Meet George Jetson – Your New Chief Procurement Officer

Transcript of a discussion on how rapid advances in artificial intelligence and machine learning are poised to reshape procurement.

Listen to the podcast. Find it on iTunes. Get the mobile app. Download the transcript. Sponsor: SAP Ariba.

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you're listening to BriefingsDirect.

Gardner

Our next technology innovation thought leadership discussion explores how rapid advances in artificial intelligence (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 join me in welcoming back Chris Haydon, Chief Strategy Officer at SAP Ariba. Good to have you with us, Chris.

Chris Haydon: Great to be here again.

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?

Transaction intense

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.

Haydon

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.

It's not about upstream and downstream, it's about end-to-end process, and re-imagining and reinventing that.

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 (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.

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.

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.

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?

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."

Think larger than yourself in trying to solve that problem differently. Those cloud deployment models really help you.

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.

More visible

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.

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.

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.

Gardner: Well, it certainly sounds like an area where intelligence would have a very marked improvement, and we'll look for some interesting news there as well.

I'm afraid we'll have to leave it there. You've been listening to a BriefingsDirect thought leadership podcast discussion on how rapid advances in AI and machine learning are poised to reshape procurement.

We've heard how, as we enter 2017, applied intelligence, derived from entirely new data analysis, benefits redefines productivity. Lastly, we've been presented with SAP Ariba’s view on where we can take business intelligence aspects into more types of process and more refinement of the procurement function.

With that, please join me in thanking our guest, Chris Haydon, Chief Strategy Officer at SAP Ariba. Thank you, sir.

Haydon: Thank you.

Gardner: And a big thank you as well to our audience for joining this SAP Ariba-sponsored business innovation thought leadership discussion. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator. Thanks again for listening, and do come back next time.

Listen to the podcast. Find it on iTunes. Get the mobile app. Download the transcript. Sponsor: SAP Ariba

Transcript of a discussion on how rapid advances in artificial intelligence and machine learning are poised to reshape procurement. Copyright Interarbor Solutions, LLC, 2005-2016. All rights reserved.

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How New Technology Trends Disrupt the Very Nature of Business

Transcript of a discussion on how major new trends and technology are translating into disruption, and for the innovative business -- opportunity.

Listen to the podcast. Find it on iTunes. Get the mobile app. Download the transcript. Sponsor: SAP Ariba.

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you’re listening to BriefingsDirect.

Gardner

Our next technology innovation thought leadership discussion focuses on how major new trends in technology are translating into disruption, and for the innovative business -- opportunity.

From invisible robots, to drones as data servers -- from virtual reality to driverless cars -- technology innovation is faster than ever, impacting us everywhere, broadening our knowledge, and newly augmenting processes and commerce. We'll now explore the ways that these technology innovations translate into business impacts, and how consumers and suppliers of services and goods can best prepare.

To learn more about the future of business innovation, we’re joined by two guests, Greg Williams, Deputy Editor of WIRED UK, and Alex Atzberger, President of SAP Ariba.

Greg, as we see a lot of trends happening, a lot of change in the industry, people talk about the pace picking up quicker than ever. What are some of the major disrupting trends that you see in technology, and then which of those do you think are going to be the most impactful for business people?

Greg Williams: You listed a whole bunch of things, which are all incredibly important in moving forward. They're near-term in ways that sometimes people don’t consider them to be near-term. Technology shifts tend to be almost things we don’t notice. They're not happening slowly any longer; they're happening quickly, and we're almost not seeing them.

Atzberger

We talk about something like robotics. Now, you can see all kinds of incredible things. You can see in Japan a robot caregiver that can lift elderly people out of their beds and can care for them in that way. You can see slightly sinister videos from Boston Dynamics of robot dogs running along that look pretty scary. But what most innovation looks like are things that we almost don’t notice are there.

For instance, and this is a boring example, an ATM is kind of a robot; a vacuum cleaner is; an elevator is. Those are things we don’t necessarily notice. They're not as dramatic as we think.

I should just caveat that and say that everything is moving very, very quickly right now. That's why it’s hard to make very clear predictions.

The other thing that’s important is this joining up of lots of different technologies. That’s the biggest trend that I see right now. We can talk about satellites and drones, which are effectively servers in the sky or we can talk about autonomous mobility and augmented reality, but it’s all about connecting the dots.

Technology players

One thing that's interesting now is the way that car manufacturers are all technology players. Every automotive manufacturer is figuring out that what they have is a computer on wheels. They have to figure out how, when people drive into a parking lot, they make an automatic payment via the vehicle. How can the vehicle know that people’s groceries are ready to be picked up at a certain point.

