{"id":2559,"date":"2020-11-25T10:40:49","date_gmt":"2020-11-25T10:40:49","guid":{"rendered":"https:\/\/davra.com\/?p=2559"},"modified":"2020-11-27T12:37:24","modified_gmt":"2020-11-27T12:37:24","slug":"davra-commentary-gartner-enterprise-iiot-critical-capabilities-2020","status":"publish","type":"post","link":"https:\/\/davra.com\/davra-commentary-gartner-enterprise-iiot-critical-capabilities-2020\/","title":{"rendered":"Davra Commentary: Gartner Enterprise IIoT Critical Capabilities 2020"},"content":{"rendered":"

Gartner has released their Magic Quadrant findings for 2020, and to supplement these findings, they also research 18 vendor\u2019s critical capabilities. The research is intended to aid organisations in their search for the best-matched IIoT vendor by assessing the vendors on a multitude of use cases and core IIoT functionality.\u00a0<\/span><\/p>\n

With up to 50% of industrial enterprises set to envelop IIoT in some way by 2024, it\u2019s imperative that you choose a reliable company to partner with. Gartner chose the four use cases to precisely match what the current needs are of industrial organisations:<\/span><\/p>\n

\u2022 Condition Monitoring: monitoring asset conditions in heterogeneous industrial organisations.<\/span><\/p>\n

\u2022 Connected Industrial Assets: an Industrial IoT platform deployed by an organisation that uses subsystems, modules and components that create large volumes of data.<\/span><\/p>\n

\u2022 Predictive Analytics for Equipment: IoT platforms that enable monitoring asset conditions and then using analytics to determine when the equipment needs repair and maintenance.\u00a0<\/span><\/p>\n

\u2022 Intermittently Connect Asset: the platform monitoring an intermittently connected asset to the cloud.\u00a0\u00a0<\/span><\/p>\n

The rated vendors must provide the core capabilities for an IIoT platform, including:<\/span><\/p>\n

\u2022 Device management,\u00a0\u00a0<\/span><\/p>\n

\u2022 Integration,<\/span><\/p>\n

\u2022 Data management,<\/span><\/p>\n

\u2022 Analytics,<\/span><\/p>\n

\u2022 Application enablement and management,<\/span><\/p>\n

\u2022 Security,<\/span><\/p>\n

\u2022 Ease of implementation and use,<\/span><\/p>\n

\u2022 Deployment options.<\/span><\/p>\n

Lists such as these propel organisations to do better; by gaining insights into where they can improve and how to strengthen the positive aspects of their company further.\u00a0<\/span><\/p>\n

2020 IIoT Magic Quadrant Highlights\u00a0<\/span><\/h1>\n

Companies dropped from the list: Accenture and Atos.\u00a0<\/span><\/p>\n

Companies added: AWS, Braincube, Microsoft, Samsung SDS<\/span><\/p>\n

Notable Vendors: Hitachi, Software AG, Davra, Litmus and Microsoft\u00a0<\/span><\/p>\n

The rankings are based on their total scores from the four use cases; condition monitoring, predictive analytics for equipment, connected industrial assets and intermittently connected assets.<\/span><\/p>\n

1. Hitachi\u00a0<\/strong><\/h2>\n

Hitachi is a formidable force when comparing them to last year\u2019s report; as their only downfall seems to be that they are still lagging on the device management front. Hitachi\u2019s Lumada platform is not only playing the industrial field, but they are also expanding into IoT platforms for building management with Microsoft\u2019s Azure. Due to Hitachi\u2019s sheer size, they are maintaining a stable position in these reports.\u00a0<\/span><\/p>\n

2. Microsoft\u00a0<\/strong><\/h2>\n

Microsoft is a new addition to the report and comes in with a high ranking. This year Microsoft acquired Israeli IoT security firm CyberX, so it comes as no surprise that they rank highly for their security components. They seem to be involved in many industries, from green- and brownfield sites to fleet management and automotive manufacturing, giving them that competitive edge.\u00a0<\/span><\/p>\n

