2016 Campaigners Look to Deep Big Data Analysis and Querying to Gain an Edge in Reaching Voters

Transcript of a discussion on how data analysis services startup BlueLabs in Washington helps presidential campaigns better know and engage with potential voters.

Listen to the podcast. Find it on iTunes. Get the mobile app. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Dana Gardner: Welcome to the next edition of the Hewlett Packard Enterprise (HPE) Voice of the Customer podcast series. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing discussion on business digital transformation. Stay with us now to learn how agile companies are fending off disruption in favor of innovation.

Gardner

Our next case study explores how data-analysis services startup BlueLabs in Washington, D.C. helps presidential campaigns better know and engage with potential voters.

We'll learn how BlueLabs relies on analytics platforms that allow a democratization of querying, of opening the value of vast big data resources to more of those in the need to know.

In this example of helping organizations work smarter by leveraging innovative statistical methods and technology, we'll discover how specific types of voters can be identified and reached.

Here to describe how big data is being used creatively by contemporary political organizations for two-way voter engagement, we're joined by Erek Dyskant Co-Founder and Vice President of Impact at BlueLabs Analytics in Washington. Welcome, Erek.

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Erek Dyskant: I'm so happy to be here, thanks for having me.

Gardner: Obviously, this is a busy season for the analytics people who are focused on politics and campaigns. What are some of the trends that are different in 2016 from just four years ago. It’s a fast-changing technology set, it's also a fast-changing methodology. And of course, the trends about how voters think, react, use social, and engage are also dynamic. So what's different this cycle?

Dyskant: From a voter-engagement perspective, in 2012, we could reach most of our voters online through a relatively small set of social media channels -- Facebook, Twitter, and a little bit on the Instagram side. Moving into 2016, we see a fragmentation of the online and offline media consumption landscape and many more folks moving toward purpose-built social media platforms.

If I'm at the HPE Conference and I want my colleagues back in D.C. to see what I'm seeing, then maybe I'll use Periscope, maybe Facebook Live, but probably Periscope. If I see something that I think one of my friends will think is really funny, I'll send that to them on Snapchat.

Where political campaigns have traditionally broadcast messages out through the news-feed style social-media strategies, now we need to consider how it is that one-to-one social media is acting as a force multiplier for our events and for the ideas of our candidates, filtered through our campaign’s champions.

Gardner: So, perhaps a way to look at that is that you're no longer focused on precincts physically and you're no longer able to use broadcast through social media. It’s much more of an influence within communities and identifying those communities in a new way through these apps, perhaps more than platforms.

Social media

Dyskant: That's exactly right. Campaigns have always organized voters at the door and on the phone. Now, we think of one more way. If you want to be a champion for a candidate, you can be a champion by knocking on doors for us, by making phone calls, or by making phone calls through online platforms.

You can also use one-to-one social media channels to let your friends know why the election matters so much to you and why they should turn out and vote, or vote for the issues that really matter to you.

Gardner: So, we're talking about retail campaigning, but it's a bit more virtual. What’s interesting though is that you can get a lot more data through the interaction than you might if you were physically knocking on someone's door.

Dyskant: The data is different. We're starting to see a shift from demographic targeting. In 2000, we were targeting on precincts. A little bit later, we were targeting on combinations of demographics, on soccer moms, on single women, on single men, on rural, urban, or suburban communities separately.

Dyskant

Moving to 2012, we've looked at everything that we knew about a person and built individual-level predictive models, so that we knew each person's individual set of characteristics made that person more or less likely to be someone that our candidate would have an engaging conversation through a volunteer.

Now, what we're starting to see is behavioral characteristics trumping demographic or even consumer data. You can put whiskey drinkers in your model, you can put cat owners in your model, but isn't it a lot more interesting to put in your model that fact that this person has an online profile on our website and this is their clickstream? Isn't it much more interesting to put into a model that this person is likely to consume media via TV, is likely to be a cord-cutter, is likely to be a social media trendsetter, is likely to view multiple channels, or to use both Facebook and media on TV?

That lets us have a really broad reach or really broad set of interested voters, rather than just creating an echo chamber where we're talking to the same voters across different platforms.

Gardner: So, over time, the analytics tools have gone from semi-blunt instruments to much more precise, and you're also able to better target what you think would be the right voter for you to get the right message out to.

One of the things you mentioned that struck me is the word "predictive." I suppose I think of campaigning as looking to influence people, and that polling then tries to predict what will happen as a result. Is there somewhat less daylight between these two than I am thinking, that being predictive and campaigning are much more closely associated, and how would that work?

Predictive modeling

Dyskant: When I think of predictive modeling, what I think of is predicting something that the campaign doesn't know. That may be something that will happen in the future or it may be something that already exists today, but that we don't have an observation for it.

In the case of the role of polling, what I really see about that is understanding what issues matter the most to voters and how it is that we can craft messages that resonate with those issues. When I think of predictive analytics, I think of how is it that we allocate our resources to persuade and activate voters.

Over the course of elections, what we've seen is an exponential trajectory of the amount of data that is considered by predictive models. Even more important than that is an exponential set of the use cases of models. Today, we see every time a predictive model is used, it’s used in a million and one ways, whereas in 2012 it might have been used in 50, 20, or 100 sessions about each voter contract.

Gardner: It’s a fascinating use case to see how analytics and data can be brought to bear on the democratic process and to help you get messages out, probably in a way that's better received by the voter or the prospective voter, like in a retail or commercial environment. You don’t want to hear things that aren’t relevant to you, and when people do make an effort to provide you with information that's useful or that helps you make a decision, you benefit and you respect and even admire and enjoy it.

Dyskant: What I really want is for the voter experience to be as transparent and easy as possible, that campaigns reach out to me around the same time that I'm seeking information about who I'm going to vote for in November. I know who I'm voting for in 2016, but in some local actions, I may not have made that decision yet. So, I want a steady stream of information to be reaching voters, as they're in those key decision points, with messaging that really is relevant to their lives.

I want a steady stream of information to be reaching voters, as they're in those key decision points, with messaging that really is relevant to their lives.

I also want to listen to what voters tell me. If a voter has a conversation with a volunteer at the door, that should inform future communications. If somebody has told me that they're definitely voting for the candidate, then the next conversation should be different from someone who says, "I work in energy. I really want to know more about the Secretary’s energy policies."

Gardner: Just as if a salesperson is engaging with process, they use customer relationship management (CRM), and that data is captured, analyzed, and shared. That becomes a much better process for both the buyer and the seller. It's the same thing in a campaign, right? The better information you have, the more likely you're going to be able to serve that user, that voter.

Dyskant: There definitely are parallels to marketing, and that’s how we at BlueLabs decided to found the company and work across industries. We work with Fortune 100 retail organizations that are interested in how, once someone buys one item, we can bring them back into the store to buy the follow-on item or maybe to buy the follow-on item through that same store’s online portal. How it is that we can provide relevant messaging as users engage in complex processes online? All those things are driven from our lessons in politics.

Politics is fundamentally different from retail, though. It's a civic decision, rather than an individual-level decision. I always want to be mindful that I have a duty to voters to provide extremely relevant information to them, so that they can be engaged in the civic decision that they need to make.

Gardner: Suffice it to say that good quality comparison shopping is still good quality comparison decision-making.

Dyskant: Yes, I would agree with you.

Relevant and speedy

Gardner: Now that we've established how really relevant, important, and powerful this type of analysis can be in the context of the 2016 campaign, I'd like to learn more about how you go about getting that analysis and making it relevant and speedy across large variety of data sets and content sets. But first, let’s hear more about BlueLabs. Tell me about your company, how it started, why you started it, maybe a bit about yourself as well.

Dyskant: Of the four of us who started BlueLabs, some of us met in the 2008 elections and some of us met during the 2010 midterms working at the Democratic National Committee (DNC). Throughout that pre-2012 experience, we had the opportunity as practitioners to try a lot of things, sometimes just once or twice, sometimes things that we operationalized within those cycles.

Jumping forward to 2012 we had the opportunity to scale all that research and development to say that we did this one thing that was a different way of building models, and it worked for in this congressional array. We decided to make this three people’s full-time jobs and scale that up.

Moving past 2012, we got to build potentially one of the fastest-growing startups, one of the most data-driven organizations, and we knew that we built a special team. We wanted to continue working together with ourselves and the folks who we worked with and who made all this possible. We also wanted to apply the same types of techniques to other areas of social impact and other areas of commerce. This individual-level approach to identifying conversations is something that we found unique in the marketplace. We wanted to expand on that.

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Increasingly, what we're working on is this segmentation-of-media problem. It's this idea that some people watch only TV, and you can't ignore a TV. It has lots of eyeballs. Some people watch only digital and some people consume a mix of media. How is it that you can build media plans that are aware of people's cross-channel media preferences and reach the right audience with their preferred means of communications?

Gardner: That’s fascinating. You start with the rigors of the demands of a political campaign, but then you can apply in so many ways, answering the types of questions anticipating the type of questions that more verticals, more sectors, and charitable organizations would want to be involved with. That’s very cool.

Let’s go back to the data science. You have this vast pool of data. You have a snappy analytics platform to work with. But, one of the things that I am interested in is how you get more people whether it's in your organization or a campaign, like the Hillary Clinton campaign, or the DNC to then be able to utilize that data to get to these inferences, get to these insights that you want.

What is it that you look for and what is it that you've been able to do in that form of getting more people able to query and utilize the data?

Dyskant: Data science happens when individuals have direct access to ask complex questions of a large, gnarly, but well-integrated data set. If I have 30 terabytes of data across online contacts, off-line contacts, and maybe a sample of clickstream data, and I want to ask things like of all the people who went to my online platform and clicked the password reset because they couldn't remember their password, then never followed up with an e-mail, how many of them showed up at a retail location within the next five days? They tried to engage online, and it didn't work out for them. I want to know whether we're losing them or are they showing up in person.

