‘Rethink Data’ Report Reveals That 68% Of Data Available To Businesses Goes Unleveraged

I first started hearing seriously about data ops last year at a couple of IT conferences. Then a group of former Kepware executives founded High Byte to point data ops specifically to the manufacturing industry. I told them I thought they had something there.

A representative of Seagate Technology sent me information about a study done with IDC about data in organizations. I haven’t had a relationship with Seagate for many years, but this is a timely report about enterprise data pointing out that 68% of data available goes unleveraged and that manufacturing is a laggard in this arena.

As enterprise data proliferates at an unprecedented pace – set to grow at a 42.2.% annual rate over the next two years – a new report from Seagate and IDC has revealed that the majority (68%) of data available to enterprises goes unleveraged, meaning data management has become more important than ever. 

Furthermore and somewhat surprisingly, the manufacturing sector shows the lowest level of task automation in data management, lowest rate for full integration of data management functions as well as low adoption of both multicloud and hybrid cloud infrastructures. 

The report also identifies the missing link of data management—DataOps—which can help organizations harness more of their data’s value and lead to better business outcomes.

The report, Rethink Data: Put More of Your Data to Work—From Edge to Cloud is based on a survey of 1500 global enterprise leaders commissioned by Seagate and conducted by the research firm IDC.

“The report and the survey make clear that winning businesses must have strong mass data operations,” says Seagate CEO Dave Mosley. “The value that a company derives from data directly affects its success.”

Some additional findings include:

  • The top five barriers to putting data to work are: 1) making collected data usable, 2) managing the storage of collected data, 3) ensuring that needed data is collected, 4) ensuring the security of collected data, and 5) making the different silos of collected data available.
  • Managing data in the multicloud and hybrid cloud are top data management challenges expected by businesses over the next two years.
  • Two thirds of survey respondents report insufficient data security, making data security an essential element of any discussion of efficient data management.

The missing link of data management is reported to be data operations, or DataOps. IDC defines DataOps as “the discipline connecting data creators with data consumers.” While the majority of respondents say that DataOps is “very” or “extremely” important, only 10% of organizations report having implemented DataOps fully. The survey demonstrated that, along with other data management solutions, DataOps leads to measurably better business outcomes. It boosts customer loyalty, revenue, profit, cost savings, plus results in other benefits.

“The findings of this study illustrating that more than two-thirds of available data lies fallow in organizations may seem like disturbing news,” said Phil Goodwin, research director, IDC and principal analyst on the study. “But in truth, it shows how much opportunity and potential organizations already have at their fingertips. Organizations that can harness the value of their data wherever it resides—core, cloud or edge—can generate significant competitive advantage in the marketplace.”

Report Identifies 4 Changes CEOs Must Implement To Maximize Digitization

Report Identifies 4 Changes CEOs Must Implement To Maximize Digitization

Digitization is on everyone’s lips these days. If you have not taken steps to implement and improve digital data flow, you are probably already behind. I receive information regularly from PwC and here is a new report on how digitization is reshaping the manufacturing industry. The report takes a look at 8 companies and showcase how they improved their efficiency, productivity and customer experience by ensuring they have the right capabilities central to their operating model and by matching them with strong skill sets in analytics and IT.

Pressure from the consumer, new regulations and advances in information technology are all reasons that are pushing manufacturing organizations to digitize so they can avoid falling behind the new breed of market-leading ‘digital champions.’ The report identifies 4 significant changes CEOs must implement to maximize the benefits of digitization.

1. Drive organizational changes that address new digital capabilities and digitalized processes – e.g., product and process design and engineering, end-to-end procurement, supply chain/distribution and after-sales – right from the top, because these are so new and different

2. Hire more software and Internet of Things (IoT) engineers and data scientists, while training the wider workforce in digital skills

3. Learn from software businesses, which have the ability to develop use cases rapidly and turn them into software products

4. Extend digitalization beyond IT to include significant operational technologies (OT) such as track and trace solutions and digital twinning

From the report, “Already, digitally ‘smart’ manufacturers are gaining a competitive advantage by exploiting emerging technologies and trends such as digital twinning, predictive maintenance, track and trace, and modular design. These companies have dramatically improved their efficiency, productivity, and customer experience by ensuring these capabilities are central to their operating models and by matching them with strong skill sets in analytics and IT. “

During 2018 and early 2019, PwC conducted in-depth digitisation case studies of eight industrial and manufacturing organisations in Germany, the US, India, Japan and the Middle East. Drawing on discussions and interviews with CEOs and division heads, we explored the key triggers for change these companies faced, assessed how digital solutions are being implemented and how digitisation is affecting key aspects of their operating models. We also compared our eight organisations with other publicly cited digitisation case studies, and leveraged PwC’s 2018 study Digital Champions: How industry leaders build integrated operations ecosystems to deliver end-to-end customer solutions and other ongoing PwC research.

