How manufacturers are harnessing the value of smart product data to generate real business value
The hype around “smart” products continues to grow as manufacturers, vendors and even customers speculate about the opportunities resulting from embedding sensors in passive objects that communicate information. Examples are everywhere - from the Nest thermostat, which uses a learning system to program itself, to Nike, which looks more like a tech company than a sportswear manufacturer. In fact, 50 billion devices are forecasted to be Internet-enabled by 2020, and somewhere between 40 and 60 per cent of the value of a modern product is now in its software.
Sensor-enabled products are transmitting large volumes of real-time data, and companies are capturing it all in powerful technology platforms. Yet many manufacturers are struggling to understand what to do with the information and how intelligent products will transform business operations.
All types of machines and products are currently being made to connect to the digital world right out of the box – from sensors in sewer pipes and home appliances to chips in tires and parking garages. Yet it is the ability to sift through the information they send and make sense of it in a timely manner that has the greatest implication for manufacturers.
To extract the value from data, it must be actionable. And to make data actionable, manufacturers need an infrastructure in place that provides:
• access to data from any location;
• access to information at any time;
• the ability to process data quickly; and
• the ability to easily view and share information in the right context.
Take, for example, Pirelli - one of the world’s biggest tire manufacturers and exclusive supplier for the Formula One racing championships. Pirelli collects real-time information on performance from sensors embedded in the tires and then uses these insights to improve the car mid-race.
Profitability in data
The information provided by sensors in smart products can be used by manufacturers to help them either reduce costs or increase revenue, both of which add to bottom-line profitability. On the cost side of the equation, the biggest opportunity from product data is the chance to identify and act on trends as they are happening. Known as predictive analytics, companies with the ability to collect and analyse the right data in real-time gain the distinct advantage of clearly understanding what is happening and then acting on it before competitors.
For example, SK Solutions uses data transmitted from sensors on machinery to constantly monitor activity, such as the machinery’s position, weight and inertia, along with wind speed and direction, temperature, etc. This information is analysed and applied to detect potential accidents before they occur. Should a problem be uncovered, the auto pilot takes over, making immediate adjustments. Minimizing risks, reducing accidents and proactively reacting to environmental hazards is saving money as well as lives.
Data gathered from remotely monitoring product performance can also be used to lower operational costs by automating or transforming a business process such as routine maintenance. For example, data transmitted from components can be used to predict when a product will start showing signs of fatigue and need replacing. Based on the predictive information, a maintenance request can be automatically issued and scheduled according to the resources available (i.e., a technician’s location, skills and availability). Finally, predictive analytics can help shorten design cycles and improve product quality.
In the automotive industry, for example, manufacturers can identify problems with a particular design and make immediate corrections on the assembly line to avoid designing in the problem on future models.
From a revenue standpoint, there’s a plethora of after-sale service opportunities available for those who can leverage data analytics. Manufacturers are in a unique position to combine product knowledge with usage data to offer insightful product monitoring services. For example, manufacturers or vendors could alert users when a product is not being used correctly or even rapidly engineer customized offerings based on real-world, real-time feedback. Accessing the right data at the right time can also help sell a product. Data analysis can be used to price a product based on performance or sell a product while it’s still in manufacturing.
In manufacturing today, high-quality is assumed. The new focus is not so much on how a product is made, but in the data it transmits. Manufacturers who can capture the right information, sift through it, make sense of it and use it to either lower costs or increase revenue will be the ones that succeed in the future. To do so requires the right infrastructure, intimate customer knowledge and a willingness to embrace a new era where information is king.
Pradeep Amladi is vice-president, Marketing, Manufacturing, Energy and Natural Resources Industries, for SAP.
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