by Gary Mintchell | Oct 31, 2017 | Commentary, News
I was putting together this piece on mergers and acquisitions when I received word that Emerson had been in conversations to acquire Rockwell Automation. Final price was $27.5 billion. That wasn’t sweet enough. The Rockwell board turned it down.
Note: I feel vindicated. I told an investment company once that they could never touch Rockwell with their war chest of $1 billion. Figured I was safe on that one.
I don’t see Rockwell as wanting to sell. Despite a friend telling me for 15 years that it had to sell, I just never saw that necessity. But I do think that consolidation is rampant in the industry right now. Schneider Electric and ABB have been acquiring strategic companies to compete with Siemens. An Emerson / Rockwell combination would have awesome market share.
Because of weaknesses elsewhere, I’m not sure either really needs the deal to survive. But I think the industry is coming to that point. My thoughts were that the most logical suitors for Rockwell were Emerson and ABB. Sources at ABB have told me that they did the evaluation (of course) and figured that Rockwell would be hard to digest. So, it went with B+R Automation.
My feeling is that this deal is not finished. But it will settle for a while until Rockwell’s share prices stabilize. Then we’ll see. Trying to integrate that Rockwell culture would be a supreme challenge for the best managers, though. It’ll be interesting.
Meanwhile, I received a quarterly update from PwC regarding global industrial manufacturing deals with disclosed values greater than $50 million.
What follows is from the PwC report.
Industrial manufacturing M&A results for Q3 2017 displayed much of the same as the previous quarter with relatively flat value and volume levels. Deal value came in at $16.5 billion while the number of deals announced were 57 compared to 55 in Q2 2017.
Cross sector global and US deal volume has modestly increased for the third consecutive quarter indicating the appetite to seek out M&A plays is still active and healthy. US cross-sector deal volume is substantially up for the first nine months of 2017 vs. 2016 which correlates with
the double digit volume increases seen in the industrial manufacturing sector over the same period.
Although there is an eagerness to investment in technology and innovation, industrial manufacturing remains somewhat risk-averse, especially as it relates to targeting larger size investments. As highlighted in our second quarter report, the slowness of implementing
trade, regulatory and tax reform in the US and the uncertainty of its implications continues to be a barrier to some. Conversely, others have accepted its existence and shifted their investment strategies to mitigate against these uncertainties.
• Deal value for the first nine months of 2017 was $52.6 billion, 18% lower than the first nine months of 2016, while deal volume saw an increase from 150 deals to 170 deals from the first nine months of 2017 vs. 2016.
• Deal value for Q3 2017 was $16.5 billion compared with $16 billion in Q2 2017. Deal volume increased slightly from 55 deals in Q2 2017 to 57 deals in Q3 2017, a 4% increase.
• The average deal size in Q3 2017 was 21% lower than the 2017 YTD quarterly average of $367 million, indicating a preference towards smaller transactions.
• There were four megadeals (deals greater than $1 billion) in Q3 2017 with an aggregate transaction value of $7.7 billion. Three of the deals were crossborder deals.
• The largest deal announced in Q3 2017 was the Swiss firm ABB acquisition of US-based GE Industrial Solutions for $2.6 billion.
• Asia and Oceania remains the most active region, accounting for 56% and 35% of M&A deal volume and value during Q3 2017.
• There were 14 megadeals announced in the first nine months of 2017 ($24.3 billion) compared to 17 in the same period of 2016 ($55.9 billion).
• Seven of the top ten megadeals in the first nine months of 2017 include China or the US as a part of the transaction vs. four over the same period in 2016.
Strategic investors continue to account for the largest share of deal activity in the sector with $12.9 billion of value and 27 deals for the quarter. As shown below, this reflects 78% of value and 65% of volume. Financial investor deal value for the first nine months of 2017 was $15.9 billion vs. $12.8 billion over the same period in 2016. This contribution is consistent with previous quarters and implies the market is more attractive for companies who can create synergies.
Deal value in the industrial manufacturing sector continues to be constrained as deal makers are still wary of the current investment playing field. Many of the same political uncertainties, particularly in the US and Europe, linger and have been the primary influence in declining average deal size over the last three quarters of 2017.
For foreign investors looking to capitalize on attractive businesses in the US there are positive and negative factors simultaneously working against one another. On the positive side, the Federal Reserve sees confidence in the US economy and plans to gradually continue to increase the federal funds rate. However, negative influencing the deals environment is the current administration’s inability to progress its agenda related to tax, trade, and healthcare.
We project the industry will close out the year in similar fashion to each of the three quarters of 2017 unless we see a catalyst event in the market such as tax reform.
