Click here to close now.

Welcome!

Cloud Expo Authors: Pat Romanski, Elizabeth White, Liz McMillan, Blue Box Blog, Kathy Thomas

Related Topics: Big Data Journal, Microservices Journal, Virtualization, AJAX & REA, Cloud Expo, SDN Journal

Big Data Journal: Article

From Metrics to Success

Ford scours for more big data to bolster quality, improve manufacturing, streamline processes

Ford has exploited the strengths of big data analytics by directing them internally to improve business results. In doing so, they scour the metrics from the company’s best processes across myriad manufacturing efforts and through detailed outputs from in-use automobiles -- all to improve and help transform their business.

So explains Michael Cavaretta, PhD, Technical Leader of Predictive Analytics for Ford Research and Advanced Engineering in Dearborn, Michigan. Cavaretta is one of a group of experts assembled this week for The Open Group Conference in Newport Beach, California.

Cavaretta has led multiple data-analytic projects at Ford to break down silos inside the company to best define Ford’s most fruitful data sets. Ford has successfully aggregated customer feedback, and extracted all the internal data to predict how best new features in technologies will improve their cars.

As a contributor to the The Open Group conference and its focus on "Big Data -- The Transformation We Need to Embrace Today," Cavaretta explains how big data is fostering business transformation by allowing deeper insights into more types of data efficiently, and thereby improving processes, quality control, and customer satisfaction.

The interview was moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: The Open Group is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: What's different now in being able to get at this data and do this type of analysis from five years ago?

Cavaretta: The biggest difference has to do with the cheap availability of storage and processing power, where a few years ago people were very much concentrated on filtering down the datasets that were being stored for long-term analysis. There has been a big sea change with the idea that we should just store as much as we can and take advantage of that storage to improve business processes.

Gardner: How did we get here? What's the process behind the benefits?

Sea change in attitude

Cavaretta: The process behind the benefits has to do with a sea change in the attitude of organizations, particularly IT within large enterprises. There's this idea that you don't need to spend so much time figuring out what data you want to store and worry about the cost associated with it, and more about data as an asset. There is value in being able to store it, and being able to go back and extract different insights from it. This really comes from this really cheap storage, access to parallel processing machines, and great software.

Cavaretta

I like to talk to people about the possibility that big data provides and I always tell them that I have yet to have a circumstance where somebody is giving me too much data. You can pull in all this information and then answer a variety of questions, because you don't have to worry that something has been thrown out. You have everything.

You may have 100 questions, and each one of the questions uses a very small portion of the data. Those questions may use different portions of the data, a very small piece, but they're all different. If you go in thinking, "We’re going to answer the top 20 questions and we’re just going to hold data for that," that leaves so much on the table, and you don't get any value out of it.

The process behind the benefits has to do with a sea change in the attitude of organizations, particularly IT within large enterprises.

We're a big believer in mash-ups and we really believe that there is a lot of value in being able to take even datasets that are not specifically big-data sizes yet, and then not go deep, not get more detailed information, but expand the breadth. So it's being able to augment it with other internal datasets, bridging across different business areas as well as augmenting it with external datasets.

A lot of times you can take something that is maybe a few hundred thousand records or a few million records, and then by the time you’re joining it, and appending different pieces of information onto it, you can get the big dataset sizes.

Gardner: You’re really looking primarily at internal data, while also availing yourself of what external data might be appropriate. Maybe you could describe a little bit about your organization, what you do, and why this internal focus is so important for you.

Internal consultants
Cavaretta: I'm part of a larger department that is housed over in the research and advanced-engineering area at Ford Motor Company, and we’re about 30 people. We work as internal consultants, kind of like Capgemini or Ernst & Young, but only within Ford Motor Company. We’re responsible for going out and looking for different opportunities from the business perspective to bring advanced technologies. So, we’ve been focused on the area of statistical modeling and machine learning for I’d say about 15 years or so.

