SpeedTrack: Bringing Data up to Speed

0
164

More power lies with that organization that knows how to interpret its data well. This, is a fact known to anybody working with data.

The automotive industry is one such sector where there is a massive overload of data, and all of it needs to be closely analyzed in order to make decisions that drive processes. This is more clearly exhibited in cases wherein the manufacturer has to undertake a recall or respond to consumer complaints. Even though automakers, suppliers, and government officials make keen attempts to track such issues in order to understand the root causes, it simply ends up being a herculean task to organize and analyze the large volumes of dynamic data.

The closest answer to the above dilemma is JD Power SafetyIQ, powered by SpeedTrack’s patented technology. This online application helps auto industry professionals analyze vehicle safety data in a more efficient manner. It integrates National Highway Traffic Safety Administration (NHTSA) data with JD Power automotive data. The biggest advantage of this is that the data is categorized and can be searched by vehicle make, model, year, age and component. For example, manufactures and suppliers are empowered with the capability to do a comparative analysis such as identifying which model series within a segment has the most complaints per 1,000 vehicles sold.

Through SafetyIQ, all public automotive recall data from the NHTSA website is collected and gathered in a single place which facilitates easier navigation and analysis. The collected data include all recalls to date, defect investigations, technical service bulletins, individual consumer complaints, automakers’ completion rates of existing recalls and normalized data by 1,000 sales. SafetyIQ allows users to see and read the entire complaint population and intuitively search and discover word combinations contained within the complaints. This, along with the parameters of the vehicle and component dimensions, gives the consumer the most relevant detailed information that they can use.

While most analytics solutions focus on storing and querying data, which requires intimate knowledge of the data and its structure, SpeedTrack’s Guided Information Access (GIA) platform works in the opposite manner. The GIA extracts all information contained in the data and guides the users to insights along the way. This has a three- fold benefit – the productivity of analysts and decision support staff is increased, the customer experience is fast and intuitive, and every story within the data is made crystal clear to the consumer. SpeedTrack’s online solutions just don’t stop there. Another major solution that the company has rolled out is the California Healthcare Solution, which enables hospitals to easily explore large, complex data to answer important questions on the fly. The numbers that have been produced as a direct output of implementing these solutions are overwhelming – a 500% increase in analyst productivity and 300% to 750%+ ROI’s attributable to cost savings and new revenue opportunity identification.

It is by no means a surprise that SpeedTrack (www.speedtrack.com) holds 8 granted patents and 10 additional patents that are currently pending. Each of them have been designed to combine human knowledge and intuition with software that provides guidance to answers while giving rise to additional questions, which ultimately leads to powerful insights and discovery. SpeedTrack works with the vision of giving anyone access to best answers, regardless of their technical expertise or, the size & complexity of the underlying data.As part of future plans in business, SpeedTrack hopes to associate with more major brands, such as JD Power, to bring premium online products to different markets. And as expected, the organization hopes to continue delivering extraordinary value to their customers, employees, partners and shareholders with ROI’s that speak volumes of the company’s success.

“SpeedTrack enables interactive n-dimensional comparative analytics and discovery for Big Data”