专注于技术和紧密的反馈循环产生创造性的解决方案

Innovation leads the way as 365bet体育在线注册官网 seeks to solve the big issues facing the freight industry.

迈克尔·森弗特伯对蜂巢活动的第一印象 365bet体育在线注册官网 是他不会很快忘记的吗.

“I was sitting on the brokerage floor with all of the brokers who are trying to connect freight from shippers to the right carriers, 它令人兴奋，节奏也快,”他记得. It was 2019 and Senftleber was on the floor as a consultant to help identify ways to improve the company’s logistics supply chain workflow. But the challenge was so invigorating that he eagerly embraced the opportunity to lead the charge to evolve the way Arrive serves its partners. “有太多的创新机会.”

Michael Senftleber，首席技术官

现任公司首席技术官, Senftleber is focused on building a true technology organization within 365bet体育在线注册官网.

“We have product managers, UX designers and engineers,” Senftleber said. “We’re not just taking requirements and handing them off to an engineer. 我们的目标是解决真正的商业问题.”

这样做, Arrive’s tech function has grown to more than 150 people who make up 12 product teams, including outputs that support their in-house brokers as well as external shippers and carriers.

随着公司持续快速扩张, Senftleber, Senior Software Engineer Julia Brown and VP of Carrier Strategy Blair Blake shared with Built In Austin what new team members can expect.

How has Arrive’s business model evolved to become more tech-integrated?

布莱尔·布莱克，Carrier Strategy的副总裁

布雷克: Arrive started at the logistics load level by creating relationships between shippers and carriers. We would bring in demand and our brokers would source available capacity through phone calls. We still believe t在这里’s a necessity to build relationships and provide this best-in-class service, but now we’ve added the ability to be interconnected with our internal teams and our external partners through technology. 例如, 通过我们的载体门户, we’re able to help a driver whose load was cancelled on a Saturday night locate a new booking option on the spot.

布朗: We also went from using a third-party system that tracked loads to building our own that we could control end-to-end and collect data to power our machine learning pricing models. Now, we have all this data and we’re figuring out how to use it to provide a good user experience.

What are some of the engineering philosophies and practices that Arrive’s team runs on?

Senftleber: 我们不是在冲压小部件. 这是一条技术创新的道路. 我们正在用产品的思维方式解决真正的问题. 我们有一种授权的观念，即这里没有人是接受命令的人. 相反，我们的团队拥有一个产品. 他们与产品共存并维护它. 这允许团队深入了解他们的专业领域. 我们不认为工作是在当天完成某件事. We think more about what we can do today to make it better in the long term.

布雷克: 在我们真正推出产品或技术解决方案之前, 我们通过用户验收测试并验证所有内容. We encourage drivers and carriers to give us feedback through various channels and beta tests. 然后，我们再次通过内部流程进行迭代. It’s our belief that we are not trying to build on the assumption of what our carriers and customers want. We’re talking with them to make sure we’re building according to their needs.

布朗: This tight feedback loop is a lot more interesting than other positions I’ve held

Julia Brown，高级软件工程师

because it allows us to work faster and receive instantaneous feedback. This is the first time I’ve worked somew在这里 w在这里 a large portion of our users are colleagues. 我可以去另一栋大楼看他们使用我们的产品, 是什么影响了我们的技术决策. 我们可以更清楚地看到他们的痛点是什么.

是什么让这项工作对工程师有吸引力? 

Senftleber: You get to see in person how someone is interacting with what you’re building. This allows our engineers to understand how our users are interacting with it, 它是如何达到预期目的的, if they are enjoying it and if it’s actually addressing their problem. 我们的工程师, 就像我们技术部门的每个人一样, can sit down with people and have lunch with those who are actively using the software.

 This real-time feedback creates a sense that what you’re building actually matters. I think a lot of people in tech at some point ask if anyone actually cares about what they are building. To have access to stakeholders and users creates a sense of closure and purpose.

布朗: 新员工的影响是相当迅速的. We’re in a pure growth stage right now and creating new teams and product areas, 例如针对运营商的到达边缘, 我们的托运人门户, 批量定价和一般基础设施.

我们也在定义我们工程团队的文化, 所以每一位新工程师都将在这一过程中发挥作用.

你的团队目前在做什么? 

Senftleber: 除了全面招聘之外, we’re also investing more in data science to double the team over the next year. This will help us be more efficient and guide us to make the right decisions at the right time. An example of this would be if a shipper asks if they can move a load from A to B next Tuesday. 我们的匹配系统, 它下面运行着一个数据科学模型, will predict which three carriers are the most likely ones to accept the load, 建议先打电话给哪家公司，并预测费用.

We’re also building out a platform that we’ve extended outside of our internal customers to our partners. Now, the carriers can log into our software and interact with our internal folks and the shippers.

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