AnalyticsInsight-Driven Growth in Automotive and Industrial Equipment

Data, data, everywhere...but how to derive meaningful insights from it?

The answer, as most auto and industrial executives now acknowledge1, is analytics: the systematic search for meaning among the mass of “Big Data” generated by the intelligent and connected devices, systems and processes that constitute the Industrial Internet of Things (IIoT).

Accenture research shows that 82 percent of organizations now recognize Big Data as a significant source of value2. What’s more, they plainly recognize its power to help make their value chains more flexible and customer-centric. 83 percent of automotive executives are planning to move toward real-time enterprise

platforms and systems (including analytics platforms), for example, while the personalized customer experience is a Top 3 priority for 86 percent of industrial executives, and the most important priority of all for 33 percent of them3.

Indeed, industrial and automotive players are now starting to view analytics much as the leading digital retailers of the world already do: the key to agile, responsive and relevant business models that drive true innovation and competitive advantage. Their challenge going forward will be to find ways of embedding analytics throughout their enterprises—and fuel profitable growth with the insights thus enabled.

Multiple potential benefits

Analytics can keep equipment operating, save on warranty costs, and even more effectively apply insurance rates.

• Remote diagnostics and predictive maintenance to keep equipment operating. Analysis of real-time data generated by equipment sensors can tell manufacturers when maintenance interventions are needed. Acting on this insight not only enhances the safety of machinery for those using it or working in its vicinity, it can also reduce machinery downtime. For mining and construction firms with far-flung locations, addressing a performance issue before a breakdown occurs may save hundreds of thousands of dollars a day. And conveniently scheduled maintenance and minimal downtime doesn’t just keep projects on schedule. Such capabilities can also keep customers happy, significant to loyalty and thus, of course, higher sales.

A strategic role Once largely the domain of back-office functions, analytics has evolved to play a much more strategic role for industrial and automotive companies.

Production and all related processes are more data intensive than ever, and so have become rich sources of critical insights. By mining those insights, organizations can improve the performance of their core business—and generate new sources of revenue.

Thanks to intelligent software embedded right across the manufacturing value chain, industrial equipment manufacturers, for example, can analyze machine performance in real time to pre-empt potential problems and limit costly downtime. Similarly, Original Equipment Manufacturers (OEMs) can analyze diverse streams of data to develop relevant, location-based vehicle services and customized offers for individual car drivers.

On-demand analytics platforms allow the swift compilation, formatting and cleansing of the heterogeneous data streams—both structured and unstructured—that comprise Big Data. Less time needs to be spent on integrating and reporting, and more can be spent on actually analyzing: winnowing out irrelevancies and focusing on the small but critical amounts of information that can generate true insights about customers, operations or channels.

Analytics solutions are also significantly more sophisticated. Yesterday’s descriptive analytics helped quantify and confirm what has already occurred. Today’s more advanced, predictive analytics help companies understand what will happen in the future. Seeing trends as they develop allows manufacturers to seize new opportunities as they occur, or even to get ahead of them. It also helps keep customers happy—and saves money (see Multiple benefits sidebar below).

• Remote analytics to save on warranty costs. Manufacturers frequently fix or replace a machine in the event of a breakdown during the warranty period. But if data reveals that the car or equipment was not used properly, or exceeded the bounds of standard usage, the owner or user would be responsible for repairs.

• Data analysis to reduce insurance rates. Digitally enabled vehicles that are impervious to hacking carry less risk, and so should give their owners an advantage when buying insurance. Data analysis of driving history and behavior such as breaking and speed patterns may also impact insurance rates, as well as enabling future design refinements that better reflect expected usage.

Accenture research shows that82 percent of organizations nowrecognize Big Data as a significantsource of value.

The challenges A number of hurdles are limiting widespread adoption of analytics, the following among them:

• A widening talent deficit. The demand for data scientists far outstrips supply within most industries, and especially in such sectors as auto and industrial equipment, which may seem less glamorous than high tech, and don’t generate the extensive media coverage that life sciences or even finance do. Companies would need to determine the pros and cons of building, buying, or borrowing analytic talent to develop the capabilities they need.

• Difficulty in operationalizing analytics. Issues such as governance and funding, how to embed analytics as part of everyday high-level decision-making, and even shifting employee mindsets to rely less on intuition or experience and more on data can all slow analytics-driven value generation.

• Driving adoption of analytics across an ever-expanding and more complex ecosystem. Global companies operate dynamic, global networks of suppliers and logistics business

In short, by leveraging analytics as an embedded capability, throughout the value chain, auto and industrial enterprises can improve entire global ecosystems of suppliers, facilities and logistics, as well as respond to shifts in consumer needs and behavior, and to emerging trends in market demand and supply.

Reaping the rewards of analytics can be challenging, for sure. And our work with auto and industrial companies has identified a number of hurdles that limit widespread adoption (see The challenges sidebar below).

Even so, many C-suite executives are exploring ways to make data flow more easily, quickly and usefully through their enterprises (Figure 1). And some leading players are already ahead of the game.

partners, employees, business, and channel partners. Such ecosystems work seamlessly, in symbiosis. But in reality, the organizations that comprise them differ greatly in both their use of analytics and their analytics capabilities, as well as in their significance to the “parent” manufacturer. Auto and industrial companies would need to prioritize which partners to work with most closely on their analytics endeavors.

• New, more data-driven competitors. Amazon and Google offer analytics as-a-service, as do a fair number of global CPG (Consumer Packaged Goods) and consulting firms. These organizations compete for top talent while their continued investments in analytics position them in the vanguard of data science. Companies still struggling to build analytics capabilities are therefore left far behind and the gap grows larger. Auto and industrial companies would need to learn from these players, and leverage their innovations to stay abreast of analytics trends.

