Honeywell Survey: Data analytics investment on the rise

霍尼韋爾調(diào)查：數(shù)據(jù)分析投資在上升

A recent survey of manufacturing executives indicates many respondents (67 percent) are pressing ahead with plans to invest in data analytics even as they pare back spending in other areas to combat tough business conditions.

最近一項(xiàng)針對(duì)制造業(yè)高管的調(diào)查顯示，多數(shù)受訪者（67％）正加緊計(jì)劃投資數(shù)據(jù)分析，即使他們?cè)谙鳒p其他方面的支出以應(yīng)對(duì)極具挑戰(zhàn)的經(jīng)營(yíng)環(huán)境。

The reason: Many say they view data analytics – a key component of the Industrial Internet of Things (IIoT) – as a viable solution to a cycle of problems that lead to downtime and lost revenue.

原因是：不少人表示，數(shù)據(jù)分析作為工業(yè)物聯(lián)網(wǎng)（IIoT）的關(guān)鍵組成部分，他們認(rèn)為這是應(yīng)對(duì)導(dǎo)致停機(jī)及收益受損等一系列問(wèn)題行之有效的解決方案。

More than 200 North American manufacturing executives took part in the survey titled “Data’s Big Impact on Manufacturing: A Study of Executive Opinions.” The survey was jointly conducted by Honeywell Process Solutions (HPS) and KRC Research Inc., from May 23 to June 8, 2016.

200多名北美制造領(lǐng)域高管參加了這個(gè)題為“數(shù)據(jù)對(duì)制造業(yè)的大影響：管理者觀點(diǎn)研究”的調(diào)查，活動(dòng)由霍尼韋爾過(guò)程解決方案和KRC Research公司聯(lián)合開(kāi)展，時(shí)間從2016年5月23日至6月8日。

“Executives need to keep their businesses running smoothly and safely, and they’re banking on IIoT technologies to help navigate challenges, even during cash-strapped times,” said Andrew Hird, vice president and general manager, HPS Digital Transformation. “The IIoT by Honeywell is the next step in that evolution.”

“管理者需要保持業(yè)務(wù)的平穩(wěn)和安全運(yùn)行，即便是在現(xiàn)金緊張時(shí)候，他們也投資工業(yè)物聯(lián)網(wǎng)技術(shù)以應(yīng)對(duì)挑戰(zhàn)，” 霍尼韋爾過(guò)程控制部數(shù)字化轉(zhuǎn)型業(yè)務(wù)副總裁兼總經(jīng)理Andrew Hird說(shuō)道。“霍尼韋爾工業(yè)物聯(lián)網(wǎng)方案正是實(shí)現(xiàn)這個(gè)演變的下一步舉措。”

Among other key findings of the survey:

•    Some companies are feeling pressure to continue working under the threats of unscheduled downtime and equipment breakdowns, which are viewed the most detrimental to maximizing revenue.

•    The majority of companies say they are already investing in data analytics technology.

•    More than a quarter said they don’t plan to invest in data analytics in the next year; of that group, not understanding the benefits of data analytics and inadequate resources are among the most cited reasons for this lack of investment.

該調(diào)查的其它主要發(fā)現(xiàn)包括：

•    一些公司面臨在意外停機(jī)及設(shè)備故障的威脅下不得不繼續(xù)運(yùn)營(yíng)的壓力，而這些因素正是擴(kuò)大收益的最大障礙。

•    大多數(shù)公司表示它們已經(jīng)開(kāi)始對(duì)數(shù)據(jù)分析技術(shù)進(jìn)行投資。

•    超過(guò)25%的受訪者表示在未來(lái)一年不打算對(duì)數(shù)據(jù)分析進(jìn)行投資，他們給出的大部分原因，主要是不了解數(shù)據(jù)分析所帶來(lái)的好處以及資源不足。

A Tough Cycle of Downtime

艱難的停機(jī)周期

Unscheduled downtime was ranked as the top threat to maximizing revenue, but 42 percent of respondents admitted to running equipment harder than they should. When asked how often their companies experienced a list of issues in recent years, 71 percent of respondents said they experienced equipment breakdowns at least occasionally, while 64 percent said the same for unscheduled downtime.

