Kishore Kumar, CEO of AllThingsMine
The Internet of Things (IoT) has captured the imaginations of consumers and businesses alike with its exciting possibilities. Smart refrigerators that enable direct grocery ordering! Mattresses that know how much you slept! Calendars that tell you when to leave for meetings to avoid traffic!
However, the greatest impact of the IoT will not be to create a world reminiscent of the Jetsons. Instead, it will transform the way industries operate and shape the future of business to be more efficient and effective, but progress hinges on analytics.
Predictions about the future of the IoT are filled with massive numbers. Cisco estimates that the IoT will grow to a 50 billion device juggernaut by 2020 and generate a $19 trillion market. GE predicts that the Industrial Internet alone will add $15 trillion of revenue to the global GDP over the next 20 years.
All of these devices will generate (and already are generating) vast amounts of data. Today, at what is really the beginning of the IoT, 2.5 quintillion bytes of data produced every day. According to IDC, the amount of data on the planet will grow 10-fold to 44 zettabytes by 2020, and the IoT will account for one-tenth of the worlds data.
This staggering amount of data creates staggering challenges. Most businesses are just not equipped to handle this deluge or effectively use analytics to extract value from it. Data is only as valuable as what you do with it. If data is continuously flowing in but analytics are not adroitly deployed, that data is worthless. For the IoT to realize its full potential, and for businesses to reap full benefits from it, analytics has to be a top priority. Organizations must learn how to mine IoT data effectively and implement the right tools and processes to act and react to that data. However, the way that IoT analytics are used vary from sector to sector.
To demonstrate the potential of the IoT and the importance of analytics, lets take a look at how this technology will affect the future of a number of key industries.
Most major retailers today are having sensors placed throughout their stores. These sensors can detect the presence of people in aisles, the quantity of products on the shelves, the zone of movement, and more. They can identify which products are flying off the shelves (and which are not), as well as provide insight into when and why sales are happening. In addition, IoT analytics can show retailers how factors like in-store promotions, staff salaries, and displays affect their top line.
Armed with this information, retailers can make changes, such as switching the location of a display or hiring more sales reps, to test whether those actions have an impact. In this case, analytics provides retailers with insight into how the business is running, where the gaps are that need to be filled, and how to best use logistics and product placing to drive optimal results. Moreover, IoT analytics can be used to predict what a retailer is likely to need going forward – shelf sensors plus weather data plus location data together can tell a retailer how many jackets to stock.
Secondly, IoT analytics can help retailers provide a personalized experience to customers that turns them into repeat buyers. Data collected from the sensors can combine with information from individual shoppers smartphones. This creates a contextual picture for what that shopper is interested in that enables the retailer to act. For example, if a customer has previously purchased mens shirts from a clothing retailer, then that is a prime opportunity to push a sale or discount for mens shirts to their phone. Salespeople can also be dispatched to answer questions if, say, a user is browsing for a new TV. These kinds of personalized experiences create stickiness that will encourage customers to come back to the store, thus increasing business revenue.
Oil & Gas
The oil & gas sector is not exactly known for being fast-moving or innovative, but the benefits of deploying IoT analytics are dramatic. In a report from GE, Apache Oil and Gas claimed that if the global oil & gas industry improved pump performance by 1 percent, it would increase oil production by half a million barrels a day and earn the industry an additional $19 billion a year.
As with retail, the IoT can benefit oil & gas companies in two key ways. The first is operational. To understand what is happening with pumps at any given time, and more importantly, to immediately know if something is wrong. In the past, an employee would have to physically go and check on pumps. Now, an employee sits elsewhere and watches as data from sensors on walls, pipes and other drilling equipment flows in. If there appears to be a problem, then functions and machinery can be shut down before the problem causes damage or gets worse. This is beneficial for safety, as well as to prevent unnecessary costs.
Furthermore, predictive analytics will make it possible for oil & gas companies to anticipate if and when something is likely to happen, such as a pump failure. This empowers them to be even more proactive, act faster, and make smarter decisions, thereby minimizing lost production and accidents.
In addition to making operations more efficient, analytics will also help oil & gas companies grow their business. According to a report from Deloitte, the IoTs promise not only exists in helping oil & gas companies reduce risks and improve operational efficiency, but also in creating an entirely new asset: information about these elements of their businesses. Oil & gas companies can use IoT analytics to boost production, increase active rig time, explore subsurface geology, map changes in reservoirs over time, enhance well and pump designs, and more. In addition, midstream companies can use IoT analytics to find the best paths to market, identify price differentials, and leverage incentives. The opportunities are endless for the corporations ready to take advantage of them.
The healthcare industry is a prime candidate for IoT analytics because it is already filled with sensors. If you look in a patients hospital room, there are blood pressure sensors, heart rate monitors, thermometers, IVs and much much more. Rather than relying on personal experience and physical symptoms, technology is enabling healthcare providers to collect health data in real time and use predictive analytics to anticipate what will happen next.
As we saw with retail and oil & gas, the benefits of IoT analytics are both in driving operational efficiency and in using predictive analytics to drive better outcomes. The same GE report mentioned above gives the example of a hospital in Florida that gave each patient a tag to monitor their journey. The tags track their movements and location, and interface with bed placement timestamps. Analyzing data from the tags enabled the medical center to optimize patient flow and reduce emergency department wait times by an impressive 68 percent. Additionally, hospitals can use IoT analytics to monitor the usage of healthcare equipment; track clinical financial and operational measures; and manage workforce productivity and engagement.
As for the latter benefit, healthcare providers can use IoT analytics to anticipate patient outcomes and respond with targeted interventions when needed. The GE report cited another hospital that used IoT analytics to drive earlier diagnosis of sepsis, which is a leading cause of in-hospital mortality, and saved hundreds of lives. The IoT enables hospitals and care providers to improve care, address risk factors and symptoms of chronic disease early, and provide positively reinforcing feedback. Each of those improvements leads to healthier, happier patients and a stronger healthcare system overall.
These are just a few of the industries that will have futures shaped by the IoT. In each case, deploying sensors and effectively managing and processing the data that comes from them enables organizations to improve everything, from the way they operate to the way the interact with their customers. There is no doubt that the IoT tidal wave is coming, and the organizations that thrive will be those that equip themselves with analytics early on.
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