南加州大學(xué)機(jī)器視覺實(shí)驗(yàn)室

By Tom Davenport*

湯姆·達(dá)文波特*

Analytics are typically viewed as an exercise in data, software and hardware. However, if the analytics are intended to influence decisions and actions, they are also an exercise in organizational change. Companies that don’t view them as such are likely not to get much value from their analytics projects.

一個(gè) nalytics通常被看作是數(shù)據(jù)，軟件和硬件的練習(xí)。 但是，如果分析旨在影響決策和行動(dòng)，那么它們也是組織變革中的一項(xiàng)練習(xí)。 不這樣看的公司可能不會(huì)從他們的分析項(xiàng)目中獲得太多價(jià)值。

One organization that is pursuing analytics-based organizational change is Southern California Edison (SCE). A key focus of their activity is safety predictive analytics — understanding and predicting high-risk work activities by the company’s field employees that might lead to a life threatening and/or life altering incident causing injury or death. Safety issues, as you might expect, are fraught with organizational peril-politics, lack of transparency, labor relations, and so forth. Even reporting a close call runs counter to typical organizational cultures. These organizational perils are a concern to SCE as well, but the company has created an approach to address them. SCE hasn’t completely mastered safety predictive analytics and the requisite organizational changes, but it’s making great progress.

南加州愛迪生(SCE)是一個(gè)致力于基于分析的組織變革的組織。 他們的活動(dòng)的重點(diǎn)是安全預(yù)測(cè)分析-了解和預(yù)測(cè)公司現(xiàn)場(chǎng)員工的高風(fēng)險(xiǎn)工作活動(dòng)，這可能會(huì)導(dǎo)致生命危險(xiǎn)和/或改變生命的事故，從而導(dǎo)致人身傷亡。 如您所料，安全問(wèn)題充滿了組織的危險(xiǎn)政治，缺乏透明度，勞資關(guān)系等等。 甚至報(bào)告關(guān)閉呼叫都與典型的組織文化背道而馳。 這些組織風(fēng)險(xiǎn)也是SCE關(guān)心的問(wèn)題，但是公司已創(chuàng)建了一種解決方法。 SCE尚未完全掌握安全性預(yù)測(cè)分析和必要的組織更改，但正在取得巨大進(jìn)展。

A Structure for Analytical Change

分析變化的結(jié)構(gòu)

Key to the success of the SCE approach is the structure of the analytical team that is addressing safety analytics. It is small, experienced, and integrated. Two of the key members of the team are Jeff Moore and Rosemary Perez, and they make a dynamic combination. Moore is a data scientist who works in the IT function; Perez works in Safety, Security, and Business Resiliency, and is a “Predictive Analytics Advisor.” In effect, Moore handles all the analytics and modeling activities on the project, and Perez, who has many years of experience in the field at SCE, leads the change management activities.

SCE方法成功的關(guān)鍵是致力于安全分析的分析團(tuán)隊(duì)的結(jié)構(gòu)。 它體積小，經(jīng)驗(yàn)豐富且集成。 團(tuán)隊(duì)的兩個(gè)主要成員是Jeff Moore和Rosemary Perez，他們是一個(gè)充滿活力的組合。 Moore是從事IT職能的數(shù)據(jù)科學(xué)家。 Perez從事安全性，安全性和業(yè)務(wù)彈性方面的工作，并且是“預(yù)測(cè)分析顧問(wèn)”。 實(shí)際上，Moore負(fù)責(zé)處理該項(xiàng)目上的所有分析和建模活動(dòng)，而在SCE領(lǐng)域擁有多年經(jīng)驗(yàn)的Perez領(lǐng)導(dǎo)變更管理活動(dòng)。

Steps to manage organizational change started at the beginning of the project and have persisted throughout it. One of the first objectives was to explain the model and variable insights to management. Outlining the range of possible outcomes allowed Perez and Moore to gain the support needed for a company-wide deployment. Since Perez had relationships and trust in the districts, she could introduce the project concept to field management and staff without the concern about “Why is Corporate here?” Perez noted that it’s important to be transparent when speaking with the teams.

管理組織變更的步驟始于項(xiàng)目的開始，并貫穿于整個(gè)項(xiàng)目。 首要目標(biāo)之一是向管理人員解釋該模型和各種見解。 概述了可能的結(jié)果范圍后，Perez和Moore獲得了整個(gè)公司范圍內(nèi)部署所需的支持。 由于Perez在各地區(qū)之間擁有關(guān)系和信任，因此她可以將項(xiàng)目概念介紹給現(xiàn)場(chǎng)管理人員和員工，而不必?fù)?dān)心“為什么在這里有公司？” 佩雷斯指出，與團(tuán)隊(duì)交談時(shí)保持透明很重要。

That trust has resulted in the district staff’s willingness to listen and share their ideas on how best to deploy the model, to address missing variables and data, and to drive higher levels of adoption.