意外停機(jī)是收益最大化的最大威脅，但有42%的受訪者承認(rèn)其設(shè)備超負(fù)荷運(yùn)行。當(dāng)被問(wèn)及近年來(lái)出現(xiàn)一系列問(wèn)題的頻率時(shí)，71%的受訪者表示至少偶爾會(huì)出現(xiàn)設(shè)備故障，64%的受訪者表示出現(xiàn)過(guò)同樣頻率的意外停機(jī)。

“Running plant equipment harder than appropriate presents a host of issues ranging from equipment breakdowns to potential safety incidents,” said Hird. “Those issues inevitably lead to more downtime, which leads back to lost revenue. It’s easy to see how many companies feel they’re caught in a vicious cycle. Predictive analytics achieved through an effective solution can help companies break out of that cycle.”

Hird 表示：“工廠設(shè)備超負(fù)荷運(yùn)行會(huì)帶來(lái)設(shè)備故障、潛在安全事故等一系列問(wèn)題。這些問(wèn)題無(wú)可避免地會(huì)導(dǎo)致更多的停機(jī)時(shí)間，從而造成營(yíng)收損失。很明顯，很多企業(yè)覺(jué)得他們陷入了一個(gè)惡性循環(huán)。通過(guò)一個(gè)有效的解決方案來(lái)實(shí)現(xiàn)預(yù)測(cè)性分析可以幫助企業(yè)打破這種循環(huán)。”

Forty percent ranked unscheduled downtime as the biggest threat to maximizing revenue. Other threats included:

•    Supply chain management issues (39 percent)

•    Inadequate staffing (37 percent)

•    Off-spec products (36 percent)

•    Equipment breakdowns (32 percent)

40%的受訪者認(rèn)為意外停機(jī)是收益最大化的頭號(hào)威脅。其他威脅包括：

•    供應(yīng)鏈管理問(wèn)題（39%）

•    人員配備不足（37%）

•    產(chǎn)品不合格（36%）

•    設(shè)備故障（32%）

Data Analytics as a Viable Solution

數(shù)據(jù)分析是可行的解決方案

Data analytics is a key component of a successful IIoT implementation for manufacturers. Most respondents had favorable views of the benefits of data analytics as a solution. For example, the executives said they agreed big data analytics can reduce the occurences of:

•    Equipment breakdowns (70 percent)

•    Unscheduled downtime (68 percent)

•    Unscheduled maintenance (64 percent)

•    Supply chain management issues (60 percent)

數(shù)據(jù)分析是制造商成功實(shí)施工業(yè)物聯(lián)網(wǎng)的關(guān)鍵組成部分。大多數(shù)受訪者對(duì)數(shù)據(jù)分析作為解決方案所帶來(lái)的收益持積極態(tài)度。比如，高管們表示大數(shù)據(jù)分析能夠降低以下問(wèn)題的發(fā)生頻率：

•    設(shè)備故障（70%）

•    意外停機(jī)（68%）

•    非計(jì)劃維護(hù)（64%）

•    供應(yīng)鏈管理問(wèn)題（60%）

Respondents said they believe data can enable well-informed decisions in real time (63 percent), limit waste (57 percent), and predict the risk of downtime (56 percent).

受訪者表示，他們相信數(shù)據(jù)有助于其獲得必要的信息并實(shí)時(shí)做出正確決定（63%），減少浪費(fèi)（57%），并預(yù)測(cè)停機(jī)風(fēng)險(xiǎn)（56%）。

“It’s easy to put that puzzle together – these executives correctly believe data analytics can help them combat the biggest threat they see to business: unscheduled downtime,” Hird said. “This is why they feel it makes sense to continue investing.”

