The next BriefingsDirect technology innovation thought leadership discussion explores how rapid advances in artificial intelligence (NYSE:AI) and machine learning are poised to reshape procurement -- like a fast-forwarding to a once-fanciful vision of the future.
Whereas George Jetson of the 1960s cartoon portrayed a world of household robots, flying cars, and push-button corporate jobs -- the 2017 procurement landscape has its own impressive retinue of decision bots, automated processes, and data-driven insights.
We won't need to wait long for this vision of futuristic business to arrive. As we enter 2017, applied intelligence derived from entirely new data analysis benefits has redefined productivity and provided business leaders with unprecedented tools for managing procurement, supply chains, and continuity risks.
To learn more about the future of predictive -- and even proactive -- procurement technologies, please welcome Chris Haydon, Chief Strategy Officer at SAP Ariba. The discussion is moderated by BriefingsDirect's Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: It seems like only yesterday that we were content to gain a common view of the customer or develop an end-to-end bead on a single business process. These were our goals in refining business in general, but today we've leapfrogged to a future where we're using words like "predictive" and "proactive" to define what business function should do and be about. Chris, what's altered our reality to account for this rapid advancement from visibility into predictive -- and on to proactive?
Haydon: There are a couple of things. The acceleration of the smarts, the intelligence, or the artificial intelligence, whatever the terminology that you identify with, has really exploded. It's a lot more real, and you see these use-cases on television all the time. The business world is just looking to go in and adopt that.
And then there's this notion of the Lego block of being able to string multiple processes together via an API is really exciting -- that coupled with the ability to have insight. The last piece, the ability to make sense of big data, either from a visualization perspective or from a machine-learning perspective, has accelerated things.
These trends are starting to come together in the business-to-business (B2B) world, and today, we're seeing them manifest themselves in procurement.
Gardner: What is it about procurement as a function that's especially ripe for taking advantage of these technologies?
Haydon: Procurement is obviously very transaction-intense. Historically, what transaction intensity means is people, processing, exceptions. When we talk about these trends now, the ability to componentize services, the ability to look at big data or machine learning, and the input on top of this contextualizes intelligence. It's cognitive and predictive by its very nature, a bigger data set, and [improves] historically inefficient human-based processes. That's why procurement is starting to be at the forefront.
Gardner: Procurement itself has changed from the days of when we were highly vertically integrated as corporations. We had long lead times on product cycles and fulfillment. Nowadays, it's all about agility and compressing the time across the board. So, procurement has elevated its position. Anything more to add?
Haydon: Everyone needs to be closer to the customer, and you need live business. So, procurement is live now. This change in dynamic -- speed and responsiveness -- is closer to your point. It's also these other dimensions of the consumer experience that now has to be the business-to-business experience. All that means same-day shipping, real-time visibility, and changing dynamically. That's what we have to deliver.
Gardner: If we go back to our George Jetson reference, what is it about this coming year, 2017? Do you think it's an important inception point when it comes to factoring things like the rising role of procurement, the rising role of analytics, and the fact that the Internet of Things (IoT) is going to bring more relevant data to bear? Why now?
Haydon: There are a couple of things. The procurement function is becoming more mature. Procurement leaders have extracted those first and second levels of savings from sourcing and the like. And they have control of their processes.
With cloud-based technologies and more of control of their processes, they're looking now to how they're going to serve their internal customers by being value-generators and risk-reducers.
How do you forward the business, how do you de-risk, how do you get supply continuity, how do you protect your brand? You do that by having better insight, real-time insight into your supply base, and that's what's driving this investment.
Gardner: We've been talking about Ariba being a 20-year-old company. Congratulations on your anniversary of 20 years.
Haydon: Thank you.
AI and bots
Gardner: You're also, of course, part of SAP. Not only have you been focused on procurement for 20 years, but you've got a large global player with lots of other technologies and platform of benefits to avail yourselves of. So, that brings me to the point of AI and bots.
It seems to me that right at the time when procurement needs help, when procurement is more important than ever, that we're also in a position technically to start doing some innovative things that get us into those words "predictive" and more "intelligent."
Set the stage for how these things come together.
Haydon: You allude to being part of SAP, and that's really a great strength and advantage for a domain-focused procurement expertise company.
The machine-learning capabilities that are part of a native SAP HANA platform, which we naturally adopt and get access to, put us on the forefront of not having to invest in that part of the platform, but to focus on how we take that platform and put it into the context of procurement.
