Wednesday, September 5, 2018

Ryder Cup provides extreme use case for managing the digital edge for 250K mobile golf fans

The next BriefingsDirect extreme IT-in-sports use case examines how an edge-computing Gordian Knot is being sliced through innovation and pluck at a prestigious live golfing event.

We will now explore how the 2018 Ryder Cup match between European and US golf players places a unique combination of requirements on its operators and suppliers. As a result, the IT solutions needed to make the Ryder Cup better than ever for its 250,000 live spectators and sponsors will set a new benchmark for future mobile sports events.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to describe the challenges and solutions for making the latest networks and applications operate in a highly distributed environment is Michael Cole, Chief Technology Officer for the European Tour and Ryder Cup. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions. 

Here are some excerpts:

Gardner: What is the Ryder Cup, set for September 2018 near Paris, for those who might not know? 
Cole: The Ryder Cup is a biannual golf event, contested by teams representing Europe and the United States. It is without doubt the most prestigious team event in golf and arguably the world’s most compelling sporting contest in the world.

As such, it really is our blue-ribbon event and requires a huge temporary infrastructure to serve 250,000 spectators -- over 50,000 super fans every day of the event -- but also media, journalists, players, and their entourages.

Gardner: Why do you refer this as blue-ribbon? What is it about the US versus Europe aspect that makes it so special?

Cole: It’s special for the players, really. These professionals play the majority of their schedule in the season as individuals. The Ryder Cup gives them the opportunity to play as a team -- and that is special for the players. You can see that in the passion of representing either the United States or Europe.

Gardner: What makes the Ryder Cup such a difficult problem from this digital delivery and support perspective? Why are the requirements for a tournament-wide digital architecture so extreme?

Cole: Technology deployment in golf is very challenging. We have to bear in mind that every course essentially is a greenfield site. We very rarely return to the same course on two occasions. Therefore, how you deploy technology in an environment that is 150 acres large – or the equivalent of 85 football pitches -- is challenging. And we must do that as a temporary overlay for four days of operation, or three days for the Ryder Cup, operationally leading in, deploying our technology, and then bumping out very quickly onto the next event.

We typically deploy up to five different infrastructures: one for television; another for the tournament television big digital screens in the fan zones on the course; the scoring network has its own infrastructure; the public Wi-Fi, and, of course, we have the back-of-house operational IT infrastructure as well. It’s a unique challenge in terms of scale and complexity.

Gardner: It also exemplifies the need for core data capabilities that are deeply integrated with two-way, high-volume networks and edge devices. How do you tie the edge and the core together effectively?

Data delivery leads the way

Cole: The technology has a critical role to play for us. We at the European Tour lead the transformation in global golf -- very much putting in data at the heart of our sports to create the right level of content and insight for our key stakeholders. This is critical.

For us this is about adopting the Hewlett Packard Enterprise (HPE) Intelligent Edge network and approach, which ensures the processing of data, location-based services, and the distribution of content that all takes place at the point of interaction with our key stakeholders, i.e., at the edge and on the golf course.
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Gardner: What do you mean by location services as pertains to the Ryder Cup? How challenging is that to manage?

Cole: One of the key benefits that the infrastructure will provide is an understanding of people and their behavior. So, we will be able to track the crowds around the course. We will be able to use that insight in terms of behaviors to create value -- both for ourselves in terms of operational delivery, but also for our sponsors by delivering a better understanding of spectators and how they can convert those spectators into customers.

Big BYOD challenges 

Gardner: This is also a great example of how to support a bring-your-own-device (BYOD) challenge. Spectators may prefer to use their cellular networks, but those aren’t always available in these particular locations. What is it about the types of devices that these fans are using that also provides a challenge?

Cole: One of the interesting things that we recently found is the correlation between devices and people. So whilst we are expecting more than 51,000 people per day at the Ryder Cup, the number of devices could easily be double or triple that.

