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OpenText Announces Availability of New Cognitive AI Platform


Catching-up on developments that occurred while we were away on summer holiday, we call attention to Supply Chain Matters readers that Enterprise Information Management (EIM) technology provider OpenText held its OpenText Enterprise World 2017 customer conference in Toronto earlier this month.

The most significant announcement generated from this conference was the announced availability of OpenText Magellan, a new artificial intelligence and analytics technology platform designed to allow users the abilities to acquire, merge, manage and analyze volumes of data and content resident across various enterprise systems.

We initially called attention to the Magellan effort in our highlights of last year’s OpenText Enterprise World conference. At that time, Project Magellan was described as a next generation cognitive platform designed to integrate voice, video, natural language processing and other content. It was outlined as an open-systems based platform that would leverage both the Spark Apache platform along with the analytics capabilities of Actuate, OpenText’s prior acquired advanced analytics provider.

A year ago, CEO Mark Barrenechea was not shy in making a direct head-to-head technology comparison with the IBM Watson Cognitive platform and that his company will compete directly as an alternative platform in the market. As promised, OpenText management timed the formal announcement of general availability at this year’s conference.

An on-stage demonstration of this new platform described the application as an artificial intelligence based data discovery tool where data scientists or sophisticated users can utilize drag and drop technology to build rather advanced algorithms to collections of existing data sets. Once such algorithms are established, they can be applied to subsequent analysis of existing data to provide a basis for more predictive analytics related to areas such as customer buying patterns, refining of specific customer demographics or even specific supply chain management decision needs such as predictions of specific product or customer demand based on buying and other external patterns.

Once again, there was an emphatic emphasis on the leveraging of standard open languages such as Apache Spark vs. the proprietary technology approach of IBM’s Watson platform.  The important emphasis for OpenText is the ability to deliver a cognitive AI platform with pre-integrated open stack components with minimized efforts and expertise required to go-live, at a more attractive price point.

From our lens, the obvious question is whether the market is currently ready to adopt such a platform. Candidly, OpenText has not previously been viewed for its openness approach, but Magellan represents a bold pivot in company and product strategy. The opportunity to present a direct and perhaps more attractive alternative to IBM Watson is predicated on three unanswered questions.

The first and most obvious is the ability of the company’s sales, marketing, technical representatives, or systems integration partners to provide a cohesive and comprehensive sales development approach related to an enterprise class cognitive platform vs. a custodial information management platform. This is where market readiness will provide the litmus test as well as the notions of targeting the most obvious starting points that large collections of customers need technology to solve. Our belief is that there could well be various mission-critical supply chain management decision-making needs in such evaluations, especially approaches that can leverage externally based information sources that represent the entire product or services value-chain.  To its credit, OpenText has recruited individuals with experience in such areas.

The second is the ultimate price-point established for Magellan, which we have not been able to ascertain up to this point. Total cost competitiveness remains a rather sensitive criterion for technology adoption, especially in enterprise dimensions. Head-to-head competition can be based on price or functionality. In most cases and by our observations, price trumps functionality.

The third, and likely most important open question is the development of a record of accomplishment of installed customer value and active cognitive platform customer advocates. This has been an area where IBM Watson, as well as other providers, have had a mixed record of accomplishment to-date, and will serve as OpenText’s greatest opportunity over the coming months. While OpenText has established valued relationships with enterprise vendors such as SAP and Oracle, being perceived as a direct competitor in cognitive platform requires walking a very fine line.

Supply Chain Matters we continue to monitor this area and will provide timely updates in the coming weeks.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.


IDC Updates Global Spending Forecast for Internet of Things Technology

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This week, quantitative market research firm IDC released its Worldwide Semiannual Internet of Things Spending Guide, that at the surface, provides strong evidence of meaningful IoT related IT spending this year, and in future years.

