Tag Archives: IoT
EpicMix is a website, data integration solution and web application that provides a great example of how companies can provide more value to their customers when they think about data-ready architecture. In this case the company is Vail Resorts and it is great to look at this as an IoT case study since the solution has been in use since 2010.
The basics of EpicMix
* RFID technology embedded into lift tickets provide the ability to collect data for anyone using one at any Vail managed. Vail realized they had all these lift tickets being worn and there was an opportunity to use them to collect data that could enhance the experience of their guests. It also is a very clever way to collect data on skiers to help drive segmentation and marketing decisions.
* EpicMix just works. If any guest wants to take advantage all they have to do is register on the website or download the mobile app for their Android or iOS smart phone and register. Having a low bar to use is important to getting people to try out the app and even if people do not use the EpicMix website or app Vail is still able to leverage the data they are generating to better understand what people do on the mountain. (Vail has a detailed information policy and opt out policy)
* Value added features beyond data visibility. What makes the solution more interesting are the features that go beyond just tracking skiing performance. These include private messaging between guests while on the mountain, sharing photos with friends, integration to personal social media accounts and the ability for people to earn badges and participate in challenges. These go beyond the generation one solution that would just track performance and nothing else.
This is the type of solution that qualifies as a IoT Personal Productivity solution and a Business Productivity solution.
- For the skier it provides information on their activity, communication and sharing information on social media.
- For Vail it allows them to better understand their guests, better communicate and offer their guests additional services and benefits and also how to use their resources or deploy their employees.
The EpicMix solution was made possible by taking advantage of data that was not being collected and then making it useful to users (skiers & guests). Having used EpicMix and similar performance tracking solutions the added communication and collaboration features are what sets it apart and the ease of use in getting started make it a great example of how fresh data can come from anywhere.
In the future it is easy to imagine features being added that streamlined ordering services for users (table reservation at the restaurant for Apre-ski) or Vail leveraging the data to make business decisions to provide more real time offers to guests on the mountain or frequent visitors on their next visit. And maybe we will see some of the new ski oriented wearables like XON bindings be integrated to solutions like EpicMix so it is possible to get even more data without having to have a second smart phone application.
Information for this post comes from Mapleton Hill Media and Vail Resorts
As reported by the Economic Times, “In the coming years, enormous volumes of machine-generated data from the Internet of Things (IoT) will emerge. If exploited properly, this data – often dubbed machine or sensor data, and often seen as the next evolution in Big Data – can fuel a wide range of data-driven business process improvements across numerous industries.”
We can all see this happening in our personal lives. Our thermostats are connected now, our cars have been for years, even my toothbrush has a Bluetooth connection with my phone. On the industrial sides, devices have also been connected for years, tossing off megabytes of data per day that have been typically used for monitoring, with the data tossed away as quickly as it appears.
So, what changed? With the advent of big data, cheap cloud, and on-premise storage, we now have the ability to store machine or sensor data spinning out of industrial machines, airliners, health diagnostic devices, etc., and leverage that data for new and valuable uses.
For example, the ability determine the likelihood that a jet engine will fail, based upon the sensor data gathered, and how that data compared with existing known patterns of failure. Instead of getting an engine failure light on the flight deck, the pilots can see that the engine has a 20 percent likelihood of failure, and get the engine serviced before it fails completely.
The problem with all of this very cool stuff is that we need to once again rethink data integration. Indeed, if the data can’t get from the machine sensors to a persistent data store for analysis, then none of this has a chance of working.
That’s why those who are moving to IoT-based systems need to do two things. First, they must create a strategy for extracting data from devices, such as industrial robots or ann Audi A8. Second, they need a strategy to take all of this disparate data that’s firing out of devices at megabytes per second, and put it where it needs to go, and in the right native structure (or in an unstructured data lake), so it can be leveraged in useful ways, and in real time.
The challenge is that machines and devices are not traditional IT systems. I’ve built connectors for industrial applications in my career. The fact is, you need to adapt to the way that the machines and devices produce data, and not the other way around. Data integration technology needs to adapt as well, making sure that it can deal with streaming and unstructured data, including many instances where the data needs to be processed in flight as it moves from the device, to the database.
This becomes a huge opportunity for data integration providers who understand the special needs of IoT, as well as the technology that those who build IoT-based systems can leverage. However, the larger value is for those businesses that learn how to leverage IoT to provide better services to their customers by offering insights that have previously been impossible. Be it jet engine reliability, the fuel efficiency of my car, or feedback to my physician from sensors on my body, this is game changing stuff. At the heart of its ability to succeed is the ability to move data from place-to-place.