That type of question maybe would make it into a business-intelligence (BI) report a few months from that, but people who are thinking about what we do every day, would say, "I wonder about this, turn it into a query, and say, "I think I found something." If we give these customers phone calls, maybe we can reset their passwords over the phone and reengage them.

Human intensive

That's just one tiny, micro example, which is why data science is truly a human-intensive exercise. You get 50-100 people working at an enterprise solving problems like that and what you ultimately get is a positive feedback loop of self-correcting systems. Every time there's a problem, somebody is thinking about how that problem is represented in the data. How do I quantify that. If it’s significant enough, then how is it that the organization can improve in this one specific area?

All that can be done with business logic is the interesting piece. You need very granular data that's accessible via query and you need reasonably fast query time, because you can’t ask questions like that when you're going to get coffee every time you run a query.

Layering predictive modeling allows you to understand the opportunity for impact if you fix that problem. That one hypothesis with those users who cannot reset their passwords is that maybe those users aren't that engaged in the first place. You fix their password but it doesn’t move the needle.

The other hypothesis is that it's people who are actively trying to engage with your server and are unsuccessful because of this one very specific barrier. If you have a model of user engagement at an individual level, you can say that these are really high-value users that are having this problem, or maybe they aren’t. So you take data science, align it with really smart individual-level business analysis, and what you get is an organization that continues to improve without having to have at an executive-decision level for each one of those things.

Gardner: So a great deal of inquiry experimentation, iterative improvement, and feedback loops can all come together very powerfully. I'm all for the data scientist full-employment movement, but we need to do more than have people have to go through data scientist to use, access, and develop these feedback insights. What is it about the SQL, natural language, or APIs? What is it that you like to see that allows for more people to be able to directly relate and engage with these powerful data sets?

It's taking that hypothesis that’s driven from personal stories, and being able to, through a relatively simple query, translate that into a database query, and find out if that hypothesis proves true at scale.

Dyskant: One of the things is the product management of data schemas. So whenever we build an analytics database for a large-scale organization I think a lot about an analyst who is 22, knows VLOOKUP, took some statistics classes in college, and has some personal stories about the industry that they're working in. They know, "My grandmother isn't a native English speaker, and this is how she would use this website."

So it's taking that hypothesis that’s driven from personal stories, and being able to, through a relatively simple query, translate that into a database query, and find out if that hypothesis proves true at scale.

Then, potentially take the result of that query, dump them into a statistical-analysis language, or use database analytics to answer that in a more robust way. What that means is that our schemas favor very wide schemas, because I want someone to be able to write a three-line SQL statement, no joins, that enters a business question that I wouldn't have thought to put in a report. So that’s the first line -- is analyst-friendly schemas that are accessed via SQL.

The next line is deep key performance indicators (KPIs). Once we step out of the analytics database, consumers drop into the wider organization that’s consuming data at a different level. I always want reporting to report on opportunity for impact, to report on whether we're reaching our most valuable customers, not how many customers are we reaching.

"Are we reaching our most valuable customers" is much more easily addressable; you just talk to different people. Whereas, when you ask, "Are we reaching enough customers," I don’t know how find out. I can go over to the sales team and yell at them to work harder, but ultimately, I want our reporting to facilitate smarter working, which means incorporating model scores and predictive analytics into our KPIs.

Getting to the core

Gardner: Let’s step back from the edge, where we engage the analysts, to the core, where we need to provide the ability for them to do what they want and which gets them those great results.

It seems to me that when you're dealing in a campaign cycle that is very spiky, you have a short period of time where there's a need for a tremendous amount of data, but that could quickly go down between cycles of an election, or in a retail environment, be very intensive leading up to a holiday season.

Do you therefore take advantage of the cloud models for your analytics that make a fit-for-purpose approach to data and analytics pay as you go? Tell us a little bit about your strategy for the data and the analytics engine.

Dyskant: All of our customers have a cyclical nature to them. I think that almost every business is cyclical, just some more than others. Horizontal scaling is incredibly important to us. It would be very difficult for us to do what we do without using a cloud model such as Amazon Web Services (AWS).

Also, one of the things that works well for us with HPE Vertica is the licensing model where we can add additional performance with only the cost of hardware or hardware provision through the cloud. That allows us to scale up our cost areas during the busy season. We'll sometimes even scale them back down during slower periods so that we can have those 150 analysts asking their own questions about the areas of the program that they're responsible for during busy cycles, and then during less busy cycles, scale down the footprint of the operation.

I do everything I can to avoid aggregation. I want my analysts to be looking at the data at the interaction-by-interaction level.

Gardner: Is there anything else about the HPE Vertica OnDemand platform that benefits your particular need for analysis? I'm thinking about the scale and the rows. You must have so many variables when it comes to a retail situation, a commercial situation, where you're trying to really understand that consumer?

Dyskant: I do everything I can to avoid aggregation. I want my analysts to be looking at the data at the interaction-by-interaction level. If it’s a website, I want them to be looking at clickstream data. If it's a retail organization, I want them to be looking at point-of-sale data. In order to do that, we build data sets that are very frequently in the billions of rows. They're also very frequently incredibly wide, because we don't just want to know every transaction with this dollar amount. We want to know things like what the variables were, and where that store was located.

Getting back to the idea that we want our queries to be dead-simple, that means that we very frequently append additional columns on to our transaction tables. We’re okay that the table is big, because in a columnar model, we can pick out just the columns that we want for that particular query.

Then, moving into some of the in-database machine-learning algorithms allows us to perform more higher-order computation within the database and have less data shipping.

Gardner: We're almost out of time, but I wanted to do some predictive analysis ourselves. Thinking about the next election cycle, midterms, only two years away, what might change between now and then? We hear so much about machine learning, bots, and advanced algorithms. How do you predict, Erek, the way that big data will come to bear on the next election cycle?

Behavioral targeting

Dyskant: I think that a big piece of the next election will be around moving even more away from demographic targeting, toward even more behavioral targeting. How is it that we reach every voter based on what they're telling us about them and what matters to them, how that matters to them? That will increasingly drive our models.

To do that involves probably another 10X scale in the data, because that type of data is generally at the clickstream level, generally at the interaction-by-interaction level, incorporating things like Twitter feeds, which adds an additional level of complexity and laying in computational necessity to the data.

Gardner: It almost sounds like you're shooting for sentiment analysis on an issue-by-issue basis, a very complex undertaking, but it could be very powerful.

Dyskant: I think that it's heading in that direction, yes.

Gardner: I am afraid we'll have to leave it there. We've been exploring how data analysis services startup BlueLabs in Washington, DC helps presidential campaigns better know and engage with potential voters. And we've learned how organizations are working smarter by leveraging innovative statistical methods and technologies, and in this case, looking at two-way voter engagement in entirely new ways -- in this and in future election cycles.

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So, please join me in thanking our guest, Erek Dyskant, Co-Founder and Vice President of Impact at BlueLabs in Washington. Thank you, Erek.

Dyskant: Thank you.

Gardner: And a big thank you as well to our audience for joining us for this Hewlett Packard Enterprise Voice of the Customer digital transformation discussion.

I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HPE-sponsored interviews. Thanks again for listening, and please come back next time.

Listen to the podcast. Find it on iTunes. Get the mobile app. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Transcript of a discussion on how data analysis services startup BlueLabs in Washington helps presidential campaigns better know and engage with potential voters. Copyright Interarbor Solutions, LLC, 2005-2016. All rights reserved.

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Building a Modern Marketing Organization in a Multi-Channel World

Transcript of a discussion on how social media and business networks have taken the lead in shaping perceptions about brands, products, and companies.

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 innovation thought leadership discussion focuses on building a modern marketing organization. Marketing today is a different game. Today’s buyers are more connected and informed than ever, and that’s creating major upheaval in the way companies promote their brands.

Social media and business networks have taken the lead in shaping perceptions about brands, products, and companies -- and savvy businesses are embracing these new channels and technologies both to increase their brand awareness and to drive sales.

We’re here with two experts to talk about these changes and how they are shaping the future of marketing. To learn more, please join me in welcoming Alicia Tillman, Chief Marketing Officer at SAP Ariba. Welcome, Alicia.

Alicia Tillman: Thank you so much, Dana, very happy to be here.

Gardner: We are also here with Pete Krainik, Founder and CEO of The CMO Club. Welcome, Pete.

Pete Krainik: Thanks, Dana and Alicia, good to reconnect again.

Tillman: Yes, of course, you, too.

Gardner: Let’s begin our conversation at a fairly high level. What are the trends, the competitive pressures, and the technology changes that are prompting companies to have to seek new and better ways to market themselves, Alicia?

Tillman: There are two things, Dana. First, when we think about trends or even new ways to market in particular, we're faced with the fact that social media, and networks have taken the lead in shaping perceptions about brands, products, and companies.

Tillman

On one hand, there’s no shortage of information, and that’s a good thing. But on the other hand, it’s really causing companies to get out ahead of that as quickly as possible, because the reality is that today’s buyers aren't struggling to find information. And so many buying decisions are made about companies and products before any interaction with a member of the sales team.

Companies are recognizing that all of the channels in the social media space that companies are going after to find information is key. Making sure that marketers are driving information in a consistent manner across these channels will aid in feeling as though your company’s value proposition and brand are being embraced and accepted in the ways that you want them to.

My second point is in terms of the competitive pressure. All companies are mostly trying to compete on a product, a piece of technology, in a lot of ways, and oftentimes your competitors are saying they already have or are about to innovate on the same thing. So companies need to force themselves to innovate beyond products. There are a lot of opportunities, in particular, thinking about how you differentiate on things such as thought leadership or standing for a particular cause.

How do you take a product and how do you use it to benefit the world in terms of driving higher good in some way? So between social media and networks, embracing those channels and then separately thinking about how you differentiate beyond just the basics of products are certainly the opportunities that companies are faced with today.

Social media

Gardner: Pete, with social media, we're more exposed than ever. People can point at whatever they see about brands or companies. How is this trend shaping the new marketing and competition?