Within the announcement are important validation for our supply chain management community, namely that the broadest appeal, value, and attraction for current IoT efforts rests in areas of manufacturing and supply chain focused business processes. IoT 425 IDC Updates Global Spending Forecast for Internet of Things Technology

The industry analyst firm now predicts that worldwide spending on IoT focused technology is expected to grow 16.7 percent this year, reach a level of $800 billion. The firm now forecasts that spending on hardware, software, services, and connectivity that enable IoT will reach $1.4 trillion in five years.

According to the analyst firm, technology hardware, manifested by sensors and modules that connect end points to networks, will be the largest spending category until the last year of the current forecast, when overtaken by the faster growing services category. The forecast indicates that software, namely horizontal and analytics focused, will represent the highest five-year technology growth rates at 29.0 and 20.5 percent CAGR respectively.

IDC indicates that the industrial use cases expected to attract the largest investments this year include $105 billion in manufacturing operations, $50 billion in freight monitoring, and $45 billion in production asset management. According to the forecast, the industries with the largest investments will be Manufacturing ($183 billion), Transportation ($85 billion), and Utilities ($66 billion).

Interesting enough, IDC indicates that the Asia Pacific region (excluding Japan) will represent the leading investment region, followed by United States and Western Europe. From our lens, these regional based forecasts are an indication that Asia-Pac firms view IoT as a core disruptive technology, and are taking an aggressive investment view to leverage such technologies.

On the consumer focused IoT side, the firm now forecasts this area to be the fourth largest market segment this year, and grow to become the third largest segment by 2021. The largest spending growth areas over the five-year window indicated to be 33.4 percent CAGR in airport facilities automation, 21.1 percent CAGR in electric vehicle charging stations, and 20.2 percent CAGR in in-store contextual marketing.

Within our own specific 2017 supply-chain focused technology predictions, we declared that IoT focused technology would continue in early stage pilots or line-of-business driven efforts to prototype new business models. We believed that industry competitor drives need needs to achieve forms of first-mover advantage in either developing new forms of digital-driven business process and achieving newer top-line revenue streams. Early efforts also help in developing required competencies in data security and interoperability among various edge and core business systems.

Judging from the latest IDC forecast data, manufacturing, asset management and transportation processes are garnering the highest interest levels in 2017. Each has a foundational aspect. A further takeaway, again from our lens, is that the near-term investment use-cases for IoT remain in the industrial sector, many of which reflect the digitization of business processes.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.


A Path Towards Internet of Things Enabled Service Management- Service Parts Planning Realities

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This blog posting represents the second of a four-part market education series, in collaboration with supply chain planning and service parts technology provider ToolsGroup.

 In our initial posting in this series, we declared that one of the most promising line-of-business areas that will benefit from Internet of Things (IoT) enabled technologies applied to supply chain management will be equipment services management, especially service and spare parts management.  Planning 3 shutterstock 394279114 300x184 A Path Towards Internet of Things Enabled Service Management  Service Parts Planning Realities

A longstanding challenge in service or replenishment parts planning and management has always been the ability to forecast item-level demand when such demand is sporadic or sudden.  Now consider the opportunities to have demand-driven or predictive failure data and information emanating directly from the physical equipment.

But with any major business transformation, there are always foundational capabilities that come first. In the specific area of IoT enabled equipment and services management, a foundational capability is usually the need for a robust, responsive, and analytically-driven service parts planning (SPP) capability.

Yet an unfortunate reality is that many manufacturing and services organizations with lower levels of process maturity have not recognized the differing process and decision-making needs required for responsive and effective SPP.  Considering a leap to an IoT enabled service management business model will likely expose this weakness.


What Makes Service Parts Planning Different?

Three fundamental differences often found in SPP are the following:

  • Contracted service levels and customer contracts determine the overall parts distribution and required service response network. When there is either equipment downtime, caused by a failing part, or when equipment consumables are suddenly out-of-stock, equipment is no longer generating value for end-customers. There is very little tolerance for inventory back-orders since non-performing equipment results in downtime costs that can far outweigh the cost of the replacement part.


