有一个说法：“得到的测量完成了。”

考虑到这一点，难怪大多数行业，从食品安全到航空旅行再到汽车制造业，都在创建指标来衡量其业务活动方面进行大量投资。但是，并非所有指标都是平等的。最成功的以数据为中心的指标驱动的公司正在更深入研究，确定关键绩效指标对成功结果至关重要。 For most industries, determining the KPIs that drive profitability isn’t a herculean task. Why is it such a challenge for construction? 

答案非常简单：交易的经典工具不适合这份工作。建筑的性质阻止了我们在其他行业中看到的加速技术。传统上，工作场所不是技术的友好场所。

移动技术是解决方案

建筑行业越来越多，现在正在捕获建立KPI所需的关键数据。现在的挑战是如何分析数据，因为并不总是清楚要专注于哪个指标或要拍摄的指标。 

For most digitally-savvy companies — and even entire industries — benchmarks are plentiful and provide the critical context needed to analyze measurements. Essentially, benchmarks are useful tools for making better sense of the world. For example, as a contractor or subcontractor, do you really know how your average number of safety issues per project compares to your competitors?

基准有助于指示此数字是高还是低。建筑业对安全问题的基准为基准，称为体验修饰率。在雇用总承包商之前，所有者可以检查出价的各种公司的EMR，并决定雇用谁。

现在，由于持续的数字化转型以及从项目生命周期各个部分收集数据的能力，该行业是否应该超越EMR？  

每个人都说同样的语言吗？ 

如果建立基准测试的第一步是数据收集，则下一步是数据标准化。执行副总裁兼首席数据官Jit Kee Chin博士萨福克, has spent her career studying data. 

According to Jit Kee, “the challenge in construction has been that the systems – and the data in the different systems – are not interoperable. That makes it very difficult to cross-compare things.”

Jit Kee notes the other aspect around data standardization and quality has to do with the fact that the construction industry hasn’t settled on standards and performance, nor are companies eager to share their data with the industry.

In the same way other industries have, over time, come together to define acceptable metrics, so, too, should construction.

AKPI的最新研新利luck究– performed by Dodge Data & Analytics andcommissioned by Autodeskidentified seven main process categories where companies should be collecting data and seeing how their performance stacks up.  

公司collecting data in these areas — including but not limited to, capturing errors and omissions discovered in documents; collecting and documents change orders; usage of technology for quality and close out — and companies can learn from this and grow from project to project. For example, how many RFIs are acceptable before they become an excessive drag on project performance? How many RFIs do peer companies have on projects of a similar type and size? If productivity turns out to be one of the key factors that drives schedule, then what factors can companies effectively zero in on to really measure productivity? 

Reaching agreements around the terms used in KPI categories – what officially counts as an “inspection technology,” or a “labor productivity factor?” – will clarify what data needs to be collected to provide meaningful answers and offer the ability to create universal benchmarks across the construction industry. 

公司可能有一天能够在与客户见面并竞标其下一个项目时充分利用该数据。将RFP列表列出“每个项目的平均变更订单数”或“平均建筑文档错误数量”为所有者提供了更好的信息，可以在其决定基础上进行决定，同时为承包商提供宝贵的卖点。 

前方的道路上有数据 

Some construction companies are well on their way to digitizing their processes and working with their data, while others are just getting started. But all companies, regardless of where they are on this spectrum, should pay attention to classifying and structuring their data moving forward around a commonly agreed terminology. 

对于所有者和总承包商来说，好处都令人信服，无法忽略：令人兴奋的新数据驱动的数字增强结构时代正在到来！

Jim Lynch is vice president and general manager of Autodesk Construction Solutions, where he leads Autodesk’s efforts to create and deliver products and services which provide the foundation for a digital construction workflow. In his more than 20-year tenure with Autodesk, Jim has held a variety of leadership roles.