[Updated] Hitachi, a large industrial conglomerate, brought together several businesses it owned and acquisitions of Pentaho and Lumada into a wholly owned enterprise called Hitachi Vantara in 2017. NEXT 2019, its third customer conference attracted a large attendance to Las Vegas.
Hitachi was founded more than 100 years ago “to make products for good.” Thus the conference theme “Powering Good.” I have to say, it is so refreshing to see some ethics emphasis on doing good on display. It gave donations to the American Heart Association and the Rainforest Connection. Nice to see some ethics and doing good on the part of corporations.
Hitachi is involved in manufacturing, so the IT group has roots there, which is of course relevant to all of us. It is not just a random act that brought a manufacturing emphasis to Lumada–although it is used in many other industries as well.
I previously wrote about new products under the Lumada brand in May and September. Following are summaries of important announcements from last week.
DataOps: Data Management for the AI Era
I walked into the stand and told the guy, “DataOps is my new hobby.” I learned much about this new (to me) technology that I wrote about for the first time only a couple of weeks ago.
DataOps was briefly described to me as a pipeline for data. Hitachi Vantara says, “DataOps is enterprise data management for the artificial intelligence (AI) era, seamlessly connecting data consumers with data creators to rapidly find and use all the value in an organization’s data.”
DataOps is not a product, service or solution. Rather, it’s a methodology, and a technological and cultural change, to improve an organization’s use of data through better data quality, shorter cycle time and superior data management. Because organizations are not analyzing most of the data they have due to legacy methods, Hitachi Vantara believes DataOps will have significant impact on the future of IT by unlocking vast amounts of previously unused data.
Hitachi Vantara announced the expansion of the Lumada platform services and solutions portfolio to help customers across industries break down data silos and drive more innovation through DataOps. Hitachi is now extending Lumada’s capabilities beyond the internet of things.
New and updated Lumada offerings include:
Lumada Data Services, a set of software services that help customers manage increasingly complex data ecosystems with an intelligent data foundation.
Interoperating with Hitachi’s proven technologies for object storage, data integration, and analytics – underpinning Hitachi Content Platform (HCP), Pentaho and Lumada – customers can now cost-effectively govern and manage all their data assets, including structured and unstructured, across data center, cloud and edge locations. Policy-based automation tools orchestrate enterprise data flows to deliver on cost savings, compliance and business growth demands.
Lumada Data Lake, an innovative, “smart” data lake offering that is self-optimizing – and which intelligently places data sets in an optimal location – continuously curates to avoid data swamps and is readily accessible to analytics anywhere.
Lumada Edge Intelligence, a new set of software and validated edge hardware devices that enable organizations to manage data and analytics at the network edge for digital use cases such as IoT, connected products, immersive customer experiences, remote and disconnected sites, and branch offices.
Hitachi Virtual Storage Platform (VSP) 5000 series and Hitachi Ops Center software form the company’s powerful next-generation storage and infrastructure foundation with a new scale- out, scale-up architecture for any workload at any scale. These technologies can accelerate data center workloads and deliver future-proof IT with a new, innovative architecture that is the ideal foundation for modernizing data center, cloud, and DataOps environments. The platform also features the world’s fastest NVMe flash array.
Hitachi Vantara expanded and enhanced its capabilities for cloud services in the first major announcement of the company’s newly formed cloud services portfolio. The portfolio includes cloud migration services, application modernization services, operations managed services, consulting services and Hitachi Enterprise Cloud (HEC). The portfolio leverages critical capabilities and industry-leading expertise from the company’s acquisition of REAN Cloud in 2018.
Data Integration and Analytics
Pentaho 8.3, the latest version of the company’s data integration and analytics platform software, introduces a series of features designed to support DataOps, a collaborative data management practice. This latest version delivers improved data agility from customers’ edge-to-multicloud environments while facilitating privacy, security and overall data governance.
Pentaho 8.3 introduces several enhancements:
- Improved drag and drop data pipeline capabilities to access and blend data that’s difficult to access
- New connector to SAP offers drag and drop blending, enriching, and offloading data from SAP ERP and Business Warehouse providing deeper insights into and greater analytic value from enterprise information
- Amazon Kinesis provides real-time data capability in an AWS environment. Pentaho allows AWS developers to ingest and process streaming data in a powerful visual environment as opposed to writing code, and blend it with other data, reducing the manual effort
- Improved integration with Hitachi Content Platform (HCP)
- IBM Information Governance Catalog (IGC) Integration
- Streaming data lineage make it easier to trace real-time data from popular protocols such as AMQP, JMS, Kafka, and MQTT
I am still talking about Emerson Exchange, and have a few more to go. This post is about analytics. Jonas Berge, Senior Director, Applied Technology, Plantweb, Emerson Automation Solutions, has often supplied me with great insight usually about networks in the past. We chatted briefly at Exchange and then followed up with email conversations. In this one, he talked about analytics.