  • Service parts component demand is often manifested in intermittent or lumpy demand signals, caused by actual equipment operational conditions or changes in operating environment. That means planning in an environment of long-tail demand, parts that exhibit larger numbers of variability, lumpy or seasonality focused demand patterns. Traditional forecasting or demand planning techniques are often ineffective in planning parts demand in such environments. That’s because SPP is far more concentrated in individual item-level planning as contrasted to product family or aggregated planning techniques. SPP planning models feature higher stock keeping unit (SKU) counts and associated long-tail demand planning computations than traditional supply chain planning models. Algorithms that capture actual parts demand, or plan for future demand need to be far more sophisticated in item level and shipping location mathematical modeling.


  • Service parts networks require the need for multi-echelon and multi-tiered inventory stocking strategies tied to more predictive parts demand. Long-tail demand can be best managed by planning that factors item level and shipping location simultaneously. SPP must therefore be able to effectively manage and optimize inventory within such multi-echelon stocking environments.


A Path to the Future

Three to five years from today, even more equipment will be acquired by “services by the hour” payment methods, saving on front-end capital equipment costs for equipment operators. Physical objects such as complex equipment, engines, motor vehicles and other forms of equipment will be communicating operational performance and service needs via IoT enabled data and information flows. For equipment manufacturers, the opportunities are new lines-of-business and incremental multi-year top-line revenues flowing from such models.

The good news for IoT enabled service management processes is that the equipment itself can provide more proactive or prescriptive indications of when a part is scheduled to fail, as well as actual maintenance data related to parts failure. Such capabilities will provide added intelligence and more accurate parts demand information that will provide additional service uptime and operational cost savings for customers and service parts providers. In addition, the ability to link the physical equipment and operational data related to equipment with a robust SPP environment adds important benefits in the ability to capture and plan more accurate, and more predictive information related to service parts or consumable parts needs and requirements across a service management network.

However, the savviest businesses recognize that the end-goal is not IoT per-se, but in building the foundational people, process and technology capabilities that can best leverage the digitization of supply chain management and decision-making processes. An IoT front end isn’t much good without an equally responsive back end planning system.

Businesses that recognized the critical differences in more effective service parts management and made the initial foundational investment in more responsive SPP process capabilities will be far better positioned to harvest the benefits of smarter and more efficient network wide inventory levels, more timely decision-making and most important of all, more responsive service and satisfaction levels for equipment customers.


Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.


Praise to APICS in Efforts to Update SCOR Reference Model

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Last week, APICS made a noteworthy announcement regarding The Supply Chain Operations Reference Model-SCOR, which we wanted to highlight for our Supply Chain Matters readers.

The supply chain educational and performance improvement organization indicates that SCOR Release 12 is currently under development by a committee of global supply chain practitioner experts and is expected to be released in the Fall, most likely in conjunction with the APICS Annual Conference. We call reader attention to the release because of the new topical areas being planned for inclusion in the new iteration, along with an increased effort to make this framework even more amendable to machine-readable language that can be leveraged for supply chain focused Cloud-based advanced analytics purposes.  APICS logo Praise to APICS in Efforts to Update SCOR Reference Model

From our lens, the planned SCOR Release 12 is a definitive acknowledgement that industry supply chain business process and advanced technology needs are rapidly changing, and manufacturers and services providers who have currently adopted tenets of SCOR need to incorporate such new factors into their performance frameworks and metrics.

APICS indicates that a SCOR job task analysis survey completed by over 1600 supply chain professionals validated the increasing importance for:

  • Sourcing and procurement processes for the SCOR framework
  • Metadata, digitization, omni-channel, and supply chain maturity model
  • Data analytics, data acquisition, data science, and predictive analysis as staff skills related to organizational supply chain initiatives
  • Continuing education and improvement of supply chain manager skills and abilities

In addition to these added context areas, ongoing APICS Special Focus Forums are addressing unique performance framework needs in areas such as humanitarian supply chains and new iterations of integrated of integrated business planning. Documentation efforts from these forums call for periodic updates to the digital library that APICS members have access to.