Typically, people these days will have two to three devices. So when we consider the Ryder Cup week [in September] and the fact that we will have more than 250,000 people attending – it’s even more devices. This is arguably the biggest BYOD environment on the planet this year, and that’s a challenge.

Gardner: What are you putting in place so that the end user experience is what they expect?

Cole: I use the term frictionless. I want the experience to be frictionless. The way they on-board, the way they access the Wi-Fi -- I want it to be seamless and easy. It’s critical for us to maximize the number of spectators using the Wi-Fi infrastructure. It equally becomes a source of data and is useful for marketing purposes. So the more people that we can get onto the Wi-Fi, convert them into registering, and then receiving promotional activity – for both us and our partners -- that’s a key measure of success.
It is critical for us to maximize the number of spectators using the WiFi infrastructure. It becomes a source of data and is useful for marketing. I want the experience to be frictionless.

Gardner: What you accomplish at the Ryder Cup will set the standard for going further for the broader European Tour. Tell us about the European Tour and how this sets the stage for extending your success across a greater distribution of golfing events.

Cole: This is without doubt the biggest investment that the European Tour has made in technology, and particularly for the Ryder Cup. So it is critical for us that the investment becomes our legacy as well. I am very much looking forward to having an adoption of technology that will serve our purposes, not only for the Ryder Cup, not only for this year, but in fact for the next four years, until the next Ryder Cup cycle.

For me it’s about an investment in a quadrennial period, and serving those 47 tournaments each year, and making sure that we can provide a consistency and quality beyond the Ryder Cup for each of our tournaments across the European Tour schedule.

Gardner: And how many are there?

Cole: We will run 47 tournaments in 30 countries, across five continents. Our down season is just three days. So we are operationally on the go every day, every week of the year.

Gardner: Many of our listeners and readers tend to be technologists, so let’s dig into the geek stuff. Tell us about the solution. How do you solve these scale problems?

Golf in a private cloud 

Cole: One of the critical aspects is to ensure that data is very much at the heart of everything we do. We need to make sure that we have the topology right, and that topology clearly is underpinned by the technological platform. We will be adopting a classic core distribution and access approach.

For the Ryder Cup, we will have more than 130 switches. In order to provide network ubiquity and overcome one of our greatest challenges of near 100 percent Wi-Fi coverage across the course, we will need 700 access switches. So this has scale and scope, but it doesn’t stop there.

We will essentially be creating our own private cloud. We will be utilizing the VMware virtual platform. We will have a number of on-premises servers and that will be configured across two network corporation centers, with full resiliency and duplicity between the two.

Having 100 percent availability is critical for my industry and delivery of golf across the operational period of three days for Ryder Cup or four days of a traditional golf tournament. We cannot afford any downtime -- even five minutes is five minutes too much.

Gardner: Just to dwell on the edge technology, what is it about the Aruba technology from HPE that is satisfying your needs, given this extreme situation of hundreds of acres and hilly terrain and lots of obstacles?
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Cole: Golf is unique because it’s a greenfield site, with a unique set of challenges. No two golf courses are the same in the world. The technology platform gives us a modular approach. It gives us the agility to deploy what is necessary where and when we need.

And we can do this with the HPE Aruba platform in a way that gives us true integration, true service management, and a stack of applications that can better enable us to manage that entire environment. That includes through the basic management of the infrastructure to security and on-boarding for the largest BYOD requirements on the planet this year. And it’s for a range of services that we will integrate into our spectator app to deliver better value and smarter insights for our commercial family.

Gardner: Tell us about Michael Cole. How did your background prepare you for such a daunting undertaking?

Cole: My background has always been in technology. I spent some 20 years with British Telecom (BT). More recently I moved into the area of sports and technology, following the London 2012 Olympics. I then worked for technology companies for the Rio 2016 Olympic Games. I have supported technology companies for the PyeongChang [South Korea] 2018 Winter Games, and also for the up and coming 2020 Tokyo Games, as well as the Pan American Games.

