Workday Podcast: How Coca-Cola Is Trailblazing the Skills Movement

Consumer packaged goods companies are under enormous pressure to innovate at a fast pace. Max Just, global director of business intelligence at Coca-Cola, discusses how the company is using machine learning to connect the future of work to new opportunities for its internal talent pool.

Josh Krist July 01, 2020
Image placeholder

This podcast was recorded in October 2019. While the world looks a lot different today, we believe this content remains valuable for helping organizations move forward.

One of my favorite memories was a time I was in the middle of the Egyptian desert in a little place called Siwa Oasis, not far from the Libyan border. I had just come into town after what felt like a 90-hour bus ride from Alexandria. I was hot, tired, and thirsty. There was Coke on the menu, so I got one. I'd always liked Coca-Cola, but in that moment nothing had ever tasted so delicious. Coca-Cola tastes like home like nothing else does, and I'm guessing that's true for many people no matter where they're from. 

That's why I was so excited to talk to Max Just, global director of business intelligence at Coca-Cola, on the Workday Podcast about how the company is maintaining a truly iconic brand while not only keeping up, but getting ahead.

Listen on SoundCloud: How Coca-Cola is Trailblazing the Skills Movement

Listen on Apple Podcasts: How Coca-Cola is Trailblazing the Skills Movement

Below you’ll find excerpts from the conversation, edited for clarity. You can find our other Workday Podcasts here.

Josh Krist: Can you tell me about some of the unique challenges that are facing the consumer packaged goods industry?

Max Just: The behaviors of the consumers are changing. Technology is transforming the marketplace at a pace that we've never seen before, and that impacts most of the CPG companies out there. The pressure to innovate at a fast pace is very high, and that forces all of us to rethink the way we do work, the way we go to market, and the way we organize ourselves. And that also forces us to shift our mind-sets and approach the work in a more agile way.

Krist: What are you doing about getting ahead or addressing some of these challenges, especially around skills?

Just: I'm responsible for HR technology, among other things, and that is a great place to be at the moment because it is changing so rapidly. It's a live representation of what we are seeing right now in the marketplace, and some of those technologies are playing a key role in enabling the way we'll work in the future. At the moment, for example, I'm experimenting with how to use machine learning for skills and the internal talent marketplace. Essentially, one of the problems that I'm trying to solve is how to surface the skills that we have available within the organization and connect it to opportunities for people to have new experiences at work. 

Krist: How are you doing that?

Just: We started working with a Workday solution called skills miner, which essentially allows us to look at the talent that we have within the organization and understand their skills—not only by their self-reported skills, but also the skills that are hidden in past experience that maybe aren’t normally labeled on a resume. Workday machine learning solutions are helping us identify all of that. This is great because when we tested skills miner in our test environment for the first time, we identified a significant amount of new skills.

Krist: Yeah, that makes sense. I was just sitting here thinking that I've never put interviewing or podcasting down as a skill on any resume or any job profile before, but it's something I've been doing for 25 years now.

Just: Yeah, and somewhere hidden in your descriptions of what you did in the past, the newer technologies are starting to identify those things and serve them to those that are looking for those types of skills.

Krist: Are there certain populations that you're looking at?

Just: We’re not limiting it at the moment because we're still learning how it works, how to adjust the different data elements, and the best way to utilize them. For example, think of a manager who wants to do a certain project, but for whatever reason, they are missing the key skill set that enables that particular project. In the traditional world, they would go and recruit for that skill in the outside market or they would bring on a contractor or a consultant. As you can imagine, that is a longer process, and prevents an associate within the company who may already have that skill from developing it even further.

Krist: So can you talk about the impact this will have on your teams?

Just: We're just starting to experiment with all of this, so it's hard to predict what all the impacts will be, but there are two clear stakeholder groups that are going to be positively impacted. If you look at it from an associate perspective, one of the key benefits is that whatever it is that they know how to do, it will be surfaced to those who are looking for those skills in real time. If we couple that with the information that we have about associates in terms of what they want to do next in their career, we can identify and suggest next steps in their careers, such as new learning opportunities to short-term assignments or projects. So all those things put together could help an associate take more control over their career than what they can do today. For leaders, many of them have the intent to develop their talent, but they may not have all the information that they need in order to help steer the careers of people that work for them. In the future, that connection will be much more feasible and dynamic due to the development of tools around skills and machine learning in the marketplace.

Krist: Do you have any thoughts about how machine learning will disrupt or change the consumer packaged goods industry in the next 10 years?

