by Gary Mintchell | Jan 13, 2016 | Automation, Events, News, Operations Management
We are closing in on February and time to start thinking about the ARC Industry Forum in Orlando. I went to my first one in 1998 and have my airline and hotel reservations for this edition.
Given the demise of general industry trade shows, there are precious few opportunities to see a large cross section of the automation and control industry. This is one.
I have 2 or 3 appointments set. If you are there, ping me. Maybe we can do a “meet up” in the lounge before everyone splits for dinner or something. Or stop me to chat during the week. ARC has once again planned an afternoon of press conferences for its sponsors. I’ll arrive in time to listen if you are presenting.
The 20th Annual ARC Industry Forum has the theme, “Industry in Transition: Navigating the New Age of Innovation”.
The conference is February 8-11, 2016 at the Renaissance Sea World in Orlando, Florida.
ARC says, “New information technologies such as Industrial Internet of Things (IIoT), Smart Manufacturing, Industrie 4.0, Digitization, and Connected Enterprise are ushering in a new age of innovation. These concepts are clearly moving past the hype, where real solutions are emerging backed by strong business cases. Expect to see innovations in smarter products, new service and operating models, new production techniques, and new approaches to design and sourcing. Join us to learn how this industrial transformation will unfold and what other companies are doing today to embrace innovation and improve their business performance.”
Questions they expect to address:
- How will inexpensive, easy-to-install sensors change existing products and plants?
- Will cyber security concerns impede disruptive innovation?
- What kind of intelligence will machines have and what value will this bring?
- What role will Wi-Fi and LTE play?
- How do Big Data and predictive and prescriptive analytics enable operational change?
- What is the opportunity in aftermarket services?
- What software capabilities are needed to achieve transformational change?
- Which industries are already changing?
- What steps can organizations take to foster innovative thinking?
Forum’s Keynote Presentations
Michael Carroll, Vice President, Innovation & Operations Excellence, Georgia-Pacific
Michael joined Georgia-Pacific in 2010 to focus his technological and entrepreneurial talents on innovation and leadership. Prior to that he and a partner formed McTech Group, a company focused on innovative products for the building products and construction industry. In addition to his Executive Vice President responsibilities, Michael formed a Joint Venture designed to sell consumer “DIY” products to big box retailers like Wal-Mart, Home Depot, and Lowe’s. Previous positions include Director of Operations at Riverwood International, CEO of North and South American Operations at Shepherd, and Principal Change Agent at Mead Paper.
Sandy Vasser, Facilities I&E Manager, ExxonMobil Development
Sandy has been with Exxon or ExxonMobil for over 35 years and has been involved in a number of Upstream projects covering offshore facilities, onshore facilities, and cogeneration facilities. He currently manages a team of about 120 electrical and I&C professionals responsible for the design, installation, and commissioning of electrical generation and distribution systems, process control systems, and safety instrumented systems for all major ExxonMobil Upstream capital projects. This team is also responsible for developing, promoting and implementing strategies, practices, processes, and tools for successfully executing project automation and electrical activities.
Rob High, Vice President and Chief Technology Officer, Watson Solutions, IBM Software Group
Rob has overall responsibility to drive Watson Solutions technical strategy and thought leadership. He works collaboratively with the Watson engineering, research, and development teams across IBM. Prior to joining Watson Solutions, Rob was Chief Architect for the SOA Foundation and member of the IBM Academy of Technology. He championed an open industry architectural definition of the principles of business and IT alignment enabled by SOA and business process optimization, as well as ensuring IBM’s software and services portfolio is architecturally grounded to enable for efficient SOA-based solutions. Rob has 37 years of programming experience and has worked with distributed, object-oriented, component-based transaction monitors for the last 26 years.
by Gary Mintchell | Jan 8, 2016 | Asset Performance Management, Automation, Data Management, Operations Management
I chatted this week with two executives from GE Digital. Jeremiah Stone is the General Manager – Industrial Data Intelligence Software at GE Digital, and Jennifer Bennett is the General Manager – Manufacturing Software Solutions (Brilliant Factory) at GE Digital.