And in this time, we’ve had a number of engagements where we’ve talked with different business customers, and people have said, "We'd really like to do this." Then, we'd look at the datasets that they have, and say, "Wouldn’t it be great if we would have had this. So now we have to wait six months or a year."

These new technologies are really changing the game from that perspective. We can turn on the complete fire-hose, and then say that we don't have to worry about that anymore. Everything is coming in. We can record it all. We don't have to worry about if the data doesn’t support this analysis, because it's all there. That's really a big benefit of big-data technologies.

The real value proposition definitely is changing as things are being pushed down in the company to lower-level analysts who are really interested in looking at things from a data-driven perspective. From when I first came in to now, the biggest change has been when Alan Mulally came into the company, and really pushed the idea of data-driven decisions.

The real value proposition definitely is changing as things are being pushed down in the company to lower-level analysts.

Before, we were getting a lot of interest from people who are really very focused on the data that they had internally. After that, they had a lot of questions from their management and from upper level directors and vice-president saying, "We’ve got all these data assets. We should be getting more out of them." This strategic perspective has really changed a lot of what we’ve done in the last few years.

Gardner: Are we getting to the point where this sort of Holy Grail notion of a total feedback loop across the lifecycle of a major product like an automobile is really within our grasp? Are we getting there, or is this still kind of theoretical. Can we pull it altogether and make it a science?

Cavaretta: The theory is there. The question has more to do with the actual implementation and the practicality of it. We still are talking a lot of data where even with new advanced technologies and techniques that’s a lot of data to store, it’s a lot of data to analyze, there’s a lot of data to make sure that we can mash-up appropriately.

And, while I think the potential is there and I think the theory is there. There is also a work in being able to get the data from multiple sources. So everything which you can get back from the vehicle, fantastic. Now if you marry that up with internal data, is it survey data, is it manufacturing data, is it quality data? What are the things do you want to go after first? We can’t do everything all at the same time.

Highest value

Our perspective has been let’s make sure that we identify the highest value, the greatest ROI areas, and then begin to take some of the major datasets that we have and then push them and get more detail. Mash them up appropriately and really prove up the value for the technologists.

Gardner: Clearly, there's a lot more to come in terms of where we can take this, but I suppose it's useful to have a historic perspective and context as well. I was thinking about some of the early quality gurus like Deming and some of the movement towards quality like Six Sigma. Does this fall within that same lineage? Are we talking about a continuum here over that last 50 or 60 years, or is this something different?

Cavaretta: That’s a really interesting question. From the perspective of analyzing data, using data appropriately, I think there is a really good long history, and Ford has been a big follower of Deming and Six Sigma for a number of years now.

The difference though, is this idea that you don't have to worry so much upfront about getting the data. If you're doing this right, you have the data right there, and this has some great advantages. You’ll have to wait until you get enough history to look for somebody’s patterns. Then again, it also has some disadvantage, which is you’ve got so much data that it’s easy to find things that could be spurious correlations or models that don’t make any sense.

The piece that is required is good domain knowledge, in particular when you are talking about making changes in the manufacturing plant. It's very appropriate to look at things and be able to talk with people who have 20 years of experience to say, "This is what we found in the data. Does this match what your intuition is?" Then, take that extra step.

Gardner: How has the notion of the Internet of things being brought to bear on your gathering of big data and applying it to the analytics in your organization?

Cavaretta: It is a huge area, and not only from the internal process perspective -- RFID tags within the manufacturing plans, as well as out on the plant floor, and then all of the information that’s being generated by the vehicle itself.

The Ford Energi generates about 25 gigabytes of data per hour. So you can imagine selling couple of million vehicles in the near future with that amount of data being generated. There are huge opportunities within that, and there are also some interesting opportunities having to do with opening up some of these systems for third-party developers. OpenXC is an initiative that we have going on to add at Research and Advanced Engineering.

