Supply Chain Innovation – Digital CxO Podcast EP100

Hello and welcome to the digital CXO podcast. I'm Amanda Ani and I'm excited to be here today with Jen Chu. She is the Vice President of Solutions and Consulting at Bristol Cone.

How are you doing today? I'm great. It's glad to be with you.

Wonderful. Happy to have you on the show. So can you share a little bit about yourself, your background, and then maybe about Bristol Cone and the services that you provide?

Yeah, sure. Well, as you mentioned, I lead solutions and consulting at Bristol Cone. We're a supply chain specialist organization, so we help global 2000 organizations, um, meet their challenges, whether or not it's around visibility or resiliency or cost efficiency.

Those are sort of the typical biggest challenges we see large companies struggling with as they think about how to, you know, plan, source and make their, um, their products. Um, I've been in consulting for, um, actually a little over 30 years now. Um, I started with Pricewaterhouse.

I spent time, um, working for them in both New York and London. So I started to get a little bit of international exposure. Um, I spent time at Forrester research, leading research into their enterprise applications space.

Um, and then along the way spent a little time at IBM and Deloitte and TCS all along the way, working with both business and IT executives, helping them solve challenges at the intersection of supply chain and technology. Wonderful. Well, it sounds like you're definitely the person to talk to about the transformation of the supply chain, which is our topic for today.

Great. Alright, so we're talking about innovation and transformation of the supply chain. So first off, what steps can company leaders undertake for strong partnerships between technology and talent in order to drive digital transformation?

Yeah, so thanks. I think that's a, a great question and, and not necessarily obvious for a lot of supply chain executives that we work with, right? They, they immediately, um, well frequently they will jump right to, it must be a tech problem, right?

Let me, what can SAP do for me here? Or what can you know, x, y, z fill in the blank, you know, specialist package do for me? And most of the time what we find is that even when organizations, you know, pick the right package, deploy the right technology, the supply chain transformation can still fail.

And we see that that root cause is often that the technology wasn't adopted, the people weren't trained, the people weren't ready for the change, or there's been too much change coming at the talent in the organization and it's overwhelming. Um, or just that the change was layered on top of everything they're already expected to do. And so, um, the dealing with the, the people challenges around a supply chain transformation is often underestimated.

Um, and, um, and under planned for. Yeah, absolutely. That is a big issue to consider.

So next, how can supply chain companies handle the evolving customer demands and the need for increased speed and efficiency? Yeah, so now you're asking about the demand planning, which is, um, really challenging and in a variety of different ways depending on which industry you are talking about, right? So if you're in a, uh, if you're a retailer, um, it's no longer just people walking into your storefront, right?

You've got people ordering in all sorts of different ways. So the multi-channel demand forecasting is complicated. Um, you've got, uh, you know, big, um, manufacturers who are dealing with, uh, whipsaw in demand on a global basis.

So there's a whole geopolitical aspect that, uh, organizations are now having to deal with. And then there's just changes in the buyer pattern. And I mean, even as, as, um, as specific as like, what's gonna be the impact of the tariff news right now that Trump has been elected?

There's a lot of uncertainty and demand that that sort of political news injects now into the conversation for planners. And so what we really try to advise our, our clients is that if you don't have visibility right, then anything that you anticipate or forecast or plan for is likely to be wrong, right? Already forecasting is hard, but if you're doing it without good baseline information, it's definitely gonna be wrong.

So starting with visibility is usually a good place to start. Yeah, absolutely. Well, how, what tips do you have for business leaders as far as how can they stay ahead of this evolving technology and and harness the technology to remain at the forefront of the supply chain?

Yeah, so here's where AI often comes into the picture. People assume that that's going to be a, um, panacea, right? It's gonna solve all of our problems, and it gets coverage like that sometimes.

And while I don't believe that's necessarily, you know, true, I'm not a total Pollyanna about ai, I do think there's a valid role for AI to play. Um, and it will be impactful across all of our, um, you know, our, uh, economy. But when we start to think about AI as a tool that organizations should have in, in their toolbox, it really starts with data readiness.

Um, the old adage, garbage in, garbage out is still true. And if you've got bad data or poor data, or you're missing data or poorly trained data, right, then you're only going to accelerate bad decisions. Um, and so we wanna, we start with a strong data foundation.

Um, next is the people challenge, which we hit right out of the gate. So if your people aren't ready for ai, if they've not been trained, if they now, uh, if they're unable to start to think in scenario and what if an interaction with the digital assistant, then that's a skillset we need to get ready and build out. And the organizations, um, we need to get people out of the rote day-to-day transactional activities and into problem solving.

And that's fundamentally a different challenge than most, uh, you know, uh, supply chain workers are, um, engaged with from, you know, if you just look at their, um, the way that they spend their eight or nine hour days in the office, it's a big shift with ai. So thinking about data, thinking about people, and then, you know, there's some IT things around hardware and software, which are probably not for the general audience, but you know, there's certainly investments that need to be made, made there all before you start to think about deploying that very specific AI bot or digital assistant. So we really encourage people to think foundationally first, um, as the AI digital assistant start to mature.