Krainik: I think Alicia is spot-on. I host dinners with chief marketing officers (CMOs), and I'm chatting behind doors on these issues around the new competitive landscape. If you look at the pressures faced by CMOs, you still have the same process or the same thought -- I need to sell more products, I need to differentiate myself, I need to get leads, I need to close, I need to build the brand. Those things and concepts haven’t changed, but you have a whole new wave of extremely agile competitors now, like Uber, like Airbnb.

Krainik

How is the cloud impacting that? You have the new players that you never had to deal with before. You have new media channels, new influencers. In the past, media mostly meant working on press releases. But the whole world has changed. You talked about it, and Alicia again talked about social.

And then, this whole issue of speed of change and how to keep up with it is interesting. How do I, as an organization, keep up with all the changes?

Marketing is completely different than it was five or 10 years ago. There are just too many choices, too much noise, too much outbound. CMOs are getting hundreds of emails a day from someone selling some product and they're not even looking at it. Those kinds of pressures are building, as Alicia said, and taking the competition to the next level. Those things are top of mind right now for CMOs.

Gardner: Alicia, in this environment of disruption, of fast-paced change, of so much noise and information, you recently completed a significant update of the Ariba brand, and you’ve launched a new name and logo. Why did you do that at this time and how did you go about that differently than you would have done 5 or 10 years ago?

Tillman: Ariba was founded some 18 years ago, and at the time, the company had set out on a mission to build a single solution to help companies manage their spend. If we reflect on the past 18 years, you see all the ways in which our business has evolved, in which buyer needs and the economies have evolved, and how our business has worked to evolve and be ahead of that. Today, Ariba is the world’s largest marketplace for all business-to-business (B2B) transactions.

We have two million companies and $1 trillion in commerce that run through the Ariba Network. When we think about some of the significant change that has happened notably in the past four years, number one, we were acquired by SAP. SAP is a global leader in enterprise application software. It has an incredible brand, and is an incredibly sound and operationally and financially stable company known throughout the world. It’s really important to us to take that brand reputation into our identities.

First, we've added the SAP name to our brands, now calling ourselves SAP Ariba. And secondly, the logo, the mark, or the bug as some people like to call it, that fits alongside the company name is equally important. The visual representation of our brand needs to well support the business we're in and the value proposition we offer.

Pete said it really well. When we think about the marketplace that we're in today, there are new competitors, new influencers, and so many choices that we have an obligation as marketers to help buyers clear through the clutter, understand where the differentiation exists within companies, and associate themselves with a company that is most relevant to their needs.

Showcasing customers

So, we evolved our logo and made it into a mark that really showcases our customers, which are both buyers and sellers. Within our logo there's a connection there that’s reflected to support how Ariba brings those two buying populations together.

In addition to that, we've worked to adapt a new tone in our messaging. Messaging got simple and clear to piece point about all the choices that exist. You’ve got to focus on a simple and clear message, and one that is very understood and very relevant for your customers.

Gardner: Pete touched on this issue of so much information available, and research confirms that consumers are looking at multiple channels when they make a purchase. They have much more of an ability to do research and to get social commentary. I myself find, in my own buying, that I'm ready to push the button to buy something, but then I'll glance at the comments or some of the recommendations, and actually back away. So this is really a big deal.

So how do we, as marketers, think about different ways to accommodate these new behaviors by buyers, and how do we then provide information to them as sellers to help them along the way?

Krainik: One thing some of the top CMOs or top brands are doing is moving away from a campaign-focus to 360-degree coverage. I was a CMO before I started The CMO Club, and the profession has moved beyond kind of the "blah, blah, blah" to true focus. There’s the ability to make sure that the content is relevant, that the stories are there, that you’ve identified the advocates, and people underestimate the value of that.

Everybody is driven by mobile now. It's truly a mobile workforce. We're always doing everything on mobile.

You talked a minute ago about how you check on social media or with people you know or respect, and they say, "This product is good, this product isn’t, or I had a great experience here." How do you spend the time making sure you know who those advocates are, who the influencers are, how to engage employees, and really focusing on getting to that. It’s such an important thing that I think people don’t think about as much.

Another piece that there’s not enough focus on: Everybody is driven by mobile now. It's truly a mobile workforce. We're always doing everything on mobile. So making sure when we talk about multichannel and we talk about going where the customers are, we need to be sure it’s in the format they want as well. We want them saying that we have this great website, this great digital space. If you’re not going to mobile, then you’re missing the boat.

Gardner: Alicia, anything to offer on ways marketers need to do things differently to accommodate these new buyer behaviors?

Tillman: I think a lot about the power of consistency and how marketers need to have their finger on the pulse of the channels that their customers are getting information from. Pete’s organization, The CMO Club, hosted a fantastic CMO roundtable a couple of weeks ago where the topic was how to stay ahead of the digital transformation, and how marketers are embracing digital transformation.

One of the questions was how much of our budget is dedicated to a digital platform to support our marketing? Certainly, the percentages were quite high, but we also found that there is still budget being invested in your more traditional channels, including things like print and events. Events in particular, because of the face-to-face communication that occurs and how business is still done over a handshake, and we can’t underestimate that.

Strong balance

Striking a strong balance between your digital marketing channels as well as your traditional marketing channels is key. Keeping the message consistent in how we market between those channels is also quite key, and then understanding the various buyer personas that you speak with. If you’re creating a digital campaign for the CIO audience, the messages are going to be different from how you would market to a chief financial officer (CFO) audience.

As an example, and it’s really important, back to an earlier point I made around relevancy, you’ve got to stay consistent, but you also have to make sure you’re being relevant, and then taking into account a strong balance between the new digital channels that exists, but also not underestimating the power that still remains with some of our more traditional channels.

Krainik: Alicia, I think you're spot-on. I loved the comment about staying true and consistency, and you’ve demonstrated that with what you’ve done. I know you talked about what we actually see in the market. It’s the importance of creating the brand story and being consistent to that story.

It’s more important now than ever, because then you can get your employees, your advocates, and all your stakeholders supporting that brand story, regardless of the channel. Brand consistency is more important now than the actual advertising campaigns. You’ve done a great job and I think you're spot-on with that. It makes the multichannel execution easier, if you’ve got that nailed, as opposed to chasing it campaign to campaign.

Brand consistency is more important now than the actual advertising campaigns.

Tillman: Yeah, absolutely.

Gardner: Well, Alicia, at this point, where we have these challenges, we're also facing some great new tools in the marketplace, ways to get more information, get customization, use big data, and leverage cloud models to extend our reach, but also to gather more information in better ways. Tell me what you think some of the strong tools are, and I am going to imagine that the SAP Hybris marketing suite is among them.

Tillman: I'd start by ensuring that you have a strong marketing automation platform. It's becoming commonplace in most marketing organizations, large or small, for the past five years or so and it’s certainly growing in size in terms of marketing organizations that are raising the technology.

Essentially, this technology allows you to automate the lead generation process to help you manage campaigns in an automated way, help you nurture the leads that are coming through your demand waterfall in an automated way. The leads that you’re handing off to sales are more qualified than they ever had been before.

You have such an extreme ability to nurture these leads using digital campaigns in these automated ways. That’s my first recommendation: you need to pursue marketing automation technology.

The other thing that exists within these technologies is not just an ability to help you manage your campaigns and manage the nurture strategies within them, but it’s also the data that these technologies provide.

As you integrate them with your company's sales customer-relationship-management (CRM) system, it gives you really unprecedented abilities to show where the demand is being created, and how you can most effectively demonstrate the support of marketing to the ultimate growth of the pipeline, and then of course, to the growth of the business.

Focus on measurement

So it is a must-have that you focus on that in particular. That’s the leading place that I would start. Then, there's all of that getting into the analytics. Every marketer should always be focused on measurement. Measurement is the sole thing that has enabled me to grow my team, whether that be headcount or investment.

When you're not sitting across the table from your CEO or my president talking in terms of numbers and data that are showing the true impact as marketing’s existence on the companies thought of mind, you’re essentially not having a conversation, and you will not have an ability to grow your team. So I highly advise that you look at strong marketing automation and data and analytical structure to enable you to help support your programs.

Gardner: What’s super powerful these days about the data is that we're not only gaining a 360-degree view of customers, but we're able to react in near real time, and then target them with precise customization. How are those tools being used, from your vantage point, that sort of feedback loop and an instant ability to know what a customer is doing, learn inference, compare that to other datasets and then offer something back to them, which really should engage them?

Data is what needs to be at the backbone of your operations within the marketing organization, because it really informs everything.

Tillman: Obviously, being part of SAP, I could spend all day talking about the advanced analytical tools that exist, and having the sort of in-memory computing technologies like S/4HANA, which is the backbone of SAP. These tools have the power to look at large datasets quickly. There are many cloud sales applications that work to provide customer information that marketers need in a central location, it’s available at a glance, and it’s delivered in context that’s truly most important for marketers.

There’s so much flexibility in the cloud. Companies can pull together information in real time or live, as we like to say here at SAP, pulling from so many sources. Data is what needs to be at the backbone of your operations within the marketing organization, because it really informs everything from where you can innovate and where campaigns are having the most success, to what that next big thing is going to be to help propel the company forward. And that’s a big part of what’s the core of a marketing organization.

Gardner: Pete, any additional thoughts about what you’re hearing from your CMO audience about use of these data tools?

Krainik: I’ve seen a shift among CMOs in the last year to two years on how they approach data tools. They used to approach it by looking at the tools currently available and choosing one that catches their eye. Now, there are a number of really bright CMOs out there who are actually taking the approach of assuming that they have total visibility, total velocity, and can get total value at their fingertips from a design perspective, whether it’s for demand and lead generation or a campaign. So they start with that assumption, then they design what that ideal tool would be. And then they evaluate the tools’ capabilities and processes.

By the way, what’s equally is important, I found out talking to CMOs is that you can have the great tools, but if you don’t have the right team and expertise to run it, post implementation, it can cause a problem. That’s an interesting approach. If you could have any piece of information what would like to begin with, what would you like to have to know about your customers? It just opens up some interesting ideas to really stretch the envelope versus force fitting, and I am sure, Alicia, you are seeing that too with some of your customers.