Williams

Although it’s nice to list robots and autonomous vehicles and other clear technological shifts, the thing that we're really seeing is the speeding up and this coming together, this joining and connecting of the dots. Basically, all are based on three things: ubiquitous computing, mobile technology, and the cloud. Those three things underpin pretty much everything that we're going to be talking about in the next 20 minutes.

Gardner: Alex, when I hear Greg, I'm thinking business networks, although people in the consumer space might not think of them as business networks. It’s the network effect, it’s intelligence shared, it’s linking things up and allowing the pace to increase and people to share knowledge and activities. What do you see as the crossover from the consumer space in the behaviors and culture of technology and then how does that translate to the business idea of a network?

Alex Atzberger: I was recently in Dubai, and they have a Museum of the Future that they're launching this year. In the Museum of the Future, you can see what it would be like to be going to a doctor to get a new body part to jump higher or move faster. You look at these types of ideas, and the business embraces the same sort of idea. How can I augment my business to actually run smarter and be better? What are things on which I can augment myself to use data better?

You can no longer be an island as a company. You need to share ideas and innovation with others.

You can no longer be an island as a company. You need to share ideas and innovation with others. You need to be connected, and when you're connected, you can transform your business, you can do new things, you can take on new capabilities, and you can augment your business.

Companies ask us, "Now that I'm connected to a network, how can I get data out of that network to improve my business processes and do things better?" That's what they basically call the augmented enterprise, to get augmented intelligence to that business.

Gardner: We're seeing different patterns, not only in adoption, but expectations. People are seeing a mobile device tied to a cloud that has deep learning capabilities, and feedback loops that are applying the data back and forth. People are becoming ready for the next move. They want the technology to guide them. And they also don't want to take the time to learn a process; it has to be intuitive to them.

So how do these human behavioral aspects of anticipating a proactive technological helping hand impact both us in our consumer space, as well as what we would expect in our business environment?

Simplicity is key

Williams: Simplicity is absolutely key to all technology. We have to think about the end user. The end user or the customer is always the most important thing in any kind of technology process.

Going back to what Alex was talking about in terms of artificial intelligence (AI), what it’s going to allow us to do is be a lot more predictive in terms of consumer behavior and customer behavior.

If you look at something like natural language processing now, some of the startups in that space who are working with automotive manufacturers, to go back to my previous example, they will look at trends on social media and elsewhere. They can look at import and export data maybe and they can look at those predictive trends and make predictions about General Motors, their sales in the next quarter.

From the sky, we can look at parking lots at malls like Target, Costco, and Walmart and we can make predictions about how the quarterly earnings report for Walmart or whatever is going to be pretty strong this quarter.

Simplicity is absolutely key to all technology. We have to think about the end user.

What we are looking at is this constant connecting of the dots, and to Alex’s point, this incredible accumulation of data. That’s the real tough thing for businesses right now. I don’t think there’s any business out there that doesn’t understand the value of data. This phrase "big data" is one that you'll hear at every single conference, but how can we possibly parse value out of that? How can we use that data in a predictive way, rather than as a lagging indicator?

Most businesses have used data as a historical indicator. So, it's looking at sales reports or whatever other data is important within your organization. How we can use all those external factors is going to become increasingly important for businesses. Can we see how our competitors are doing by looking at the job postings that they have maybe? How can we see what their next move is in terms of manufacturing by looking at their import/export data? Can we look at the amount of money they're spending on Google AdWords and see what keywords they're spending money on?

As I said previously, it’s about connecting of the dots and bringing this information together, and also figuring it out, having someone within your organization who's not going to get overwhelmed by this data, but is curating it, and knows what’s important and what’s not important to the enterprise, because a lot of it isn’t.

Gardner: User experience plays a huge role in how we can consume and make good on this technology, on this data, on this analysis. What Greg said about simplicity can be deceiving. It might seem simple to the end user, but an awful lot has to happen in order for that effect to take place.

So Alex, one of the interesting things I've seen with SAP Ariba recently is this notion of Guided Buying. I love that word "guided," because you're anticipating the user, heading them off on complexity, but what does it take behind-the-scenes to actually make that happen?

Guided Buying

Atzberger: There’s a whole lot that it takes to get this going. The idea of Guided Buying was always that simplicity that all customers are asking us for. It’s really about how I make the user feel empowered and give the power to the user, but at the same time, embed intelligence in the software.

In our cloud applications, we thought through every step of the process, starting with monitoring how users were behaving with the system. So it’s a design thinking approach, and it starts off with deep empathy with the user. That’s the first point.

The second point is understanding what the business actually wants to accomplish, because the business actually runs a business. They have rules, methodologies, things that they want to achieve.