Authors
Paul Elie, US Industrial Manufacturing Deals Leader
Bobby Bono, US Industrial Manufacturing Leader
Barry Misthal,Global Industrial Manufacturing Leader
by Gary Mintchell | Oct 27, 2017 | Internet of Things, Manufacturing IT, Operations Management, Software
GE Digital continues to build out its platform and ecosystem of applications while new GE CEO John Flannery confirmed his commitment to the digitalization strategy begun under his predecessor.
The sixth Minds + Machines conference featured about 90% growth in attendance from last year. Begun five years ago not long after the company began assembling its digital strategy as a thought leadership gathering, the conference has evolved into a substantial user conference. Attendance was reported at about 3,700 filling much of Moscone Center West in San Francisco.
I’ve summarized the announcements from the event below. My initial takeaway for the biggest news of the day was GE’s emphasis on building a partner ecosystem. As the company built out its Predix platform, it seemed to be on a track for keeping everything close to home. Saying that they could move more quickly to market, they talked about working more with partners. One executive told me that the partnership with Microsoft for Predix on Azure was the most significant announcement of the week.
This is my first time here and reinforces the idea that GE Digital is a major player in the industry segment begging comparison with Siemens. Some thought also ABB (they should not have forgotten Schneider) also.
Most of my discussions involved Asset Performance Management, the new Operations Performance Management (see below), and helping me understand Predix.
Following is a summary of announcements:
Flannery touched on some statistics from a survey concerning the “digital gap” of perceived importance of a digital transformation and how far along companies are.
GE Digital Industrial Evolution Index
The inaugural Index reflects a total score of 63 on a scale of 100 and indicates that while outlook for the Industrial Internet is very strong, scoring 78.3 (out of 100), company readiness significantly lags, scoring 55.2 (out of 100). This disconnect – between outlook and company readiness – presents both a challenge and opportunity for companies seeking to benefit from the IIoT. 86% believe digital industrial transformation is important to the competitiveness of their companies, with the majority (76%) rating the ability to provide higher quality services as the foremost outcome of digital industrial transformation.
GE unveiled expansions to its suite of edge-to-cloud technologies and industrial applications.
Edge-to-Cloud Intelligence on Any Industrial Asset, Anywhere
GE Digital is expanding its Predix Edge capabilities to help run analytics as close to the source of data as possible. Predix Edge gives customers with limited connectivity, latency limitations, regulatory or other constraints a way to deploy applications closer to the originating data.
Enhancements include:
• Predix Edge Manager allows customers to support large fleets of edge devices – up to 200,000 connected devices from a single console.
• Predix Machine enables microservice-based applications to run at the edge on customers’ virtualized data center infrastructure or on server-class hardware from GE or its partners. This also supports Predix Edge Manager, which was previously available only as a cloud service.
• Predix complex event processing (CEP) allows for faster and more efficient analytics and other event processing at extreme low latency, available at the edge in Q1 2018.
Predix Platform on Microsoft Azure
Announced last year and available generally in 2018, GE Digital and Microsoft partnership extends the accessibility of Predix to Microsoft’s global cloud footprint, including data sovereignty, hybrid capabilities and advanced developer and data services, enabling customers around the world to capture intelligence from their industrial assets.
Operations Performance
Alongside its Asset Performance Management (APM) software, the core application, GE Digital introduced Operations Performance Management (OPM), a solution helps industrials optimize the throughput of industrial processes.
OPM uses real-time and historical data – along with advanced analytics – to help customers make better operational decisions. The solution provides an early warning if industrial processes deviate from plan, arms operators with the information and time to troubleshoot operational issues and helps them take preventative actions to meet business goals. GE Digital’s OPM software initially targets the mining industry and will expand to additional industries early next year.
Enhanced Field Service Management Solutions
With service technicians looking to embrace technology to improve their productivity and deliver a better experience for customers, ServiceMax from GE Digital announced several enhancements to its FSM suite – enabling even greater efficiencies and bringing advanced analytics to service operations.
• Artificial intelligence-enabled predictive service times now integrate the Apache Spark AI engine to improve service time estimates.
• Additionally, a new application integration solution enables service providers to launch and share FSM data with third-party mobile applications installed on the same device.
• New capabilities in schedule optimization allow for dependent job scheduling between work orders for multiple visits aimed at improving first-time fix rates.
Predix Studio
GE Digital also introduced Predix Studio to help companies build and scale their own industrial applications and extend its Asset Performance Management (APM) suite. Available in Q1 2018, Predix Studio simplifies the development process by giving customers the ability to extend applications and empower industrial subject matters experts to build apps in a low-code, high-productivity environment.