Tillman: Absolutely.

Gardner: Alicia, looking to the future, what do you see as some of the greatest challenges that marketers are facing? I'm thinking the perhaps the user experience is going to become more important over time, but how do you see that?

New opportunities

Tillman: There are a couple of things. The war to differentiate and to bring new opportunities, new leads, into the business is always going to be a reality for marketers. They're always going to need to have a very clear brand, a very simple message, and one that’s differentiated and relevant.

So focusing on your brand story and ensuring that that brand story is consistent across all of the buying and marketing channels, and is relevant and is compelling is always going to be a reality for marketers, because your brand drives the growth of your business’s bottom line. It’s what fuels your pipeline; it’s what fuels the sale of your product; it's what enables you to tell your story around differentiation. So, there always needs to be a clear focus there.

The other thing too, and I had mentioned this in one of my opening comments, is around this notion of differentiation and thinking beyond products in ways in which you can differentiate yourself. As an example, I work in a B2B space, but think about some of the best consumer brands in the world, and those that we support in our personal lives.

Often, I like to reflect on the brands that I support in my personal life, and when I think about what the similarities are between those brands and why I am so loyal to them, not only are their products best in class, but they’ve actually put their products to use beyond what the day-to-day objective is.

If you think of a brand like Tom’s or Starbucks, they have filled brand promises around where they source their materials, where they donate portions of their revenue. And when we think about the millennial population as one, but any buyer, there is a much greater desire for them to partner with organizations that stand for something versus ones that don’t. B2B organizations, in particular, have a tremendous opportunity to think beyond the level in which they’re competing with day after day, and think about what is that higher good.

It’s really how we're taking our value proposition and using it to create higher good in the world around things that people care about and really mater at the end of the day. That’s the real opportunity for marketers.

When we talk about visions, vision statements should be operational, and it’s really how we're taking our value proposition and using it to create higher good in the world around things that people care about and really mater at the end of the day. That’s the real opportunity for marketers.

Gardner: Pete, what advice would you offer the CMOs as they think to overcome these challenges in order to reach this vision of a brand-driven and customer-centric world?

Krainik: The two most important things are, first, that I would put my energies around making sure that I have a marketing organization that has the new marketing skills and new technical skills needed for success. Number one, get the best and the brightest.

The other thing, in addition to the differentiation that was discussed, is this whole issue of ecosystem of innovation: creating an ecosystem, understanding how I am going to look to the outside to bring in new ideas, new startup capabilities, new energy. Those are the two essentials for success. If you don’t do those, I think people are going to be in trouble long term.

Gardner: I'm afraid we will have to leave it there. You’ve been listening to a BriefingsDirect podcast discussion focused on how to build a modern marketing organization. We’ve heard how social media and business networks have taken the lead in shaping perceptions about brands, products, and companies. And we have learned how savvy companies are embracing these new channels and technologies to increase their brand awareness and drive sales.

So, please join me now in thanking our guests, Alicia Tillman, Chief Marketing Officer at SAP Ariba, and Pete Krainik, Founder and CEO of The CMO Club.

And a big thank you too to our audience as well for joining this SAP Ariba-sponsored business innovation and 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 social media and business networks have taken the lead in shaping perceptions about brands, products, and companies. Copyright Interarbor Solutions, LLC, 2005-2016. All rights reserved.

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The Open Group Amsterdam Conference Panel Delves into How to Best Gain Business Value From Open Platform 3.0

Transcript of a podcast from The Open Group Conference, exploring the future and direction of Open Platform 3.0.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: The Open Group.

Dana Gardner: Hello, and welcome to a special BriefingsDirect Podcast coming to you from a recent The Open Group Conference on May 13 in Amsterdam.

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, and I’ll be your host for these discussions focused on  Enabling Boundaryless Information Flow.

Today, we present a series of presentations and a panel discussion on obtaining value from Open Platform 3.0, which is the shift to big data, cloud, Internet-of-Things, mobile, and social in a combination that impacts business. Follow the ongoing discussions on twitter at #ogChat. 

First, I will hand it off to today's moderator, Stuart Boardman, a Senior Business Consultant at KPN and The Open Platform 3.0 Forum co-chairman. 

He'll be followed by Dr. Chris Harding, Director for Interoperability at The Open Group and The Open Platform 3.0 Forum Director, who will then hand it off to Lydia Duijvestijn, Executive Architect at IBM Global Business Services in the Netherlands. 

Later in the program, joining Stuart, Chris and Lydia, will be our additional panelists. They are: Andy Jones, Technical Director for EMEA at SOA Software; TJ Virdi, Computing Architect in the Systems Architecture Group at Boeing and also co-chair of the Open Platform 3.0 Forum; Louis Dietvorst, Enterprise Architect at Enexis in the Netherlands; Sjoerd Hulzinga, Charter Lead at KPN Consulting; and lastly, Frans van der Reep, Professor at the Inholland University of Applied Sciences. 

And now, here's our moderator, Stuart Boardman.

Stuart Boardman: Welcome to the first afternoon session about obtaining value from Open Platform 3.0, and how we're actually going to get value out of the things that we want to implement from big data, social, and the Internet-of-Things, etc., in collaboration with each other. 

Boardman

We're going to start off with Chris Harding, who is going to give us a brief explanation of what the platform is, what we mean by it, what we've produced so far, and where we're trying to go with it. 

He'll be followed by Lydia Duijvestijn, who will give us a presentation about the importance of non-functional requirements (NFRs). If we talk about getting business value, those are absolutely central. Then, we're going to go over to a panel discussion with additional guests. 

Without further ado, here's Chris Harding, who will give you an introduction to Open Platform 3.0. 

Purpose of architecture

Dr. Chris Harding: Hello, everybody. It's a great pleasure to be here in Amsterdam. I was out in the city by the canals this morning. The sunshine was out, and it was like moving through a set of picture postcards. 

Harding

It's a great city. As you walk through, you see the canals, the great buildings, the houses to the sides, and you see the cargo hoists up in the eaves of those buildings. That reminds you that the purpose of the arrangement was not to give pleasure to tourists, but because Amsterdam is a great trading city, that is a very efficient way of getting goods distributed throughout the city. 

That's perhaps a reminder to us that the primary purpose of architecture is not to look beautiful, but to deliver business value, though surprisingly, the two often seem to go together quite well. 

Probably when those canals were first thought of, it was not obvious that this was the right thing to do for Amsterdam. Certainly it would not be obvious that this was the right layout for that canal network, and that is the exciting stage that we're at with Open Platform 3.0 right now.

We have developed a statement, a number of use cases. We started off with the idea that we were going to define a platform to enable enterprises to get value from new technologies such as cloud computing, social computing, mobile computing, big data, the Internet-of-Things, and perhaps others.

We developed a set of business use cases to show how people are using and wanting to use those technologies. We developed an Open Group business scenario to capture the business requirements. That then leads to the next step. All these things sound wonderful, all these new technologies sound wonderful, but what is Open Platform 3.0? 

Jones

Though we don't have the complete description of it yet, it is beginning to take shape. That's what I am hoping to share with you in this presentation, our current thoughts on it. 

Looking historically, the first platform, you could say, was operating systems -- the Unix operating system. The reason why The Open Group, X/Open in those days, got involved was because we had companies complaining, "We are locked into a proprietary operating system or proprietary operating systems. We want applications portability." The value delivered through a common application environment, which was what The Open Group specified for Unix, was to prevent vendor lock-in. 

The second platform is the World Wide Web. That delivers a common services environment, for services either through accessing web pages for your browser or for web services where programs similarly can retrieve or input information from or to the web service. 

The benefit that that has delivered is universal deployment and access. Pretty much anyone or any company anywhere can create a services-based solution and deploy it on the web, and everyone anywhere can access that solution. That was the second platform. 

Common environment

The way Open Platform 3.0 is developing is as a common architecture environment, a common environment in which enterprises can do architecture, not as a replacement for TOGAF. TOGAF is about how you do architecture and will continue to be used with Open Platform 3.0. 

Open Platform 3.0 is more about what kind of architecture you will create, and by the definition of a common environment for doing this, the big business benefit that will be delivered will be integrated solutions. 

Yes, you can develop a solution, anyone can develop a solution, based on services accessible over the World Wide Web, but will those solutions work together out of the box? Not usually. Very rarely. 

Virdi

There is an increasing need, which we have come upon in looking at The Open Platform 3.0 technologies. People want to use these technologies together. There are solutions developed for those technologies independently of each other that need to be integrated. That is why Open Platform 3.0 has to deliver a way of integrating solutions that have been developed independently. That's what I am going talk about. 

The Open Group has recently published its first thoughts on Open Platform 3.0, that's the White Paper. I will be saying what’s in that White Paper, what the platform will do -- and because this is just the first rough picture of what Open Platform 3.0 could be like -- how we're going to complete the definition. Then, I will wrap up with a few conclusions. 

So what is in the current White Paper? Well, what we see as being eventually in the Open Platform 3.0 standards are a number of things. You could say that a lot of these are common architecture artifacts that can be used in solution development, and that's why I'm talking about a common architecture environment.

Statement of need objectives and principles is not that of course; it's why we're doing it. 

Dietvorst

Definition of key terms: clearly you have to share an understanding of the key terms if you're going to develop common solutions or integrable solutions. 

Stakeholders and their concerns: an important feature of an architecture development. An understanding of the stakeholders and their concerns is something that we need in the standard. 

A capabilities map that shows what the products and services do that are in the platform. 

And basic models that show how those platform components work with each other and with other products and services. 

Explanation: this is an important point and one that we haven’t gotten to yet, but we need to explain how those models can be combined to realize solutions. 