I was with one CPO who told me, "Alex, I look at this beautiful software, but you're making it too easy to buy. I don’t want people to just go out and buy stuff." That’s absolutely a good point, but what we're doing is embedding the logic of the buying in the enterprise into Guided Buying. That’s the difference between B2C and B2B.

The idea of Guided Buying was always that simplicity that all customers are asking us for. It’s really about how I make the user feel empowered and give the power to the user, but at the same time, embed intelligence in the software.

In B2C you can have that beautiful experience. You just want to make the experience so seamless that you drive commerce. In B2B, you want to guide the commerce, to be more relevant and fit your company goals. That requires a slightly different approach to how you solve that problem. We're obviously deeply committed to solving that problem in the context of giving users as much freedom and choice as possible while enabling the business to achieve their goals.

Williams: Alex used a really great phrase and it’s one that we actually had a discussion about in the office, which is the importance of design thinking within organizations. When you think about software or any technology, the user experience is your brand. So, it’s the people experiencing it.

Pretty much in every organization now, the "design brief" is a really important part of the organization. Maybe designers need to be brought in, whether they're software designers or in the B2C space, UX designers. They need to have a seat at the top table these days, because they're such an integral part of defining any kind of brand.

Atzberger: We hire a lot of designers into SAP Ariba, but interestingly, a lot of the engineers come and say they need to think about design as well. So, it’s not like design is still a separate department. At one point, design becomes part of what we call a scrum team that basically builds the software, and an engineer should have a point of view as well in terms of what is good design.

You could argue that there are some sites that don’t necessarily look pretty, but they're really easy to use. So, it’s not just about the visualization and the fonts, etc.; it’s about also how many clicks and the logic behind it. That’s where product people want to be product people. They don’t want to just be engineers or just designers.

Important element

Gardner: I suppose another important element to this is not only that user experience where one-size-fits-all, but a user experience where customization is brought to bear, and because of the technology, because of the intelligence, access to a cloud infrastructure, we can do that. There are examples of customization at the individual worker level, where role-based and policy-based approaches can do that.

We're also seeing with the SAP Ariba cloud, you're bringing master data, vendor data, for example, into the cloud, cleansing it, making it usable, but still keeping it germane to that particular company, so that this isn’t just a business app for everyone. Let’s delve a little bit into this idea of customization specifically to a company and then even down to the individual user. How is that so important now in business applications, Alex?

Atzberger: The premise of the cloud was always speed. What you gave up for the speed was the ability to customize, especially in enterprise systems. What we're now saying is that you can have a level of individuality and things that are important to you, either through configuration or through extending the platform that you're on.

That’s the power of the technology that comes to bear when you look at platforms today. If you look at Amazon Web Services or what SAP is doing with the HANA Cloud Platform, it’s essential, because it gives the capabilities to companies to actually customize further.

At the same time, we have a concept of the private and the public persona, because at the end of the day, there is some data that’s private to a company and then there's data that's publicly shared. We need to be very sensitive of what data is relevant and in what context.

Gardner: Greg, one of the areas where business can get out in front of the technology curve is this idea of customization and anticipatory or predictive analytics’ benefits. It seems that we're only scratching the surface here. When I go on Netflix, they still can’t pick shows that I really want to watch. When I go to Amazon and they have My Box or My Stuff, it's really just things I already bought with a little bit of augmentation.

What we're now saying is that you can have a level of individuality and things that are important to you, either through configuration or through extending the platform that you're on.

If we can take this to the full potential of customization, and I think businesses can because they have access to the data and they can be policy-based and in probably a better way than a mass consumer environment could, what’s the potential here, when the machines can really start getting us customization, predictive analytics, and apply that to how we get productive in our business sense? It strikes me as something quite significant?

Williams: Yeah, it is. I was talking to someone in a California startup who is developing a sales tool. This person worked for many years in a very large enterprise that builds CRM software. His new business is very interesting because he's trying to do what you described. He's trying to do it almost being a search engine for the entire business Internet. I know this has to be verified, but their claim is that they are much more efficient than regular salespeople.

Say you're trying to sell your software product into a telco. You'll spend a lot of time learning about the person who purchases, those services. You'll go to conferences, read blogs, develop networks, and put a lot of effort into this process.

His startup suggests that they'll be able to not only identify the companies that you're able to sell into, but they'll be able to identify the actual individuals. It will become a lot more detailed in terms of this is what they're interested in and this is what they're not interested in. This is the conference that they've been to. Increasingly, we'll have more-and-more intelligence on people, their habits, their preferences, their interests, and their connections.

