by Peter High, published on Forbes
6-20-2016
Artificial intelligence (AI) is a white hot topic today as judged by the amount of capital being put behind it, the number of smart people who are choosing it as an area of emphasis, and the number of leading technology companies that are making AI the central nervous system of their strategic plans. Witness Google’s CEO’s plan to put AI “everywhere.”
There are some estimates that five percent of all AI talent within the private sector are currently employed by Google. Perhaps no on among that rich talent pool has as deep a set of perspectives as Geoff Hinton. He has been involved in AI research since the early 1970s, which means he got involved before the field was really defined. He also did so before the confluence of talent, capital, bandwidth, and unstructured data in need of structuring came together to put AI at the center of the innovation roadmap in Silicon Valley and beyond.
A British born academic, Hinton is considered a pioneer in the branch of machine learning referred to as deep learning. As he mentions in my extended interview with him, we are on the cusp of some transformative innovation in the field of AI, and as someone who splits his time between Google and his post at the University of Toronto, he personifies the value at the intersection between the research and theory and the practice of AI.
(To listen to an unabridged audio version of this interview, please click this link. This is the eighth interview in my artificial intelligence series. Please visit these links to interviews with Mike Rhodin of IBM Watson, Sebastian Thrun of Udacity, Scott Phoenix of Vicarious, Antoine Blondeau of Sentient Technologies, Greg Brockman of OpenAI, Oren Etzioni of the Allen Institute for Artificial Intelligence, and Neil Jacobstein of Singularity University.
Peter High: Your bio at the University of Toronto notes that your aim is to discover a learning procedure that is efficient at finding complex structure in large, high dimensional data sets, and to show that this is how the brain learns to see. I wonder if you can talk a little bit about that and about what you are working on day to day as the Emeritus University Professor at the University of Toronto as well as a Distinguished Researcher at Google today.
Geoffrey Hinton: The brain is clearly very good at taking very high dimensional data, like the information that comes along the optic nerve is a million weights changing quite fast with time, and making sense of it. It makes a lot of sense of it in that when we get visual input we typically get the correct interpretation. We cannot see an elephant when there is really a dog there. Occasionally in the psychology lab things go wrong, but basically we are very good at figuring out what out there in the world gave rise to this very high dimensional input. After we have done a lot of learning, we get it right more or less every time. That is a very impressive ability that computers do not have. We are getting closer. But it is very different from, for example, what goes on in statistics where you have low dimensional data and not much training data, and you try a small model that does not have too many parameters.
The thing that fascinates me about the brain is that it has hugely more parameters than it has training data. So it is very unlike the neural nets that are currently being very successful. What is happening at present is we have neural nets with millions of weights and we train them on millions of training examples and they do very well. Sometimes billions of weights and billions of examples. But we typically do not have hugely more parameters than training data, and that is not true with the brain. The brain has about ten thousand parameters for every second of experience. We do not really have much experience about how systems like that work or how to make them be so good at finding structure in data.
High: Where would you say we are on the continuum of developing true artificial intelligence?
To read the full article, please visit Forbes
6-6-2016
Over the past decade and a half, Microsoft co-founder, Paul Allen, has created three “Allen Institutes” for Brian Science, Cell Science, and Artificial Intelligence. The Institute for AI was founded in 2013, andits mission is “to contribute to humanity through high-impact AI research and engineering.”
In early 2014, Allen tapped serial entrepreneur, Oren Etzioni, as chief executive officer. Etzioni has a PhD in computer science, has been a professor at the University of Washington, and founded or co-founded a number of companies, including Farecast (sold to Microsoft in 2008) and Decide (sold to eBay in 2013).
The goal of Etzioni’s research is to solve fundamental problems in AI, particularly the automatic learning of knowledge from text. In our far ranging conversation, we discuss the specifics of his goal, the pace of innovation in AI more generally, safety concerns, and how they should be dealt with, the government’s role in mitigating risks of AI, and a variety of other topics.
(To listen to an unabridged audio version of this interview, please click this link. This is the fifth interview in my artificial intelligence series. Please visit these links to interviews with Mike Rhodin of IBM Watson, Sebastian Thrun of Udacity, Scott Phoenix of Vicarious, Antoine Blondeau of Sentient Technologies, and Greg Brockman of OpenAI.)
Peter High: You are the CEO of the Allen Institute for Artificial Intelligence whose mission is to contribute to humanity through high impact AI research and engineering. Can you provide your definition for high impact AI research and engineering?