Digital Twin Analytics Workbench
A solution that applies a library of algorithms and templates to make it faster and easier for companies to build their own digital twins on Predix. The Analytics Workbench, currently a technology preview from GE Power, can be used to augment existing digital twins with new data streams. For example, power producers using drones to inspect wind turbine blades, pipelines or fuel reserves can integrate visual inspection data into the digital twins they already use to manage generation assets and grid infrastructure.
by Gary Mintchell | Oct 25, 2017 | Internet of Things
Interesting that just as I was planning my trip to San Francisco to attend GE Digital’s Minds + Machines conference a publicist representing Simon-Kucher, a German-based pricing model consultancy, pitched me an interview with Adam Echter, Senior Director.
First, some context. In our community, we view GE Digital as a supplier. Although GE makes PLCs and other control equipment, it is known for software—Cimplicity, iFix, Proficy, Predix. The company, though, in reality makes its money from large assets—locomotives, power generation, jet engines, and the like.
As Jeff Immelt restructured the company jettisoning some of Jack Welch’s favored, but losing, investments. GE became less of media and finance returning to its roots in industrial manufacturing.
Searching for a better sales and profit model, GE famously began selling thrust rather than jet engines. Or it sold uptime rather than equipment. To do this, it needed to develop its own Industrial Internet of Things ecosystem.
The pricing model is known as consumption-based.
Echter sees us living in a time of transition where the IIoT, which was once the controlled domain of a limited number of ultra-large multinational corporations, will blossom into an uncontrollable ecosystem providing Billion dollar opportunities for hundreds of companies. As the complexity of the IIoT continues to explode and demands for complicated specialties emerge, large players like GE are seeing their pricing power diminish and a plethora of market participants emerging with new and disruptive monetization models. GE monetized their pricing power because they controlled all layers of the system; capital equipment, sensors, communications, data processing and storage.
GE was able to lock all inputs into flat pricing models, then sell their output on an open-ended consumption model. As the complexity of the IIoT scales, it has become increasingly difficult for manufacturers of this first-moving technology like GE to retain control.
What he means by the complexity is that other suppliers are getting into the act. They want to sell through GE the same way GE is selling to its customers. This will take a potentially big bite out of profits.
Meanwhile, Immelt has been replaced by the board.
What are you seeing from suppliers? Or, what are you demanding? Ecosystems? I spent considerable time explaining the ecosystem that MIMOSA is proposing that is totally based on standards. The Linux Foundation, promoted by Dell Technologies and others, has developed an open source ecosystem for the IIoT.
Is this the future?
by Gary Mintchell | Oct 24, 2017 | Internet of Things, Operations Management
Just when I was saying last week that the The Industrial Internet Consortium (IIC) had been very busy, I interviewed Eric and Wael about this newly published the IIC Industrial IoT Analytics Framework Technical Report (IIAF). It is the first IoT-industry technical document to include a complete set of instructions that IIoT system architects and business leaders can use to deploy industrial analytics systems in their organizations.
People I talked with used to think that the Industrial Internet of Things was all about sensors, or the Internet, or Things. Actually, it is nothing without databases and analytics. And here is the IIC to provide a framework for systems architects.
From the news release:
IDC has predicted that by 2020 one tenth of the world’s data will be produced by machines. Yet without an analytics blueprint, that data could sit unused, never being analyzed and turned into useful insights. The IIAF is a first-of-its-kind blueprint for system architects and designers to map analytics to the IIoT applications they are supporting, to ensure that business leaders can realize the potential of analytics to enable more-informed decision making.
“Using analytics to provide insights is the holy grail of industrial IoT,” said Wael William Diab, IIC Industrial Analytics Task Group Chair, IIC Steering Committee Member and Senior Director at Huawei. “The IIC IIAF takes a holistic approach by developing the foundational principles of industrial analytics as well as looking at the complete picture from design considerations to creation of business value and functionality. This entire ecosystem approach is valuable to both business leaders as well as technologists, engineers and architects looking to deploy IIoT systems.”
The IIC IIAF is the first document to offer a broad scope of requirements and concerns for industrial analytics applied to IIoT systems. It shows IIoT system architects the steps involved in developing analytics for IIoT systems with state-of-the-art information, including definitions and information flows that shows how the technologies can be applied to the applications. Guidance is provided how and where to deploy industrial analytics based on the characteristics of the applications and outcome expectations. In addition, the IIAF looks at emerging technologies including artificial intelligence (AI) and big data, which are expected to play an increasingly important role in industrial analytics.