This paper is the result of ongoing collaboration between PwC and the Global Manufacturing and Industrialisation Summit (GMIS). GMIS provides a forum for industry leaders to interact with governments, technologists and academia in order to navigate the challenges and opportunities brought about by the digital technologies of the Fourth Industrial Revolution. PwC has been a knowledge partner with GMIS since 2016.

The eight case studies in this report make clear how far the role of digital technology goes beyond traditional IT systems. It also encompasses OT and data and analytics technologies. Full integration and linkage among these different technologies, and the ecosystems they are part of, are essential to a successful digital transformation. Yet success is impossible without a digitally smart workforce that is familiar with Industry 4.0 skills and tools.

These challenges are the subject of the second part of the report Digital Champions: How industry leaders build integrated operations ecosystems to deliver end-to-end customer solutions, which will be published in January 2020.

The report will elaborate further on the emerging theory of digital manufacturing and operations, in which successful, digitised industrial organisations will increasingly have to act like software companies in response to four key factors:

  • The connected customer seeks a batch size of one, necessitating greater customisation of products and delivery time, improved customer experience, use of online channels and outcome-based business models.
  • Digital operations require both engineering and software abilities to enable extensive data analysis and IoT-based integration, as well as digitisation of products and services.
  • Organisations need augmented automation, in which machines become part of the organisation via closely connected machine–worker tasks and integrated IT and OT.
  • Future employees will be ‘system-savvy craftspeople’ with the skills to use sensors in order to collect and analyse accurate data, as well as design and manage connected processes.

About the authors

Anil Khurana is PwC’s global industrial, manufacturing and automotive industry leader. He is a principal with PwC US.

Reinhard Geissbauer is a partner with PwC Germany based in Munich. He is the global lead for PwC’s Digital Operations Impact Center.

Steve Pillsbury is a principal with PwC US and the US lead for PwC’s Digital Operations Impact Center.

Report Identifies 4 Changes CEOs Must Implement To Maximize Digitization

Industrial Manufacturers Are Behind the Industrial IoT Innovation Curve

Sean Riley, Global Director of Manufacturing and Transportation at Software AG, discussed Industrial IoT (IIoT) implementation in industry with me a couple of weeks ago. Now, a survey sponsored by Software AG has been released revealing that manufacturers are not scaling IIoT across the enterprise due to failure to invest in predictive analytics and innovative integration strategies.

The shocking thing to me about the survey is that it mirrors survey results over the past three or four years. Executives and managers recognize a problem further even acknowledging that this is something that could cost them competitively against the market even putting them out of business. Yet, they cannot figure out how to do it right. They whine about how tough it is.

Sounds to me like a new crop of leadership is needed.

There are good practices taught some 40 years ago when I took a deep dive while implementing my first IT project. Things like understanding the system first. Bringing all the departments in on the plans, work to be done, and benefits we all would get. Some recommendations from Software AG sound that familiar—breaking silos, bringing IT and OT organizations closer together (a management problem, not a technical one), transparency in the project roll out.

The survey of over 125 North American manufacturers primarily in the heavy industry and automotive sectors revealed inability to scale IIoT investments across their enterprises results in losing millions of dollars in potential profits.

The survey also revealed that the vast majority of manufacturers queried report that their IIoT investments are limited – locked in one small department or sector of their company – preventing these organizations from sharing the power of IIoT across their enterprises.

Other key findings include:

  • 80% of all survey respondents agree that processes around IIoT platforms need to be optimized or they will face a competitive disadvantage but very few are doing this
  • IT-OT integration is considered one of the most difficult tasks – with 57% of automotive manufacturers stating that this has prevented them from realizing full ROI from their IIoT investments
  • 84% of automotive and heavy industry manufacturers agree that the most important area of IIoT is “monetization of product-as-a-service-revenue.” However, optimizing production is still important with 58% of heavy industry and 50% of automotive manufacturers agreeing with that statement
  • Curiously, defining threshold-based rules is considered almost as difficult as leveraging predictive analytics to scale IIoT. More than 60% of respondents stated that defining threshold-based rules was as difficult as integrating IT systems and IoT sensors into existing control systems.