Standards and guidelines

Finally, it's not enough to just have those models; there needs to be the standards and guidelines that govern how the products and services interoperate. These are not standards that The Open Group is likely to produce. They will almost certainly be produced by other bodies, but we need to identify the appropriate ones and, probably in some cases, coordinate with the appropriate bodies to see that they are developed.

van der Reep

What we have in the White Paper is an initial statement of needs, objectives, and principles; definitions of some key terms; our first-pass list of stakeholders and their concerns; and maybe half a dozen basic models. These are in an analysis of the use cases, the business use cases, for Open Platform 3.0 that were developed earlier. 

These are just starting points, and it's incomplete. Each of those sections is incomplete in itself, and of course we don't have the complete set of sections. It's all subject to change. 

This is one of the basic models that we identified in the snapshot. It's the Mobile Connected Device Model and it comes up quite often. And you can see, that stack on the left is a mobile device, it has a user, and it has a platform, which would probably be Android or iOS, quite likely. And it has infrastructure that supports the platform. It’s connected to the World Wide Web, because that’s part of the definition of mobile computing. 

On the right, you see, and this is a frequently encountered pattern, that you don't just use your mobile phone for running an app. Maybe you connect it to a printer. Maybe you connect it to your headphones. Maybe you connect it to somebody's payment terminal. You might connect it to various things. You might do it through a USB. You might do it through Bluetooth. You might do it by near field communication (NFC). 

It's fundamental to mobile computing and also somewhat connected to the Internet of Things.

But you're connecting to some device, and that device is being operated possibly by yourself, if it was headphones; and possibly by another organization if, for example, it was a payment terminal and the user of the mobile device has a business relationship with the operator of the connected device.

That’s the basic model. It's one of the basic models that came up in the analysis of use cases, which is captured in the White Paper. As you can see, it's fundamental to mobile computing and also somewhat connected to the Internet-of-Things.

That's the kind of thing that's in the current White Paper, a specific example of all those models in the current White Paper. Let’s move on to what the platform is actually going to do? 

There are three slides in this section. This slide is probably familiar to people who have watched presentations on Open Platform 3.0 previously. It captures our understanding of the need to obtain information from these new technologies, the social media, the mobile devices, sensors, and so on, the need to process that information, maybe on the cloud, and to manage it, stewardship, query and search, all those things. 

Ultimately, and this is where you get the business value, it delivers it in a form where there is analysis and reasoning, which enables enterprises to take business decisions based on that information.

So that’s our original picture of what Open Platform 3.0 will do. 

IT as broker

This next picture captures a requirement that we picked up in the development of the business scenario. A gentleman from Shell gave the very excellent presentation this morning. One of the things you may have picked up him saying was that the IT department is becoming a broker.

Traditionally, you would have had the business use in the business departments and pretty much everything else on that slide in the IT department, but two things are changing. One, the business users are getting smarter, more able to use technology; and two, they want to use technology either themselves or to have business technologists closely working with them.

Systems provisioning and management is often going out to cloud service providers, and the programming, integration, and helpdesk is going to brokers, who may be independent cloud brokers. This is the IT department in a broker role, you might say. 

But the business still needs to retain responsibility for the overall architecture and for compliance. If you do something against your company’s principles, it's not a good defense to say, "Well, our broker did it that way." You are responsible. 

That's why we're looking for Open Platform 3.0 to define the common models that you need to access the technologies in question.

Similarly, if you break the law, your broker does not go to jail, you do. So those things will continue to be more associated with the business departments, even as the rest is devolved. And that’s a way of using IT that Open Platform 3.0 must and will accommodate. 

Finally, I mentioned the integration of independently developed solutions. This next slide captures how that can be achieved. Both of these, by the way, are from the analysis of business use cases. 

Also, you'll also notice they are done in ArchiMate, and I will give ArchiMate a little plug at this point, because we have found it actually very useful in doing this analysis. 

But the point is that if those solutions share a common model, then it's much easier to integrate them. That's why we're looking for Open Platform 3.0 to define the common models that you need to access the technologies in question.

It will also have common artifacts, such as architectural principles, stakeholders, definitions, descriptions, and so on. If the independently developed architectures use those, it will mean that they can be integrated more easily.

So how are we going to complete the definition of Open Platform 3.0? This slide comes from our business use cases’ White Paper and it shows the 22 use cases we published. We've added one or two to them since the publication in a whole range of areas: multimedia, social networks, building energy management, smart appliances, financial services, medical research, and so on. Those use cases touch on a wide variety of areas.

You can see that we've started an analysis of those use cases. This is an ArchiMate picture showing how our first business use case, The Mobile Smart Store, could be realized. 

Business layer

And as you look at that, you see common models. If you notice, that is pretty much the same as the TOGAF Technical Reference Model (TRM) from the year dot. We've added a business layer. I guess that shows that we have come architecturally a little way in that direction since the TRM was defined. 

But you also see that the same model actually appears in the same use case in a different place, and it appears all over the business use cases.

But you can also see there that the Mobile Connected Device Model has appeared in this use case and is appearing in other use cases. So as we analyze those use cases, we're finding common models that can be identified, as well as common principles, common stakeholders, and so on. 

So we have a development cycle, whereby the use cases provide an understanding. We'll be looking not only at the ones we have developed, but also at things like the healthcare presentation that we heard this morning. That is really a use case for Open Platform 3.0 just as much as any of the ones that we have looked at. We'll be doing an analysis of those use cases and the specification and we'll be iterating through that. 

This enables enterprises to derive business value from social computing, mobile computing, big data, the Internet-of-Things, and potentially new technologies. 

The White Paper represents the very first pass through that cycle. Further passes will result in further White Papers, a snapshot, and ultimately The Open Platform 3.0 standard, and no doubt, more than one version of that standard.

In conclusion, Open Platform 3.0 provides a common environment for architecture development. This enables enterprises to derive business value from social computing, mobile computing, big data, the Internet-of-Things, and potentially new technologies. 

Cognitive computing no doubt has been suggested as another technology that Open Platform 3.0 might, in due course, accommodate. What would that lead to? That would lead to additional use cases and further analysis, which would no doubt identify some basic models for common computing, which will be added to the platform. 

Open Platform 3.0 enables enterprise IT to be user-driven. This is really the revolution on that slide that showed the IT department becoming a broker, and devolvement of IT to cloud suppliers and so on. That's giving users the ability to drive IT directly themselves, and the platform will enable that. 

It will deliver the ability to integrate solutions that have been independently developed, with independently developed architectures, and to do that within a business ecosystem, because businesses typically exist within one or more business ecosystems. 

Those ecosystems are dynamic. Partners join, partners leave, and businesses cannot necessarily standardize the whole architecture across the ecosystem. It would be nice to do so, but by the time you finish the job, the business opportunity would be gone. 

So independently developed integration of independently developed architectures is crucial to the world of business ecosystems and delivering value within them. 

Iterative process

The platform will deliver that and is being developed through an iterative process of understanding the content, analyzing the use cases, and documenting the common features, as I have explained.

The development is being done by The Open Platform 3.0 Forum, and these are representatives of Open Group members. They are defining the platform. And the forum is not only defining the platform, but it's also working on standards and guides in the technology areas. 

For example, we have reformed a group to develop a White Paper on big data. If you want to learn about that, Ken Street, who is one of the co-chairs, is in this conference. And we also have cloud projects and other projects.

But not only are we doing the development within the Forum, we welcome input and comments from other individuals within and outside The Open Group and from other industry bodies. That’s part of the purpose of publishing the White Paper and giving this presentation to obtain that input and comment. 

The platform will deliver that and is being developed through an iterative process of understanding the content, analyzing the use cases, and documenting the common features

If you need further information, here's where you can download the White Paper from. You have to give your name and email address and have an Open Group ID and then it's free to download. 

If you are looking for deeper information on what the Forum is doing, the Forum Plato page, which is the next URL, is the place to find it. Nonmembers get some information there; Forum members can log in and get more information on our work in progress. 

If your organization is not a member of The Open Group, you can find out about Open Group membership from that URL. So thank you very much for your attention.

Boardman: Next is Lydia Duijvestijn, who is one of these people who, years ago when I first got involved in this business, we used to call Technical Architects, when the term meant something. The Technical Architect was the person who made sure that the system actually did what the business needed it to do, that it performed, that it was reliable, and that it was trustworthy. 

That's one of her preoccupations. Lydia is going to give us a short presentation about some ideas that she is developing and is going to contribute to The Open Platform 3.0. 

Quality of service

Lydia Duijvestijn: Like Stuart said, my profession is being an architect, apart from your conventional performance engineer. I lead a worldwide community within IBM for performance and competency. I've been working a couple of years with the Dutch Research Institute on projects around quality of service. That basically is my focus area within the business. I work for Global Services within IBM. 

Duijvestijin

What I want to achieve with this presentation is for you to get a better awareness of what functional requirements, functional characteristics, or quality of service characteristics are, and why they won't just appear out of the blue when the new world of Platform 3.0 comes along. They are getting more and more important. 

I will zoom in very briefly on three categories; performance and scalability, availability and business continuity, and security and privacy. I'm not going to talk in detail about these topics. I could do that for hours, but we don’t have the time. 

Then, I'll briefly start the discussion on how that reflects into Platform 3.0. The goal is that when we're here next year at the same time, maybe we would have formed a stream around it and we would have many more ideas, but now, it's just in the beginning.

This is a recap, basically, of a non-functional requirement. We have to start the presentation with that, because maybe not everybody knows this. They basically are qualities or constraints that must be satisfied by the IT system. But normally, it's not the highest priority. Normally, it's functionality first and then the rest. We'll find out about that later when the thing is going into production, and then it's too late. 

So what sorts of non-functionals do we have? We have run-time non-functionals, things that can be observed at run-time, such as performance, availability, or what have you. We also have non-run-time non-functionals, things that cannot apparently be tested, such as maintainability, but they are all very important for the system. 

Non-functionals are fairly often seen as a risk. If you did not pay attention to them, very nasty things could happen.

Then, we have constraints, limitations that you have to be aware of. It looks like in the new world, there are no limitations, cloud is endless, but in fact it's not true. 

