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新技術のフォーカスグループ:機械学習の適用性を証明するオペレータ

Emerging Technologies Focus Group: Operators – Prove Machine Learning's Applicability

 

出版社 出版年月電子版価格 ページ数
Heavy Reading
ヘビーリーディング社
2018年5月US$3,495
エンタープライズライセンス(PDF)
12

サマリー

米国調査会社ヘビーリーディング社(Heavy Reading)の調査レポート「新技術のフォーカスグループ:機械学習の適用性を証明するオペレータ」は、機械学習に関する9つの質問から現在と今後の計画を明示した。その結果、サービスプロバイダが機械学習技術を統合するのはいつどこであるかを示したが、サービスプロバイダの機械学習の広範な導入は適用性が証明されるまでは停滞するだろう。

EXECUTIVE SUMMARY(PDF)

More than 80 percent of panelists on this month's Thought Leadership Council (TLC) say their service-provider organizations have either already or will deploy machine learning by the end of this year. And almost 60 percent of panelists say their company's understanding of machine learning is either excellent or good.

But almost 70 percent of those panelists also say that for machine learning to become mainstream, their companies must see proven case studies and applications in the market. As one panelist said, "The key word is mainstream. We need to bring machine learning out of the data scientist's offices and share it across the organization."

Indeed, almost 60 percent of panelists said the biggest obstacle machine learning faces is that there is no clear understanding of its applicability. As such, one panelist challenged machine-learning vendors, "Go to the mass-market/free development route in the next three years to develop more machine-learning ambassadors in the industries, and don't just limit your marketing efforts to the data analysts, scientists and Big Data practitioners."

TLC circumvents traditional industry hype to ascertain how service providers are really responding to important industry technologies and trends. What makes this initiative so unique is that participants discuss issues in a completely anonymous forum, enabling them to share insights and express business realities that otherwise could not be shared.

This focus group covered in Emerging Technologies Focus Group: Operators – Prove Machine Learning's Applicability was asked nine questions about machine learning to ascertain current and future plans, how well it's understood and influences impacting the technology. The results clearly indicate that service providers are integrating the technology when and where it's understood and most obviously applicable; however, widespread adoption of machine learning for service providers will lag until applicability is proven.

TLC members were asked to rate their company's general understanding of machine learning. Results are shown in the following excerpt. An equal number of panelists, 33 percent, said their companies have either a good or average understanding of machine learning; another 25 percent of panelists rated their company's understanding of machine learning as excellent.

Emerging Technologies Focus Group: Operators – Prove Machine Learning's Applicability is published in PDF format.



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プレスリリース

[プレスリリース原文]

Operators Begin Initial Forays Into Machine Learning

Heavy Lifting Analyst Notes
Denise Culver,
Online Research Director
5/1/2018
 

Almost 60% of service providers in this month's Thought Leadership Council (TLC) say machine learning will become a critical part of their company's network operations by 2020. Not surprisingly, perhaps, the majority of those service providers will use machine learning first in predictive maintenance.

In fact, 91% of panelists in the Council said machine learning is considered a critical technology in predictive maintenance. One provider explained that machine learning "is easily integrated into predictive maintenance because it takes advantage of automated pattern recognition and can be used to address [an] operator's biggest pain point: service-level degradation, which in turn helps prevent customer complaints and reduces churn."

Indeed, the message from service providers in this month's forum was clear: they believe machine learning can be a valuable asset, and they're finding small but interesting ways to apply it right now. For machine learning to gain more ground, however, developers have their work cut out, as revealed in the latest TLC report, Emerging Tech Focus Group: Operators -- Prove Machine Learning's Applicability. Council members were asked a series of nine questions about machine learning to ascertain current and future plans, how well it's understood and influences impacting the technology.

About half the panelists in this month's forum say their companies already have deployed machine learning, and several discussed ways in which it's already being deployed. One panelist explained how machine learning is being used by his company to boost sales in the international B2B market, where his company has a low win ratio due to several factors, including aggressive market competition, a variety of competitor products and a variety of customer needs in requests for proposal (RFP).

"Machine learning was used to capture the hidden patterns of lost and won bids and score the bids according to a classification algorithm," he said. It has been so successful that the company is now utilizing algorithm recommendations to determine the best way to sell standard products in the global market for MPLS, voice wholesale minutes, Internet and other similar products.

Despite these positive signs for machine learning's applicability, panelists were quick to point out that machine learning isn't always easy to understand or apply. More than half of panelists say the biggest obstacle machine learning faces is a lack of clear understanding in terms of how it can be applied.

As one panelist said, "There isn't a clear and consolidated experience regarding the concrete results that machine learning can provide."

TLC is a Heavy Reading research initiative that consists of panels of CSP experts focused on key areas of telecom development, including service assurance, SD-WAN, automation, 5G and IoT. Members participate in Q&A forums several times a year, and all information disclosed by Council members remains anonymous.

— Denise Culver, Director of Online Research, Heavy Reading

 

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