Oren Etzioni: It starts with Paul Allen, who is a visionary and scientific philanthropist. He won the Carnegie Medal for Philanthropy last year. He has been passionate for decades about AI research and the potential of AI to benefit humanity.
In January 2014, we were launched as a nonprofit research institute in Seattle. We are now fifty people – about half PhDs and half engineers – and the question that we ask ourselves when we get up in the morning is “What can we do using the techniques?” Ultimately, to me, the computer is just a big pencil. What can we sketch using this pencil that makes a positive difference to society, and advances the state of the art, hopefully in an out-sized way? We are small compared to the teams that Google and Facebook and others have, but we want to punch above our weight class.
One of the things we have noticed as we have developed expertise in natural language processing and machine learning is that there are millions of scientific papers published every year – nobody can keep up. Google Scholar came on the scene about a decade ago and indexed all these papers, but there is too much information: You do a simple query and experience overload. What we need are techniques to help people cut through the clutter and hone in on key results. The approach we have taken is to use AI methods to filter irrelevant results—to extract key information like the topic of the paper, the figures that are involved, the citations that are influential, etc., etc.— in order to help people find the papers that they need. We have launched a free service on the internet called SemanticScholar.org, which currently indexes several million computer science papers. Our hypothesis is that if we can make scientists better at their job, then we can help solve some of humanity’s thorniest problems. We are starting with computer scientists, but we want to expand to medical researchers and ultimately doctors. Even a specialist does not have the latest information about your condition– they just cannot keep up. They are diagnosing you and treating you based on, at best, incomplete and potentially erroneous information. We want to help change that.
High: If you were to think about the next decade, what are some of the promising future attributes outcomes that you foresee with the developments that are coming down the pipeline and with regard to AI generally speaking?
Etzioni: AI is becoming pervasive in its use in technology in society. Marc Andreessen famously said that software is eating the world. One might riff on that and say that AI is eating software, in the sense that everywhere where there is a software solution, there is the potential for an AI solution.
Cars are a great example: They have become complex computers. There are more than one hundred fifty computers in the average car. There is the potential now to have a car drive itself using AI. The reason that is exciting is that it could reduce the number of accidents we have on the roads today due to distracted human drivers or humans driving under the influence. Our highways and our roads are underutilized because of the allowances we have to make for human drivers. We could pack the roads a lot more densely and reduce traffic congestion and greenhouse gases and all those things if traffic were more efficient, so that is a great example. But, anywhere you look in society I see the potential for AI to help.
High: I read a paper of yours from a number of months back in which you said, “The popular dystopian vision of AI is wrong for one simple reason: it equates intelligence with autonomy.” I wonder if you could unpack that insight a little bit.
Peter High
5-12-2016
Excerpt from the Article:
Novelis is a leading producer of rolled aluminum, and a global leader in aluminum recycling. The company’s aluminum is used in everything from automobiles to architecture to beverage cans to consumer electronics. Much of the company’s aluminum is re-created from material already in the world today, saving natural resources and allowing for the creation of consumer products that have a lower environmental footprint. Through its recycling leadership, what would have otherwise been discarded becomes the material for new creation.
Despite attaining more than $10 billion in revenue with more than 10,000 employees, the company never had a CIO prior to the incumbent, Karen Renner, who joined nearly five years ago. Renner had been a CIO at multiple units within General Electric, and as such was used to process excellence. What she found at Novelis was an IT department in need of new, standardized processes. As she discusses with CIO Insight contributor, Peter High, the journey has been a fruitful one.
CIO Insight: You are the first CIO in the company’s history. The company grew to a tremendous size before hiring a CIO. Why was that, and what led to the conclusion that one was needed?
Renner: In order to deliver on many of Novelis’ transformation strategies, an overhaul of the information technology and data was required. The information infrastructure was unable to meet the aggressive expansions required to enter and provide the data streams required for the automotive market. We also needed modern technology to support our employees working across geographies and to meet growing demands for mobility and collaboration technologies. In order to develop and execute a global IT strategy taking into account the varying regional requirements, the CIO role was created.
CIO Insight: How would you describe the culture of the IT team when you joined, and what have you done to change it?
Renner: We have an excellent team of IT professionals at Novelis with a great mix of technical business process knowledge and program management skills. We act as one team and trusted advisors to deliver best-fit information technology solutions that people value and enjoy using. The biggest cultural shift was to broaden the reach of the team to think bigger and broader–how technology can influence outside of a local requirement to our regions or globally.