3. Software AG<\/strong><\/h2>\n

With their code-free, fast-to-deploy workflows, services like Software AG\u2019s Cumulocity IoT platform should appeal to users that want to get up and running quickly. But according to the Critical Capabilities report, they lack in the ease of use and implementation. This should be taken into account for future scalability and deployment, but if they\u2019re seen as visionaries then perhaps they can figure it out as they go along!<\/span><\/p>\n

4. Altizon<\/strong><\/h2>\n

Altizon did considerably well in the critical capabilities report this year, as they\u2019ve worked on slight weaknesses such as their analytics by developing custom applications for their customers. They\u2019ve even created a new business intelligence suite called Datonis BI that integrates with their IIoT platform for data exploration and analysis.\u00a0<\/span><\/p>\n

5. Davra\u00a0<\/strong><\/h2>\n

Davra scored highly on the critical capabilities report, with the ease of implementation and use, deployment options and device management outshining many others on the list. Our analytics IoT attributes seemed to have swapped from strength to weakness over the last year, according to the list. We still highly value our ability to \u201cenable both predictive analytics and strong visualisation and dashboarding capabilities\u201d, according to last year\u2019s critical capabilities report. This year we also expanded our base by opening up a new office in Rome, to cater to our growing European customer base. Our logistics and fleet maintenance scores highly, which no doubt will stand out when all those COVID vaccines need to be shipped!\u00a0<\/span><\/p>\n

6. Litmus<\/strong><\/h2>\n

Despite being relatively new players to the field, Litmus is moving quickly up the rankings. They are becoming significant players in the rail and industrial areas, due to their offline capabilities and length of operations while being disconnected.\u00a0\u00a0<\/span><\/p>\n

7. IBM<\/strong><\/h2>\n

IBM has made slight positive moves in this year\u2019s magic quadrant, although they still score relatively low on the application enablement front, probably due to its sheer size. It hasn\u2019t been deployed in the intermittently connected asset side of the industry, which perhaps brought down its rating this year in the report.\u00a0<\/span><\/p>\n

8. Flutura<\/strong><\/h2>\n

Flutura is edging towards the leader\u2019s segment on the magic quadrant, and their analytics is powering them on ahead. No doubt their partnership with Hitachi is propelling them forward. Still, they need to work on their device management software to remain competitive in the oil and drilling industries.\u00a0\u00a0<\/span><\/p>\n

9. Qi0<\/strong><\/h2>\n

This neighbouring company is making moves in the right direction, as its PARCS digital twin framework is proving to be successful in the aviation industry. The company\u2019s product lines distinguish themselves by being built by industrial engineers and geared towards enterprises that want to undergo comprehensive digital transformations. They have also partnered with WWT to develop even more comprehensive solutions for their customers.\u00a0<\/span><\/p>\n

10. AWS<\/strong><\/h2>\n

AWS are a new entrant this year and have already scored exceptionally high on the magic quadrant, moving towards the challenger position. Similar to other service providers, they struggle to dig deep into providing core functionality because they are spread too thin. Still, they rank highly with security which will benefit those more considerable industrial assets, but analytics will need to be provided themselves by those companies.\u00a0<\/span><\/p>\n

11. Eurotech<\/strong><\/h2>\n

Eurotech\u2019s ability to execute may have dropped this year on the magic quadrant, but their digital twin models still hold fast. Their focus is on microservice architecture, but analytics functionality is letting them down, but hopefully, we can see them regain their positioning next year.\u00a0<\/span><\/p>\n

