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Jack Doheny Companies’ Data-Driven Culture Saves Millions Of Dollars
技术
- 应用基础设施与中间件 - 数据可视化
- 分析与建模 - 预测分析
适用行业
- 运输
- 公用事业
适用功能
- 商业运营
- 质量保证
用例
- 车队管理
- 预测性维护
- 过程控制与优化
服务
- 系统集成
- 数据科学服务
挑战
The decision to evaluate BI solutions came in the wake of what could be defined as a “cultural revolution” taking place in JDC: from siloed data, with each stakeholder holding on to his or her own data and only sharing it with others on a “need to know” basis, to a corporate culture of complete transparency of information that aims to make data available to everyone, and challenge them to make good use of it. The data itself was being stored in a Cobalt character-based CRM system running on the IBM RS/6000 platform, as well as Excel spreadsheets. This data consisted of sales, operational, utilization, financial and other data. Prior to Sisense, reporting was done with Excel and Access. JDC has been looking for some sort of dashboard software for roughly two years but did not find any product that could suit their needs, until they ran into Sisense in a user group in which two Sisense customers had presented it. The VP of Parts and Business Systems downloaded the trial version right there at the convention, and within two days was already publishing dashboards.
关于客户
Jack Doheny Companies (JDC) is the North American market leader in vacuum equipment, specializing in large vacuum trucks used for sucking up waste, liquid or dry product. The company’s current annual sales cycle is around $220 million dollars, and it has some 750-800 trucks in its rental fleet. JDC runs its operations from 16 facilities spread throughout the United States and Canada. The company has a significant presence in the vacuum equipment industry, running a fleet of hundreds of trucks covering the United States and Canada. JDC is a multi-million dollar company with a strong market position and a large operational footprint.
解决方案
Sisense was ultimately selected due to its ease of use, and mainly the product’s ability to merge large datasets. JDC stores its data in many Sort and Filter tables created in Excel in order to refine and consolidate the data from the CRM. The ability to pull in the Excel data and mash-up with the Cobalt (CRM) data was a game-changer. JDC were similarly wowed by Sisense’s performance: generating an Elasticube build of 4 million rows takes a mere few minutes. During the trial they were quickly able to replicate what they had been doing in Excel, then started playing around with other features such as the heatmaps and were immediately sold on Sisense. Since Sisense was deployed in JDC, data has started driving strategic business decisions. For example, the company planned to spend $250 million on equipment in one year – but after visualizing the data in BI dashboards and displaying the locations and utilization rates of trucks, that figure was reduced to $130 million. Part of this was due to external circumstances, but part was the result of viewing a heatmap visualizing the locations of the company’s current fleet of trucks, which made executives realize that there were holes in their coverage in the USA – which in turn led to a decision to open two additional facilities.
运营影响
数量效益
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