CIO Insight: I imagine there was a good deal of foundational investments that were necessary in the early days. How did you prioritize and what did you prioritize to do first?
Renner: We had three transformation work streams that we started simultaneously: 1. infrastructure, 2. business process automation and simplification and 3. collaboration and workforce mobility.
As many of the programs were interconnected, we built a high level, integrated plan that enabled us to understand the dependencies. The demand for new systems, processes and tools was incredible—our prioritization strategy was completely aligned to the overall Novelis strategy.
To read the full article, please visit CIO Insight
4-4-2016
Arne Josefsberg has held a number of technology executive positions in his career. He spent 26 years at Microsoft developing the company’s data center and cloud infrastructure, dating back to the original MSN team and continuing up through Office 365 online service. He spent time as the Chief Technology Officer at ServiceNow. A bit more than two years ago, he joined GoDaddy as its chief infrastructure officer and chief information officer — an important role for the company as it expanded from a US-centric domain registrar to a multi-national cloud-services company for small businesses. During his tenure, the company’s revenue has grown nearly 50 percent to $1.6 billion.
This CIO-plus role that Josefsberg has is part “classic IT,” as he calls it, and part driver of the development of a “globally scalable cloud infrastructure that is high performance and secure that delivers services to our small business customers.” Though his mandate and purview is broader than that of the average CIO, the way he thinks about his role offers insights to all CIOs as they strive to add greater levels of value to their company’s and to the company’s customers.
(To listen to an unabridged audio version of this interview, please visit this link. This is the 29th interview in the CIO-plus series. To read the prior 28 with CIO-pluses from the likes of Boeing, Verizon, P&G, and Walgreens, among others, please click this link. To read future articles in the series, please click the “Follow” link above.)
Peter High: I thought we would begin with a background on GoDaddy’s business. I have no doubt a number of people will know it from its provocative Super Bowl commercials, which is certainly the first place that I heard about the organization. It has clearly grown a great deal since its early days. Could you take a moment to provide an overview of the business?
Arne Josefsberg: I joined GoDaddy almost two years ago. GoDaddy is the world’s largest domain registrar. It is what we were known for, and that is where the business started twelve plus years ago. What some people do not understand now is that we have expanded our product suite quite a bit over the years. Domain registry continues to be a big part of our business, but we also do hosting for small businesses – everything from managed WordPress to dedicated hosting – a broad suite of hosting services. We have a website builder that is super easy for the non-technical audience to quickly build a website. We have also started to build various productivity tools for small businesses, search engine optimization tools to make their websites more resonant and visible in the market. We also added a GoDaddy bookkeeping application.
Our vision is to be the enabler for small business. Our focus is exclusively on small business. We count well over thirteen million customers globally and have grown pretty fast. It is an exciting area, and is quite inspiring. Our mission is to help the little guy be successful running and managing the business by providing accessible and cost efficient technology for them to get online. What I found super exciting is that we have thirteen million customers, but if you look at the market globally, we believe that there is in the range of two hundred and twenty million small businesses around the world. Many of them are not even online today, but clearly that is where the world is going. You have to have a website to present your business and interact with your customers.
We also think there is a circular trend from a business world dominated by large enterprises (big conglomerates) and we think that is breaking down to much more entrepreneurial smaller companies. We want to enforce and enhance that trend, and arm the small business with the kind of tools, websites, and domains that can help them get online without having an IT organization. We are about leveling the playing field between the little guy and the larger companies.
3-8-2016
Kim Stevenson has been the CIO of Intel for the past four years. As I have noted in the past, she has dramatically increased the value derived from IT by adopting the practices of the more traditional revenue centers of the company. One of the best examples of this is the development of an IT annual report that mirrors that of the company as a whole. (Check out her latest IT annual report here.) The theme of her latest annual report is “Intel: From the Backroom to the Boardroom.” This refers to IT’s becoming more relevant to the board of the company, but it is also a good summation of her own career in recent years.
Since becoming CIO, Stevenson has been on the boards of multiple companies including her current appointment to the board of Cloudera. Many CIOs wish to join boards these days, and Stevenson offers sage advice on way sin which others might follow in her footsteps. It begins by performing well internally, being transparent, and, if you truly wish to be a board-level CIO, making that known with anyone who might aid you in that process.