A further area addressed by a specific forum are opportunities to make SCOR more of a fabric in IT-centric supply chain analytics, dashboarding and overall integrated decision-support capabilities. Currently available is the software- SCOR Business Process Management Accelerator powered by Software AG’s ARIS tool. The tool itself can be extended via an open API to other Cloud-based ERP or specialty supply chain management applications, allowing analytics data to reference existing SCOR metrics. APICS further indicates a willingness to work with added software providers on other analytics and decision-support needs that seek to leverage existing SCOR performance or metrics relationship data. By our way of thinking, there is added opportunity down the road for the ability to incorporate artificial intelligence or machine learning techniques with SCOR frameworks for more predictive factors of supply chain performance.

Supply Chain Matters applauds the recognition of all the above as emerging drivers of supply chain success and of areas that can truly continue to benefit from a common supply chain reference model.

A final note relates to the need for augmented SCOR training, considering the addition of the above timely topics.  A recent conversation with Peter Bolstorff, APICS Executive Vice President, Corporate Development acknowledged the need for stepped-up training, given the added content areas with SCOR-12. The organization is currently working on stepped-up plans for SCOR training, in addition to current company hosted and public training activities. We anticipate further announcements in this area in the weeks to come.

Industry supply chain process and decision-support needs are indeed changing and its go to observe supply chain professional organizations adapting tools, frameworks, and training to help organizations manage such changes.


Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.

Jabil Raises the Bar in Providing Supply Chain Cloud Platform and Decision Support Needs

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This week, product solutions provider Jabil Circuit made a significant announcement, one that places this company as a supply chain Cloud based technology provider in addition to its other product value-chain design and manufacturing contract services (CMS).

As an independent supply chain advisory service, we have long ago predicted that large volume contract manufacturers would have to broaden their services models to grow market-share and profitability. Jabil is about to demonstrate the notions of providing an end-to-end supply chain focused decision support platform to support product value-chain management needs.

Jabil’s InControl SaaS is described as a multi-tenant, intelligent supply chain cloud platform that provides network wide connectivity, advanced analytics, and built-in machine learning capabilities to optimize near real-time decision-making.

Earlier this month, this analyst had the opportunity to speak with Jabil’s executive team to review highlights of InControl SaaS, and candidly, the full functionality would rival that provided some existing supply chain best-of-breed software providers in today’s tech marketplace. The other important difference is the coupling of specialized managed services in addition to what appears to be a sophisticated B2B network platform.

In its entirety, support encompasses five supply chain focused applications, a decision support platform, coupled with bundled procurement and supply chain focused managed services. The latter managed services include areas that span strategy, procurement sourcing, procurement business process outsourcing, supply network optimization and social responsibility. From our view, the target customers are those that are seeking their supply chain sourcing, operational and decision-making needs focused in a singular integrated platform, especially up and coming product companies that cannot afford the up-front or ongoing expense of investing in complete product value-chain needs.

Jabil’s market messaging emphasizes that the technology has been- built for practitioners, by practitioners, in-essence providing an emphasis on the company’s built-up process and technology development experiences in supporting various aspects of manufacturing and supply chain management needs of its over 250 existing customers, including some of the most complex yet highly recognized supply chains.

While the product was announced this week, the timetable for full functionality currently extends through the first-half of 2018. General availability of the InControl SaaS platform and applications begins in the third quarter, with various other elements planned for latter stages. Pricing is noted as a per-month/per application model with on-boarding, integration and implementation priced separately. Jabil’s go-to-market strategy includes its in-house supply chain, procurement, and professional services team, along with an external partnership with professional services firm PwC.

Included in our 2017 Predictions for Industry and Global Supply Chains was our belief that B2B network platform and managed services providers would provide enhanced supply chain focused analytics and intelligence capabilities, and Jabil’s InControl platform strategy and an existing example of that trend. The interesting twist for the market is the ability to select from either existing supply chain and manufacturing contract services providers, B2B network platform providers, or best-of-breed or ERP software providers. The ultimate decision for which partner will thus be highly dependent on individual business need, existing system landscape and future needs.

Our takeaway is that industry supply chain teams gain the benefits of added choices and of specific expertise, including that of actual on the ground practitioners.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.

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