Analytics Drive Automotive and Equipment Growth

Jan. 25, 2016
Traditionally applied to business functions, analytics have begun to play a more strategic role in helping OEMs and auto companies drive greater innovation, gain a competitive advantage and improve profitability.

Automotive and industrial equipment manufacturers are recognizing that analytics can be a source of much greater value to their organizations -- beyond generating customer insights -- if they apply them throughout the enterprise.

Analytics can derive meaningful insights from the Big Data generated by the Industrial Internet of Things (IIoT). Traditionally, analytics have been applied by sales and marketing or back-office functions dedicated to one area of the business. But in recent years, analytics have begun to evolve into a process that can play a more strategic role in helping OEMs and auto companies drive greater innovation, gain a competitive advantage and improve profitability.

According to recent research (“Accenture Technology Vision for Industrial Equipment 2015,”, 83 percent of automotive executives are planning to develop real-time enterprise platforms, including analytics platforms. Adopting such an approach can enable both auto and OEM companies to spend more time gathering relevant information that can generate true insights about their operations, as well as their customers. For example, by embedding intelligent software across their value chain, OEMs can analyze machine performance in real time to preempt potential problems and limit costly downtime. In addition, automakers can analyze diverse streams of data to develop more relevant, location-based services and customized services for drivers.

Widespread adoption of analytics, however, is not without challenges that should be considered. These include a widening talent deficit, where demand for much-needed data scientists is outstripping supply. This is a particularly significant issue in the auto and OEM sectors, exacerbated as more data-driven enterprises like technology and consumer goods companies compete for the same talent. Companies also might find it difficult to institutionalize analytics across their organizations, especially since their ecosystem will likely continue to expand.

Despite these issues, leading industrial manufacturers are leveraging the expanded use of analytics in a number of ways to strengthen performance and grow. These include:

Ensuring product reliability. The requirement and specifications for most products change over time. Manufacturers that use analytics to receive early feedback about a product’s performance will be able to deliver the most reliable product to market in a timely manner—a key element of sustaining a competitive edge. One industrial company, for instance, is using operating analytics to continually assess the performance of its latest locomotive that will help refine the machine’s design and make it more appealing to the market.

Enhancing the customer experience. In another example, a leading OEM has built a telematics solution that allows its customers to monitor their fleet in real time, identifying maintenance needs and replacing parts quickly. The solution collects a vast amount of real-time data from machines, which proves invaluable in optimizing resources such as capacity, fuel and operators.

Generating new revenue. A major tire company has invented a solution that reduces fuel consumption in customer truck fleets, helping the inventor boost revenues. Sensors inside the vehicles collect fuel consumption, temperature, speed and location data, which is transmitted to the company’s cloud service. The data is then analyzed by the solution’s fuel experts, who make fuel-reduction recommendations to truck fleet managers. As a result, truck fleet managers can save 2 liters of fuel for every 100 km driven.

Managing future opportunities. In the past, analytics primarily have helped companies quantify and confirm what has already occurred. Today, forward-thinking manufacturers are applying more advanced, predictive analytics to understand what could happen in the future. This enables companies to seize opportunities as they occur, or even get ahead of them. According to Cisco, predictive maintenance of assets could result in savings up to 12 percent over scheduled repairs. Overall maintenance costs can be reduced by up to 30 percent, and up to 70 percent of breakdowns can be eliminated.

Widespread adoption of analytics may present new challenges, but overcoming them will be worth the effort. By leveraging analytics as an embedded capability throughout their value chain, automotive and industrial equipment manufacturers can improve their entire ecosystem, greatly enhancing their ability to compete and be more responsive in a constantly changing global market.

>> Andy Howard, [email protected], is managing director of the Automotive and Industrial Equipment Group at Accenture.

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