The conversation opened with the idea that it’s about data. Companies must become data-driven. But then it’s also beyond data. Not all data sets are equal. And it’s not just about finding anomalies–it’s really about finding that data and anomalies that matter most to business success.
Then we went a direction that I’ve never gone with GE before–remote monitoring and diagnostics (RM&D) targeted to reliability engineers. The often overlooked skillset of reliability engineers, and how their knowledge offers a distinct competitive advantage to companies battling it out in the industrial market.
As the advantages from unlocking big data insights continue to benefit enterprises of all sizes, data scientists – the gatekeepers and analysts of this data – have become an increasingly popular career choice. In fact, The Harvard Business Review proclaimed data scientists to be “the sexiest job of the 21st century.” But with more advanced Remote Monitoring and Diagnosis (RM&D) technologies being utilized to find and address problems before they happen, reducing the costs of planned and unplanned downtime, the emerging industrial superstars are reliability engineers.
This list summarizes our conversation:
- RM&D in the cloud uncovers the gap of reliability-centered maintenance and operations. This new technology shines a light on an old problem for customers– frustrations around the fact that they’re not able to executive consistently on maintenance and operations.
- Successful asset monitoring is more than just software. Organizations have a false sense of security that if they install monitoring software, they instantly have a handle on their operations. But the real secret in handling the complexity that monitoring creates with RM&D is the reliability engineers that can run and interpret the technology.
- Identifying anomalies in RM&D is not the problem. Identifying anomalies that matter to operations is the problem. RM&D create numerous alerts so it’s hard for an organization to know which ones to really focus on. Reliability engineers have the expertise to shift through the notifications and identify false positives, telling their organizations which ones to ignore and which ones to pay attention to.
- Cloud-based business strategy is becoming less about technology and more about knowledge sharing. The benefits of utilizing cloud technology are increasingly becoming centered on the fact that organizations can internally share and learn from a pooled knowledge base, no matter the location. The cloud offers a way for reliability engineers to capture and preserve knowledge that is crucial to the business’s ongoing success.
Stone said that this idea ties in to GE’s strategy itself. As disciples of Deming, the company is data driven, and a lot of that means remote monitoring and diagnostics for GE’s fleet. Incorporating technologies such as those from the SmartSignal acquisition, company engineers and managers are now excited. With the RM&D, they now can execute on goals, avoid failure, achieve greater reliability, and be more proactive. “Now we are excited to bring tools we use to the rest of the industrial world.”
Today’s RM&D enables excellence in manufacturing from a larger, systemic view, in order to deliver business advances, added Stone. Now engineers and managers can look at the entire scope/span of problem, not just one process or loop. “We help companies on the journey beginning with an assessment of where they are and what they want to achieve. We offer professional services to help them figure out what are outcomes they want to achieve. Not just getting connected to get data but doing it in a way that makes sense.”
Bennett pointed to the variety and complexity of data. “The problem has been all data has been in silos, but the value is upstream and downstream. Some challenges in manufacturing are often quite complex. Data flows from contexts requiring tracking back to cause. The platform we’re building on Predix brings data together. We can make insightful decisions. In RM&D we’re looking at history records, maintenance records, and the like. In the past we relied on people who have knowledge and experience for data. Now we can combine and analyze.”
We started discussing workforce and the challenges of recruiting and retaining younger people. Stone noted that young people today are looking for autonomy, mastery, and purpose. “What was magic 20 years ago isn’t now. We find a sense of curiosity in new people and a desire for a job with meaningful impact.”