Creative business

Take your Netflix example. Netflix moves simply from being a content delivery service to being a creative business by looking at this kind of Venn diagram of its users interests. They saw that there was a sweet spot that overlapped with Kevin Spacey, David Fincher, and the original House of Cards from the UK. They saw that there’s this huge amount of people who love those three things. They said, "Great. Let's commission this series."

Every time that users interact with the service, it's helping to improve it. Netflix knows what you watch, when you watch it, where you stop, where you don’t finish, where you fast-forward, and where you rewind. So, they're collecting huge amounts of data that can be used not just to understand consumer behavior, but also to get insights that can be used for decisions around content.

Gardner: So, Alex, translate this to the business environment, the business network that your company is aligned with can be the determiner of how effective this new trend towards customization, anticipation and being more of a science than an art for sales for example that Greg mentioned is. This to me says the right network with the right information is a crucial decision for you. How does that work in terms of companies differentiating themselves based on who they work with in their ecosystem?

What we see a lot is that businesses are connecting to networks to conduct global business, to find new market opportunities, and become much better at actually mining and understanding that data to become more pointed in terms of what solutions they actually want to provide to the market.

Atzberger: First of all, any company that engages in a network and then captures the data to make better business decisions is already on that journey. If you look at the social networks today, if you like three things on Facebook, Facebook knows more about you than your best friend. If you like more than 10 things, Facebook knows more about you than your spouse. That’s the logic, and the same happens in business networks as well.

What we see a lot is that businesses are connecting to networks to conduct global business, to find new market opportunities, and become much better at actually mining and understanding that data to become more pointed in terms of what solutions they actually want to provide to the market.

But we're still at the very beginning of this trend. We're working with companies on enabling Data as a Service, where they leverage the data itself to create more insight into their business, pursue better business opportunities, change their product offering actually and innovate with their supplier base. If we do that, we're impacting real change, and that's absolutely feasible today, but we're still early on.

Gardner: Any examples, Alex, of companies that really get this and that are showing some demonstrable benefits, that are really tagging on innovation to what their businesses were traditionally, but taking it in a new direction based on some of these technological benefits that we’ve talked about -- poster children for innovation perhaps.

Atzberger: When I think about poster children for innovation, I think about companies that are really looking to the network as infrastructure. What are the other things I can do through this network in order to change my business or add new capabilities?

What I love is when we have customers who talk about the fact that they can actually change their industry. Or their entire supply chain. We have a one high-tech manufacturer who thinks about how they can get demand signals much faster to their supplier base so they can actually impact the end customer. I like that thinking a lot.

Gardner: Greg, last thoughts on what's to come, how technology and business combine to transform how we get things done and perhaps even improve our quality of life?

Solving big problems

Williams: That’s obviously the fundamental end result, one hopes, of all technological change -- that people have better lives and we solve big problems. Looking forward, we're going to see, as Alex has been describing, a real joining of the dots. There aren’t necessarily going to be things that are dramatic, but we're going to see increasing amounts of AI, for instance, offering us insights in industries such as healthcare that only machines are capable of determining because of the sheer volume of data that they can analyze.

I was talking to a guy who worked in the security industry recently. They do a lot of work for the Pentagon. He was telling me that they did an analysis of tweets about ISIL during one week in August last year and they noticed that most of them were about security or the security situation in various parts of Northern Iraq and Syria, account promotion, religion, and strategic updates, but then they came across an outlier that they never noticed before.

That’s obviously the fundamental end result, one hopes, of all technological change -- that people have better lives and we solve big problems.

The official ISIS accounts were re-tweeting any mention of female fighters or women in ISIL -- there was clearly a big push by ISIL to recruit women. What happens? Six weeks later, we had the first female suicide bomber in Europe in Paris. Now, those things probably are not linked, but I think we're able to see things in the data now that we have never been able to see before and I think they increasingly will be putting those things to use.

Gardner: I’m afraid we’ll have to leave it there. You’ve been listening to a BriefingsDirect thought leadership podcast discussion on how major new trends and technology are translating into disruption, and for the innovative business -- opportunity. And we’ve heard how technology innovations translate into business impacts, and how consumers and suppliers of services and goods can best prepare.

So please join me in thanking our guests, Greg Williams, Deputy Editor, WIRED UK in London, and Alex Atzberger, President of SAP Ariba.

And a big thank you too to our audience for joining this SAP Ariba-sponsored business innovation thought leadership discussion.

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator. Thanks again for listening, and do come back next time.

Listen to the podcast. Find it on iTunes. Get the mobile app. Download the transcript. Sponsor: SAP Ariba.

Transcript of a discussion on how major new trends and technology are translating into disruption, and for the innovative business -- opportunity. Copyright Interarbor Solutions, LLC, 2005-2016. All rights reserved.

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