Non-functionals are fairly often seen as a risk. If you did not pay attention to them, very nasty things could happen. You could lose business. You could lose image. And many other things could happen to you. It's not seen as something positive to work on it. It's seen as a risk if you don’t do it, but it's a significant risk. 

We've seen occasions where a system was developed that was really doing what it should do in terms of functionality. Then, it was rolled into production, all these different users came along, and the website completely collapsed. The company was in the newspapers, and it was a very bad place to be in. 

As an example, I took this picture in Badaling Station, near the Great Wall. I use this in my performance class. This depicts a mismatch between the workload pattern and the available capacity. 

What happens here is that you take the train in the morning and walk over to Great Wall. Then you've seen it, you're completely fed up with it, and you want to go back, but you have to wait until 3 o’clock for the first train. The Chinese people are very patient people. So they accept that. In the Netherlands people would start shouting and screaming, asking for better.

Basic mismatch

This is an example from real life, where you can have a very dissatisfied user because there was a mismatch between the workload, the arrival pattern, and available capacity. 

But it can get much worse, here we have listed a number of newspaper quotes as a result of security incidents. This is something that really bothers companies. This is also non-functional. It's really very important, especially when we go towards always on, always accessible, anytime, anywhere. This is really a big issue. 

There are many, many non-functional aspects, as you can see. This guy is not making sense out of it. He doesn’t know how to balance it, because it's not as if you can have them all. If you put too much focus on one, it could be bad for the other. So you really have to balance and prioritize. 

Not all non-functionals are equally important. We picked three of them for our conference in February: performance, availability and security. I now want to talk about performance. 

It's really very important, especially when we go towards always on, always accessible, anytime, anywhere. This is really a big issue. 

Everybody recognizes this picture. This was Usain Bolt winning his 100 meters in London. Why did I put this up? Because it very clearly shows what it's all about in performance. There are three attributes that are important.

You have the response time, basically you compare the 100 meters time from start to finish. 

You have the throughput, that is the number of items that can be processed with the time limit. If this is an eight-lane track, you can have only eight runners at the same time. And the capacity is basically the fact that this was an eight lane track, and they are all dependent on each other. It's very simple. But you have to be aware of all of them when you start designing your system. So this is performance. 

Now, let’s go to availability. That is really a very big point today, because with the coming of the Internet in the '90s, availability really became important. We saw that when companies started opening up their mainframes for the Internet, they weren't designed for being open all the time. This is about scheduled downtime. Companies such as eBay, Amazon, Google are setting the standard. 

We come to a company, and they ask us for our performance engineering. We ask them what their non-functional requirements are. They tell us that it has to be as fast as Google.

Well, you're not doing the same thing as Google; you are doing something completely different. Your infrastructure doesn’t look as commodity as Google's does. So how are you going to achieve that? But that is the perception. That is what they want. They see that coming their way.

Big challenge

They're using mobile devices, and they want it also in the company. That is the standard, and disaster recovery is slowly going away. RTO/RPO are going to 0. It's really a challenge. It's a big challenge.

The future is never-down technology independence, and it's very important to get customer satisfaction. This is a big thing.

Now, a little bit about security incidents. I'm not a security specialist. This was prepared by one of my colleagues. Her presentation shows that nothing is secure, nothing, and you have all these incidents. This comes from a report that tracks over several months what sort of incidents are happening. When you see this, you really get frightened. 

Is there a secure site? Maybe, they say, but in fact, no, nothing is secure. This is also very important, especially nowadays. We're sharing more and more personal information over the net. It's really important to think about this. 

What does this have to do with Platform 3.0? I think I answered it already, but let's make it a little bit more specific. Open Platform 3.0 has a number of constituents, and Chris has introduced that to you. 

In the Internet of Things,we have all these devices, sensors, creating huge amounts of data. They're collected by very many different devices all over the place. 

I want to highlight the following clouds, the ones with the big letters in it. There is Internet-of-Things, social, mobile, cloud, big data, but let’s talk about this and briefly try to figure out what it means in terms of non-functionals. 

In the Internet of Things,we have all these devices, sensors, creating huge amounts of data. They're collected by very many different devices all over the place. 

If this is about healthcare, you can understand that privacy must be ensured. Social security privacy is very important in that respect. And it doesn’t come for free. We have to design it into the systems. 

Now, big data. We have the four Vs there; Volume, Variety, Velocity, and Veracity. That already suggests a high focus on non-functionals, especially volume, performance, veracity, security, velocity, performance, and also availability, because you need this information instantaneously. When decisions have to be made based on it, it has to be there. 

So non-functionals are really important for big data. We wrote a white paper about this, and it's very highly rated. 

Cloud has a specific capacity of handling multi-tenant environments. So we have to make sure that the information of one tenant isn’t entered in another tenant’s environment. That's a very important security problem again. There are different workloads coming in parallel, because all these tenants have to have very specific types of workloads. So we have to handle it and balance it. That’s a performance problem. 

Non-functional aspects

Again, there are a lot of non-functional aspects. For mobile and social, the issue is that  you have to be always on, always there, accessible from anywhere. In social especially, you want to share your photos, you personal data, with your friends. So it's social security again. 

It's actually very important in Platform 3.0 and it doesn’t come for free. We have to design it into our model. 

That's basically my presentation. I hope that you enjoyed it and that it has made you aware of this important problem. I hope that, in the next year, we can start really thinking about how to incorporate this in Platform 3.0. 

Boardman: Let me introduce the panelists: Andy Jones of SOA Software, TJ Virdi from Boeing, Louis Dietvorst from Enexis, Sjoerd Hulzinga from KPN, and Frans van der Reep from Inholland University. 

The subject of interoperability, the semantic layer, is going to be a permanent and long running problem.

We want the panel to think about what they've just heard and what they would like Platform 3.0 to do next. What is actually going to be the most important, the most useful, for them, which is not necessarily the things we have thought of.

Andy Jones: The subject of interoperability, the semantic layer, is going to be a permanent and long running problem. We're seeing some industries. for example, clinical trials data, where they can see movement in that area. Some financial services businesses are trying to abstract their information models, but without semantic alignment, the vision of the platform is going to be difficult to achieve. 

Louis Dietvorst: For my vision on Platform 3.0 and what it should support, I am very much in favor of giving the consumer or the asking party the lead, empower them. If you develop this kind of platform thinking, you should do it with your stakeholders and not for your stakeholders. And I wonder how can we attach those kind of stakeholders that they become co-creators. I don’t know the answer. 

Male Speaker: Neither do I, but I feel that what The Open Group should be doing next on the platform is, just as my neighbor said, keep the business perspective, the user perspective, continuously in your focus, because basically that’s the only reason you're doing it. 

In the presentation just now from Lydia about NFRs, you need to keep in mind that one of the most difficult, but also most important, parts of the model ought to be the security and blind spots over it. I don’t disagree that they are NFRs. They are probably the most important requirements. It’s where you start. That would be my idea of what to do next. 

Not platform, but ecosystem

Male Speaker: Three remarks. First, I have the impression this is not a platform, but an ecosystem. So one should change the wording, number one.You should correct the wording. 

Second, I should stress the business case. Why should I buy this? What problem does it solve? I don’t know yet. 

The third point, as the Open Group, I would welcome a lobby to make IT vendors, in a formal sense, product reliable like other industries -- cars, for example. That will do a lot for the security problem the last lady talked about. IT centers are not reliable. They are not responsible. That should change in order to be a grownup industry. 

TJ Virdi: I agree about what’s been said, but I will categorize in three elements here what I am looking for from a Boeing perspective on what platform should be doing: how enterprises could create new business opportunities, how they can actually optimize their current business processes or business things, and how they can optimize the operational aspects. 

So if there is a way to expedite these by having some standardized way to do things, Open Platform 3.0 would be a great forum to do that. 

In the bottom layers, in the infrastructure, there is lot of reliability. Everything is very much known and has been developed for a long time.

Boardman: Okay, thanks.Louis made the point that we need to go to the stakeholders and find out what they want. Of course, we would love if everybody in the world were a member of The Open Group, but we realize that that isn’t going to be the case tomorrow, perhaps the day after, who knows. In the meantime, we're very interested in getting the perspectives of a wider audience. 

So if you have things you would like to contribute, things you would like to challenge us with, questions, more about understanding, but particularly if you have ideas to contribute, you should feel free to do that. Get in touch probably via Chris, but you could also get in touch with either TJ or me as co-chairs, and put in your ideas. Anybody who contributes anything will be recognized. That was a reasonable statement, wasn’t it Chris? You're official Open Group? 

Is there anybody down there who has a question for this panel, raise your hand? 

Duijvestijn: Your remark was that IT vendors are not reliable, but I think that you have to distinguish the layers of the stack. In the bottom layers, in the infrastructure, there is lot of reliability. Everything is very much known and has been developed for a long time. 

If you look at the Gartner reports about incidents in performance and availability, what you see is that most of these happen because of process problems and application problems. That is where the focus has to be. Regarding the availability of applications, nobody ever publishes their book rate.

Boardman: Would anybody like to react to that?

Male Speaker: I totally agree with what Lydia was just saying. As soon as you go up in the stack, that’s where the variation starts. That’s where we need to make sure that we provide some kind of capabilities to manage that easily, so the business can make those kind of expedited way to provide business solutions on that. That’s where we're actually targeting it. 

The lower in the stack we go, it's already commoditized. So we're just trying to see how far high we can go and standardize those things.

Two discussions

Male Speaker: I think there are two discussions together; one discussion is about the reliability on the total [IT process], where the fault is in a [specific IT stack]. I think that’s two different discussions.

I totally agree that IT, or at least IT suppliers, need to focus more on reliability when they get the service as a whole. The customers aren’t interested in where in the stack the problem is. It should be reliable as a whole, not on a platform or in the presentation layer. That’s a non-issue, non-operational, but a non-issue. The issue is it should be reliable, and I totally agree that IT has a long way to go in that department.  