“Manufacturers place a high value on IIoT, but they are encountering serious difficulties in unlocking the complete intended value to unleash their innovation across their organizations,” said Riley. “Fortunately, there is a way for them to quickly and easily resolve this problem. By investing in the right IT-OT integration strategy that leverages sensors, predictive analytics, machine learning, control applications, and product quality control, manufacturers can fix this problem in less than 6-12 months while realizing other key benefits, namely extended equipment lifetime, reduced equipment maintenance costs and accessing more accurate data for production-quality improvements.”

Riley outlined five best practices for manufacturers to follow when looking to scale their IIoT investments across their enterprises and realize immediate profits and competitive advantage. Those best practices are:

1. Ensure clear collaboration between IT and the business by leveraging a step by step approach that starts focused and has clear near term and long- term objectives to scale

2. Create a transparent roll out process and don’t let other plants or departments move ahead outside of it

3. Give IT the ability to connect at speed with a digital production platform that is proven to be successful

4. Leverage a GUI driven, consistent platform to enable an ecosystem of IT associates, business users and partners around the platform

5. Enable the plant or field service workers to work autonomously without continual support from IT through GUI driven analytics, centralized management and easy, batch device connectivity and management

Riley also stated that it is critically important for manufacturers to select the best possible IIoT integration platform supported by key enabling technologies like streaming analytics, machine learning, predictive analytics and a larger ecosystem. Software AG’s Cumulocity IoT platform recently received the highest use case scores from Gartner Group in the brand new “Critical Capabilities for Industrial IoT Platforms” report which included Monitoring Use Case, Predictive Analytics for Equipment Use and Connected Industrial Assets Use Case for its IoT.

The Software AG IIoT Implementation survey was completed in Q2 2019 by Software AG and an independent third-party research house. The survey queried nearly 200 respondents at large manufacturing companies across automotive, heavy industry, high-technology, electronics, pharmaceutical and medical device industries. The respondents were primarily senior executives leading Manufacturing or Information Technology with the breakdown of 50% Managers, 38% Directors and 13% Vice Presidents or higher.

Software AG product

The press release contained some information about the company’s IoT platform—Cumulocity.

Being device and protocol agnostic allows it to connect, manage, and control any “thing” over any network. Cumulocity IoT is open and independent, letting customers connect to millions of devices without being locked into one single vendor.

Schneider Electric Finally Completes Industrial Software Sale (sort of)

Schneider Electric Finally Completes Industrial Software Sale (sort of)

A little consolidation in the industrial software space. Remember when Schneider Electric was shopping its software division a couple of years ago and came up with a reverse acquisition with AVEVA? And the deal fell apart almost a year ago?

Well, it seems that Schneider spent the year internally restructuring such that it could pull off this weird financial transaction. Announced Monday evening, the two companies have reached an agreement to ship SE software to AVEVA forming a new company with SE as a 60% owner and AVEVA holds the other 40%. Plus AVEVA shareholders get some cash in the deal.

Management touts the transaction as having a clear and compelling business logic.  Reasons include building a “global leader in engineering and industrial software”, covering entire asset lifecycle management, and positioned for further acquisitions.

I’ve believed that Schneider would sell off its software businesses ever since the deal for Invensys was announced. Some venture capitalists have talked with me about potential acquisitions. Evidently no one wanted to buy it. I thought maybe Wonderware could make it on its own as a spinoff, but there probably wasn’t enough financial payoff for Schneider with that sort of deal.

However, this also isn’t a clear divestiture. One is left wondering what the future will bring in a couple of years when this transaction matures.

The Management of the Enlarged AVEVA Group will be comprised of:

  • Key members of the existing executive management team of AVEVA, namely Dave Wheeldon (Chief Technology Officer and currently also Deputy Chief Executive Officer) and Steen Lomholt-Thomsen (Chief Revenue Officer) are expected to remain in place following completion;
  • Ravi Gopinath, currently Executive Vice President of the Schneider Electric Software Business, will be appointed as Chief Operating Officer of the Enlarged AVEVA Group. He will report to the Chief Executive Officer of the Enlarged AVEVA Group; and
  • David Ward will continue in his current role as Chief Financial Officer of AVEVA, until a new Chief Executive Officer is appointed. Following such appointment it is intended that David Ward will be appointed to the role of Company Secretary of the Enlarged AVEVA Group.

