruitment process more personal and responsive. Unfortunately, when done poorly, they make you feel like you’ve been dumped in a system you can’t get out of.
RIX: Your role merges digital and recruiting strategies. How can analytics and automation inform talent supply decisions?
JH: You can’t rely on a pure automation strategy; operational expertise also has to come into play. Let’s start with something like standardizing job taxonomy. What you call an accountant and what I call an accountant may be two different jobs. As much as systems cannot do a great job with organizing unstructured data, we can accelerate that process by engaging the front line operations team to validate, thus creating benchmarks that can be trusted.
On a grander level, we can inject science into the talent supply chain to help analyze buy-build-borrow strategies:
- The buy strategy is straightforward – if internal talent isn’t sufficient, we buy it on the external market.
- With build, you develop needed skills over time within your employee population.
- But if you need to borrow the talent—to use resources from another organization to help accomplish the work—how do you know which model works for your business? When do you use traditional temporary labor, or get an outcome from a service provider, or leverage the platform economy?
Once you have the visibility into those mediums, you can start to discover the right ratio of each input type, allowing you to achieve the business goals that you have laid out, within the individual labor market you are operating in! The business strategy of how work gets accomplished is being elevated, and when you have the data, you can tell some amazing stories.
RIX: What are some real-life examples?
JH: So if a client needs to drive cost out of their workforce, what’s a typical first move? A hiring freeze. But we can often demonstrate the unintended consequences, such as increasing their cost level by 60% due to turnover and higher costs for borrowed labor. Before they rush to a strategy, we try to help companies rethink their strategy beyond the old norms. Not everyone’s open-minded, though. It’s like consumers – some are early adopters, and some are not.
It’s our job is to take all this complexity and make it simple for their environment. It’s like the quote attributed to Mark Twain, “I didn’t have time to write a short letter, so I wrote a long one instead.” As partners, we must be willing to take the time to simplify the story to make the change consumable. Otherwise, people get fearful.
RIX: Have you encountered any unexpected applications?
JH: Here’s one. At Kelly we’ve always said the future of work has four dimensions – workforce, workplace, technology, and social norms. We’re dealing with dramatic changes in the workplace that are affecting the other areas. Think about your physical work environment. The place you call work, the chair you’re sitting in, has changed dramatically over the last five to ten years and it’s going to change more.
Not all companies have thought this through. They’re making 30-year decisions about facilities and workplaces, yet how often are they engaged into the workforce planning process? What type of culture are you looking to create? Do your facilities and workforce plans align? How will it be impacted by the “gig economy”?
RIX: What are some of the limitations to adopting automated solutions?
JH: We’re seeing a lot of players in the market promoting their ‘unique’ algorithms looking for business or investors. But those algorithms aren’t going to get smarter unless and until they’re applied against large volumes of data. It’s as if everyone is willing to spend a million dollars on machine learning technology, but they’re only applying it to about $10,000 worth of data. The data sets just aren’t big enough yet to make machine learning fully viable.
But that’s why there are so many great opportunities for creative collaboration, particularly across non-parallel industries. As boundaries are crossed, machines will get smarter much faster. At Kelly, we’ve experienced that first-hand by tapping into our supplier community. They’ve delivered some “a-ha moments” that have unlocked more value from our analytics.
RIX : As a talent advisor, who are you typically working within an organization to build long-term strategies?
JH: It’s easy to say, “You have to deal with the C-suite,” but we’re seeing a lot more of operations, HR, and procurement coming together today. Procurement and HR created centralized models that reduce risk through standardization and lower costs through scale. But more often, the consumerization of work means that those models simply are not fit for purpose. Because of this, we are spending more time with line management and focusing on the user experience.
RIX: When looking across different perspectives and verticals, how does Kelly as a team stay forward-thinking enough to be able to offer compelling input? How do you scale?
JH: Read incessantly and don’t be afraid of what’s possible. My core role is R&D for the company, and my passion is talking to people who are curious. As design thinking becomes a norm and more companies think about it, the dialogue has become so much richer. It’s why I travel as much as I do; I need to sit with customers but also with talent.
RIX: One final question, what’s the origin of your Twitter handle @unclejunkmuses?
JH: It started because my oldest nephew got John and Uncle mixed up. I’m the youngest of eight children, and all my 20-odd nieces and nephews refer to me as Uncle Junk. By itself that handle was taken, but I like telling stories, so it became @unclejunkmuses.