信任使地區(qū)工作人員愿意聽取并分享他們關(guān)于如何最好地部署模型，解決缺失的變量和數(shù)據(jù)以及提高采用率的想法。

The team took all the time needed to get stakeholders engaged. Moore came into the project in the summer of 2018, and he was able to get a machine learning model up and running in a month or so, but presenting it, socializing it, and gaining buy-in for it took far longer. Moore and Perez met with executives of SCE in November and December of 2018. Within days of these meetings the safety model analytics project became a 2019 corporate goal for SCE. Safety was the company’s number one priority, and it was willing to try innovative ideas to move it forward. For such a small team to have their work made into a corporate goal is unusual at SCE and elsewhere.

團(tuán)隊(duì)花了所有時(shí)間讓利益相關(guān)者參與。 Moore于2018年夏天加入該項(xiàng)目，他能夠在一個(gè)月左右的時(shí)間內(nèi)建立并運(yùn)行機(jī)器學(xué)習(xí)模型，但提出，社交化并獲得認(rèn)可需要花費(fèi)更長(zhǎng)的時(shí)間。 Moore和Perez于2018年11月和12月會(huì)見了SCE的高管。在這些會(huì)議的幾天內(nèi)，安全模型分析項(xiàng)目成為SCE的2019年企業(yè)目標(biāo)。 安全是公司的第一要?jiǎng)?wù)，它愿意嘗試創(chuàng)新的想法來(lái)推動(dòng)安全。 在SCE和其他地方，讓這么小的團(tuán)隊(duì)將他們的工作定為公司目標(biāo)是不尋常的。

The Risk Model

風(fēng)險(xiǎn)模型

SCE now has an analytical risk-based framework, and risk scores for specific types of work activities and the context of the work. The model draws from a large data warehouse at SCE with work order data, structure characteristics, injury records, experience and training, and planning detail. All those factors were not previously linked, and there was — as is often the case with analytics — considerable data engineering necessary to pull together and relate the data.

SCE現(xiàn)在具有一個(gè)基于風(fēng)險(xiǎn)的分析框架，以及針對(duì)特定類型的工作活動(dòng)和工作環(huán)境的風(fēng)險(xiǎn)評(píng)分。 該模型來(lái)自SCE的大型數(shù)據(jù)倉(cāng)庫(kù)，其中包含工單數(shù)據(jù)，結(jié)構(gòu)特征，傷害記錄，經(jīng)驗(yàn)和培訓(xùn)以及計(jì)劃細(xì)節(jié)。 所有這些因素以前都沒有關(guān)聯(lián)，并且(通常在分析中是這樣)有大量的數(shù)據(jù)工程需要整合在一起并關(guān)聯(lián)數(shù)據(jù)。

The machine learning model scores activities that teams in the field perform, like setting a new pole or replacing an insulator. Each activity may be more or less dangerous depending on the time of year, day of the week, weather, crew size and composition, and so forth. Replacing a pole, for example, may be only a moderate risk task in itself, but when done on the side of a hill in the rain with a crane it becomes very high risk.

機(jī)器學(xué)習(xí)模型對(duì)現(xiàn)場(chǎng)團(tuán)隊(duì)執(zhí)行的活動(dòng)進(jìn)行評(píng)分，例如設(shè)置新桿或更換絕緣子。 根據(jù)一年中的時(shí)間，一周中的某天，天氣，工作人員的人數(shù)和組成等，每種活動(dòng)可能或多或少具有危險(xiǎn)性。 例如，更換桿子本身可能只是一個(gè)中等風(fēng)險(xiǎn)的任務(wù)，但是當(dāng)在雨中的山坡上用起重機(jī)完成操作時(shí)，這將是非常高的風(fēng)險(xiǎn)。

Instead of generic safety messages to employees, SCE can now get much more specific by describing the risk of particular activities they perform on the job in a particular context.

現(xiàn)在，SCE可以通過(guò)描述員工在特定上下文中執(zhí)行的特定活動(dòng)的風(fēng)險(xiǎn)，而不是向員工發(fā)送一般性安全消息，從而變得更加具體。

As the model learns it will recommend specific approaches to reduce the risk of a job, like altering the crew mix or crew size, requiring additional management presence, using specific equipment or rigging to perform the work, or creating a longer power outage in order to do the job more slowly. The latter recommendation runs counter to the culture of not inconveniencing customers, but if the model specifically recommends it, then the teams will discuss the contributing factors as well as their years of experience to mitigate the risk before executing the work.