Personalizedcustomer experience is a Top 3 priorityfor 86 percent of industrial executives.

Success storiesBy leveraging both the multiple levels of connectivity enabled by the Industrial Internet of Things and the power of Big Data analytics, leading auto and industrial companies are:

• Offering better, more reliable products. The requirements and specifications for most products change over time. So receiving early feedback about the performance of products, and especially new products, is critical to getting the most reliable product to market at speed. General Electric, for example, is using operating analytics to continually assess the performance of its latest locomotive, which has 250 sensors measuring 150,000 data points per minute, and thus gather insights that will help refine the machine’s design4.

• Enhancing the customer experience. In another example, Caterpillar has built a telematics solution that allows its customers to monitor their fleet in real time, identify maintenance needs swiftly, and replace parts fast. It collects a vast amount of real-time data from machines, which proves invaluable in optimizing such resources as capacity, fuel and operators5.

• Generating new revenue opportunities. Michelin solutions’ new EFFIFUEL™ solution reduces fuel consumption in truck fleets—and helps boost its inventor’s revenues. Sensors inside vehicles collect data on fuel consumption, temperature, speed and location and transmit it to the cloud service of a Michelin solutions partner, whose fuel experts then analyze the data and make fuel-reduction recommendations to fleet managers, while Michelin solutions’ instructors train their drivers. As a result, truck fleet managers can save two liters of fuel for every 100 kilometers driven. Moreover, since EFFIFUEL™ also includes the outsourcing of tires on a per-kilometer-driven basis with EFFITIRES™ 6, Michelin solutions’ revenue potential is further enhanced.

Companies that view data as a true business asset and use it to become masters of analytics are in pole position to provide analytics “as-a-service” and help drive top-line revenue growth. What’s more, thanks to cross-industry collaboration, they don’t have to do it alone.

Taleris, for example, has allied with General Electric to optimize fleet usage by leveraging advanced analytics7. Accenture, meanwhile, is working with MIT to fund research into how business analytics can help global companies in six key industries—banking, health, insurance, retail, communications, and energy—solve some of their most critical challenges8.

Supports faster processingby leveraging advances in hardware and software for computer clusters,

enabling them to operate more e�ciently than ever.

by enabling users and applications to connect to the data infrastructure in universally acceptable ways and by ensuring that query results are delivered as quickly as required.

Supports faster interactivity

speeding up the ability to gain the insights required to make the business decision facing them and to satisfy their clients’ expectations.

Reduces user wait time,

Why accelerate data?(Figure 1)

How Accenture Can Help

Accenture can help auto and industrial companies harness the power of analytics to close the gap between analytics “haves” and “have-nots”. Our teams of industry and analytics professionals help clients build foundational capabilities and make long-term investment decisions that position analytics as a competitive advantage. We work with cross-functional teams to:

• Focus investment on your most critical outcomes. We bring not only analytics experience, but also industry and functional experience to identify key analytics applications across your organization’s value chain.

• Embed analytics in your operating model. We leverage our operational and change management experience to help organizations adopt and infuse a more rigorous, insight-driven operating strategy to enhance their efficiency and reduce costs.

• Provide implementations and capabilities to bridge the talent gap. It can take months, if not years to build the right in-house talent in this area. But Accenture can provide analytics as a managed service while organizations build their own talent pool, or for the long term. In either case, we act as your thought partner, embedding strategic analytics in your organization and helping capture its value.

Citations

1. The Accenture Technology Vision 2015 - Industrial Equipment Industry: Engineered to Deliver in the Digital Era, Accenture, July 2015. https://www.accenture.com/us-en/insight-accenture-technology-vision-industrial-equipment-2015

2. Big Success with Big Data. Accenture, April 2014. Download at https://acnprod.accenture.com/us-en/~/media/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Industries_14/Accenture-Big-Data-POV.pdf

3. The Accenture Technology Vision 2015 - Industrial Equipment Industry: Engineered to Deliver in the Digital Era, Accenture, July 2015. https://www.accenture.com/us-en/insight-accenture-technology-vision-industrial-equipment-2015

4. GE Reports Website: ‘How the Golden Spike Gave Us National Train Day’ May 8, 2014. http://www.gereports.com/post/85146706165/how-the-golden-spike-gave-us-national-train-day/

5. Accenture, Caterpillar partner on Telematics Solutions, August 2014.http://www.machinetomachinemagazine.com/2014/08/11/accenture-caterpillar-partner-on-telematics-solutions/

6. Michelin solutions press release, July 11, 2013.

7. Taleris website, “Etihad Airways and Taleris Implement New Technology to Predict Aircraft Maintenance Faults, Reduce Flight Delays,” BusinessWire, June 18, 2013; “Brains for Planes: Etihad Taps Big Data to Keep Planes on Time,” GE Reports, June 18, 2013.

8. Annual Research Update – The Accenture and MIT Alliance in Business Service, Accenture 2014. https://www.accenture.com/us-en/~/media/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Technology_9/Accenture-MIT-Alliance-Business-Analytics-Brochure.pdf

About AccentureAccenture is a global management consulting, technology services and outsourcing company, with more than 358,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world’s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$31.0 billion for the fiscal year ended Aug. 31, 2015. Its home page is www.accenture.com.

ContactFor more information contact:

Andrew Fanoandrew.e.fano@accenture.com

Bodo Körberbodo.koerber@accenture.com

Robert Borerr.borer@accenture.com

www.accenture.com/digitalindustry

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