Doug Slater 09月30日 19:08
科技风险如何影响商业指标
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科技风险是企业的重要商业问题。文章解释了如何将科技风险(如代码债务、过时软件等)转化为商业指标(如收入和利润)。通过映射技术风险到业务指标,技术人员可以更有效地说服公司解决技术问题。文章提出了三个步骤:识别业务指标、识别技术风险、将技术风险映射到业务指标。这种量化方法有助于企业理解技术债务的潜在成本,从而做出更明智的决策。

💼 企业通常优化业务指标,如收入和利润。技术问题若没有预期对底线的影响,领导层会优先考虑其他资本化工作。技术债务的痛苦在于量化它,以及资源似乎有更有利可图的用途。

🔍 识别业务指标:了解企业跟踪的指标,通常是“赚更多钱”或“花更少钱”的具体实例。例如,食品分销商需要采购、存储、处理和包装食物,并快速分发,最终影响净利润。

⚠️ 识别技术风险:技术风险是企业依赖的、可能产生意外成本的技术,如有缺陷的内部代码库、过时的软件、过期的服务器支持窗口和复杂的架构。质量与风险相关:高质量软件的漏洞较少,更容易更改。

📊 映射技术风险到业务指标:每个风险可能导致一个或多个危害,每个危害都可能给企业带来成本。例如,患者数据库的安全漏洞可能导致品牌声誉受损,进而影响销售漏斗转化率和客户流失率。

🔑 通过将技术风险与业务成本联系起来,技术人员可以更有效地说服公司解决技术问题。如果无法将技术风险与有意义的业务成本联系起来,则应接受它不是商业优先事项。

Tech risk is a business concern. Instead of vaguely bemoaning "tech debt" and hoping to "do things right", explain its potential costs with words the business understands.

Tech Risks mapped onto Business Metrics

Introduction

5 months ago, Reddit user Agent_Aftermath posted in /r/AskProgramming:

Why are so many companies so ambivalent or uncommitted to addressing tech-debt?

I think most engineers can empathize with this problem. We've all worked in codebases or infrastructures that smelled worse than a dirty diaper while our organization seemed unmoved or even resisted remediation.

The responses enumerated the many disincentives for addressing tech debt and presented only a few tenuous solutions. The top response succinctly captures the diagnosis:

It is more difficult to quantify the value of addressing tech debt as opposed to creating a new feature. --oofy-gang

The problem is not that tech debt is not real, nor that addressing it is frivolous. The pain lurks in quantifying it and that there are apparently more profitable uses of resources.

Note that for the rest of this article, I will use the term tech risk instead of tech debt. Why: In short, unlike mortgages, quality issues exact repayment suddenly and unpredictably. You can read my more detailed explanation here.

What a Business Values

Boardrooms always optimize for business metrics, and in capitalism, all business processes reduce to revenue and profit*. If technical issues have no anticipated effect on the bottom line, then leadership will readily prioritize other capitalizable work.

It would be ludicrous for a CTO to stand up in a board meeting and declare, "I'm happy to share that engineering has closed all open bugs in the backlog." This statement conveys no meaning to the board. It is unactionable techno-babble. Rather, the CTO knows to translate to business-speak: "I'm happy to share that this quarter we'll able to deploy 100% of our resources to new feature development, and because of this efficiency we will not renew our offshore QA contract, saving $3M over last quarter."

The key word above is anticipated. There is high-quality research[1] and literature[2] demonstrating that internal tech quality is a business concern after all. Indirectly, the board does care about the engineering backlog, because engineering is a business unit, and business units cost or earn money.

Let's now focus on how you, a technical person, can present engineering concerns as business concerns. I have distilled your task into three steps:

    Identify business metricsIdentify tech risksMap tech risks onto business metrics

* Funded startups, nonprofits, and businesses with philanthropic goals may have more nuanced motives than just net profit.

Identify Business Metrics

If you're not sure what metrics your business is tracking, ask. They will usually be instantiations of "make more money" or "spend less money". However, revenues and profit may be linked to business processes with second-order metrics and performance indicators. For example, a food distributor must:

The overall business metric "net profit" will be a complex result of its many business processes.

Identify Tech Risks

A tech risk is a technology that a business depends on that could have unexpected costs. Examples include a buggy internal codebase, outdated software[3], servers past their vendor support window, and overcomplicated architectures. Quality is correlated with risk: high-quality software has less bugs and is easier to change.

These risks can cause events which negatively affect business metrics. For example:

An FMEA[4] is helpful for prioritization, i.e. to decide which risks most merit mitigation. In this style of risk analysis, the risk is quantified in terms of its probability of occurrence and severity of the harm it could cause. You won't be able to fill in the severity column until you've completed the mapping to business metrics below.

Tech RiskProbability of OccurrenceSeverity of Harm
Security flaw in shipment DB1%Low. Low-value shipment data exfiltrated
Security flaw in patient DB1%Severe. Protected Health Information exfiltrated
Server disk fails10% after 5 yearsModerate. Production interrupted 1 day

Map Tech Risks onto Business Metrics

Each risk presents one or more harms, each of which can realize cost to the business. Sometimes the path to a business metric will traverse one or more business processes. For example, it may not be immediately apparent how a damaged brand reputation can affect revenues, but a reduced sales funnel conversion rate will directly impact the bottom line.

EventBusiness Metric Impacted
Low-value shipment data exfiltratedNone; who cares?
Protected Health Information exfiltratedBrand reputation damaged → Sales Funnel Conversion % (fewer new customers)
Protected Health Information exfiltratedBrand reputation damaged → Churn (customers leave)
Production interrupted 1 dayCan’t fulfill committed sales → 1% loss of quarterly revenue

Step back for a second and compare the items on the left and right. The CEO's eyes may glaze over at the annual HIPAA training, but connecting a PHI breach convincingly to the company's sales conversion rate will make them listen.

Conversely, if you can't meaningfully associate a tech risk with a business cost, then you should accept that it is not a business priority. In the example above, we don't need to prioritize hardening the shipment DB.

Conclusion

To convince your company to address "tech debt", map from tech risks to business metrics. Be prepared to discover that some tech risks don't matter.

Next...

Subscribe to my email list below. I plan to write more.

References

    Code Red: The Business Impact of Code QualityAccelerate: The Science of Lean Software and DevOpsEnd-of-life (EOL)Failure Mode and Effects Analysis

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科技风险 业务指标 技术债务 量化分析 企业决策
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