Start with data to build a better supply chain

In business, the acceleration of change means enterprises have to live in the future, not the present. Having the tools and technologies to enable forward-thinking and underpin digital transformation is key to survival. Supply chain procurement leaders are tasked with improving operational efficiencies and keeping an eye on the bottom line. For Raimundo Martinez, global digital solutions manager of procurement and supply chain at bp, the journey toward building a better supply chain starts with data.

“So, today, everybody talks about AI, ML, and all these tools,” says Martinez. “But to be honest with you, I think your journey really starts a little bit earlier. I think when we go out and think about this advanced technology, which obviously, have their place, I think in the beginning, what you really need to focus is in your foundational [layer], and that is your data.”

In that vein, all of bp’s data has been migrated to the cloud and its multiple procurement departments have been consolidated into a single global procurement organization. Having a centralized, single data source can reduce complexities and avoid data discrepancies. The biggest challenge to changes like data centralization and procurement reorganization is not technical, Martinez says, but human. Bringing another tool or new process into the fold can cause some to push back. Making sure that employees understand the value of these changes and the solutions they can offer is imperative for business leaders.

Honesty toward both employees and end users—where an enterprise keeps track of its logistics, inventory, and processes—can be a costly investment. For a digital transformation journey of bp’s scale, an investment in supply chain visibility is an investment in customer trust and business reputability.

“They feel part of it. They’re more willing to give you feedback. They’re also willing to give you a little bit more leeway. If you say that the tool is going to be, or some feature is going to be delayed a month, for example, but you don’t give the reasons and they don’t have that transparency and visibility into what is driving that delay, people just lose faith in your tool,” says Martinez.

Looking to the future, Martinez stresses the importance of a strong data foundation as a precursor to taking advantage of emerging technologies like AI and machine learning that can work to create a semi-autonomous supply chain.

“Moving a supply chain from a transactional item to a much more strategic item with the leverage of this technology, I think, that, to me, is the ultimate vision for the supply chain,” says Martinez.

This episode of Business Lab is produced in partnership with Infosys Cobalt.

Full Transcript

Raimundo Martinez: Hi, Laurel. Thanks for having me today.

Laurel: So, let’s start with providing some context to our conversation. bp has been on a digital transformation journey. What spurred it, and how is it going?

Raimundo: I think there’s many factors spurring digital transformation. But if I look at all of this, I think probably the key one is the rate of change in the world today and in the past. I think instead of slowing down, I think the rate of change is accelerating, and that makes business survivability the need to have quick access to the data to almost not live in today, but live in the future. And having tools and technologies that allow them to see what is coming up, what routes of action they can take, and then to enact those mitigation plans faster.

And I think that’s where the digital transformation is the key enabler of that. And I would say that’s on the business side. I think the other one is the people mindset change, and that ties into how things are going. I think things are going pretty good. Technology wise, I’ve seen a large number of tools and technologies adopted. But I think probably the most important thing is this mindset and the workforce and the adoption of agile. This rate of change that we just talked in the first part can only probably be achieved in tame when the whole workforce has this agile mindset to react to it.

Laurel: Well, supply chain procurement leaders are under pressure to improve operational efficiencies while keeping a careful eye on the bottom line. What is bp’s procurement control tower, and how has it helped with bp’s digital transformation?

Raimundo: Yeah, sure. In a nutshell, think about old as myriad of systems of record where you have your data and users having to go to all of those. So, our control tower, what it does, is consolidate all the data in a single platform. And what we have done is not just present the data, but truly configured the data in form of alerts. And the idea is to tell our user, “This is what’s important. This are the three things that you really need to take care now.” And not stopping there, but then saying, “Look, in order to take that action, we’re giving you a summary information so you don’t have to go to any other system to actually understand what is driving that alert.” But then on top of that, we’re integrating that platform with this system’s record so that request can complete it in seconds instead of in weeks.

So, that in a nutshell, it’s the control tower platform. And the way have helped… Again, we talk about tools and people. So, on the tool side, being able to demonstrate how this automation is done and the value of it and being able for other units to actually recycle the work that you have done, it accelerates and inspire other technical resources to take advantage of that. And then on the user side, one of the effects that have, again, this idea of the ability mindset, everything that we’ve done in the tool development is agile. So, bringing the users into that journey have actually helped us to also accelerate that aspect of our digital transformation.

Laurel: On that topic of workplace agility. In 2020, bp began a reorganization that consolidated its procurement departments into that single global procurement organization. What were the challenges that resulted from this reorganization?

Raimundo: Yeah. To give you a more context on that. So, if you think about bp being this really large global organizations divided in business units, before the organizations, every one of these business units have their own procurement departments, which handle literally billions of dollars that’s how big they were. And in that business, they have the ERP systems, your contract repository, your process and process deviation. But you only manage the portfolio to that. Once you integrate all of those organizations into a single one, now your responsibility become across some of those multiple business units, that has your data in all of these business systems.

