Big data and IoT promise to speed up the information highway
Big Data and the Internet of Things (IoT) promise to help firms separate the signal from the smoke within the endless stream of bits and bytes flowing into their data centres. Working together, they are raising the speed limit on the information highway.
In anatomical terms, Big Data technology and processes are the brain and IoT sensors serve as the electronic eyes, ears and nervous system. By connecting the unconnected, the latter also provides a voice for all the linked physical world objects to speak directly to expanding group analytical systems in today’s digital tool box.
The recent DHL and Cisco Internet of Things Trend Report concluded that there will be 50 billion devices connected to the Internet by 2020, up from 15 billion today. Cisco’s economic analysis states that IoT will help the supply chain and logistics sector generate US$1.9 trillion worldwide in Value at Stake over the next decade. Along the way, the number of computer applications (apps) that enable smartphones or tablet etc. tools to access information, pay bills or lock doors remotely will jump from the current one million to five million by 2020.
Says Bill McBeath, Newton, MA-based chief research officer, ChainLink Research Inc., “The IoT will revolutionize decision making. By connecting the previously unconnected, we create incredible potential for businesses to improve the speed and accuracy of decision-making through the analysis and application of digital information. It enables dramatically faster cycle times, highly dynamic processes, adaptive customer experiences and, through the ecosystem of people and technology, the potential for breakthrough performance gains.”
Big Data is the catch-all term for emerging analytical systems and processes that extract business value from all those petabytes of data. A concrete example of its impact is how analytics has revolutionized sports statistics. Today, when NHL executives talk about performance metrics, they pay less attention to old-time stats related to individual scoring, defence and goalkeeping. They now focus on newfangled concepts such as team puck management. It calculates the probability of winning games by measuring when, where and how long their team controls the puck.
Analysts claim that the key indicator of winning games is holding the puck in their opponent’s end longer and closer to their goal crease than vice-versa. That insight is based on the age-old hockey adage -you can’t score without the puck. And if you can keep the puck away from the other team in your own end, they can’t score either. Coming soon are enhanced player- and action-tracking systems featuring infrared cameras capturing the position and movement throughout the game from RFID chips imbedded in players’ jerseys and pucks.
The breakthrough in Big Data is timely because organizations need all the help they can get to handle torrents of data from the explosive growth in social media sources and electronic gadgets. Despite the almost daily arrival of new analytical tools, more than 90% of data stored in corporate databases sits untouched.
But decision makers now realize that their firm’s competitiveness and even its very existence may depend on converting the contents of their databases into reliable predictions and insights. They must update their internal operations and move faster to adapt to ever-changing world events, market forces, customer preferences and behaviour. To succeed in today’s marketplace, they must leverage data to create new processes, products and services.
The Big Data/IoT combination can lead to strange logistics bedfellows. For example, European automakers such as Volvo and Audi have started working together with e-vendors such as Amazon and carriers including DHL, a unit of Deutsche Post DHL, to deliver consumer parcels to car trunks.
At the 2014 Mobile World Congress, Volvo showcased a system, aka “roam delivery”, that notifies consumers through their smartphones or tablets when a carrier plans to drop off or pick up items from their car. Volvo’s digital key system permits access to car trunks by enabling a carrier driver to locate them on its corporate GPS system and open the trunk using a single-use, digital key sent to the driver’s hand-held device. Car trunks are the latest addition to the growing list of consumer delivery destinations.
To stay competitive, German auto giant Audi has combined with Amazon and DHL to test-drive its own version of car-trunk delivery. Besides becoming a reverse logistics station for product returns similar to the Volvo system, Audi’s service will also serve as a novel pick-up and delivery spot for properly paid letters and parcels for Deutsche Post.
Many of today’s cars are already connected to the IoT by automakers’ telematics systems such as Volvo’s On Call, Audi’s MMI, or General Motors’ OnStar etc. Newer Volvo models already offer the necessary trunk-delivery technology. Audi is busy developing special equipment, which can be easily installed on both current and future models.
“By turning the car into a pick-up and drop-off zone through digital keys, we solved a lot of problems delivering goods to people, not places,” said Klas Bendrik, Group CIO at Volvo Car Group. This IoT-aided solution will benefit European logistics and transportation sector players since the cost of missed parcel deliveries in the region totals about 1 billion euros (C$1.44 billion) per year.
All these transactions and encounters create more data about individual consumers, where they live, how much they spend etc. After undergoing Big Data analysis, all the participants – vendors, car makers, carriers, government agencies etc. – will have more solid inputs at their disposal for developing future business plans and strategies.