There are a couple of pretty obvious areas. There's no doubt that when you've got the largest B2B network, billions in spend, and hundreds and millions of transactions on invoicing, you apply some machine learning on that. We can start doing a lot smarter matching an exception management on that, pretty straightforward. That's at one end of the chain.
On the other end of the chain, we have bots. Some people get a little bit wired about the word "bot," "robotics," or whatever, maybe it's a digital assistant or it's a smart app. But, it's this notion of helping with decisions, helping with real-time decisions, whether it's identifying a new source of supply because there's a problem, and the problem is identified because you've got a live network. It's saying that you have a risk or you have a continuity problem, and not just that it's happening, but here's an alternative, here are other sources of a qualified supply.
Gardner: So, it strikes me that 2017 is such a pivotal year in business. This is the year where we're going to start to really define what machines do well, and what people do well, and not to confuse them. What is it about an end-to-end process in procurement that the machine can do better that we can then elevate the value in the decision-making process of the people?
Haydon: Machines can do better in just identifying patterns -- clusters, if you want to use a more technical word. They transform category management and enables procurement to be at the front of their internal customer set by looking not just at their traditional total cost of ownership (NYSE:TCO), but total value and use. That's a part of that real dynamic change.
What we call end-to-end, or even what SAP Ariba defined in a very loose way when we talked about upstream, it was about outsourcing and contracting, and downstream was about procurement, purchasing, and invoicing. That's gone, Dana. It's not about upstream and downstream, it's about end-to-end process, and re-imagining and reinventing that.
The role of people
Gardner: When we give more power to a procurement professional by having highly elevated and intelligent tools, their role within the organization advances and the amount of improvement they can make financially advances. But I wonder where there's risk if we automate too much and whether companies might be thinking that they still want people in charge of these decisions. Where do we begin experimenting with how much automation to bring, now that we know how capable these machines have been, or is this going to be a period of exploration for the next few years?
Haydon: It will be a period of exploration, just because businesses have different risk tolerances and there are actually different parts of their life cycle. If you're in a hyper growth mode and you're pretty profitable, that's a little bit different than if you're under a very big margin pressure.
For example, maybe if you're in high tech in the Silicon Valley, and some big names that we could all talk about are, you're prepared to be able to go at it, and let it all come.
If you're in a natural-resource environment, every dollar is even more precious than it was a year ago.
That's also the beauty, though, with technology. If you want to do it for this category, this supplier, this business unit, or this division you can do that a lot easier than ever before and so you go on a journey.
Gardner: That's an important point that people might not appreciate, that there's a tolerance for your appetite for automation, intelligence, using machine learning, and AI. They might even change, given the context of the certain procurement activity you're doing within the same company. Maybe you could help people who are a little bit leery of this, thinking that they're losing control. It sounds to me like they're actually gaining more control.
Haydon: They gain more control, because they can do more and see more. To me, it's layered. Does the first bot automatically requisition something -- yes or no? So, you put tolerances on it. I'm okay to do it if it is less than $50,000, $5,000, or whatever the limit is, and it's very simple. If the event is less than $5,000 and it's within one percent of the last time I did it, go and do it. But tell me that you are going to do it or let's have a cooling-off period.
If you don't tell me or if you don't stop me, I'm going to do it, and that's the little bit of this predictive as well. So you still control the gate, you just don't have to be involved in all the sub-processes and all that stuff to get to the gate. That's interesting.
Gardner: What's interesting to me as well, Chris, is because the data is such a core element of how successful this is, it means that companies in a procurement intelligence drive will want more data, so they can make better decisions. Suppliers who want to be competitive in that environment will naturally be incentivized to provide more data, more quickly, with more openness. Tell us some of the implications for intelligence brought to procurement on the supplier? What we should expect suppliers to do differently as a result?
Notion of content
Haydon: There's no doubt that, at a couple of levels, suppliers will need to let the buyers know even more about themselves than they have ever known before.
That goes to the notion of content. It's like there is unique content to be discovered, which is whom am I, what do I do well and demonstrate that I do well. That's being discovered. Then, there is the notion of being able to transact. What do I need to be able to do to transact with you efficiently whether that's a payment, a bank account, or just the way in which I can consume this?
Then, there is also this last notion of the content. What content do I need to be able to provide to my customer, aka the end user, for them to be able to initiate the business with them?