Digital Transformation has a foundation in data. Data is useless without a formal way of thinking about it. There are two kinds of analytics tools.
We are left with two tasks. We must first understand the two types, how they are derived and their strengths and weaknesses.Then we choose the right analytics tool for the problem.
There are principles-driven tools and data-driven tools.
One must remember that advanced predictive techniques can only be practically applied to a subset of use cases.
An over-emphasis on one approach means companies won’t position themselves to capture all the potential benefits.
When factoring the effort and expertise required to develop accurate machine-learning models, remember most organizations already have systems in place to record maintenance- and reliability-related data, but the effectiveness of such systems can be undermined by poor housekeeping. The same assets or issues may be described in different ways in different systems, for example, making integration difficult. Companies may use free-text fields to record issues or maintenance actions, making automated search or data analysis harder. Or critical data may be inaccessible, locked away in spreadsheets or on paper notes.
The application of machine-learning techniques to monitor asset condition has already received considerable attention, even though their cost and complexity may ultimately limit their application.
When a machine is prone to a narrow range of well-understood failure modes, it is often possible to address a potential problem in a simpler way, for example by monitoring the temperature or vibration of a component against a set threshold.
Model-based predictive maintenance becomes a breakthrough way to solve selected high-value problems. This approach has the most potential where there are well-documented failure modes with high associated downtime impact, for example in a critical machine on a larger production line.
Root-cause problem solving, using approaches such as fault-tree analysis as well as cause-and-effect or failure-modes-and-effects analysis (FMEA), is a fundamental part of any organization’s maintenance and reliability strategy.
Not all condition-monitoring techniques require elaborate algorithms or complex models, however. Data-driven condition-monitoring approaches use simple queries that are run periodically or in real time against time-series data generated by machines and external sensors. If threshold conditions are passed, these systems can trigger investigative or corrective action in the digital-reliability-engineering workflow, or directly to maintenance execution.
This announcement from Schneider Electric originated from the conference in Barcelona that I will be attending in Austin, Texas. It supports a trend we’re seeing of suppliers breaking software into specific-purpose chunks to make it easier for customers to purchase, install, and maintain. The EcoStruxure Plant Performance Advisors suite points toward food and beverage; mining, minerals and metals; oil and gas; water and wastewater; and other industrial enterprises.
These comprise a specialized suite of smart manufacturing apps and digital services, providing easy-to-understand, real-time analytics.
“The digital transformation vision is coming to life for industrial operations,” said Sophie Borgne, senior vice president, Schneider Electric Digital Plant. “Industry 4.0 has embraced digitalization but now must get out of ‘pilot purgatory’ and scale up. Respecting an industrial enterprise’s operational investment, the modular EcoStruxure Plant Performance Advisors make it easy for plants of all sizes—not just big corporations to modernize at a sustainable pace and accelerate their digital transformation in very simple, step by step manner.”
Data-driven Plant Performance Management
Schneider rightly contends that IIoT blurs the line between information technology (IT) and operational technology (OT) yielding great amounts of data. The Advisors enhance asset optimization, asset performance management, predictive maintenance, and real-time decision-making.
Schneider Electric utilizes digitalization in its own factories. Using technology, including EcoStruxure Plant Performance Advisors, its Smart Factory in Bantam, Indonesia is reporting a 44% reduction in machine downtime in one year. The Schneider Electric Smart Factory in Vaudreil, France also implemented EcoStruxure Plant Performance Advisors, which contributed to:
- 10% reduction in energy consumption
- 25% improvement in plant operations efficiency.
- 20% reduction in maintenance costs.
- 20% reduction in diagnosis and repair time.
EcoStruxure Plant Advisors are fully configurable, off-the-shelf solutions for easy integration into even the most advanced systems. By providing users with a familiar application theme and environment, an efficient plant can create synergies for processes and empower digital operators. This greatly reduces the user learning curve, saving time and money.
Schneider Electric’s modular and scalable EcoStruxure Plant Advisors suite includes:
- EcoStruxure Pumping Performance Advisor is a new digital service for the continuous improvement of water and wastewater pumping assets in 24/7 operations. By addressing challenges such as cost of water, plants can save up to 15% in OPEX through pump optimization.