“Industrial Analytics is changing rapidly, from data lake to stream processing and machine learning. Our framework provides a common understanding and encourages interoperability across the IIoT ecosystem,” said K. Eric Harper, IIC Industrial Analytics Task Group Chair, IIC Steering Committee Member and Senior Principal Scientist at ABB. “With this foundation, it is more likely that applications will be able to adopt new technologies and techniques in the future without substantial rework.”
Analytics have been applied to other many other fields such as finance and retail to improve the customer experience and increase corporate revenue. The major differentiation in industrial settings is the physicality of the systems. For example, if IIoT systems are not configured correctly, or if their maintenance schedule is wrong, the systems can cause physical harm. Analysis and improvement of operational maintenance across multiple systems must be performed with extreme diligence, and are as important to technology leaders as they are to business leaders looking to increase profits.
“Industrial analytics are the engine that takes data from industrial systems and creates value and insight to get business results,” said Will Sobel, IIC Industrial Analytics Task Group Chair and Chief Strategy Officer at VIMANA. “The sophistication of analytical methods in other domains, such as finance and media, have been evolving at a breakneck pace, but little has been done to apply these techniques to industrial systems. The IIAF provides the special considerations one needs to consider before one uses these technologies in an industrial system.”
When analytics are applied to machine and process data, they help optimize decision-making and enable intelligent operations. These new insights and intelligence can be applied across all levels of any enterprise in any industry if the appropriate data can be collected, curated and analytics are applied correctly.
“In transforming machine raw data into actionable information, industrial analytics plays a crucial role in the industrial Internet just like refineries that turns crude oil into high energy fuel. The actionable information from the analytics is the fuel that drives the optimization of industrial operations and production, the creation of new revenue streams and the enablement of new business models,” said Shi-wan Lin, IIC Technology Working Group Chair and CEO and Co-Founder, Thingswise, LLC.
The full IIC Industrial IoT Analytics Framework Technical Report and list of IIC members who contributed can be found on the IIC website.
by Gary Mintchell | Oct 23, 2017 | Manufacturing IT, Operations Management
Infrastructure-as-a-Service. Remember several years ago when Amazon started selling space and time on its servers? And people thought they were crazy. Is this a business?
Well, as the old vaudeville comedian and TV pioneer Jimmy Durante used to say, “Everybody wants to get into the act.”
We have lots of “–as-a-service” things going on over the past 15 years or so. Software, Application, Platform. Here Rockwell Automation leverages its partnerships with Cisco, Panduit, and Microsoft (who has its own Infrastructure-as-a-Service) to offer an extension to its longtime strategy of using Ethernet as a networking backbone to its Connected Enterprise vision.
Designing, deploying and maintaining this infrastructure can be complex and time consuming for many companies, and is often too costly for their capital budgets. Rockwell Automation has introduced its Infrastructure-as-a-Service (IaaS) offering to address these challenges.
Rockwell’s IaaS reduces the burden of network deployments by combining pre-engineered network solutions, on-site configuration and 24/7 remote monitoring into a single five-year contract. The result is simplified ordering and commissioning upfront, and can help improve network reliability long term. The service can also ease budgetary strains by shifting networking costs from a capital expense to an operating expense.
Rockwell’s Solution
All aspects of IaaS are aligned to the Converged Plantwide Ethernet (CPwE) reference architectures developed by Rockwell Automation and Cisco. Leveraging best-in-class technologies and architectures, companies can optimize their network infrastructure’s performance, efficiency and uptime, as well as address security risks.
“Companies of all sizes are eager to digitally transform their operations in a Connected Enterprise, but many are limited in their ability to connect their infrastructure,” said Sherman Joshua, connected services portfolio manager, Rockwell Automation. “Often, a combination of time, talent and budgetary constraints hold them back. IaaS helps relieve these pressures by combining turnkey networking solutions with our highest level of support.”
IaaS is offered with two Rockwell Automation pre-engineered network solutions, including the Industrial Data Center (IDC) and the Industrial Network Distribution Solution (INDS). These solutions are designed for industrial use and incorporate industry-leading technologies from Rockwell Automation Strategic Alliance partners Cisco, Panduit and Microsoft.
The IDC provides all the hardware and software needed to transition to a virtualized environment, and is designed to deliver high availability and fault tolerance. The INDS is a network distribution package that helps end users achieve secure, high-capacity connectivity between the control room and throughout the plant floor.
Under an IaaS contract, Rockwell Automation will size, assemble and test the infrastructure, including configuration and on-site deployment at the customer’s facility. Contracts include 24/7 remote monitoring of critical system parameters to help prevent outages and failures, as well as proactive system maintenance and checks to improve reliability. Support response is guaranteed within 10 minutes, but actual response times average three minutes.