根據(jù)模型學(xué)習(xí)的知識(shí)，它將推薦降低工作風(fēng)險(xiǎn)的特定方法，例如更改人員組成或人員規(guī)模，需要額外的管理人員在場(chǎng)，使用特定設(shè)備或索具執(zhí)行工作，或造成更長(zhǎng)的停電以做得慢一點(diǎn) 后一種建議與不給客戶帶來(lái)麻煩的文化背道而馳，但是如果模型特別推薦，團(tuán)隊(duì)將在執(zhí)行工作之前討論影響因素以及他們多年的經(jīng)驗(yàn)以減輕風(fēng)險(xiǎn)。

The project has led to several more general findings, which are of greatest interest to SCE executives. For example, management has long been interested in using data to understand changing safety risk profiles of the field teams over time as a result of increasing/decreasing workloads or as weather patterns change. While the predictive model considers more than 200 variables, the findings from the model have been summarized into the top fifteen distinct drivers of serious injury and fatality. Some shifting of variables is expected over time, but there has been great interest in better understanding the initial set of risk factors.

該項(xiàng)目帶來(lái)了一些更普遍的發(fā)現(xiàn)，這是SCE高管最感興趣的。 例如，長(zhǎng)期以來(lái)，管理層一直對(duì)使用數(shù)據(jù)來(lái)了解隨著工作量的增加/減少或天氣模式的變化而導(dǎo)致現(xiàn)場(chǎng)團(tuán)隊(duì)的安全風(fēng)險(xiǎn)概況發(fā)生變化的興趣。 盡管預(yù)測(cè)模型考慮了200多個(gè)變量，但該模型的發(fā)現(xiàn)已匯總為嚴(yán)重傷害和死亡的前15個(gè)不同驅(qū)動(dòng)因素。 預(yù)計(jì)隨著時(shí)間的推移，變量會(huì)發(fā)生一些變化，但是人們對(duì)更好地了解最初的風(fēng)險(xiǎn)因素非常感興趣。

Deploying the Model

部署模型

Moore and Perez are in the early stages of deploying the model; they’ve rolled it out to six of 35 districts thus far. Each district has a unique personality, and they don’t want cookie-cutter answers on how to deploy in their district.

Moore和Perez處于模型部署的早期階段； 到目前為止，他們已將其推廣到35個(gè)地區(qū)中的六個(gè)地區(qū)。 每個(gè)地區(qū)都有獨(dú)特的個(gè)性，他們不希望獲得有關(guān)如何在自己的地區(qū)中部署的答案。

Moore, whose primary role was to create the model, said he has realized that safety analytics are not just about a model. “I started out thinking it was about an algorithm, but I realized many other factors were involved in improving safety.” Moore said that he gets some pressure to move on to analytics in other parts of the business, but “in order to see your models come to life you have to go through this kind of process.” And everyone at SCE believes the safety work is critical.

摩爾主要負(fù)責(zé)創(chuàng)建模型，他說(shuō)，他已經(jīng)意識(shí)到安全分析不僅是模型。 “我開始以為這是一種算法，但我意識(shí)到提高安全性還涉及許多其他因素。” 摩爾說(shuō)，他承受著轉(zhuǎn)移到業(yè)務(wù)其他部門的分析工作的壓力，但是“為了使您的模型變得栩栩如生，您必須經(jīng)歷這種過(guò)程。” SCE的每個(gè)人都認(rèn)為安全工作至關(guān)重要。

Perez, whose primary focus is change management, listed some of the organizational changes in deployment. “There might be training issues — not only on analytics, but also communication, leadership and ownership. There might be process concerns--how we plan and communicate work. There may be technology concerns in using the system.”

Perez主要關(guān)注變更管理，列出了部署中的一些組織變更。 “可能存在培訓(xùn)問(wèn)題，不僅涉及分析，還涉及溝通，領(lǐng)導(dǎo)力和所有權(quán)。 可能存在過(guò)程問(wèn)題-我們?nèi)绾斡?jì)劃和溝通工作。 使用該系統(tǒng)可能會(huì)涉及技術(shù)問(wèn)題。”

Perez also says the process of working with a district is critical. “You can’t just walk into a district and disrupt their work flow for no reason,” she says. “They want to know your purpose and your objective. We try to connect, show transparency, and build trust that we are here to help, that we are here to observe how they mitigate risk, to share our findings, and to see how the findings might be integrated into their work practices. We hope they will help us understand the complexity they face every day.”