(To listen to an unabridged audio version of this interview, please visit this link. This is the 17th interview in the “Board-Level CIO” series. To read past interviews with CIOs from P&G, Biogen, Kroger, Cardinal Health, and the World Bank Group, among others, please visit this link. To read future articles in the series, please click the “Follow” link above.)
Peter High: I thought we would talk a bit about some of your priorities in the year ahead, which I know include adoption of Big Data analytics to find opportunities and to solve challenges faster. Could you explain some of the ways in which IT is going to do that, and also some of the other priorities that are on your roadmap for the year ahead?
Kim Stevenson: Analytics is at the top of my pyramid because it is a transformational initiative around Intel. I have shifted from a technology view for 2016 to a leadership problem. We are bringing our entire Intel leadership team forward to think about shifting using Big Data predicative analytics versus traditional statistical methods. The reason I say it is a leadership problem is because often you will find in a predictive model that you will get answers that are inconsistent with your historical experience. We use regression analysis a lot here at Intel. If you look at a regression analysis line, you effectively get a mean and you drive towards that regression line. If you use an isobar analysis, what you get is the personalization of hot spots and you would maybe take three or four different actions than what a regression line would tell you. You get good results with traditional statistics. You can get outstanding results if you switch to the more predictive models. And that takes a shift in a leadership mindset as much as it does a technology mindset. We have been working on that with our most senior leaders at Intel. The receptivity is really high, but the cultural shift is also really difficult.
High: I know you have talked about the need for IT to be an advocate driving this change. What are the methods you are using to communicate this and provide a vision of the value that the organization will garner for this journey?
3-11-2016
Teacher Retirement System of Texas (TRS) is the largest public retirement system in Texas in both membership and assets. It is the sixth largest public pension plan in the U.S. and is among the 20 largest in the world. The agency serves more than 1.4 million people–1,081,505 are public and higher education members, and 377,738 are retirement recipients. System net assets total approximately $128.5 billion. As CIO, Chris Cutler oversees and provides strategic direction for the use of technology and information resources that enables TRS to successfully fulfill its mission. As Cutler tells CIO Insight contributor Peter High, he wears many hats: business leader, technology evangelist, business partner, recruiter, change agent and bridge builder.
Peter High: Please describe your role as CIO of the Teacher Retirement System of Texas.
Chris Cutler: As CIO, I wear many hats. These hats include: business leader, technology evangelist, business partner, recruiter, change agent and bridge builder.
Business Leader
As a business leader I serve as a member on the TRS Executive Council. The TRS Executive Council is comprised of C-suite executives and led by our executive director. This council provides guidance to the executive director and makes final decisions on overall corporate policies and directions.
Technology Evangelist
As technology evangelist, I am responsible for educating the Executive Council and our business leaders on the technology and services IT provides and how they can best leverage our offerings. This role also includes marketing the value of IT and building support for future technology initiatives.
Business Partner
IT is a business enabler, providing secure and highly available technology solutions that enhance the efficiency and effectiveness of TRS and our members. As such, it’s my job to ensure IT is seen by our individual business areas as a true business partner, not just simply a service provider. IT needs to truly understand the business of TRS and be proactive in helping solve business problems and recommend innovations that move our business forward.
Recruiter
The most important asset an IT division has is its people. This may sound a bit cliché, but it is true–especially in IT. As CIO, it’s my job to promote the TRS IT Division both internally and externally as well as to actively seek out individuals who would make good additions to our team. Also, just as important, is demonstrating the leadership, vision and support needed to keep the great employees we already have.
Change Agent
The one thing that is certain in IT is it’s going to change. Many times these technology changes have a significant impact on the rest of the business and/or provide an opportunity for improving efficiency. As such, the CIO often finds himself or herself in the position of change agent, promoting and leading enterprise projects that bring about significant shifts in the organization.
Bridge Builder
Finally, as CIO I have a unique view into the varying business units and their cultures. This gives me a unique perspective on how the business runs, how it communicates and how decisions are made. This also provides opportunities to build strong business relationships within the different business areas. With this knowledge and relationships, I can often be a catalyst in helping build bridges and achieve understandings across the different business areas when conflicts arise.
2-29-2016
Sentient Technologies has patented evolutionary and perceptual capabilities that provide customers with highly sophisticated solutions, powered by the largest compute grid dedicated to distributed artificial intelligence. The company also has a war chest of $143 million in venture investment, the most of any artificial intelligence company. Antoine Blondeau founded Sentient Technologies nearly nine years ago, though it was in stealth mode for the majority of that period.