So, if you want to create a report, then it’s really complicated because you have to not only go to these different systems, but the taxonomy of the data is different. So, an example, some business will call their territory, North America, the other one will call it east and west coast. So, if you want a report for a new business owner, it becomes really, really hard, and also the reports might not be as complete as they are. So, that really calls for some tools that we need to put in place to support that. And on top of that, the volume of requests now is so greater that just changing and adding steps to process aren’t going to be enough. You really need to look into automation to satisfy this higher demand.

Laurel: Well, speaking of automation, it can leverage existing technology and build efficiencies. So, what is the role of advanced technologies, like AI, machine learning and advanced analytics in the approach to your ongoing transformation?

Raimundo: So, today, everybody talks about AI, ML, and all these tools. But to be honest with you, I think your journey really starts a little bit earlier. I think when we go out and think about this advanced technology, which obviously, have their place, I think in the beginning, what you really need to focus is in your foundational, and that is your data. So, you ask about the role of the cloud. So, for bp, what we have done is all of the data used to reside in multiple different sites out there. So, what we have done is all the data now has been migrated to the cloud. And then what the cloud also allows is to do transformations in place that help us really homogenize, what I just described before, North America, South America, then you can create another column and say, okay, now call it, whatever, United States, or however you want to call it.

So, all of this data transformation happened in a single spot. And what that does is also allow our users that need this data to go to a single source of truth and not be pulling data from multiple systems. An example of the chaos that that creates is somebody will be pulling invoice and data from Spence, somebody will pull in PayData. So, then you already have data discrepancy on the reporting. And having a centralized tool where everybody goes for the data reduces so much complexity on the system.

Laurel: And speaking about that kind of complexity, it’s clear that multiple procurement systems made it difficult to maintain quality compliance as well, and as well as production tracking in bp supply chain. So, what are some of the most challenging aspects of realizing this new vision with a centralized one-stop platform?

Raimundo: Yeah, we have a good list in there. So, let me break it into maybe technical and people, because I think people is something that we should talk about it. So, technical. I think one of the biggest things in technical is working with your technical team to find the right architecture. This is how your vision fits into our architecture, which will create less, let’s say, confusion and complexity into your architecture. And the other side of the technical challenge is finding the right tools. I’ll give you an example for our project. Initially, I thought, okay, RPA [robotic process automation] will be the technology to do this. So, we run a pilot RPA. And obviously, RPA has incredible applications out there. But at this point, RPA really wasn’t the tool for us given the changes that could happen on the screens from the system that we’re using. So, then we decided instead of going to RPA, going to API.

So, that’s an example of a challenge of finding exactly the right tool that you have. But to be honest with you, I think the biggest challenge is not technical, but human. Like I mentioned before, people are immersed in the sea of change that is going on, and here you come with yet another tool. So, even the tool you’re giving them might be a lot more efficient, people still want to cling to what they know. So, if they say, “Look, if I have to spend another two hours extracting data, putting Excel, collating and running a report…” Some people may rather do that than go to a platform where all of that is done for them. So, I think change management is key in these transformations to make sure that they’re able to sell or make people understand what the value of the tool is, and overcome that challenge, which is human normal aversion to change. And especially when you’re immersed on this really, really sea of change that was already going as a result of the reorganization.

Laurel: Yeah. People are hard, and tech can be easy. So, just to clarify, RPA is the robotic process automation in this context, correct?

Raimundo: Yeah, absolutely. Yeah. Sorry about the pretty layered… Yeah.

Laurel: No, no. There’s lots of acronyms going around.

So, inversely, we’re just discussing the challenges, what are the positive outcomes from making this transformation? And could you give us an example or a use case of how that updated platform boosted efficiency across existing processes?

Raimundo: Absolutely. Just quick generic. So, generic things is you find yourself a lot in this cycle of that data. The users look at the applications that said that data’s not correct, and they lose the appetite for using that, but the problem is they own the data, but the process to change the data is so cumbersome that people don’t really want to take ownership of that because they said, “Look, I have 20 things to do. The least in my list is updating that data.”

So, we’re in this cycle of trying to put tools out for the user, the data is not correct, but we’re not the ones who own the data. So, the specific example of how we broke that cycle is using automation. So, to give you an example, before we create automation, if you needed to change any contract data, you have to find what the contract is, then you have to go to a tool like Salesforce and create a case. That case goes to our global business support team, and then they have to read the case, open the system of record, make the change. And that could take between days or weeks. Meantime, the user is like, “Well, I requested this thing, and it hasn’t even happened.”

So, what we did is leverage internal technology. We already had a large investment on Microsoft, as you can imagine. And we said, look, “From Power BI, you can look at your contract, you can click on the record you want to change. Power App comes up and tells you what do you want to do.” Say, I want to change the contract owner, for example. It opens a window, says, “Who’s the new person you want to put in?” And as soon as you submit it, literally, within less than a second, the API goes to the system of record, change the owner, creates an email that notifies everybody who is an stakeholder in that contract, which then increases visibility to changes across the organization.