So I have always been passionate about technology, but increasingly passionate about the use of technology in sports. What I bring to the European Tour is the broader insight around multinational global sports and events and bringing that insight into golf.

Gardner: Where is the Ryder Cup this year?

Cole: It’s being held just outside Paris at Versailles, at Le Golf National. And there’s a couple of things I want to say on this. It's the first time that the European Tour has been held in Europe outside of United Kingdom since 1997 at Valderrama in Spain.

The other interesting aspect, thinking about my background around the Olympics, is actually Le Golf National is the venue for the 2024 Paris Olympic Games; in fact, where the event of golf will be held. So, one of my key objectives is to create a compelling and sustainable legacy for those games in 2024.

Gardner: Let’s fast-forward to the third week of September 2018. What will a typical day in the life of Michael Cole be like as you are preparing and then actually executing on this?

Test-driven tech performance 

Cole: Well, there is no typical day. Every day is very different, and we still have a heavy schedule on our European Tour, but what is critical is the implementation phase and the run in to the Ryder Cup.

My team was on site to start the planning and early deployment some six months ago, in February. The activity now increases significantly. In the month of June, we took delivery of the equipment on site and initiated the Technology Operations Center, and in fact, the Wi-Fi is now live.

We also will adopt one of the principles from the Olympics in terms of test events, so we will utilize the French Open as a test event for the Ryder Cup. And this is an important aspect to the methodology.
I am very pleased with the way we are working with our partner, HPE, and its range of technology partners.

But equally, I am very pleased in the way that we are working with our partner, HPE, and its range of technology partners. In fact, we have adopted an eight-phase approach through staging, through design, and through configuration off site, on site. We do tech rehearsals.

So, the whole thing is very structured and methodical in terms of the approach as we get closer to the Ryder Cup in September.

Gardner: We have looked at this through the lens of technology uniqueness and challenge. Let’s look at this through the lens of business. How will you know you have succeeded through the eyes of your sponsors and your organization? It seems to me that you are going to be charting new ground when it comes to business models around location, sporting, spectators. What are some of the new opportunities you hope to uncover from a business model perspective?

Connect, capture, create

Cole: The platform has three key aspects to it, in my mind. The first one is the ability to create the concept of a connected golf course, a truly connected course, with near 100 percent connectivity at all times.

The second element is the ability to capture data, and that data will drive insights and help us to understand behavioral patterns of spectators on the course.
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The third aspect, which is really the answer to your question, is how we utilize that intelligence and that insight to create real value for our sponsors. The days of sponsors thinking activation was branding and the hospitality program are long gone. They are now far more sophisticated in their approach and their expectations are taken to a new level. And as a rights holder we have an obligation to help them be successful in that activation and achieve their return on investment (ROI).

Moving from a spectator to a lead, to a lead to a customer, from customer to an advocate is critical for them. I believe that our choice of technology for the Ryder Cup and for the European Tour will help in that journey. So it’s critical in terms of the value that we can now deliver to those sponsors and not just meet their expectations -- but exceed their expectations.

Gardner: Beinga New Englander, I remember well in 1999 when the Ryder Cup was in Brookline, Massachusetts at The Country Club. I was impressed not only by the teams from each continent competing, but it also seemed like the corporations were competing for prestige, trying to outdo one another from either side of the pond in how they could demonstrate their value and be part of the pageantry.

Are the corporations also competing, and does that give them a great platform to take advantage of your technology?

Collaborate and compete

Cole: Well, healthy competition is good, and if they all want to exceed and compete with each other that can only be good news for us in terms of the experience that we create. But it has to be exceptional for the fans as well.

So collaboration and competition, I think, are critical. I believe that any suite of sponsors needs to operate both as a family, but also in terms of that healthy competition.