Huge number of sensors

We have a lot of data coming from the vehicle. There’s huge number of sensors and processors that are being added to the vehicles. There's data being generated there, as well as communication between the vehicle and your cell phone and communication between vehicles.

There's a group over at Ann Arbor Michigan, the University of Michigan Transportation Research Institute (UMTRI), that’s investigating that, as well as communication between the vehicle and let’s say a home system. It lets the home know that you're on your way and it’s time to increase the temperature, if it’s winter outside, or cool it at the summer time.

The amount of data that’s been generated there is invaluable information and could be used for a lot of benefits, both from the corporate perspective, as well as just the very nature of the environment.

Gardner: Just to put a stake in the ground on this, how much data do cars typically generate? Do you have a sense of what now is the case, an average?

Cavaretta: The Energi, according to the latest information that I have, generates about 25 gigabytes per hour. Different vehicles are going to generate different amounts, depending on the number of sensors and processors on the vehicle. But the biggest key has to do with not necessarily where we are right now but where we will be in the near future.

With the amount of information that's being generated from the vehicles, a lot of it is just internal stuff. The question is how much information should be sent back for analysis and to find different patterns? That becomes really interesting as you look at external sensors, temperature, humidity. You can know when the windshield wipers go on, and then to be able to take that information, and mash that up with other external data sources too. It's a very interesting domain.

With the amount of information that's being generated from the vehicles, a lot of it is just internal stuff.

Gardner: What skills do you target for your group, and what ways do you think that you can improve on that?

Cavaretta: The skills that we have in our department, in particular on our team, are in the area of computer science, statistics, and some good old-fashioned engineering domain knowledge. We’ve really gone about this from a training perspective. Aside from a few key hires, it's really been an internally developed group.

Targeted training

The biggest advantage that we have is that we can go out and be very targeted with the amount of training that we have. There are such big tools out there, especially in the open-source realm, that we can spin things up with relatively low cost and low risk, and do a number of experiments in the area. That's really the way that we push the technologies forward.

Talking with The Open Group really gives me an opportunity to be able to bring people on board with the idea that you should be looking at a difference in mindset. It's not "Here’s a way that data is being generated, look, try and conceive of some questions that we can use, and we’ll store that too." Let's just take everything, we’ll worry about it later, and then we’ll find the value.

It's important to be thinking about data as an asset, rather than as a cost. You even have to spend some money, and it may be a little bit unsafe without really solid ROI at the beginning. Then, move towards pulling that information in, and being able to store it in a way that allows not just the high-level data scientist to get access to and provide value, but people who are interested in the data overall. Those are very important pieces.

The last one is how do you take a big-data project, how do you take something where you’re not storing in the traditional business intelligence (BI) framework that an enterprise can develop, and then connect that to the BI systems and look at providing value to those mash-ups. Those are really important areas that still need some work.

There are many companies, especially large enterprises, that are looking at their data assets and wondering what can they do to monetize this, not only to just pay for the efficiency improvement but as a new revenue stream.

Gardner: For those organizations that want to get started on this, how do you get started?

Understand that it maybe going to be a little bit more costly and the ROI isn't going to be there at the beginning.

Cavaretta: We're definitely a huge believer in pilot projects and proof of concept, and we like to develop roadmaps by doing. So get out there. Understand that it's going to be messy. Understand that it maybe going to be a little bit more costly and the ROI isn't going to be there at the beginning.

But get your feet wet. Start doing some experiments, and then, as those experiments turn from just experimentation into really providing real business value, that’s the time to start looking at a more formal aspect and more formal IT processes. But you've just got to get going at this point.