These three dimensions of being discovered, how to be dynamically transacted with, and then actually providing the content of what you do even as a material of service to the end user via the channel. You have to have all of these dimensions right.
That's why we fundamentally believe that a network-based approach, when it's end to end, meaning a supplier can do it once to all of the customers across the [Ariba] Discovery channel, across the transactional channel, across the content channel is really value adding. In a digital economy, that's the only way to do it.
Gardner: So this idea of the business network, which is a virtual repository for all of this information isn't just quantity, but it's really about the quality of the relationship. We hear about different business networks vying for attention. It seems to me that understanding that quality aspect is something you shouldn't lose track of.
Haydon: It's the quality. It's also the context of the business process. If you don't have the context of the business process between a buyer and a seller and what they are trying to affect through the network, how does it add value? The leading-practice networks, and we're a leading-practice network, are thinking about Discovery. We're thinking about content; we're thinking about transactions.
Gardner: Again, going back to the George Jetson view of the future, for organizations that want to see the return on their energy and devotion to these concepts around AI, bots, and intelligence. What sort of low-hanging fruit do we look for, for assuring them that they are on the right path? I'm going to answer my own question, but I want you to illustrate it a bit better, and that's risk and compliance and being able to adjust to unforeseen circumstances seems to me an immediate payoff for doing this.
Severance of pleadings
Haydon: The United Kingdom is enacting a law before the end of the year for severance of pleadings. It's the law, and you have to comply. The real question is how you comply.
You eye your brand, you eye your supply chain, and having the supply-chain profile information at hand right now is top of mind. If you're a Chief Procurement Officer (CPO) and you walk into the CEO's office, the CEO could ask, "Can you tell me that I don't have any forced labor, I don't have any denied parties, and I'm Office of Foreign Assets Control (OFAC) compliant? Can you tell me that now?"
You might be able to do it for your top 50 suppliers or top 100 suppliers, and that's great, but unfortunately, a small, $2,000 supplier who uses some forced labor in any part of the world is potentially a problem in this extended supply chain. We've seen brands boycotted very quickly. These things roll.
So yes, I think that's just right at the forefront. Then, it's applying intelligence to that to give that risk threshold and to think about where those challenges are. It's being smart and saying, "Here is a high risk category. Look at this category first and all the suppliers in the category. We're not saying that the suppliers are bad, but you better have a double or triple look at that, because you're at high risk just because of the nature of the category."
Gardner: Technically, what should organizations be thinking about in terms of what they have in place in order for their systems and processes to take advantage of these business network intelligence values? If I'm intrigued by this concept, if I see the benefits in reducing risk and additional efficiency, what might I be thinking about in terms of my own architecture, my own technologies in order to be in the best position to take advantage of this?
Haydon: You have to question how much of that you think you can build yourself. If you think you're asking different questions than most of your competitors, you're probably not. I'm sure there are specific categories and specific areas on tight supplier relationships and co-innovation development, but when it comes to the core risk questions, more often, they're about an industry, a geography, or the intersection of both.
Our recommendation to corporations is never try and build it yourself. You might need to have some degree of privacy, but look to have it as more industry-based. Think larger than yourself in trying to solve that problem differently. Those cloud deployment models really help you.
Gardner: So it really is less of a technical preparatory thought process than process being a digital organization, availing yourself of cloud models, being ready to think about acting intelligently and finding that right demarcation between what the machines do best and what the people do best.
Haydon: By making things digital they are actually more visible. You have to be able to balance the pure nature of visibility to get at the product; that's the first step. That's why people are on a digital journey.
Gardner: Machines can't help you with a paper-based process, right?
Haydon: Not as much. You have to scan it and throw it in. Then, you are then digitizing it.
Gardner: We heard about Guided Buying last year from SAP Ariba. It sounds like we're going to be getting a sort of "Guided Buying-Plus" next year and we should keep an eye on that.
Haydon: We're very excited. We announced that earlier this year. We're trying to solve two problems quickly through Guided Buying.
One is the nature of the ad-hoc user. We're all ad-hoc users in the business today. I need to buy things, but I don't want to read the policy, I don't want to open the PDF on some corporate portal on some threshold limit that, quite honestly, I really need to know about once or twice a year.
So our Guided Buying has a beautiful consumer-based look and feel, but with embedded compliance. We hide the complexity. We just show the user what they need to know at the time, and the flow is very powerful.
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