Just: From my point of view, one of the key disruptions of the future is the abundance of real-time data that the digital economy will continue to bring. That will change the way we do business with our consumers because we will know significantly more about them. More data will be available about them and about what they may need, allowing us to use that data to try to win in the marketplace. So, for CPG companies, we'll have the opportunity to provide better products at the right time and even predict the needs of the consumers, particularly as connectivity continues to grow in its availability around the world. So that brings a lot of opportunities, definitely, but it also brings a lot of challenges because companies are not necessarily wired to use all that data and make decisions as fast as that data suggests. I think that is going to force the industries to have the necessary infrastructure to make decisions based on it and change very quickly.

If you think about industries where the supply chain is so rigid, that's where I think machine learning plays a key role. By delivering and deploying the right tools to assess and serve the insights of that data in real time into the hands of decision-makers, it's critical to win in the marketplace.

Krist: That makes perfect sense. So what advice would you give to other companies looking to capitalize on machine learning?

Just: I would advise to be brave. There is a lot to discover and those that lead from the front will reap the benefits of it very quickly. Most importantly, be agile. Now more than ever, shifting from a traditional mind-set into a mind-set of failing fast, learning from it, and trying again will produce more benefits than putting the best solution out there over a longer period of time, because as time passes that solution will probably no longer be relevant.

Krist: Switching gears just a little bit, you selected Workday Human Capital Management in 2015. What ultimately led to your selection and what were you hoping to achieve?

Just: We were coming from a very dated on-premise solution that was highly customized to multiple locations around the world, and it’s hard to get a full visibility of what’s going on from an HR perspective when you are set up that way. The processes were very cumbersome, and the data wasn't easy to surface and learn from. We were looking for something significantly more modern that could bring innovation at a faster pace. We selected Workday among the competitors at the time.

Krist: Can you talk a little bit about your HR transformation since then?

Just: Our HR transformation started in 2010, when we set up our first a shared services organization in Latin America. That's the time that I started at Coke, initially as a consultant and then as an employee. What we first did was set up shared services centers of excellence that would work with corporate HR and their strategic business partners from around the world to drive the best services to the marketplace. Then we created shared services centers in three locations around the world, still working with our own old technology, but we put internal call centers and CRM to manage the needs of our internal clients. The last thing that we did was replace our HR system, which we started looking into in 2015, and went live in 2017 with Workday. So that, in a nutshell, is what we've done. And then since then, we've constantly had to iterate the way we do work, based on the things that we were just describing. The needs of the business constantly change, and we need to adapt and be more agile as well.

Krist: Earlier I asked about advice for companies wanting to integrate machine learning. Would your advice be the same for companies wanting to transform and modernize their HR systems and the way they deliver HR?

Just: I think it's a much larger initiative to drive depending on where you start from, the amount of work that needs to get done is quite significant. If I had the opportunity to do it all over again, I would think about bringing in newer technology, such as Workday, earlier than when we did. The amount of transformation that we can drive with such an implementation is so high that it's probably a very good place to start from. My advice is just look at how you can leverage technology right off the bat versus at the end.

Krist: Because technology does change your processes, right?

Just: It does. We’ve got to be very careful that we don't drive the experience from the process, but the process to follow the experience, if you know what I mean.

Krist: That makes perfect sense. So is machine learning the next big game-changer when it comes to your HR transformation?

Just: It's a key part of it, definitely. As part of the new generation of employees, they have an interest in doing new things on a constant basis. It’s quite hard because the regular mechanism for that is to first identify the job that you want to do, which is typically identified by talking to people or looking at postings, applying to them, and hopefully a few months later, you'll get the job and start transitioning from your old one. The younger generations don't have that level of patience. Their curiosity and their willingness to do new things more frequently is something that we haven't seen before, and therefore, we're not wired to do it. I think machine learning plays a key role in identifying what those people want to do and, at the same time, helps their leaders and managers in the organization connect with them and build an avenue so that opportunity turns into real-life experience in a much more dynamic way than the process that I described before. So hopefully that will help us retain the talent that is curious and willing to do new things, and then most importantly, reap the benefits of the experiences that they gain.

Krist: Right, very interesting. Well, that's all the time we have for today. I want to thank my guest, Max Just, global director of Business Integration at Coca-Cola, for joining me. I’m Josh Krist on the Workday Podcast—please subscribe on iTunes or your favorite podcast app. Thank you very much.

More Reading