One improvement in the job situation is the ability to spend more time problem solving and less time gathering data. According to studies, a typical data and analytics project required 80% of the time just collecting and collating data. Stone noted, “Our focus is on dramatically minimizing amount of time to get the data so people can start moving toward problem solving and analytics. Traditionally reliability engineers have been frustrated by availability of data. We are talking about taking it from calendar time to wrist watch time. Then we give collaborative capability. Both newer and more senior engineers are delighted with this new possibility to spend more time problem solving.”
by Gary Mintchell | Jan 6, 2016 | Operations Management
Tim Sowell of Schneider Electric Software (Wonderware) thinks out in front of the curve. His customer contacts help keep him on his toes. His new year’s kick-off blog post revealed four key areas for the coming year based on a conversation with a customer.
These insights should turn our attention away from media glitz and toward doing real work using technologies plus insights.
You might ask what about “big data” and the “internet of things” but these are technologies that will be part of the enabling system for a new operational solution.
In his previous blog he had asked, “how much transformation was happening?” He received a comment from a friend saying the momentum of change is well underway, and happening at increasing pace.
There were 4 areas that he felt his business and associated industry where trying grapple with to stay ahead.
1/ Agility of effective, valued products and brands to the market. So the challenge of “new product Innovation” and then “New Product Introduction” and delivering it to the market at the correct margin to be competitive in timely manner is a whole focus. His comment was this is the core competitive advantage that his company identifies.
2/ Operational Workforce transformation. He agrees with me that too much focus has been on the “aging workforce issue” and that most of HR and Operational teams have missed the bigger transformation, and that is the one of new generation work methods and transformation in workspace that goes with it. He felt like his company woke up to this mid way thru last year when they could not just not fill positions, but are having significant challenges in retaining talent, not within the company but in roles. He felt like initially people thought that would just get a transition to a new workforce yes younger of different experience. But they had not realized that way in which people will work, think, interact, and gain satisfaction will also change. [I think this is a key insight. For years I have written and spoken about getting past the “aging workforce” discussion. In many cases companies had to bring previously laid off engineers back as contractors in order to get essential engineering done. They just couldn’t get the new people needed using the same old tools and methods. Gary]
3/ “Planet Awareness, Image”. He raised this as a real strategy for evolving the brand of the company to been seen as proactive to the environment, to attract further “feeling satisfaction” of customers. He also stated that government regulation, and increasing costs of disposing of waste, and energy costs also are now seen a significant bottom line costs, and must be managed more efficiently. But during this discussion, it was also clear that the perception of being “proactive to the environment” in use of energy, carbon footprint, environment etc was also a key strategy for attractive talent to work in the company. [This idea has been coming for many years. I am happy to see it gaining traction in a major company. I think leadership in our industry that attracts bright, young people must tap into larger societal themes. Gary.]
4/ Transparency across the total product value chain. [Technology has been moving us this direction for some time. Once again, human work is catching up to the technological capabilities. Gary]
It was clear that the 4 strategies was really about changing the way in which the company manages and executes operational work, no matter how big or small.
Pillars of Operational Solution approach:
- Everyone having access to information and knowledge no matter their state or location, this means internet becomes a part of the solution backbone.
- Cyber Security is very much top of mind, both in strategy to secure, manage, to contain cost and risk.
- Data validation/ and contextualization, if transparency and faster decisions are required how do you gain consistent information across different sites. \
- Delivering a new “operational Workspace/ experience” that has embedded knowledge that does not get stale, and enables imitative learning for a dynamic and collaborative workforce.
by Gary Mintchell | Dec 19, 2015 | Data Management, News, Operations Management
Big Data comes with all that data transported by the Internet of Things. Big Data has little value unless you can tap into it for the information that you need for that decision you need to make in the next hour or two.
Anodot recently contacted me about a new analytics solution it has developed. For most of us, it is sufficient to know that such solution exists. Others may want to see what it’s up to.
The company just exited stealth mode introducing its real-time anomaly detection solution, which the company maintains will disrupt the static nature of today’s Business Intelligence (BI) with patented machine learning algorithms for big data. Pinpointing performance issues and business opportunities in real time, Anodot enables its customers to increase operational efficiency and maximize revenue generation.
The company also announced it closed a $3 million Series A funding round led by Disruptive Partners, bringing total funding in the company to $4.5 million. The company will use the funding to accelerate its product roadmap and expand its sales activity, focusing on the ad tech, e-commerce, IoT and manufacturing industries in the U.S. and EMEA.