After stints at Salesforce.com and Good Technology was looking for the next challenge. He had been involved in artificial intelligence for 15 years, making him an early pioneer in the field, and already had hit a home run by being involved in developing the technology that would become Siri, of iPhone fame.
Blondeau claims we are still in the very early days of artificial intelligence’s evolution, but his vision is to create technology that will mimic the human interaction. One of the first uses of the technology is in retail, replicating the experience of having a sophisticated advisory helping to curate your shopping experience. In this interview, Blondeau provides his vision for the company, his thoughts about the future of AI, the balance between AI innovation and AI safety, as well as a variety of other topics.
(To listen to an unabridged audio version of this interview, please click this link. This is the fourth article in a series on leaders in artificial intelligence, which includes interviews with Mike Rhodin of IBM Watson and Sebastian Thrun of Udacity. To read future articles in the series, please click the “Follow” link above.)
High: Artificial intelligence seems to be gaining tremendous momentum, whether it is venture capital, media coverage, or simply progress that is obvious in the world. There are clearly a couple of trends that have made this possible in recent years: the emergence of relatively low-cost available computing power and the vast, growing abundance of data that companies in every industry are collecting. I think I have heard you say that we are in the first inning here of the game, as so much innovation is ahead of us. As somebody who got into this 15 to 20 years ago, long before this boom, where do you see things now, and how do you think things are evolving?
Blondeau: You are right on the money when you talk about what has happened over the past five or seven years that is making this possible. Some of the team members and I worked on the precursor to what became Siri. At the time, we were thinking of an algorithm running on one machine or a few machines. What has happened over the past few years is that you have the data, it is broadly available, and one of the things that we foresaw was not only that data would explode but the dimensionality of data would explode. It will connect a lot of types of data that had not been connected before. That is a big help.
The second thing is that we have moved from thinking of the machine being the compute to the network being the compute, which means that we can harness an enormous amount of compute cycles. In our case, that means running our system on up to two million CPU cores. We also have a few thousand GPU cores. It is a massive system. When we thought of this company seven years ago, we had the vision forward, but could not quite imagine how we could get there. I think now we can.
The last thing is that when you begin to think about the scale, you can begin to address problems that you had not thought were solvable previously. The ambitious nature of what you do can go up significantly. You can tackle dimensionality, you can tackle complex decision making. Effectively, you are looking at comprehensively including every step of decision making in the machine, or in this giant network machine, which previously was not something thought of as possible. That is the high level.
High: I would like to dive a bit further into the details of how this becomes reality, and how that has impacted the way in which you have thought about entering different markets. I have heard you speak about the applications in some of the primary industries where there are tremendous amounts of data and where there are particularly big problems to solve, like financial services and healthcare. I found it interesting that one of your first areas to apply Sentient Technologies is in retail and online shopping. I would love to understand further how you have chosen where to focus.
Blondeau: One of the things we did was building a powerful platform, but you never succeed by building a platform. You need to apply it to know that it is working and scales to multiple industries. So, we decided to monetize it to address trading, aspects of e-commerce, and the online content discovery experience, as well as, at the research level, institutions like MIT, University of Toronto, and Oxford to work on less immediately monetizable problems, but world problems nonetheless. I am talking here about genomics and patients in an ICU context.
In each case, the common denominator is a few things. One, can you try to solve a problem that has not been solved before? The complexity of the decision making process is key here. The second thing is can you encapsulate the whole decision making process within the machine?
2-22-2016
Quest Diagnostics is a $7.5 billion provider of diagnostic testing information services. It collects vast amounts of data: twenty billion test results, one hundred fifty million medical test requisitions in 2014, and testing services that touch about one third of the adults in the US. It is up to Lidia Fonseca, Quest Diagnostics’ CIO to organize, tag, and structure the data so that the company can turn information into insights and insights into actions. By effectively categorizing and partitioning the data, the big data conundrum has turned into a massive opportunity for the company, and it has also made that data much more secure.
Fonseca’s depth of experience in data analytics, security, and developing innovations that are leading to revenue augmentation have brought her to the attention of those who need that experience at the board level. In July of 2014, she joined the board of Gannett, a $2.9 billion international media and marketing solutions company. In this interview, she discusses all the above and more, and toward the end of the interview, provides insights into how she successfully became a board-level CIO.