I received this from Vertical Research Partners analyst Jeff Sprague:

  • Deal Structure Overview – Schneider Electric announced today the combination of its industrial software business and AVEVA to create a global leader in engineering and industrial software. On completion, Schneider will own 60% of the combined new AVEVA group while existing AVEVA shareholders will have 40% equity ownership. However, SU is contributing a little over 60% of the proforma EBITA in addition to a £550MM payment, and allowing AVEVA to distribute a £100mm dividend to AVEVA shareholders at or around completion. Schneider will benefit from unlocking the higher trading multiple of its Software business outside of the Group structure, in addition to future synergies (unquantified). We estimate the transaction creates 42 euro cents of value to SU’s stock price. Closing is expected to be at or around end of 2017.
  • Strategic Rationale – The combined company will provide engineering services and industrial software, with combined revenues of £657.5mm and adjusted EBITA of £145.8mm for the financial year ended March 2017. The combined portfolio will cover process simulation to design and construction to manufacturing operations/ optimization. As shown below, AVEVA is very strong in the front end design and engineering work while SU is strong in O&M and asset optimization. The company noted an ability to create a more streamlined solution as it will control both ends of the spectrum. Management also indicated plans to scale up with future M&A. AVEVA will also enhance the value proposition of Schneider’s existing IOT platform (ExoStructure).

The only interest I’ve seen with total asset lifecycle management is with the OIIE platform from MIMOSA (download whitepaper from my site). A few end-user companies have shown interest in that, but I don’t know that the combined companies will offer much of a competitive advantage in that regard. That would require strong management bringing the disparate parts together into a whole.

For example, I only point to GE Digital whose recent public woes with the Predix system point to the difficulties of software integration.

Data-Driven Decision Making—Connected Vehicles

Data-Driven Decision Making—Connected Vehicles

The afternoon stream I moderated at the Industry of Things World conference focused on connected vehicles—Construction Equipment, Trucks, Airplanes. I also interviewed a farm equipment manufacturer about some perhaps surprising uses of data-driven decision making in agriculture.

But first, a thought from another keynote address:

From a NASA study—If you want to employ a creative genius, you’ll have 98% success employing a 3-5 year old; if you hire an adult, you probability of success drops to 2%.

Data-Driven Agriculture

I caught up with Alexander Purdy of John Deere between sessions. He’s not an engineer or IT manager like many of the attendees and speakers (he had a later keynote). He on the business end. How can John Deere grab a competitive advantage and serve customers through connected data? After a career as a consultant, he loves actually doing things.

His group deals in guidance systems and digital solutions. Guidance systems essentially link a GPS to large farm equipment. Not only does this ensure the rows of corn are nice and straight, the digital decision making increases coverage and yield.

Deere’s digital solutions include online JDLink, JDonline, and an ops center. A farmer can sit in her office and plot out planting regimes setting up everything before going into the field. There is even a way to collaborate on methods and local information.

Let’s take seeding for example. Sensors connected back to the system can feedback soil conditions. This helps the planter decide for each seed in a cornfield the optimum x, y, and z (yes, they measure depth of planted seed). The idea is to get each plant to grow at about the same rate.

Connected Construction Equipment

Kjell Jespersen, Caterpillar, spoke on huge construction equipment. Customers have been using the large amount of data generated by construction equipment mainly for improving maintenance. However, they crave better productivity data to manage their business. Developing the systems for gathering and analyzing all the data will become crucial as a competitive advantage—or failure to do so could force a company to exit the business.

Connected Trucking

Turning to the long-haul trucking business, companies are turning to truck suppliers such as Volvo and Mack Trucks to provide connected vehicle technology to provide data for improved customer support. According to Evandro Silva, Manager Connected Vehicle Services, Volvo Group Trucks North America, a telematics solution was used to develop a connected service that enables quick diagnosis of issues, proactive scheduling for repairs, and confirmation that needed parts are in stock and ready to install—all while the truck is still on the job.

Airplane Digital Twin

Robert Rencher, Senior Systems Engineer and Associate Technical Fellow, The Boeing Company, took the discussion to a new level—literally. From equipment that stays firmly on the ground, Rencher discussed the role of a “digital twin” throughout the lifecycle of an aircraft. A digital twin is defined within a system representing the characteristics of the object and the virtual environment in which the digital representation of objects and their physical equivalent, vice versa, are represented digitally and co-exist such that the object’s past, current, and future capabilities and can be assessed and evaluated in real-time. As an object progresses through each phase of its lifecycle, various systems interface with the digital twin.

Next Year

Look for information about next year’s conference and all the other conferences.  Next year will be about the same time of year in San Diego. Details are still being worked out. Check out twitter conversations at #IoTClan