Boardman: I'm going to move on to another question, because an interesting question came up on the Tweets. The question is: "Do you think that Open Platform 3.0 will change how enterprises will work, creating new line of business applications? What impact do you see?" An interesting question. Would anybody like to endeavor to answer that?

Male Speaker: That’s an excellent question actually. When creating new lines of business applications, what we're really looking for is semantic interoperability. How can you bridge the gap between social and business media kind of information, so you can utilize the concept of what’s happening in the social media? Can you migrate that into a business media kind of thing and make it a more agile knowledge or information transfer. 

We are seeing a trend towards line of business apps being composed from micro-apps. So there's less ownership of their own resources.

For example, in the morning we were talking about HL7 as being very heavyweight for healthcare systems. There may be need to be some kind of an easy way to transform and share information. Those kind of things. If we provide those kind of capabilities in the platform, that will make the new line-of-business applications easier to do, as well as it will have an impact in the current systems as well. 

Jones: We are seeing a trend towards line of business apps being composed from micro-apps. So there's less ownership of their own resources. And with new functionality being more focused on a particular application area, there's less utility bundling. 

It also leads on to the question of what happens to the existing line of business apps. How will they exist in an enterprise, which is trying to go for a Platform 3.0 kind of strategy? Lydia’s point about NFRs and the importance of the NFRs brings into light a question of applications that don’t meet NFRs which are appropriate to the new world, and how you retrofit and constrain their behavior, so that they do play well in that kind of architecture. This is an interesting problem for most enterprises. 

Boardman: There's another completely different granularity question here. Is there a concept of small virtualization, a virtual machine on a watch or phone? 

Male Speaker: On phones and all, we have to make a compartmentalized area, where it's kind of like a sandbox. So you can consider that as a virtualization of area, where you would be doing things and then tearing that apart. 

It's not similar to what virtualization is, but it's creating a sandbox in smart devices, where enterprises could utilize some of their functionality, not mingling up with what are called personal device data. Those things are actually part of the concept, and could be utilized in that way. 

Architectural framework

Question: My question about virtualization is linked to whether this is just an architectural framework. Because when I hear the word platform, it's something I try to build something on, and I don’t think this is something I build on. If you can, comment on the validity of the use of the word platform here. 

Male Speaker: I don’t care that much what it is called. If I can use it in whatever I am doing and it produces a positive outcome for me, I'm okay with it. I gave my presentation the Internet-of-Things, or the Internet of everything, or the everywhere or the Thing of Net, or the Internet of People. Whatever you want to call it, just name it, if you can identify its object that’s important to you. That’s okay with me. The same thing goes for Platform 3.0 or whatever.

I'm happy with whatever you want to call it. Those kinds of discussions don't really contribute to the value that you want to produce with this effort. So I am happy with anything. You don't agree?

What we're really trying to do is provide some kind of capabilities that would expedite enterprises to build their business solutions on that.

Male Speaker: A large part of architecture is about having clear understandings and what they mean.

Male Speaker: Let me augment what was just said, and I think Dr. Harding was also alluding to this. It is in the stage where we're defining what Platform 3.0 is. One thing for sure is that we're going to be targeting it as to how you can build that architectural environment. 

Whether it may have frameworks or anything is still to be determined. What we're really trying to do is provide some kind of capabilities that would expedite enterprises to build their business solutions on that. Whether it's a pure translation of a platform per se is still to be determined. 

Boardman: The Internet-of-Things is still a very fuzzy definition. Here we're also looking at fuzzy definitions, and it's something that we constantly get asked questions about. What do we mean by Platform 3.0? 

The reason this question is important, and I also think Sjoerd’s answer to it is important, is because there are two aspects of the problem. What things do we need to tie down and define because we are architects and what things can we simply live with. As long as I know that his fish is my bicycle, I'm okay. 

It's one of the things we're working on. One of the challenges we have in the Forum is what exactly are we going to try and tie down in the definition and what not? Sorry, I had to slip that one in. 

I wanted to ask about trust, how important you see the issue of trust. My attention was drawn to this because I just saw a post that the European Court of Justice has announced that Google has to make it possible for any person or organization who asks for it to have Google erase all information that Google has stored anywhere about them

I wonder whether these kinds of trust issues going to become critical for the success of this kind of  ecosystem, because whether we call it a platform or not, it is an ecosystem.

Trust is important

Male Speaker: I'll try to start an answer. Trust is a very important part ever since the Internet became the backbone of all of those processes and all of those systems in those data exchanges. The trouble is that it's very easy to compromise that trust, as we have seen with the word from the NSA as exposed by Snowden. So yes, trust ought to be a part of it, but trust is probably pretty fragile the way w're approaching it right now. 

Do I have a solution to that problem? No, I don't. Maybe it will come in this new ecosystem. I don't see it explicitly being addressed, but I am assuming that, between all those little clouds, there ought to be some kind of a trust relationship. That's my start of an answer.

Andy Jones: Trust is going to be one of those permanently difficult questions. In historical times, maybe the types of organizations that were highest in trust ratings would have been perhaps democratic governments and possibly banks, neither of which have been doing particularly well in the last five years in that area. 

It’s going to be an ethical question for organizations who are gathering and holding data on behalf of their consumers. We know that if you put a set of terms and conditions in front of your consumers, they will probably click on "agree" without reading it. So you have to decide what trust you're going to ask for and what trust you think you can deliver on. 

That data can then be summarized across groups of individuals to create an ensemble dataset. At what level of privacy are we then?

Data ownership and data usage is going to be quite complex. For example, in clinical trials data, you have a set of data, which can be identified against the named individual. That sounds quite fine, but you can then make that set of data so it’s anonymized and is known to relate to a single individual, but can no longer identify who. Is that as private? 

That data can then be summarized across groups of individuals to create an ensemble dataset. At what level of privacy are we then? It seems to quickly goes out of the scope of reason and understanding of the consumer themselves. So the responsibility for ethical behavior appears to lie with the experts, which is always quite a dangerous place.

Male Speaker: We probably all agree that trust management is a key aspect when we are converging different solutions from so many partners and suppliers. When we're talking about Internet of data, Internet-of-Things, social, and mobile, no one organization would be providing all the solutions from scratch. 

So we may be utilizing stuff from different organizations or different organizational boundaries. Extending the organizational boundaries requires a very strong trust relationship, and it is very significant when you are trying to do that.

Boardman: There was a question that went through a little while ago. I'm noticing some of these questions are more questions to The Open Group than to our panel, but one I felt I could maybe turn around. The question was: "What kind of guidelines is the Forum thinking of providing?"

I'd like to do is turn that around to the panel and ask: what do you think it would be useful for us to produce? What would you like a guideline on, because there would be lots of things where you would think you don’t need that, you'll figure it out for yourself. But what would actually be useful to you if we were to produce some guidelines or something that could be accepted as a standard? 

Does it work?

Male Speaker: Just go to a number of companies out there and test whether it works. 

Male Speaker: In terms of guidelines, you mentioned it very well about semantic interoperability. How do you exchange information between different participants in an ecosystem or things built on a platform. 

The other thing is how you can standardize things that are yet to be standardized. There's unstructured data. There are things that need to be interrogated through that unstructured data. What are the guiding principles and guidelines that would do those things? So maybe in those areas, Platform 3.0 with the participations from these Forum members, can advance and work on it. 

Andy Jones: I think contract, composition, and accumulation. If an application is delivering service to its end users by combining dozens of complementary services, each of which has a separate contract, what contract can it then offer to its end user?

Boardman: Does the platform plan to define guidelines and directions to define application programming interfaces (APIs) and data models or specific domains? Also, how are you integrating with major industry reference models? 

Just for the information, some of this is work of other parts of The Open Group's work around industry domain reference models and that kind of thing. But in general, one of the things we've said from the Platform, from the Forum, is that as much as possible, we want to collate what is out there in terms of standards, both in APIs, data models, open data, etc.

No single organization would be able to actually tap into all the advancement that’s happening in technologies, processes, and other areas where business could utilize those things so quickly.

We're desperate not to go and reproduce anybody else’s work. So we are looking to see what’s out there, so the guideline would, as far as possible, help to understand what was available in which domain, whether that was a functional domain, technical domain, or whatever. I just thought I would answer those because we can’t really ask the panel that.

We said that the session would be about dealing with realizing business value, and we've talked around issues related to that, depending on your own personal take. But I'd like to ask the members of the panel, and I'd like all of you to try and come up with an answer to it: What do you see are the things that are critical to being able to deliver business value in this kind of ecosystem?

I keep saying ecosystem, not to be nice to Frans, I am never nice to Frans, but because I think that that captures what we are talking about better. So do you want to start TJ? What are you looking for in terms of value? 

Virdi: No single organization would be able to actually tap into all the advancement that’s happening in technologies, processes, and other areas where business could utilize those things so quickly. The expectations from business values or businesses to provide new solutions in real-time, information exchange, and all those things are the norm now. 

We can provide some of those as a baseline to provide as maybe foundational aspects to business to realize those new things what we are looking as in social media or some other places, where things are getting exchanged so quickly, and the kind of payload they have is a very small payload in terms of information exchange.

So keeping the integrity of information, as well as sharing the information with the right people at the right time and in the right venue, is really the key when we can provide those kind of enabling capabilities.

Ease of change

Andy Jones: In Lydia’s presentation, at the end, she added the ease of use requirement as the 401st. I think the 402nd is ease of change and the speed of change. Business value pretty much relies on dynamism, and it will become even more so. Platforms have to be architected in a way that they are sufficiently understood that they can change quickly, but predictably, maintaining the NFRs. 

Louis Dietvorst: One of the reasons why I would want to adopt this new ecosystem is that it gives me enough feeling that it is a reliable product. What we know from the energy system innovations we've done the last three or four years is that the way you enable and empower communities is to build up the trust themselves, locally, like you and your neighbor, or people who are close in proximity. Then, it’s very easy to build trust. 