(To listen to an unabridged audio version of this interview, please visit this link. This is the 16th interview in the “Board-Level CIO” series. To read past interviews with CIOs from P&G, Biogen, Kroger, Cardinal Health, and the World Bank Group, among others, please visit this link. To read future articles in the series, please click the “Follow” link above.)
Peter High: I thought we would begin with your role. You are the Chief Information Officer of Quest Diagnostics. I wonder if you could provide a description of the organization as well as your role within the organization.
Lidia Fonseca: We are a leading provider of diagnostic information services. That is both clinical laboratory services as well as diagnostic information services. 2014 revenues were $7.4 Billion, and we are growing at four percent. Interestingly for us, we see about one third of US adults, and we connect with half of all physicians and hospitals in the country. We are touching the samples of five hundred thousand patients per day. We have an expansive test menu, and thousands of tests ranging from ones for cholesterol and diabetic testing, to advanced genetic, cancer, and neurology testing. We run the full gamut of medical testing.
We count on the services of forty-five thousand employees. We have about seven hundred PhDs and MDs across the company, which is great because harvesting and leveraging that knowledge is pretty significant, as we think about leveraging innovation, both on the medical side, but also on the diagnostic and data side. We operate two thousand two hundred patient service centers around the country. That is a little bit of the scale and scope of Quest.
On the data and technology front, we have the largest private clinical database. We have over twenty billion laboratory testing data points. We have more than fifty thousand providers and hospitals that are leveraging our Care360 connectivity platform. From an interaction and reach standpoint, it has been phenomenal coming here. We integrate with more than four hundred EMR providers. We are integrated with pretty much any EMR that you can think of. If our customer is using it, we are connected with them. We have a patient portal so that patients can access our services directly. We have had more than two million patients access our MyQuest patient portal. We have a significant Big Data and analytics platform that enables population health and gaps in care types of analytics. It is leveraged by partners, including the CDC and Memorial Sloan Kettering Cancer Center, to name a few.
We have partnered with Inovalon, and we will talk more about that later. By bringing that together, we have a rich data backbone and dataset brought together with what Inovalon has. It is enriching what is already one of the most expansive clinical databases around.
As CIO, in addition to the typical things you would expect a CIO to be responsible for, I have a couple of other responsibilities. One of the things I am responsible for is all of our client-facing products. It is my team that develops those. We also develop the analytics products, whether it is sophisticated reporting or population health tools. Now that is in partnership with other providers as well, bringing a new capability that maybe neither of us could bring on our own. That is a key part of our thinking is that by combining datasets, can you offer something novel to the marketplace.
2-1-2016
Jim Swanson has been the Chief Information Officer of $15 billion Monsanto for nearly two and half years after spending almost all of his career to date at healthcare companies at companies like Merck, Johnson & Johnson, and SmithKline Beecham. A scientist by training, Swanson joined the St. Louis-based provider of agricultural products for farmers because it allowed him to continue to pursue opportunities at the intersection between science, technology, and intellectual property innovation. As such, he has thought about the role of CIO much more strategically than most.
Swanson has led a sweeping digital transformation over the organization focused around five pillars that define the digital opportunity: operational excellence, business productivity, customer centricity, revenue enablement, and disruptive innovation, each of which he describes in great depth in this interview. As such, Swanson’s team is playing a significant role in revolutionizing a company in perhaps the oldest industry of all: agriculture.
(To listen to an unabridged audio version of this interview, please visit this link. To read more articles like this one, please click the “Follow” link above.)
Peter High: You are the Chief Information Officer of Monsanto. Please take a moment to describe your role.
Jim Swanson: I have responsibility for all the IT systems and data that spans Monsanto. We are in about 67 countries worldwide, and I have responsibility to deliver on the IT capabilities across that global footprint. Monsanto is comprised of two segments with a third one that is emerging. One is our crop protection business – our chemistry that helps growers with herbicides, pesticides, etc. Our second is our seed trade business – corn, canola, soy, vegetables, etc. Our third emerging area is economic services. We provide information to help growers better improve their yield, improve their outputs, reduce their inputs, and do it more sustainably. As the CIO, I have the responsibility to enable those three segments with data, tools, and capabilities for our business.