Gardner: When you do your postmortem on the platform and the technology, what will be the metrics that you will examine to determine how well you succeeded in reaching and exceeding their expectations? What are those key metrics that you are going to look for when it’s over?
The technology platform now gives us the capability to go far. Critical to the success will be the satisfaction of the spectators, players, and our commercial family.

Cole: As you would expect, we have a series of financial measurements around merchandizing, ticket revenues, sponsorship revenue, et cetera. But the technology platform now gives us the capability to go far beyond that. Critical to success will be the satisfaction; the satisfaction of spectators, the satisfaction of players, and the satisfaction of our commercial family.

Statistical scorecard 

Gardner: Let’s look to the future. Four years from now, as we know the march of technology continues -- and it’s a rapid pace -- more is being done with machine learning (ML), with utilizing data to its extreme. What might be different in four years at the next Ryder Cup technologically that will even further the goals in terms of the user experience for the players, for the spectators, and for the sponsors?

Cole: Every Ryder Cup brings new opportunities, and technology is moving at a rapid pace. It’s very difficult for me to sit here and have a crystal ball in terms of the future and what it may bring, but what I do know is that data is becoming increasingly more fundamental to us.

Historically, we have always captured scoring for an event, and that equates to about 20,000 data points for a given tournament. We have recently extended it. We now capture seven times the amount of data – including for weather conditions, for golf club types, through lie of the ball, and yardage to the hole. That all equates to 140,000 data points per tournament.
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Over a schedule, that’s 5.5 million data points. When we look at the statistical derivatives, we are looking at more than 2 billion statistics from a given tournament. And this is changing all of the time. We can now utilize Internet of things (IoT) technologies to put sensors in anything that moves. If it moves, it can be tracked. If everything is connected, then anything is possible.

Thursday, August 30, 2018

SAP Ariba's chief data scientist on how ML and dynamic processes build an intelligent enterprise

The next BriefingsDirect digital business innovation interview explores how the powerful combination of deep analytics and the procurement function makes businesses smarter and more efficient.

When the latest data science techniques are applied to more data sets that impact supply chains and optimize procurement, a new strategic breed of corporate efficiency and best practices emerge.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

To learn how data-driven methods and powerful new tools are transforming procurement into an impactful intelligence asset, BriefingsDirect recently sat down with David Herman, Chief Data Scientist for Strategic Procurement at SAP Ariba. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Why is procurement such a good place to apply the insights that we get from data science and machine learning (ML) capabilities?

Herman: Procurement is the central hub for so many corporate activities. We have documents that range from vendor proposals to purchase orders and invoices to contracts, and requests for proposal (RFPs). Lots and lots of data happens here.

So the procurement process is rich in data, but the information historically has been difficult to use. It’s been locked away inside of servers where it really couldn't be beneficial. Now we can take that information in its unstructured format, marry it with other data – from other systems or from big data sources like the news -- and turn it into really interesting insights and predictions.

Gardner: And the payoffs are significant when you're able to use analysis to cut waste or improve decisions within procurement, spend management, and supply chains.

Procurement analysis pays 

Herman: The very nature of spend analysis is changing. We implemented a neural network last year. Its purpose was to expedite the time it takes to do spend analysis. We dropped that time by 99 percent so that things that used to take days and weeks can now be done in mere hours and minutes.

Because of the technology that is available today, we can approach spend analysis differently and do it more frequently. You don’t really have to wait for a quarterly report. Now, you can look at spend performance as often as you want and be really responsive to the board, who these days, are looking at digital dashboard applications with real-time information.

Gardner: How is this now about more than merely buying and selling? It seems to me that when you combine these analytic benefits, it becomes about more than a transaction. The impact can go much deeper and wider.

Herman: It’s strategic -- and that's a new high plateau. Instead of answering historic questions about cost savings, which are still very important, we’re able to look forward and ask “what-if” kinds of questions. What is the best scenario for optimizing my inventory, for example?