佩雷斯還表示，與地區(qū)合作的過(guò)程至關(guān)重要。 她說(shuō)：“您不能無(wú)故無(wú)故走進(jìn)一個(gè)地區(qū)破壞他們的工作流程。” “他們想知道您的目的和目標(biāo)。 我們?cè)噲D建立聯(lián)系，表現(xiàn)出透明度并建立信任，我們將在這里幫助您，我們?cè)谶@里觀察他們?nèi)绾螠p輕風(fēng)險(xiǎn)，分享我們的發(fā)現(xiàn)，并了解如何將發(fā)現(xiàn)整合到他們的工作實(shí)踐中。 我們希望他們能幫助我們了解他們每天面臨的復(fù)雜性。”

Both team members say they learn something every time they visit a district. Moore notes, “You can only see the data you can see in the data warehouse — time sheets, work orders, etc. But when you talk to the people who do the work, you learn a lot about how the data is created and applied.

兩位團(tuán)隊(duì)成員都說(shuō)，他們每次訪問(wèn)某個(gè)地區(qū)都會(huì)學(xué)到一些東西。 Moore指出：“您只能看到可以在數(shù)據(jù)倉(cāng)庫(kù)中看到的數(shù)據(jù)-時(shí)間表，工作單等。但是，當(dāng)與工作人員交談時(shí)，您會(huì)學(xué)到很多有關(guān)如何創(chuàng)建和應(yīng)用數(shù)據(jù)的知識(shí)。 。

With each visit I understand the drivers better and the complexity of the work. I can also speak the language better with each district visit, and I understand the process and the equipment better as well.”

每次訪問(wèn)我都會(huì)更好地了解驅(qū)動(dòng)程序以及工作的復(fù)雜性。 每次訪問(wèn)地區(qū)時(shí)，我也可以說(shuō)更好的語(yǔ)言，而且我也更好地了解過(guò)程和設(shè)備。”

With the findings from the model, Moore and Perez are beginning to work with another partner at SCE — the HR organization. It is responsible for defining work practices, training needs, standard operating procedures, and job aids. Each of these is potentially influenced by findings about safety risks, so the goal is to incorporate analytical results into the practices and procedures.

根據(jù)模型的發(fā)現(xiàn)，摩爾和佩雷斯開始與SCE的另一個(gè)合作伙伴-人力資源組織合作。 它負(fù)責(zé)定義工作實(shí)踐，培訓(xùn)需求，標(biāo)準(zhǔn)操作程序和工作輔助工具。 所有這些都可能受到有關(guān)安全風(fēng)險(xiǎn)的調(diào)查結(jié)果的影響，因此目標(biāo)是將分析結(jié)果納入實(shí)踐和程序。

The team is already working to modify the model to incorporate new factors-one of which, not surprisingly given the situation in California, involves the risk of wildfires. Moore and Perez are also trying to create more integration of the risk scores with the work order system. They also plan to try to incorporate the risk model into other SCE business functions like Engineering, which might be able to lower the risk in the planning and construction of the electric grid. All in all, using data and analytics to improve safety is a time-consuming and multifaceted process, but what could be more important than reducing injury and fatality among SCE employees and work crews?

該小組已經(jīng)在努力修改模型以納入新的因素，考慮到加州的情況，其中之一涉及野火的風(fēng)險(xiǎn)就不足為奇了。 Moore和Perez也在嘗試將風(fēng)險(xiǎn)評(píng)分與工作單系統(tǒng)進(jìn)行更多集成。 他們還計(jì)劃嘗試將風(fēng)險(xiǎn)模型納入其他SCE業(yè)務(wù)功能(如工程)，這可能能夠降低電網(wǎng)規(guī)劃和建設(shè)中的風(fēng)險(xiǎn)。 總而言之，使用數(shù)據(jù)和分析來(lái)提高安全性是一個(gè)耗時(shí)且多方面的過(guò)程，但是與減少SCE員工和工作人員的傷害和死亡相比，還有什么更重要的呢？

*Originally published July 30, 2020 at https://www.forbes.com.

*最初于2020年7月30日發(fā)布在 https://www.forbes.com上 。

Tom Davenport is the President’s Distinguished Professor of IT and Management of Babson College, a Digital Fellow at the MIT Initiative on the Digital Economy, and a Senior Advisor to Deloitte’s Analytics and Cognitive practice.

湯姆·達(dá)文波特(Tom Davenport)是巴布森學(xué)院(Babson College)的IT與管理學(xué)系總裁，是麻省理工學(xué)院數(shù)字經(jīng)濟(jì)倡議的數(shù)字研究員，也是德勤分析與認(rèn)知實(shí)踐的高級(jí)顧問(wèn)。

翻譯自: https://medium.com/mit-initiative-on-the-digital-economy/machine-learning-spurs-change-at-southern-california-edison-63d168ca28f

南加州大學(xué)機(jī)器視覺實(shí)驗(yàn)室

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