Some call it social evidence. I know you, you know me, so I trust you. You are my neighbor and together we build a community. But the wider this distance is, the less easy it is to trust each other. That’s something you need to build in into the whole concept. How do you get the trust if it is something that's a global concept. It seems hardly possible.

Frans van der Reep: This ecosystem, or whatever you're going to call it, needs to bring the change, the rate of change. "Change is life" is a well-known saying, but lightning-fast change is the fact of life right now, with things like social and mobile specifically. 

One Twitter storm and the world has a very different view of your company, of your business. Literally, it can happen in minutes. This development ought to address that, and also provide the relevant hooks, if you will, for businesses to deal with that. So the rate of change is what I would like to see addressed in Platform 3.0, the ecosystem. 

In order to create meaningful customer interaction, what we used to call center or whatever, that is where the cognition comes in.

Male Speaker: It should be cheap and reliable, it should allow for change, for example Cognition-as-a-Service, and it should hide complexity for those "stupid businesspeople" and make it simple. 

Boardman: I want to pick up on something that Frans just said because it connects to a question I was going to ask anyway. People sometimes ask us why the particular five technologies that we have named in the Forum: cloud, big data, big-data analysis, social, mobile, and the Internet-of-Things? It's a good question, because fundamental to our ideas in the Forum that it’s not just about those five things. Other things can come along and be adopted. 

One of the things that we had played with at the beginning and decided not to include, just on the basis of a feeling about lack of maturity, was cognitive computing. Then, here comes Frans and just mentions cognitive things. 

I want to ask the panel: "Do you have a view on cognitive computing? Where is it? When we can expect it to be something we could incorporate? Is it something that should be built into the platform, or is it maybe just tangential to the platform?" Any thoughts? 

Male Speaker: I did a speech on this last week. In order to create meaningful customer interaction, what we used to call center or whatever, that is where the cognition comes in. That's a very big market and there's no reason not to include it in the lower levels of the platform and to make it into cloud. 

We have lots of examples already in the Netherlands that ICT devices recognize emotions and from recognizing speech. Recognizing emotion, you can optimize the matching of the company with the customer, and you can hide complexity. I think there’s a big market for that. 

What the business wants

Virdi: We need to look at it in the context of what business wants to do with that. It could be enabling things that could be what I consider as proprietary things, which may not be part of the platform for others to utilize. So we have to balance out what would be the enabling things we can provide as a base of foundation for everyone to utilize. Or companies can build on top of it what values it would provide. We probably have to do a little bit further assessment on that.

Male Speaker: I'd like to follow up on this notion of cognitive computing, the notion that maybe objects are self-aware, as opposed to being dumb -- self-aware being an object, a sensor that’s aware of its neighbor. When a neighbor goes away, it can find other neighbors. Quite simple as opposed to a bar code. 

We see that all the time. We have kids that are civil engineers and they pour it in concrete all the time. In terms of cost, in terms of being able to have the discussion, it's something that’s in front of us all the time. So at this time, should we probably think about at least the binary aspect of having self-aware sensors as opposed to dumb sensors?

Male Speaker: From aviation perspective, there are some areas where dumb devices would be there, as well as active devices. There are some passive sensor devices where you can just interrogate them when you request and there are some devices that are active, constantly sending sensor messages. Both are there in terms of utilization for business to create new business solutions. 

I'm certainly all in favor of devices in the field being able to tell you what they're doing and how they think they're feeling.

Both of them are going to be there, and it depends upon what business needs are to support those things. Probably we could provide some ways to standardize some of those and some other specifications. For example, an ATA, for aviation. They're doing that already. Also, in healthcare, there's HL7, looking for doing some smart sensor devices to exchange information as well. So some work is already happening in the industry. 

There are so many business solutions that have already been built on those. Maybe they're a little bit more proprietary. So a platform could provide some ways to provide a standard base to exchange that information. It may be some things relate to guidelines and how you can exchange information in those active and passive sensor devices.

Andy Jones: I'm certainly all in favor of devices in the field being able to tell you what they're doing and how they think they're feeling. I have an interest in complex consumer devices in retail and other field locations, especially self-service kiosks, and in that field quite a lot of effort has been spent trying to infer the states of devices by their behavior, rather than just having them tell you what's going on, which should be so much easier. 

Male Speaker: Of course, it depends on where the boundary is between aware and not aware. If there is thermometer in the field and it sends data that it's 15 degrees centigrade, for example, do I really want to know whether it thinks it's chilly or not? I'm not really sure about it. 

I'd have to think about it a long time to get a clear answer on whether ther's a benefit in self-aware devices in those kinds of applications. I can understand that there will be an advantage in self-aware sensor devices, but I struggle a little to see any pattern or similarities in those circumstances. 

I could come up with use cases, but I don’t think it's very easy to come up with a certain set of rules that leads to the determination whether or not a self-aware device is applicable in that particular situation. It's a good question. I think it deserves some more thought, but I can't come up with a better answer than that right now.

Case studies

Mark Skilton: I just wanted to add to the embedded question, because I thought it was a very good one. Three case studies happened to me recently. I was doing some work with Rolls Royce and the MH370, the flight that went down. One of the key things about the flight was that the engines had telemetry built in. TJ, you're more qualified to talk about this than I am, but essentially there was information that was embedded in the telemetry of the technology of the plane. 

As we know from the mass media that reported on that, that they were able to analyze from some of the data potentially what was going on in the flight. Clearly, with the band connection, it was the satellite data that was used to project it was going south, rather than north. 

So one of the lessons there was that smart information built into the object was of value. Clearly, there was a lesson learned there. 

With Coca Cola, for example, what's very interesting in retail is that a lot of the shops now have embedded sensors in the cooler systems or into products that are in the warehouse or on stock. Now, you're getting that kind of intelligence over RFID coming back into the supply chain to do backfilling, reordering, and stuff like that. So all of this I see is smart. 

Embedded technology in the dashboard is going to be something that is going to be coming in the next three to five years.

Another one is image recognition when you go into a car park court. You have your face being scanned in, whether you want it or not. Potentially, they can do advertising in context. These are all smart feedback loops that are going on in these ecosystems and are happening right now. 

There are real equations of value in doing that. I was just looking at the Open Automotive Alliance. We've done some work with them around connected car forecast. Embedded technology in the dashboard is going to be something that is going to be coming in the next three to five years with BMW, Jaguar Land Rover, and Volvo. All the major car players are doing this right now. 

So Open Platform 3.0 for me is riding that wave of understanding where the  intelligence and the feedback mechanisms work within each of the supply chains, within each of the contexts, either in the plane, in the shop, or whatever, starting to get intelligence built in. 

We talk about big data and small data at the university that I work at. At the moment, we're moving from a big-data era, which is analytics, static, and analyzing the process in situ. Most likely it's Amazon sort of purchasing recommendations or advertisement that you see on your browser today. 

We 're moving to a small-data era, which is where you have very much data in context of what's going on in the events at that time. I would expect this with embedded technologies. The feedback loops are going to happen within each of the traditional supply chains and will start to build that strength.

The issue for The Open Group is to capture the sort of standards of interoperability and connectivity much like what Boeing is already leading with, with the automotive sector , and with the airline sector. It's riding that wave, because the value of bringing that feedback into context, the small-data context is where the future lies. 

Infrastructure needed

Male Speaker: I totally agree. Not only are the devices or individual components getting smarter, but that requires infrastructures to be there to utilize that sensing information in a proper way. From the Platform 3.0 guidelines or specifications perspective, determining how you can utilize some devices, which are already smart, and others, which are still considered to be legacy, and how you can bridge those gap would be a good thing to do.

Boardman: Would anyone like to add anything, closing remarks?

Andy Jones: Everybody’s perspective and everybody’s context is going to be slightly different. We talked about whether it's a platform ora framework. In the end there will be a built universal 3.0 Platform, but everybody will still have a different view and a different perspective of what it does and what it means to them. 

My suggestion would be that, if you're going to continue with this ecosystem, try to built it up locally, in a locally controlled environment.

Male Speaker: My suggestion would be that, if you're going to continue with this ecosystem, try to built it up locally, in a locally controlled environment, where you can experiment and see what happens. Do it at many places at the same time in the world, and let the factors be proof of the pudding. 

Male Speaker: Whatever you are going to call it, keep to 3.0, that sounds snappy, but just get the beneficiaries in, get the businesses in, and get the users in.

Male Speaker: The more open, the more a commodity it will be. That means that no company can get profit from it. In the end, human interaction and stewardship will enter the market. If you come to London city airport and you find your way in the Tube, there is a human being there who helps you into the system. That becomes very important as well. I think you need to do both, stewardship and these kinds of ecosystems that spread complexity. 

Boardman: That's it for this session. I'd like to ask your applause for our panel and also our speakers.

Gardner: You've been listening to a special BriefingsDirect Podcast coming to you from The Open Group Conference on May 13 in Amsterdam. 

We've heard a series of presentations and a panel discussion, as well as a question-and-answer session, all on obtaining value from Platform 3.0. 

So a big thank you to our contributors here today: Stuart Boardman, a Senior Business Consultant at KPN and Open Platform 3.0 Forum co-chairman; Dr. Chris Harding, Director for Interoperability at The Open Group and Open Platform 3.0 Forum Director; Lydia Duijvestijn, Executive Architect at IBM Global Business Services; Andy Jones, Technical Director for EMEA at SOA Software; TJ Virdi, Computing Architect at Boeing and also a co-chair of The Open Platform 3.0 Forum; Louis Dietvorst, Enterprise Architect at Enexis; Sjoerd Hulzinga, Charter Lead at KPN Consulting; and lastly, Frans van der Reep, Professor at Inholland University of Applied Sciences. 

And of course a big thank you to our audience for joining this special podcast presentation. This is Dana Gardner, Principal Analyst at Interarbor Solutions, your BriefingsDirect host for this podcast. Thanks again for listening and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: The Open Group.

Transcript of a podcast from The Open Group Conference, exploring the future and direction of Open Platform 3.0. Copyright The Open Group and Interarbor Solutions, LLC, 2005-2014. All rights reserved.

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