That's not a conversation that procurement would normally be involved in. But in these environments and with this kind of data, procurement can help to forecast demand. They can forecast what would happen to price sensitivity. There are a lot of things that can happen with this data that have not been done so far.

Gardner: It's a two-way street. Not only does information percolate up so that procurement can be a resource. They are able to execute, to act based on the data.

Herman: Right, and that's scary, too. Let's face it. We're talking about peoples’ livelihoods. Between now and 2025, things are going to change fundamentally. In the next two to three years alone, we are going to see positions [disappear], and then we're going to have a whole new grouping of people who are more focused on analysis.

The reality is that of any kind of innovation -- any kind of productivity -- follows the same curve. I am not actually making this prediction because it’s the result of ML or artificial intelligence (AI). I am telling you every great increase in productivity has followed the same curve. Initially it impacts some jobs and then there are new jobs.

And that's what we're looking at here, except that now it’s happening so much faster. If you think about it, a five-year period to completely reshape and transform procurement is a very short period of time.

Gardner: Speaking of a period of time, your title, Chief Data Scientist for Strategic Procurement, may not have even made much sense four years ago.

Herman: That's true. In fact, while I have been doing what I'm doing now for close to 30 years, it has had different names. Sometimes, it's been in the area of content specialist or content lead. Other times, it's been focused on how we are managing content in developing new products.

And so, really, this title is new. Yet it’s the most exciting position that I've ever had because things are moving so much faster and there is such great opportunity.

Gardner: I'm sure that the data scientists have studied and learned a lot about procurement. But what should the procurement people know about data science?  

Curiosity leads the way

Herman: When I interview people to be data scientists, one of the primary characteristics I look for is curiosity. It’s not a technical thing. It’s somebody who just wants to understand why something has happened and then leverage it.

Procurement professionals in the future are going to have much more available to them because of the new analytics. And much of the analytics will not require that you know math. It will be something that you can simply look at.

For example, SAP Ariba’s solutions provide you with ML outcomes. All you do is navigate through them. That’s a great thing. If you're trying to identify a trend, if you're trying to look at whether you should substitute one product for another -- those analytic capabilities are there.
SAP Ariba's solutions provide you with ML outcomes. All you do is navigate through them. That's a great thing.

As for a use case, I was recently talking to the buyer responsible for staffing at one of SAP’s data centers. He is also responsible for equipping it. When they buy the large servers that run S4/HANA, they have different generations of hardware that they leverage. They know the server types and they know what the chip lifecycles look like.

But they've never been able to actually examine their own data to understand when and why they fail. And with the kinds of things we're talking about, now they can actually look to see what's going on with different chipsets and their lifecycles -- and make much more effective IT deployment decisions.

Gardner: That's a fascinating example. If you extrapolate from that to other types of buying, you are now able to look at more of your suppliers’ critical variables. You can make deductions better than they can because they don't have access to all of the data.

Tell us about how procurement people should now think differently when it comes to those “what-if” scenarios? Now that the tools are available, what are some of the characteristics of how the thinking of a procurement person should shift to take advantage of them?

Get smart

Herman: Anyone who's negotiated a contract walks away, glad to be done. But you always think in the back of your head, “What did I leave on the table? Perhaps soon the prices will go up, perhaps the prices will go down. What can I do about that?”

We introduced a product feature just recently in our contracts solution that allows anyone to not only fix the price for a line item, but also make it dynamic and have it tied to an external benchmark.

We can examine the underlying commodities associated with what you are buying. If the commodities change by a certain amount – and you specify what that amount is -- you can then renegotiate with your vendor. Setting up dynamic pricing means that you're done. You have a contract that doesn't leave those “what-ifs” on the table anymore.