Hird 說(shuō)道：“道理很簡(jiǎn)單，這些高管明白數(shù)據(jù)分析能夠幫助他們應(yīng)對(duì)業(yè)務(wù)運(yùn)營(yíng)所面臨的頭號(hào)威脅：意外停機(jī)。所以他們覺(jué)得有必要繼續(xù)投資。”

Additionally, more than two-thirds of respondents (68 percent) said they are currently investing in data analytics, and 50 percent said they believe their companies are right on track in their use of data analytics. Fifteen percent said they believe their companies are ahead of the curve as it relates to data analytics usage.

此外，超過(guò)三分之二的受訪者（68%）表示，他們目前正在對(duì)數(shù)據(jù)分析進(jìn)行投資，而50%的受訪者相信他們所在的公司已經(jīng)在數(shù)據(jù)分析使用方面步入了正軌。15%的受訪者表示，其公司在數(shù)據(jù)分析使用方面走在了行業(yè)前列。

Not Everyone is Sold

并非人人付諸行動(dòng)

While the majority of respondents said they are already investing and/or planning to increase their investments in data analytics in the coming year, 32 percent said they are not currently investing in data analytics. Meanwhile, 33 percent said their companies are not planning to invest in data analytics in the next 12 months, or are unaware of any plans to do so.

盡管大多數(shù)受訪者表示正在進(jìn)行或計(jì)劃在明年增加數(shù)據(jù)分析方面的投資，但仍有32%的受訪者表示目前沒(méi)有對(duì)數(shù)據(jù)分析進(jìn)行投資，33%的受訪者表示未來(lái)一年公司沒(méi)有數(shù)據(jù)分析方面的投資計(jì)劃，或者不知道這方面有什么計(jì)劃。

Of those who currently have no plans to invest:

•    61 percent believe their organizations already have systems in place to ensure safety, yield and success

•    45 percent said their companies have seen some growth without data analytics

•    42 percent said they don’t fully understand the benefits of big data

•    35 percent believe people are overstating the benefits of big data

目前沒(méi)有投資計(jì)劃的受訪者中：

•    61%的人認(rèn)為現(xiàn)有的架構(gòu)系統(tǒng)能夠確保安全性、保證產(chǎn)量，并獲得成功

•    45%的人表示在沒(méi)有數(shù)據(jù)分析的情況下他們公司依然實(shí)現(xiàn)了一定增長(zhǎng)

•    42%的人表示他們對(duì)大數(shù)據(jù)的好處不甚了解

•    35%的人表示人們夸大了大數(shù)據(jù)所能帶來(lái)的好處

Sixty-three percent of respondents who said they have no investment plans indicated they just don’t have the resources to appropriately do so, while 39 percent said they don’t have the right staff to make the most of data analytics.

在沒(méi)有投資計(jì)劃的受訪者中，63%的受訪者表示他們沒(méi)有這方面的合適資源，而39%的受訪者則表示他們沒(méi)有讓數(shù)據(jù)分析發(fā)揮最大作用的合適人才。

“For some companies, hurdles remain before the IIoT can be fully adopted,” explained Hird. “Some don’t believe they need it while others say they lack the resources to do it right. The good news is that IIoT is something that doesn’t require a wholesale change – it can be phased and scaled depending on an individual company’s circumstances. This is precisely why Honeywell says IIoT represents an evolution, not a revolution.”

“對(duì)于一些公司來(lái)說(shuō)，部署工業(yè)物聯(lián)網(wǎng)仍然存在著一些障礙，” Hird 解釋道。“有些認(rèn)為他們并不需要，另外一些則表示缺少合適的資源。好消息就是，工業(yè)物聯(lián)網(wǎng)并不需要企業(yè)大規(guī)模的改變——它可以根據(jù)各個(gè)公司的具體情況分階段實(shí)施和擴(kuò)展。這也正是霍尼韋爾將工業(yè)物聯(lián)網(wǎng)稱為一個(gè)演變，而不是變革的原因。”