Founded in June 2014, Anodot is the only analytics and anomaly detection solution that is data agnostic and automates the discovery of outliers in all business and operational data. Anodot’s platform isolates issues and correlates them across multiple parameters to surface and alert on incidents in real time.
Data analysis lag problem
“I experienced the data analysis lag problem first hand as CTO for Gett,” said Anodot CEO David Drai. “As a mobile taxi app, SMS text orders were dropped by the carrier, but it could take up to three days to spot critical issues and fix them, costing tens of thousands of dollars per incident. That’s where I got the idea for Anodot—to employ the latest advances in machine learning to detect performance problems automatically and in real time, eliminating the latency.”
Data-centric organizations share a common problem—they collect mountains of data, but deriving business value comes long after the actual event and requires data modeling experts using homegrown custom tools in a static and time-consuming process. The resulting delays in getting business insights can cost companies millions of dollars in lost revenue or production.
“There is a huge opportunity to disrupt the BI market by enabling automated and real-time insights into big data pools of metrics and KPIs,” said Tal Barnoach, Anodot board member and general partner at The Disruptive Fund, a privately held Tel Aviv/New York-based venture fund. “We have been with Anodot from the beginning. The team and the technology are terrific, we are impressed with the progress they have made to date and are excited to be participating in this next stage as they scale upward.”
Anodot is led by a proven team of three co-founders with strong credentials as entrepreneurs and technologists with deep experience in data science and global-scale SaaS infrastructures. CEO David Drai was co-founder and CTO of Cotendo for four years when it was acquired by Akamai for $300 million.
Chief Data Scientist Dr. Ira Cohen held the same position at HP Software where he led research and development in machine learning and data mining techniques. R&D VP Shay Lang has led engineering teams for more than 10 years at leading technology companies. On the board of directors, the team also includes Anthony Bettencourt, president and CEO at Imperva and a board member at Proofpoint, and Ben Lorica, O’Reilly Media’s chief data scientist and a top influencer on Twitter, as a board advisor.
Anodot is already being used in production by dozens of organizations, including Avantis (not the one that is part of Schneider Electric Software) that develops the most advanced desktop tools and monetization platforms in the world and Wix, a leading cloud-based Web development platform with millions of users worldwide.
Important issues missed
Before using Anodot, Wix said vast amounts of metrics and KPIs were measured and analyzed manually by data analysts, yet despite spending a great deal of time, important issues sometimes took days to identify.
“With Anodot we are able to detect changes very early and make decisions that have a direct impact on our business,” said Mark Sonis, monitoring team leader at Wix. “We are able to investigate issues in minutes, not hours, and it does its magic every day with little effort on our side. Anodot has become an essential solution across many of our teams including BI, R&D and DevOps.”
According to Doron Ben-David, CTO, VP R&D, Avantis, “Our vision is to enable publishers to focus on creating content, applications and media, while we provide the revenue mechanism. Fulfilling that promise means our core business revolves around numbers—the impressions, downloads, ad shares and other metrics that feed revenues and bottom lines. Anodot gives us the BI tool to track all of the metrics and KPIs that are essential to our success in real time and alerts us to issues as they happen so we can immediately respond before it impacts our customers.”
The use of solutions like Anodot’s with advanced and predictive analytics, including machine learning, will grow 65 percent faster than those without predictive functionality, according to IDC.
Unique features and advantages of Anodot Anomaly Detection include:
- Operates in real time
- Works with any type of metric or KPI and scales to any big data volume
- Uses proprietary patented machine learning algorithms
- Correlates different metrics to help identify root causes of problems and eliminate alert storms
- Simulation capability optimizes alert planning and reduces false positive alerts
- Eliminates the need for time-intensive manual analysis
- Enables non-specialists to gain the insights they want and delivers fast time-to-value
- Provides clear visualizations that help any user to understand what the data is showing them