That's a fundamental shift. That’s how contracts get smart -- a smart contract with dynamic pricing clauses.
Gardner: These dynamic concepts may have been very much at home in the City of London or on Wall Street when it comes to the buying and selling of financial instruments. But now we’re able to apply this much more broadly, more democratically. It’s very powerful -- but at a cost that's much more acceptable.

Is that a good analogy? Should we look to what Wall Street did five to 10 years ago for what is now happening in procurement?

Herman: Sure. Look, for example, at arbitrage. In supplier risk, we take that concept and apply it. When trying to understand supplier risk, begin with inherent risk. From inherent risk we try to reduce the overall risk by putting in place various practices.

Sometimes it might be an actual insurance policy. It could also be a financial instrument. Sometimes it’s where we keep the goods. Maybe they are on consignment or in a warehouse.

There are a whole host of new interesting ways that we can learn from the positives and negatives of financial services -- and apply them to procurement. Arbitrage is the first and most obvious one. I have talked to 100 customers who are implementing arbitrage in various forms, and they are all a little bit different. Each individual company has their own goal.

For example, take someone in procurement who deals with currency fluctuations. That kind of role is going to expand. It's not going to be just currency -- it is also going to be all assets. It is ways to shift and extend risk out over a period of time. Or it could even be reeling in exposure after you have signed a contract. That's also possible.

Gardner: It seems silly to think of procurement as a cost center anymore. It seems so obvious now -- when you think about these implications -- that the amount of impact to the top line and bottom line that procurement and supply chain management can accomplish is substantial. Are there still people out there who see procurement as a cost center, and why would they?

From cost to opportunity 

Herman: First of all, it's very comfortable. We can demonstrate value by saving money, and it goes right to the bottom line. This is where it matters the most. The cost is always going to be a factor here.

As one chief procurement officer (CPO) recently told me, this has been a kind of a shell game because he can't actually prove how much his organization has really saved. We can only put together a theoretical model that shows how much you saved.

As we move forward, we are going to find that cost remains part of the equation -- I think it will always be part of the equation – yet the opportunity side of the equation with the ability to work more effectively with sales and marketing is going to happen. It's actually happening now. So you will see more and more of it over the next three to five years.
We can demonstrate value by saving money, and it goes right to the bottom line. This is where it matters the most. The cost is always going to be a factor here.

Gardner: How are analytics being embedded into your products in such a way that it is in the context of such a value-enhancing process? How are you creating a user experience around analytics that allows for new ways to approach procurement?

Herman: Again, supplier risk is a very good example. When a customer adopts the SAP Ariba Supplier Risk solution, they most often come with a risk policy in place. In other words, they already know how to measure risk.

The challenges with measuring risk are commonly around access to the data. Integration is really hard. When we went about building this product we focused first on integration. Then we came up with a model. We take the historical data and come up with a reference model. We also really worked hard to make sure that any customer can change any aspect of that model according to their policy or according to whatever scenario they might be looking at.

If, for example, you have just acquired a company, you don’t know what the risks look like. You need to develop a good look at the information, and then migrate over time. With supplier risk management, both the predictive and descriptive models are completely under the control of our customers. They can decide what data flows in and becomes a feature of that model, how much it is weighted, what the impacts are, and how to interpret the impact when it's finished.

We also have to recognize when you’re talking about data outside of the organization that is now flowing in via big data, that this is an unknown. It's not uncommon for somebody look at the risk platform and say, “Turn off that external stuff so I can get my feet under the table to understand it -- and then turn on this data that’s flowing through and let me figure out how to combine them.”

At SAP Ariba, that’s what we are doing. We are giving our customers the tools to build workflow, to build models, to measure them, and now with the advent of the SAP Analytics Cloud be able to integrate that into S/4HANA.

Gardner: When we think about this as a high-productivity benefit within an individual company, it seems to me that as more individual companies begin doing this that there is a higher level of value. As more organizations in a supply chain or ecosystem share information they gain mutual productivity.

Do you have examples yet of where that's happening, of where the data analytics sharing is creating a step-change of broader productivity?