- EcoStruxure Equipment Efficiency Advisor provides real-time efficiency root cause analysis. It then recommends appropriate action plans for increasing capacity while reducing unscheduled downtime and waste, which often results in immediate 5% to 10% OEE gains.
- EcoStruxure Augmented Operator Advisor uses augmented reality to slash the amount of time a worker spends looking for information to about a tenth of current levels. By superimposing real-time data and virtual objects (point of interest, documentation, procedures) onto cabinets or machines, this “contactless maintenance” model also increases safety. EcoStruxure Augmented Operator Advisor V2.4 is easy to customize; no special platform knowledge is required. Users can also easily add augmented reality into existing procedures and export notes and analysis to share with others.
- EcoStruxure Secure Connect Advisor with embedded cybersecurity provides a digitally secure and simple asset monitoring connection for remote diagnostic and maintenance that reduces plant downtime while saving time and travel costs to maintain critical assets. In some cases, this has resulted in a shortened time to solution from over 7 days to as little as 4 hours.
EcoStruxure is Schneider Electric’s open, interoperable, IoT-enabled system architecture and platform.
I guess I did attend the last GE software conference Minds + Machines. However, the reconstituted and independent GE Digital recently held a user conference where it announced a number of upgrades to its IIoT software. These are firmly within the current trends of connecting and mobility.
The product updates include:
- Predix Essentials, which makes it easier for industrial companies to connect, visualize and analyze their data
- Asset Answers, which helps customers to understand the competitive potential of Asset Performance Management (APM) software
- Webspace 6.0, a new HTML5 interface that seamlessly brings automation data to operators across any mobile device
Predix Essentials is an easy-to-use SaaS solution, helping companies connect to disparate data sources, monitor operations, and leverage edge-to-cloud predictive analytics–reducing time-to-value for operational teams looking to reduce waste, lower costs, and increase performance.
Developed in partnership with a number of customers, including silicon chip manufacturer Intel, Predix Essentials is a natural first step for industrial businesses looking to leverage the power of cloud-based Industrial IoT technologies, providing the connectivity, visualization and analysis capabilities that are the cornerstones of a digital transformation journey, regardless of vertical or maturity.
Suitable for industrial companies of all kinds, Predix Essentials is also the foundation of GE Digital’s APM and OPM application suites, providing core functionality and bridging the entire software portfolio by connecting GE Digital cloud-based solutions to on-premises data from its Automation, MES and Historian solutions.
Identifying Maintenance Strategies
Asset Answers is a benchmarking tool that helps customers quickly import and assess data to better understand how their asset maintenance compares with similar companies in their particular domain, or even against their own internal performance across sites.
With this intelligence, customers can determine where best to invest in updating maintenance regimes or capabilities, and ultimately provide a seamless path to products like APM to manage and optimize assets across their business. Asset Answers is available for many sectors, including power generation, oil and gas and chemicals.
Improving Operator Mobility
Webspace 6.0, a web and mobility solution, brings the full visualization and control capabilities from GE’s iFIX and CIMPLICITY HMI/SCADA software seamlessly across devices, including smartwatches, phones, tablets and desktops.
Offering enhanced encryption and new zero-install HTML5 client, Webspace 6.0 improves the way that operators receive and react to operational insights, whether they are in the field, on the plant floor or at a desk, providing them the flexibility to make informed decisions and share their expertise, regardless of location. By dynamically extending automation solutions, Webspace 6.0 increases information sharing across teams, speeds the right operator actions, and improves agility with real-time visualization and control anywhere, anytime.
“GE Digital continues to release innovations that forge the way for industrial customers working on transforming their operations,” said Pat Byrne, CEO of GE Digital. “By continuing to invest across our portfolio of industrial software, and by making it easier than ever for our customers to unlock the power of the Industrial IoT, GE Digital is strengthening its customers’ ability to become more productive, efficient and safe.”
Predix Essentials, Asset Answers and Webspace 6.0 are generally available today as part of GE Digital’s portfolio of industrial software products covering HMI/SCADA, Historian, Asset Performance Management and Manufacturing Execution System applications. Today’s announcements build on a strong thread of recent investments in product innovations, all designed to solve a broad range of industrial customer challenges, including iFIX 6.0; Historian 7.2, Plant Applications 8.0 and Predix Manufacturing Data Cloud for the manufacturing sector; Grid Analytics for the power transmission and distribution market; and APM Integrity’s Compliance Management for the O&G and Power Generation industries.