And at the same time, it leaves you an audit trail. So, if somebody wants to challenge that, you know exactly what happened. So, that has been an incredible outcome of reducing cycle time from days and weeks to merely seconds, at the same time, increasing communication and visibility into the data. That has been proved one of the greatest achievements that we have.

Laurel: Well, I think you’ve really outlined this challenge. So, investing in supply chain visibility can be costly, but often bolsters trust and reputability among customers. What’s the role of transparency and visibility in a digital transformation journey of this size?

Raimundo: I keep talking about agile, and I think that’s one of the tenets. And what I will add to transparent visibility, I would add actually honesty. I think it’s very, very easy to learn from success. Everybody wants to tout the great things that they have done, but people may a little bit less inclined to speak out about their mistakes. I’ll just give you an example of our situation with RPA. We don’t feel bad about it. We feel that the more we share that knowledge with the technical teams, the much more value it has because then people will learn from that again and not commit the same mistake obviously.

But I think also what honesty do in this visibility is when you bring your users into the development team, you have that visibility. They feel part of it. They’re more willing to give you feedback. And also, they’re also willing to give you a little bit more leeway. If you say that the tool is going to be, or some feature is going to be delayed a month, for example, but you don’t give the reasons and they don’t have that transparency and visibility into what is driving that delay, people just lose faith in your tool.

Where I think the more open, the more visible you are, but also, again, with honesty, is you have a product that is so much more well received and that everybody feels part of the tool. It’s something that in every training, at the end of the training, I just say, “By the way, this is not my tool. This is your tool. And the more engaged you are with us, the much better outcome you’re going to have.” And that’s just achieved through transparency and visibility.

Laurel: So, for other large organizations looking to create a centralized platform to improve supply chain visibility, what are some of the key best practices that you’ve found that leadership can adopt to achieve the smoothest transition?

Raimundo: So, I probably think about three things. I think, one, the leadership needs to really, really do is understand the project. And when I say, understand the project, is really understanding the technical complexity, the human aspect of it, because I think that’s where your leadership has a lot of role to play. They’re able to influence their teams on this project that you’re trying to… And then they really need to understand also what are the risks associated with this project. And also that these could be a very lengthy journey. Hopefully, obviously, there’ll be results and milestones along, but they need to feel comfortable with also this agile mentality that we’re going to do features, fail, adapt, and they really need to be part of that journey.

The second biggest, I think, most important thing is having the right team. And in that, I think I’ve been super fortunate. We have a great partnership with Infosys. I’ve got one of the engineers named Sai. What the Infosys team and my technical team says is, “Look, do not shortchange yourself on the ideas that you bring from the business side.” A lot of times, we might think about something as impossible. They really encourage me to come up with almost crazy ideas. Just come with everything that you can think about. And they’re really, really incredible of delivering all the resources to bring in a solution to that. We almost end up using each other’s phrases. So, having a team that is really passionate about change, about being honest, about working together is the key to delivery. And finally, data foundation. I think that we get so stuck looking at the shiny tools out there that seem like science fiction and they’ll be great, and we forget that the outcome of those technologies are only as good as the data that we are supporting.

And data, a lot of times, it seem as like the, I don’t know, I don’t want to call it ugly sister, the ugly person in the room. But it’s really people… They’re like, “Oh, I don’t want to deal with that. I just want to do AI.” Well, your AI is not going to give you what you want if it doesn’t understand where you’re at. So, data foundation is key. Having the perfect team and technology partners and understanding the project length, the risk and being really engaged will be, for me, the key items there.

Laurel: That’s certainly helpful. So, looking ahead, what technologies or trends do you foresee will enable greater efficiencies across supply chain and operations?

Raimundo: It’s not like a broken record, bet. I really think that technologies that look at our data and help us clean the data, foresee what items we’re going to have with the data, how we can really have a data set that is really, really powerful, that is easy, and it has reflects exactly our situation, it’s the key for then the next step, which is all of these amazing technologies. If I think about our vision, for the platform is to create a semi-autonomous supply chain. And the vision is imagine having, again, first, the right data, and now what you have is AI/ML and all these models that look at that internal data, compare that with external factors.

And what it does is instead of presenting us alerts, we’ll go to the next level, and it, basically, presents scenarios. And say, “Look, based on the data that I see on the market, what you have had in your history, these are the three things that can happen, these are the plans that the tool recommends, and this is how you interact or affect that change.” So, moving a supply chain from a transactional item to a much more strategic item with the leverage of this technology, I think, that, to me, is the ultimate vision for supply chain.

Laurel: Well, Raimundo, thank you so much for joining us today on the Business Lab. This has been very enlightening.

Raimundo: Thank you. I’ve been a pleasure. And I wish everybody a great journey out there. It’s definitely a very exciting moment right now.

Laurel: Thank you.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.