Shared data, shared productivity 

Herman: Sure, two examples. The first is that we provide a benchmarking program. The benchmarking program is completely free.  As long as you are willing to share data, we share the benchmarks.

The data is aggregated, it's anonymous, and we make sure that the information cannot be re-identified. We take the proper precautions. Then, as a trusted party and a trusted host we provide information so that any company can benchmark various aspects of their specific performance.

You can, for example, get a very good idea of how long it takes to process a purchase order, the volumes of purchase orders, and how much spend is not managed because you don't have a purchase order in place. Those kinds of insights are great.

When we look at analytics across industries we find that most supply chains have become brittle. As all of us become leaner organizations, ultimately we find that industries end up relying on one or two critical suppliers.

For example, black pigment for the automotive industry was provisioned for all of the major manufacturers by just one supplier. When that supplier had a plant fire and had to shut down their plant for three months it was a crisis because there was no inventory in the supply chain and because there was only one supplier. We actually saw that in our supplier risk product before it happened.

The industry had to come together and work with one another to solve that problem, to share their knowledge, just like they did during the 2008-2009 financial crisis.

In the financial crisis, we found that it was necessary to effectively help other company’s suppliers. Traditionally that would be called collusion, but it was done with complete transparency with the government.

When you look at such ways that information can be shared -- and how industries can benefit collectively -- that's the kind of thing we see as emerging in areas like sustainability. With sustainability we are looking for ways to reduce the use of forced labor, for example.

In the fishing industry, shrimping companies have just gone through their industry association to introduce a new model that collectively works to reduce the tremendous use of forced labor in that industry today. There are other examples. This is definitely happening.

Gardner: What comes next in terms of capabilities that build on data science brought to the procurement process?

Contract evaluations 

Herman: One of the most exciting things we’re doing is around contracts. Customers this quarter are now able to evaluate different outcomes across all of their contracts. A prominent use case is that perhaps you have a cash flow shortage at the end of the year and it’s necessary to curtail spend. Maybe that’s by terminating contracts, maybe it’s by cutting back on marketing.

We picked an area like marketing so that we can drill down to evaluate rights and obligations and assess the potential impact to the company canceling those contracts. There is no way to do this today at scale other than manually.

If the chief financial officer (CFO) were to approach someone in procurement and ask this question about cash flow, they would bring in your paralegals and lawyers to begin reading the contracts. That's the only way today.
Customers are now able to evaluate different outcomes across all of their contracts. We are teaching machines to interpret the data, to evaluate cause and effect and then classify the impact so decision makers can act quickly.

What we are doing right now is teaching machines to interpret that data, to evaluate the cause and effect -- and then classify the impact so that the decision makers can take action quickly.

Gardner: You are able to move beyond blunt instruments into a more surgical understanding -- and also execution?

Herman: Right, and it redefines context. We are now talking about context in ways that we can't do today. You will be able to evaluate different scenarios, such as terminating relationships, push out delivery, or maybe renegotiating a specific clause in a contract.

These are just the very beginnings of great use cases where procurement becomes much more strategic and able to respond to the scenarios that help shape the health of the organization.

Gardner: We spoke before about how this used to be in the purview of Wall Street. They had essentially unlimited resources to devote to ML and data science. But now we are making this level of analysis as-a-service within an operating expense subscription model.

It seems to me that we are democratizing analysis so that small- to medium-size businesses (SMBs) can do what they never used to have the resources to do. Are we now bringing some very powerful tools to people who just wouldn’t have been able to get them before?

Power tools to the people 

Herman: Yes. The cloud providers create all kinds of opportunities, especially for SMBs, because they are able to buy on demand. That’s what it is. I am able to buy what I need on demand, to negotiate the price based on whether it’s on peak or off peak and get to the answers that I need much more quickly.

