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Opinion: Maximising the value of connected cars

  • Posted by admin on June 11, 2017

In 2015, nearly 17.5 million new cars were sold in the United States — the largest total ever recorded. Business is clearly booming in the auto industry, and manufacturers have every reason in the world to celebrate this resurgence. 

However, they shouldn’t celebrate for too long. With this incredibly high demand comes an increased need for production speed, efficiency, and quality — areas the industry has struggled to address throughout history.

Recently, shifts in consumer expectations have turned the production process into a much larger burden than it used to be. With technology evolving at breakneck speeds, the clamor for new products has grown louder than ever; modern consumers expect every new model — car or otherwise — to offer the latest and greatest features. 

Given the fact that it currently takes manufacturers several years to design their next models, it will be all but impossible for them to keep modern consumers happy without possessing a powerful ability to predict and react to trends.

Today’s consumers are also increasingly excited about customization. With the breadth and depth of available features changing so quickly, drivers want to be able to mix and match their favorites for a custom build. But, without automated design systems in place, customization on a mass scale is currently too costly for most manufacturers to consider.

In the midst of big changes within auto manufacturing, the mandate to operate lean and mean has also grown louder than ever. Waste and underutilization are profit killers — and on the scale of global automaking, they’re a huge challenge to root out unless plants have data analytics capabilities.

Even with sales trending upward, automakers still face real and growing issues in the coming years. The good news, however, is that the solution they need might already be built into most new cars: connectivity.

Learning from every car on the road

The smart car is swiftly racing from the drawing board to the streets, and it’s providing drivers with an exhilarating experience. With functions such as self-braking, self-parking, and automatic cruise control based on road conditions, it’s no wonder these vehicles are taking the world by storm. 

Data from these sensors needs to be democratized to unearth insights that reveal what’s happening inside the machines. They promise to offer a tidal wave of new data — and benefits — to auto manufacturers and consumers alike.

It is now standard for the majority of new car models to have some level of connectivity. According to McKinsey & Company, the modern connected vehicle has the computing power of 20 PCs and processes up to 25 gigabytes of data per hour. This power can be leveraged to deliver a game-changing amount of performance-related data to manufacturers — perhaps to the tune of more than $ 30 billion worth of increased productivity alone. 

BMW is just one automaker to jump on this opportunity; the company recently assigned 5,000 employees to work on digitization initiatives. As more and more manufacturers hop aboard the connectivity train, however, the next step will be identifying what to do with all of this data. 

Manufacturers need the ability to extract actionable insights from this tidal wave, and only through cognitive data science can they do so with accuracy and expediency. 

Armed with this capability, however, they stand to reap major economic benefits in these five areas:

  • Predictive maintenance and quality assurance: Car sensors typically send alerts to drivers and manufacturers right at the point that — or after — a problem has occurred. As these sensors improve, however, they will be able to predict problems before they affect the driver, thereby lowing the cost of maintenance and limiting breakdowns. In fact, ABI Research estimates that predictive maintenance on its own could save automakers $ 24.7 billion in 2019. By engaging in large-scale maintenance data analysis, automakers can improve future builds, assure a higher level of quality overall, and avoid being labeled brands that build shoddy products.
  • Supply chain efficiencies: Competitive shipping costs, quality control concerns, and materials shortages all conspire to make automotive supply chain management a major hurdle — and problems in the supply chain lead directly to delays for dealers and consumers. Connectivity throughout the supply chain, combined with cognitive intelligence and data science tools, can highlight supply chain problems and lead to actionable solutions. For example, a Tier 1 auto manufacturer that studied its connected supply chain for improvements was able to boost its depot throughput by 9.4 percent. 
  • Fewer warranty claims: The average auto manufacturer will spend up to 3 percent of its annual revenue paying warranty claims, according to Hortonworks — and this is on top of the damage done to the brand’s reputation. Reducing the frequency of these claims is now feasible, thanks to the data made possible by connected cars. Trend analysis will reveal problems within the supply chain that can be corrected to slash warrantable defects.
  • Optimized inventory management processes: The scale of auto manufacturing requires an incredibly precise inventory management system because small over- or underestimates can lead to millions of dollars in lost revenue. This is likely why 82 percent of senior executives report that overstock is a major concern. Achieving the perfect balance is finally possible, thanks to the real-time visibility of connected vehicles and factories. Supply and demand are monitored throughout a unified system so that inventory doesn’t become an obstacle.
  • Better-informed ERPs: Because auto manufacturers deal with a heterogeneous mix of products, materials, supply chains, and global markets, their ERP needs are greater than most. In fact, Panorama Consulting reports that 63 percent of general manufacturers exceed their ERP budget by $ 3 million, on average. Connected manufacturing, on the other hand, feeds these complex ERP systems the data they require to truly improve performance and processes.

Connectivity is a capability that’s here to stay, and it’s poised to become a key institutional asset for automakers. By capitalizing on this opportunity through cognitive data science, manufacturers can revolutionize their production processes and ensure every new model meets the high standards of modern consumers.

How do you think the value of connected cars can be maximised? Let us know in the comments.

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