You may also be interested in:

More Stories By Dana Gardner

At Interarbor Solutions, we create the analysis and in-depth podcasts on enterprise software and cloud trends that help fuel the social media revolution. As a veteran IT analyst, Dana Gardner moderates discussions and interviews get to the meat of the hottest technology topics. We define and forecast the business productivity effects of enterprise infrastructure, SOA and cloud advances. Our social media vehicles become conversational platforms, powerfully distributed via the BriefingsDirect Network of online media partners like ZDNet and IT-Director.com. As founder and principal analyst at Interarbor Solutions, Dana Gardner created BriefingsDirect to give online readers and listeners in-depth and direct access to the brightest thought leaders on IT. Our twice-monthly BriefingsDirect Analyst Insights Edition podcasts examine the latest IT news with a panel of analysts and guests. Our sponsored discussions provide a unique, deep-dive focus on specific industry problems and the latest solutions. This podcast equivalent of an analyst briefing session -- made available as a podcast/transcript/blog to any interested viewer and search engine seeker -- breaks the mold on closed knowledge. These informational podcasts jump-start conversational evangelism, drive traffic to lead generation campaigns, and produce strong SEO returns. Interarbor Solutions provides fresh and creative thinking on IT, SOA, cloud and social media strategies based on the power of thoughtful content, made freely and easily available to proactive seekers of insights and information. As a result, marketers and branding professionals can communicate inexpensively with self-qualifiying readers/listeners in discreet market segments. BriefingsDirect podcasts hosted by Dana Gardner: Full turnkey planning, moderatiing, producing, hosting, and distribution via blogs and IT media partners of essential IT knowledge and understanding.