Absolutely. So communication is the key to most businesses success. So in talking about that, um, leadership between talent and staff members, how do we have good communication and, um, encourage staff members to embrace the new technology?

Yeah, I like to think about trust and transparency, and you can't have one without the other, right? If you're not transparent as a leader, if you're not talking about what the, uh, anticipated changes are, whether or not it's AI or any sort of change in the, in the organization, then you're probably not gonna have a lot of trust. And if you don't have a lot of trust, then what reason would the staff have to go along with any of your change management ideas?

Right? So I know it's something that I try to live by and, and with my own team is establishing, you know, that transparency to share as much as I possibly can about what amp what, what I'm anticipating, the types of challenges that, that I expect us to have to deal with sourcing answers from the team, not just telling them the answer. Um, I think that all creates a, uh, a virtuous cycle.

And so not a, you know, it's not a supply chain specific answer. I think that's just a good management and leadership, um, approach. Uh, but where we see our supply chain clients ex executing on that sort of trust and transparency, we see a far higher adoption rate in the technology investments that these leaders are banking on so heavily to help them improve their supply chain.

Do you have any use case examples you would be free to share of companies you've worked with that improved and, um, showed innovation within their supply chain? Supply chain? Yeah, actually, um, so we've, uh, developed 78 specific, uh, supply chain use cases at Bristol Cone, and we're working with our, our clients and we're at various levels of, of development and adoption across those 78.

'cause some are probably, you know, um, more drawing board at this point until the technology actually catches up. But where we're seeing a tremendous amount of excitement and investment is in the SNOP process. So sales and operations planning.

And I think one of the reasons why that has become such a lightning rod for AI investments, um, and transformation in general is that it's a really painful process. It's, you know, it takes a lot of, of days, sometimes weeks of preparation. It's a lot of senior executives, um, and it's a lot of guesswork.

And so all in all, that's a pretty expensive, um, and time consuming process. And so if there is a way that we can leverage technology to, um, shorten the cycle and improve the outcome, then that is certainly an area of interest for our, our clients. And I would say it's not just one client, it's, it's across the industry.

So we serve life sciences and med tech clients, we serve consumer products and retail clients, automotive clients, et cetera. And there are people in every industry that are asking us to specifically try to address their challenges in SNOP. So I, I think that's where we see the most energy and excitement around application of this AI technology.

It's a perfect fit for it. 'cause it's data intensive, it's a lot of what if scenarios. Um, so coupled on top of all of that data crunching, you still have to have, uh, there's still a complex set of decisions that needs to be made.

So it's a, it's a really great combination of the, the human making, the final decision and recommendation, but with a whole lot of analysis that we can now outsource to some sort of digital assistant on top of a mountain of data. Wonderful. Well, the world is constantly changing.

There's many factors to consider. And what are your thoughts as far as, uh, what can we expect two years from now in the world of supply chain management? Yeah, so I think that, um, right now AI is a lot of buzz.

I think two years from now we'll actually see a fair amount of, of deployment. The, um, so, you know, I I think there's a tremendous amount of data readiness that organizations are going through now. There's also a lot of experimentation happening with AI now.

I think if we're, if we were to have a conversation 24 months from now, we'd see, you know, a fair, the, the, the bell curve, right? We would see the more aggressive organizations with a fair amount of AI bots deployed throughout their organization. I don't think that in two years we're gonna have sort of push button supply chain technology and have outsourced all of our work to, uh, you know, to the system.

Um, but I do think we'll see, I don't know, 20 to 30% of the companies with, uh, maybe 10 to 15% of their processes really actually operating on, on ai. Um, yeah, had a, a discussion the other day with a, a gentleman who works in, um, AI advising, a lot of investment banking companies, and he said, the best place to start with AI is to outsource what you have your interns do today. And I thought that was a great way to think about getting started with ai.

If it's simple and it's tactical, what a great place to start and start to build some experience in your organization in using ai, but save those really sophisticated scenarios either for a human assisted leverage of ai, um, where you don't turn over the decision making, but you turn over some of the analysis to ai. So I think we'll start to see evolution in, in, you know, on that continuum. Interesting.

Yes. That does make sense. Well, if there was one key takeaway you could leave our audience with today, what would that be?

So I would say don't underestimate the amount of the effort it's gonna take to transform the people in your organization. And so I would encourage them to think about what are the, um, the, the cultural shifts that your organization needs to, to start to think about, um, empowering your people in order to start making decisions as opposed to educating them on how to perform tasks. And that is a tremendous shift for organizations.

Um, and I, I think that organizations who figure that out will really truly be the ones who can take advantage of AI in the long run. Wonderful. Well, thank you so much for coming on our show and sharing your insights with us today.

Thank you very much. And thank you to our audience. Stay tuned.

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