SAP Ariba made that transition to a cloud model in 2008, and this is just the next generation. We know a lot about how to do it.

Gardner: For those SMBs that now have access to such cloud-based analytics services, what sort of skills and organizational adjustments should they make in order to take advantage of it?

Herman: It’s interesting. When I talk to schools, to undergraduates and graduate students, I find that many of those folks are coming out of school with the right skill sets. They have already learned Python, for example, and they have already built models. There is no mystery, there is no voodoo about this. They have built the models in the classroom.

Just like any other business decision, we want to hire the best people. So, you will want to maybe slip in a couple of questions about data sciences during your interviews, because it’s the kind of thing that a product manager, an analyst, and an IT leader need to know in the near future.

With the transition of the baby boomers into retirement, Millennials are coming up as this new group which is extremely talented. They have those skill sets and they are driven by opportunity. As you continue to challenge them with opportunities, my experience is that they continue to shine.

Gardner: David, we have talked about this largely through the lens of the buyers. What about the sellers? Is there an opportunity for people to use data in business networks to better position themselves, get new business, and satisfy their markets?

Discover new business together

Herman: We need a good platform to discover these kinds of opportunities. Having been a small business owner myself, I find that the ability for me to identify opportunities that trigger business is really essential. You really want to be able to share information with your customers and understand how you can generalize those.

I recently spoke to a small business owner who uses Google Sheets. At the end of every call, everybody on this team writes down what they had learned about the industry so they could share it among themselves. They would write down the new opportunities that they heard in a separate section of the sheet, in a separate tab. What were the opportunities they saw coming up next in their industry? That’s where they would focus their time in building a funnel, in building a pipeline around it.

When looking at it from that perspective, it’s really useful. Use the tools we have to get into these new areas of access -- and you win.

Gardner: What should people expect in the not too distant future when it comes to the technologies that support data science? Are there any examples of organizations at the vanguard of their use? Can they show us what others should expect?
We now have to look at it differently. We need to look at how to use ML to validate your risks and assumptions and then concentrate investments. ML is going to help you find your answers faster.

Herman: Here’s the way I look at it: If we are going to think about how much money you could invest and bet on the future, maybe we have 7 percent of operating income to play with, and that’s about it. That has been in the common in the past, for us to spread that spending across four, five, or six different bets.

I think now we have to look at it differently. We need to look at how to use ML to validate your risks and assumptions, of how to validate your market and then concentrate investments. We can take that 7 percent and get more out of it. That’s how ML is going to help, it’s going to help you find your answers faster.

Gardner: How should organizations get themselves ready? What should organizations that want to become more intelligent -- to attain the level of an intelligent enterprise, an intelligent SMB -- what do you recommend that they do in order to be in a best position to take advantage of these tools?

Collaborate to compete 

Herman: Historically we asked, “What is your competitive advantage?” That’s something that we talked about in the 1980s, and then we later described learning as your core competency. Now in this time, it’s who you know. It’s your partnerships.

Going back to what Google learned, Google learned how to connect content together and make money. Facebook one-upped them by learning about the relationships, and they learned how to make money based on those relationships.

Going forward, customer networks and supply chains are your differentiation. To plan for that future, we need to make sure that we have clear ways to collaborate. We can work to make the partners strategic, and to focus our energy and bets on those partners who we believe are going to make us effective.

When you look at what are the key enablers, it’s going to be technology. It’s going to be analytics. To me that’s a given in these situations. We want to find someone who is investing, looking forward, and who brings in these new capabilities -- whether it’s bitcoin or something else that is transformative in how we make companies more network-driven.

Gardner: So perhaps a variation on the theme of Metcalfe’s Law -- that the larger the network, the more valuable it is. Maybe it’s now the more collaboration -- and the richer the sharing and mutually assured productivity -- the more likely you are to succeed.

Herman: I don’t think Metcalfe’s Law is over yet. We are going to find between now and 2020, that’s where this is at.