DataOps—a phrase I had not heard before. Now I know. Last week while I was in California I ran into John Harrington, who along with other former Kepware leaders Tony Paine and Torey Penrod-Cambra, had left Kepware following its acquisition by PTC to found a new company in the DataOps for Industry market. The news he told me about went live yesterday. HighByte announced that its beta program for HighByte Intelligence Hub is now live. More than a dozen manufacturers, distributors, and system integrators from the United States, Europe, and Asia have already been accepted into the program and granted early access to the software in a exchange for their feedback.
HighByte Intelligence Hub will be the company’s first product to market since incorporating in August 2018. HighByte launched the beta program as part of its Agile approach to software design and development. The aim of the program is to improve performance, features, functionality, and user experience of the product prior to its commercial launch later this year.
HighByte Intelligence Hub belongs to a new classification of software in the industrial market known as DataOps solutions. HighByte Intelligence Hub was developed to solve data integration and security problems for industrial businesses. It is the only solution on the market that combines edge operations, advanced data contextualization, and the ability to deliver secure, application-specific information. Other approaches are highly customized and require extensive scripting and manual manipulation, which cannot scale beyond initial requirements and are not viable solutions for long-term digital transformation.
“We recognized a major problem in the market,” said Tony Paine, Co-Founder & CEO of HighByte. “Industrial companies are drowning in data, but they are unable to use it. The data is in the wrong place; it is in the wrong format; it has no context; and it lacks consistency. We are looking to solve this problem with HighByte Intelligence Hub.”
The company’s R&D efforts have been fueled by two non-equity grants awarded by the Maine Technology Institute (MTI) in 2019. “We are excited to join HighByte on their journey to building a great product and a great company here in Maine,” said Lou Simms, Investment Officer at MTI. “HighByte was awarded these grants because of the experience and track record of their founding team, large addressable market, and ability to meet business and product milestones.”
To further accelerate product development and go-to-market activities, HighByte is actively raising a seed investment round. For more information, please contact [email protected]
Learn more about the HighByte founding team —All people I’ve know for many years in the data connectivity business.
From Wikipedia: DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data analytics. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations.
DataOps incorporates the Agile methodology to shorten the cycle time of analytics development in alignment with business goals.
DataOps is not tied to a particular technology, architecture, tool, language or framework. Tools that support DataOps promote collaboration, orchestration, quality, security, access and ease of use.
From Oracle, DataOps, or data operations, is the latest agile operations methodology to spring from the collective consciousness of IT and big data professionals. It focuses on cultivating data management practices and processes that improve the speed and accuracy of analytics, including data access, quality control, automation, integration, and, ultimately, model deployment and management.
At its core, DataOps is about aligning the way you manage your data with the goals you have for that data. If you want to, say, reduce your customer churn rate, you could leverage your customer data to build a recommendation engine that surfaces products that are relevant to your customers — which would keep them buying longer. But that’s only possible if your data science team has access to the data they need to build that system and the tools to deploy it, and can integrate it with your website, continually feed it new data, monitor performance, etc., an ongoing process that will likely include input from your engineering, IT, and business teams.
As we move further along the Digital Transformation path of leveraging digital data to its utmost, this looks to be a good tool in the utility belt.
Digitally integrating and aligning manufacturing operations with the rest of the enterprise has been an elusive goal for perhaps 20 years. It was a promise of ERP. Easy to say; hard to accomplish. Then we went through all the IT/OT stuff. Here’s another take–aligning sales and operations. Speaking from bitter experience, have faster and more accurate feedback from sales would have made our lives better in operations.
Salesforce just announced Manufacturing Cloud, a new industry-specific product for manufacturers. Manufacturing Cloud brings sales and operations teams together around a unified view of market and customer demands to more accurately forecast, plan, and drive predictable business performance. With Manufacturing Cloud, companies can now better meet commitments and run a more streamlined business while improving customer satisfaction.
Here is the rationale from Salesforce: The manufacturing industry depends on predictability, as its capital-intensive businesses often have complex physical operations that cannot be quickly or inexpensively modified to meet changing customer demands. Unfortunately, operations teams aren’t always aligned with sales reps to ensure they have a single, real-time view of all aspects of their customer relationships.
Critical customer insights are siloed across spreadsheets and multiple ERP systems, which can negatively affect account performance and ultimately the ability to accurately predict demand. The resulting inventory stockouts, buildups and warehousing costs reduce operating margins and negatively impact revenue. In order for manufacturers to provide a seamless customer experience, they need a solution that helps them better understand customer needs while improving visibility across the entire value chain.