High: You operate in the world’s largest and oldest industry – agriculture. To the uneducated outsider, it may seem ironic in some ways that there is a real digital revolution that is happening within agriculture. You have just begun to describe some of that, and how it applies across the three segments of the business. Please talk about the move from analog to digital that is happening within Monsanto and the industry, more generally speaking.
Swanson: We are taking an industry that has probably done it the same way for hundreds, if not thousands of years. Over the last half decade or so, we are digitizing the farm and digitizing agriculture, which is pretty exciting. You think about the seven and a half billion people on the planet, growing to nine billion in a relatively short period, and growing the amount of food we need, and doing it sustainably is an important mission that Monsanto has. We are going to need every tool that we have to enable that. We need information, science, and technology. What is happening on the farm is a leveraging of data and information insights to provide much better ways to do agriculture than has been done in the past.
We connect combines in the field, so we can collect real-time information on how they are performing on the farm. We use analytics and data to get better insights into the performance of our products, as well as sustainable agricultural practices. We internalize and digitize our internal processes, so we connect more effectively across the “ag” ecosystem. It is rapidly evolving with sensor technology, with data, and with insights that have transformed the way that farming is done. It is having a tremendous impact on yield impact, reduced input, and more sustainable agriculture.
High: How tech-savvy are growers? Do you find that adoption is happening readily? Is it readily apparent as to how important and how valuable the new tools that are now available can be?
1-20-2016
Dan Fallon’s journey from CIO to board member to president and COO has been an interesting one. Fallon, who now serves as the president and COO of GFMI Metalcrafters, credits his strong tech background for understanding how many moving parts work together (and very often, don’t). GFMI (Gaffoglio Family Metalcrafters Inc.) was founded in 1979. An Argentinian father and his sons brought to the U.S. their passion for crafting custom cars. The Metalcrafters division helps engineer and those who create custom vehicles for the auto, aero and rail industries primarily. These can be prototypes to full functioning vehicles, including driverless. The Aerospace division creates glass, carbon fiber and other composite parts for the aerospace, auto and rail industries. Additionally, the Camera Ready Parts division prepares cars for photo shoots and commercials, including logistics management.
After 22 years at Accenture, the CTO role at Navistar and CIO role at Rewards Network, among other IT leadership roles, Dan Fallon was looking for a change that would offer more operational experience. He was convinced to join GFMI Metalcrafters as president and COO in September of 2014. In this interview with CIO Insight contributor Peter High, he highlights the reason for this move.
CIO Insight: How did you become affiliated with it as President and COO?
Dan Fallon: I have known GFMI (Gaffoglio Family Metalcrafters Inc.) for more than 20 years. My father-in-law, Mike Alexander, had worked with the Gaffoglio family for many years. Mike and his brother, Larry, were the Alexander Brothers; ground-breaking, Detroit custom car guys from the late 1950s and Mike, later in his career, worked with GFMI on select projects. Mike’s son, Mike Jr., wound up working at GFMI. In 2014, Mike asked if I’d consider joining the company to help significantly grow revenue. To run a company while growing it was where I wanted to be next. After 22 years at Accenture, and five years in IT leadership positions at a couple Fortune500 companies, I wanted to get completely immersed in business operations. Running a smaller company seemed to be the ideal—yet humbling—way for me to do so. Wow, have I learned a lot and enjoyed it. And I’m very grateful for my IT background.
CIO Insight: In recent years, you had been CTO at Navistar and CIO at Rewards Network. What did your time as a technology executive do for you in preparing for your current role as COO?
Fallon: Like Finance and HR, IT gets to “see” a very broad swath of the business, yet I believe at an even deeper level. Successful IT leaders have to understand business execution (processes, schedules and results) and where information and automation can change and accelerate execution. OK, we’ve heard that before—and it’s really hard, especially given ever-increasing competitive demands, legacy systems hangovers and the crazy challenges of changing tires on moving cars. So, as an IT guy—both ex-Accenture consultant and Fortune 500 executive—I got to see how all these moving parts work together—and very often, not. It’s like a mosaic in which some elements of the picture are clear and others are really mottled. As a result, I have this deep, innate appreciation for integration. It’s just a sense I have developed—where are the disconnects in data sharing, process performance and automated systems. So now, on yet another side of the table, COO, I can sense these disconnects; yet even more acutely because I am now directly responsible for getting it done. My time in IT helped me hone and deepen that sense which I think as a COO enables me to quickly zero in on those mottled mosaic pieces and more quickly figure out how to unblur them.