Beyond track and trace
In the brave new world of Big Data/IoT, geographic positioning systems, (GPS) found on dashboards of almost all commercial vehicles are no longer a stand-alone tool. They are becoming two-way links that both send and receive continuous streams of data.
On the receiving end, they receive up-to-the minute traffic and weather traffic reports as well as the latest news on instructions about when and where to pick up or deliver goods. Such messages help drivers optimize their routes and work schedules to boost efficiency, productivity and customer service.
Similar to optimal asset utilization in warehousing operations, a connected fleet could also pave the way for predictive asset lifecycle management. This approach leverages analytics to predict asset failures and automatically schedule maintenance checks.
One example is MoDe (Maintenance on Demand) a research project involving Volvo, DHL, and others to create a commercially viable truck that independently decides when and how it requires maintenance thanks to sensors imbedded in the oil and damper systems, which identify material wear and tear. Data is sent first through a wireless network to a central unit in the truck and then for analysis at a maintenance platform. Finally, drivers or maintenance crews receive alerts of potential damage. The solution increased vehicle uptime by up to 30% and decreased potential danger to drivers.
Driver safety gets a further boost as carriers monitor drivers’ habits and behavior more closely. Caterpillar, the construction and mining equipment maker, has introduced this technology to prevent sleepy truck drivers from causing accidents. If it senses the driver’s focus is wavering, it activates audio alarms and seat vibrations. An infrared camera can analyze a driver‘s eye movements through glasses and in darkness.
All executives, not just those in the logistics and transportation sector, are being bombarded by studies and reports touting Big Data as a miracle worker. Since it is still very early days, decision makers need to remember that IT’s basic role is to analyze data that will help them to create more business value. Big Data is just the latest version of the long line of its forebears-decision support, data mining and business intelligence solutions.
A 2012 Wall Street article concluded, “Many CIOs believe data is inexpensive because storage has become inexpensive. But data is inherently messy- it can be wrong, it can be duplicative and it can be irrelevant -which means its requires handling, which is where the real expense comes in.”
Show me the money
DHL’s INSIGHT system that includes the Teradata Value Analyzer as a costing and profitability engine enabled the carrier to abandon its former standard costing program for more specific processes that ensure that customers, lanes and contracts are indeed profitable. According to Graeme Aitken, Plantation FL-based vice-president business controlling, DHL Express, each package is scanned between 50 to 100 times between pick up and final delivery. He says, “The data arrives about five minutes after being scanned which we feed into the costing system where algorithms can tell us if we are making money on the shipment.
“If we learn that that our deliveries to a receiver are not working out, we can talk to the client to fix it with more accurate data. It can be as simple as having the wrong postal code.”
The new approach can also pinpoint problems with its existing processes. Before, many Canadian B2C deliveries were held up because consumers did not know about or pay duties and taxes on imported goods. But now they can either receive electronic notices or check online and pay electronically to speed up deliveries.
The decision to install the original INSIGHT solution was based on savings from lower IT costs and staffing cuts with no promise of other benefits. Says Aitken, “Those amounted to about $500,000. But the analyzed data enabled us to improve our business processes and productivity, margins and profitability many times that amount.
“Now as we update the system, we can no longer claim those earlier cost reductions. But we now know that better, more accurate data leads us to better business decisions.”
To ensure that organizations extract what they need from sensor-sourced data flows that matter most to their business and for long it will remain relevant, executives and analysts must ask the right questions.
“Once you set up structural efficiencies [that include linking and integrating the various different IT platforms that serve different functions] benefits will start to roll in,” said Shaun Connolly, Teradata Corp.’s Annapolis MD-based International Program Director, Transport & Logistics. “The Holy Grail becomes listening to and analyzing every bit of data all the time. As those insights become more accurate, they make predictions more reliable, so you can make decisions in real time that will help employees do their jobs better. “True success results in building predictive maintenance algorithms,” he said.
Such advanced statistical tools have also launched business-expanding opportunities in aircraft support and repairs. Says Howard Woody, Irving TX-based president, AirLease International, “Aircraft OEMs such as Boeing now offer 10-year fixed or variable cost maintenance contracts of their Dreamliner aircraft to carriers. Buyers have an option, bring in a third-party service provider or sign with the OEM. Another option is to have the lessor which owns the asset include fixed-cost maintenance as part of the leasing contract with the carrier.
“It’s becoming more popular because engine performance data is now more accurate.”
Such “power-by-hour” leasing makes more sense because such expenses are treated as off-balance-sheet, operational costs not as capital costs with outright purchases. It also protects carriers from unforeseen engine failure or possible losses when the asset is finally sold. Lessees are paying for output and performance, not just buying an asset.
The dynamic duo has all the makings of a disruptive technology. Proceed with care, but proceed.