12. PTC<\/strong><\/h2>\n

PTC scored very highly this year on the Magic Quadrant, moving from a visionary into the leader position. Which by the way, I predicted in <\/span>last year\u2019s commentary post on the magic quadrant<\/span><\/a>!\u00a0 Despite scoring highly in the magic quadrant, they did not do so well in the critical capabilities report, with some customers stating the platform was difficult to use. PTC has become one of the few SaaS platform providers that blend computer-aided design with the cloud. Its CAD and physical modelling capabilities make ThingWorks a go-to for industrial players who build their hardware and products in-house.\u00a0<\/span><\/p>\n

13. GE Digital<\/strong><\/h2>\n

GE Digital also dropped a significant amount on this year\u2019s magic quadrant. Their response planning and on-premise systems strategy has brought down their ratings. Hopefully, GE can regain their digital transformation status soon and see to a speedy recovery.\u00a0<\/span><\/p>\n

14. Samsung SDS\u00a0<\/strong><\/h2>\n

Another newcomer, they have already entered into the magic quadrant as a steady niche player. They are doing well in the condition monitoring use case due to their security, data and device management strengths. Their lightweight AI model is being pushed to carry out analytics on even small devices.\u00a0<\/span><\/p>\n

15. Exosite<\/strong><\/h2>\n

Exosite\u2019s framework is highly adaptable, although they face challenges in the ease of use and analytics ratings. Gartner mentions that their strengths highlight they should work on their connected industrial assets use case, but that their integration and data management fails them here, so perhaps this is what they can aim to work on for next year.\u00a0<\/span><\/p>\n

16. Oracle<\/strong><\/h2>\n

Oracle is slowly moving towards leaders on the magic quadrant, but the critical capabilities report says otherwise. They do seem to be undertaking a more end-to-end IIoT approach now rather than a platform approach. Their ease of use is bringing down the ratings due to causing difficulties in condition monitoring and connected industrial assets.\u00a0<\/span><\/p>\n

17. ROOTCLOUD<\/strong><\/h2>\n

In the critical capabilities report, ROOTCLOUD is stated to have challenges in their analytics and security, meaning they couldn\u2019t score too highly in any of the use cases. They have, however, moved along in the magic quadrant, but they are adept in many industries and show capabilities in leveraging protocols so customers can manage their data and machines.\u00a0<\/span><\/p>\n

18. Braincube\u00a0<\/strong><\/h2>\n

Braincube is another new entrant, with a mostly cloud-based model, therefore not being able to support the critical capabilities laid out in this report entirely. They are around since 2007 and have a background in AI, which is most likely why they scored highly in the analytics section. They are well-established in the process and chemical manufacturing industries, where they help drive their business processes too.\u00a0<\/span><\/p>\n

 <\/p>\n

Although the likes of Siemens, Schneider or ABB did not make it to the magic quadrant this year, it is also difficult to say how this year could have gone due to the global pandemic, businesses switching their processes and following government restrictions. We also didn\u2019t see the entrance of ARM or C3IOT, but maybe next year! As 5G and other connectivity options continue to spur on the uptake, it will be the successful use case drivers that show the actual value of IIoT next year.\u00a0<\/span><\/p>\n

Author<\/strong><\/h2>\n

Brian McGlynn, Davra, COO<\/p>\n

Connect on LinkedIn<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Gartner has released their Magic Quadrant findings for 2020, and to supplement these findings, they also research 18 vendor\u2019s critical capabilities. The research is intended to aid organisations in their search for the best-matched IIoT vendor by assessing the vendors on a multitude of use cases and core IIoT functionality.\u00a0 With up to 50% of […]<\/p>\n","protected":false},"author":6,"featured_media":2560,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"yst_prominent_words":[140,2324,209,73,2299,187,183,188],"_links":{"self":[{"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/posts\/2559"}],"collection":[{"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/comments?post=2559"}],"version-history":[{"count":0,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/posts\/2559\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/media\/2560"}],"wp:attachment":[{"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/media?parent=2559"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/categories?post=2559"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/tags?post=2559"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/davra.com\/wp-json\/wp\/v2\/yst_prominent_words?post=2559"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}