“In the manufacturing industry, changing customer and market demands can have a devastating effect on the bottom line, so being able to understand what is happening on the ground is imperative for success,” said Cindy Bolt, SVP and GM, Salesforce Manufacturing. “Manufacturing Cloud bridges the gap between sales and operations teams while ensuring more predictive and transparent business, so they can build deeper and more trusted relationships with their customers.”
Introducing Manufacturing Cloud
Manufacturing Cloud, the newest industry-specific product from Salesforce, delivers a new level of business visibility and collaboration between the sales and operations organizations of a manufacturing company. This allows them to have a better view of their customers through powerful new sales agreements and account-based forecasting solutions, providing visibility into their customer interactions while enabling them to generate more robust sales forecasts.
Salesforce has collaborated with major manufacturing and sales companies through the product pilot program, including Kawasaki Motors Corp., U.S.A. – Engines Division, Hitachi Chemical, CF Industries, Mipox, GELITA and more.
Manufacturing Cloud features include:
- Sales Agreements allow manufacturers to unify their run-rate business with data housed in ERP and order management systems with the contract terms negotiated—including planned volumes and revenues—so both operations and account teams can have a 360-degree view of the customer. If any changes to the agreement are needed, they are immediately incorporated into the existing sales agreement, ensuring there is always a single source of truth. This allows account teams to manage the full sales agreement lifecycle and have visibility into committed and actual order volumes, the performance of the agreement against the forecast and other time-phased custom metrics. This also simplifies the renewal process, ensuring account teams continue to bring in revenue while increasing margins.
- Account-Based Forecasting provides manufacturers with a complete view of their current business alongside future opportunities. This allows sales, finance and operations teams to develop more accurate forecasts while breaking down internal silos. Account teams can also add updates on changing customer needs or market demands, allowing the team to collaborate and adjust forecasts in real-time, helping to make business transactions, profits and revenue margins more predictable.
In addition to Manufacturing Cloud, Salesforce is also releasing new manufacturing-specific innovation across the Salesforce Customer 360 Platform to help manufacturers deliver greater transparency, streamline collaboration and grow their businesses.
- Einstein Analytics for Manufacturing provides account managers with access to an intelligent experience with out-of-the-box KPIs into account health, demand insights, product penetration and sales agreement progress. By centralizing and analyzing key data sources, account managers can proactively engage clients that are at highest risk for churn. In addition, by identifying key trends within an account, account managers can proactively grow their relationship by recommending relevant upsell and cross sell opportunities.
- Community Cloud for Manufacturing will deliver a new pre-built template specific for manufacturers that extends sales agreements to channel partners, allowing them to easily collaborate together on leads and opportunities.
- MuleSoft Anypoint Platform unlocks data from any application, data source or device—whether that data is on-premise or in the cloud. By enabling organizations to connect Manufacturing Cloud with other systems, sales and operations leaders can automate the complete order-to-cash process, create a comprehensive forecast view and drive business process automation across all sales channels.
Partners Accelerate Expansion
Salesforce has a comprehensive ecosystem of partners that will extend the power of Manufacturing Cloud. Key partners were instrumental in the development of Manufacturing Cloud, and will power digital transformation for customers in the manufacturing industry.
- Accenture: As a pilot partner, Accenture’s global experience with industrials is providing new ways to apply Manufacturing Cloud to deliver transformational value through practical, connected, cloud-enabled solutions.
- Acumen Solutions: As a design and pilot partner for Manufacturing Cloud, Acumen Solutions collaborated with Salesforce to identify personas, use cases and requirements of customers in the manufacturing space to inform product development.
- Deloitte: Cloud4M, an ISV Managed Package, was built on Manufacturing Cloud by Deloitte Digital, Deloitte’s creative digital consultancy and a Manufacturing Cloud pilot partner. Cloud4M is a pre-configured, multi-cloud software solution designed to simplify decision making in B2B sales agreements and throughout the end-to-end customer engagement process, tailored for manufacturers and industrial product companies.
- Rootstock: Rootstock’s ERP system, built on the Salesforce Platform, feeds actuals from its ERP to Manufacturing Cloud to track compliance against sales agreements. Additionally, Rootstock’s planning engine consumes sales forecasts from Manufacturing Cloud to improve the quality of production, procurement and distribution plans.
Manufacturing Cloud, Einstein Analytics for Manufacturing and Community Cloud for Manufacturing will be generally available in October, 2019.