@CloudExpo Stories
Leysin American School is an exclusive, private boarding school located in Leysin, Switzerland. Leysin selected an OpenStack-powered, private cloud as a service to manage multiple applications and provide development environments for students across the institution. Seeking to meet rigid data sovereignty and data integrity requirements while offering flexible, on-demand cloud resources to users, Leysin identified OpenStack as the clear choice to round out the school's cloud strategy. Additional...
SYS-CON Events announced today that Liaison Technologies, a leading provider of data management and integration cloud services and solutions, has been named "Silver Sponsor" of SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York, NY. Liaison Technologies is a recognized market leader in providing cloud-enabled data integration and data management solutions to break down complex information barriers, enabling enterprises to make sm...
The 17th International Cloud Expo has announced that its Call for Papers is open. 17th International Cloud Expo, to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, APM, APIs, Microservices, Security, Big Data, Internet of Things, DevOps and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding bu...
The speed of software changes in growing and large scale rapid-paced DevOps environments presents a challenge for continuous testing. Many organizations struggle to get this right. Practices that work for small scale continuous testing may not be sufficient as the requirements grow. In his session at DevOps Summit, Marc Hornbeek, Sr. Solutions Architect of DevOps continuous test solutions at Spirent Communications, will explain the best practices of continuous testing at high scale, which is r...
Collecting data in the field and configuring multitudes of unique devices is a time-consuming, labor-intensive process that can stretch IT resources. Horan & Bird [H&B], Australia’s fifth-largest Solar Panel Installer, wanted to automate sensor data collection and monitoring from its solar panels and integrate the data with its business and marketing systems. After data was collected and structured, two major areas needed to be addressed: improving developer workflows and extending access to a b...
Due of the rise of Hadoop, many enterprises are now deploying their first small clusters of 10 to 20 servers. At this small scale, the complexity of operating the cluster looks and feels like general data center servers. It is not until the clusters scale, as they inevitably do, when the pain caused by the exponential complexity becomes apparent. We've seen this problem occur time and time again. In his session at Big Data Expo, Greg Bruno, Vice President of Engineering and co-founder of StackI...
As enterprises engage with Big Data technologies to develop applications needed to meet operational demands, new computation fabrics are continually being introduced. To leverage these new innovations, organizations are sacrificing market opportunities to gain expertise in learning new systems. In his session at Big Data Expo, Supreet Oberoi, Vice President of Field Engineering at Concurrent, Inc., discussed how to leverage existing infrastructure and investments and future-proof them against e...
SYS-CON Events announced today Arista Networks will exhibit at SYS-CON's DevOps Summit 2015 New York, which will take place June 9-11, 2015, at the Javits Center in New York City, NY. Arista Networks was founded to deliver software-driven cloud networking solutions for large data center and computing environments. Arista’s award-winning 10/40/100GbE switches redefine scalability, robustness, and price-performance, with over 3,000 customers and more than three million cloud networking ports depl...
Hadoop as a Service (as offered by handful of niche vendors now) is a cloud computing solution that makes medium and large-scale data processing accessible, easy, fast and inexpensive. In his session at Big Data Expo, Kumar Ramamurthy, Vice President and Chief Technologist, EIM & Big Data, at Virtusa, will discuss how this is achieved by eliminating the operational challenges of running Hadoop, so one can focus on business growth. The fragmented Hadoop distribution world and various PaaS soluti...
The DevOps Institute (DOI) launched on Monday with the mission of serving as the premier source for aligning industry standard quality DevOps training and examination services for enterprise IT. The Institute is led by a Board of Regents who will oversee DOI’s offerings in an effort to codify and promote DevOps’ best practices and standards that enable enterprise IT to deliver more value faster to their customers. The initial Board of Regents includes Gene Kim, Lori MacVittie, Sanjeev Sharma, ...
Cryptography has become one of the most underappreciated, misunderstood components of technology. It’s too easy for salespeople to dismiss concerns with three letters that nobody wants to question. ‘Yes, of course, we use AES.’ But what exactly are you trusting to be the ultimate guardian of your data? Let’s face it – you probably don’t know. An organic, grass-fed Kobe steak is a far cry from a Big Mac, but they’re both beef, right? Not exactly. Crypto is the same way. The US government require...
Once the decision has been made to move part or all of a workload to the cloud, a methodology for selecting that workload needs to be established. How do you move to the cloud? What does the discovery, assessment and planning look like? What workloads make sense? Which cloud model makes sense for each workload? What are the considerations for how to select the right cloud model? And how does that fit in with the overall IT transformation?
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo in Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place Nov 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 17th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading in...
All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo, June 9-11, 2015, at the Javits Center in New York City. Learn what is going on, contribute to the discussions, and ensure that your enter...
Red Hat, Inc. has announced Red Hat JBoss Enterprise Application Platform (JBoss EAP) 6.4 and introduced expanded benefits for JBoss EAP subscribers deploying their Java applications in hybrid cloud environments. Enterprises are under pressure to deliver new applications fast; however, many factors, including rigid proprietary stacks, inflexible licensing agreements, and cultural silos in IT can prevent enterprises from achieving the agility they need to stay competitive. Enterprises are incre...
MeriTalk, a public-private partnership focused on improving the outcomes of government IT, today announced the results of its new report, "The Agile Advantage: Can DevOps Move Cloud to the Fast Lane?" The study, underwritten by Accenture Federal Services, reveals that approximately two-thirds of Feds say DevOps will help agencies shift into the cloud fast lane - improving IT collaboration and migration speed. But help is needed, with 66 percent saying that their agency needs to move IT services ...
There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. 8th International Big Data Expo, co-located with 17th International Cloud Expo - to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA - has announced its Call for Papers is open. As advanced data storage, access and analytics technologies aimed at handling high-volume and/or fast moving data all move center stage, aided by the cloud computing bo...
Every day we read jaw-dropping stats on the explosion of data. We allocate significant resources to harness and better understand it. We build businesses around it. But we’ve only just begun. For big payoffs in Big Data, CIOs are turning to cognitive computing. Cognitive computing’s ability to securely extract insights, understand natural language, and get smarter each time it’s used is the next, logical step for Big Data.
There's no doubt that the Internet of Things is driving the next wave of innovation. Google has spent billions over the past few months vacuuming up companies that specialize in smart appliances and machine learning. Already, Philips light bulbs, Audi automobiles, and Samsung washers and dryers can communicate with and be controlled from mobile devices. To take advantage of the opportunities the Internet of Things brings to your business, you'll want to start preparing now.
DevOps Summit, taking place Nov 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 17th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long developmen...