Lately I have been thinking a lot about what is real and just marketing fluff with the Internet of Things (IoT). From all the stories written and people that I talk to it seems I am not alone. One day there is news of what at best is a communications company receiving +100M in funding and the next there is what amounts to a re-skinned mobile app claiming to be the real IoT.
This is the first part in a series of posts where I am going to define a framework for identifying real IoT solutions and the value that they provide. In addition I will provide actual examples of companies and solutions that fit this solution definition framework.
My main issue with the entire IoT universe is that a lot of the focus in on things that do not exist or that have been around a long time and have just been re-branded. Neither of these actually do justice to the concept of IoT that is very interesting, which is using distributed data and events to deliver totally new or dynamically better solutions (think 10x or more) compared to what exists today. We are talking revolutionary and not evolutionary.
From my point of view real IoT solutions need to address one or more of the following solution areas and I will be using these and additional criteria to build out the framework.
- Personal productivity
- Business productivity
- Business critical
- Life critical
Have another point of view? Feel free to share. My next post will focus on the segment of personal productivity.
At long last, the anxiously awaited rules from the FAA have brought some clarity to the world of commercial drone use. Up until now, commercial drone use has been prohibited. The new rules, of course, won’t sit well with Amazon who would like to drop merchandise on your porch at all hours. But the rules do work really well for insurers who would like to use drones to service their policyholders. So now drones, and soon to be fleets of unmanned cars will be driving the roadways in any numbers of capacities. It seems to me to be an ambulance chaser’s dream come true. I mean who wouldn’t want some seven or eight figure payday from Google for getting rear-ended?
What about “Great Data”? What does that mean in the context of unmanned vehicles, both aerial and terrestrial? Let’s talk about two aspects. First, the business benefits of great data using unmanned drones.
An insurance adjuster or catastrophe responder can leverage an aerial drone to survey large areas from a central location. They will pin point the locations needing attention for further investigation. This is a common scenario that many insurers talk about when the topic of aerial drone use comes up. Second to that is the ability to survey damage in hard to reach locations like roofs or difficult terrain (like farmland). But this is where great data comes into play. Surveying, service and use of unmanned vehicles demands that your data can answer some of the following questions for your staff operating in this new world:
Where am I?
Quality data and geocoded locations as part of that data is critical. In order to locate key risk locations, your data must be able to coordinate with the lat/long of the location recorded by your unmanned vehicles and the location of your operator. Ensure clean data through robust data quality practices.
Where are my policyholders?
Knowing the location of your policyholders not only relies on good data quality, but on knowing who they are and what risks you are there to help service. This requires a total customer relationship solution where you have a full view of not only locations, but risks, coverages and entities making up each policyholder.
What am I looking at?
Archived, current and work in process imaging is a key place where a Big Data environment can assist over time. By comparing saved images with new and processing claims, claims fraud and additional opportunities for service can be detected quickly by the drone operator.
Now that we’ve answered the business value questions and leveraged this new technology to better service policyholders and speed claims, let’s turn to how great data can be used to protect the insurer and drone operator from liability claims. This is important. The FAA has stopped short of requiring commercial drone operators to carry special liability insurance, leaving that instead to the drone operators to orchestrate with their insurer. And now we’re back to great data. As everyone knows, accidents happen. Technology, especially robotic mobile technology is not infallible. Something will crash somewhere, hopefully not causing injury or death, but sadly that too will likely happen. And there is nothing that will keep the ambulance chasers at bay more than robust great data. Any insurer offering liability cover for a drone operator should require that some of the following questions be answered by the commercial enterprise. And the interesting fact is that this information should be readily available if the business questions above have been answered.
- Where was my drone?
- What was it doing?
- Was it functioning properly?
Properly using the same data management technology as in the previous questions will provide valuable data to be used as evidence in the case of liability against a drone operator. Insurers would be wise to ask these questions of their liability policyholders who are using unmanned technology as a way to gauge liability exposure in this brave new world. The key to the assessment of risk being robust data management and great data feeding the insurer’s unmanned policyholder service workers.
Time will tell all the great and imaginative things that will take place with this new technology. One thing is for certain. Great data management is required in all aspects from amazing customer service to risk mitigation in operations. Happy flying to everyone!!
I had the opportunity to participate in the Boulder edition of the “Where are your Wearables” Hackfest last week hosted by Quick Left.
With over a 100 people showing up and lots of first time hackers we saw eight teams form up with a mix of talents. Being a non-coder myself I simply picked a group that was not too big and offered my product talents in talking through concepts. More on what we built in a moment.
Hackfests almost always create issues when it comes to integration. Unless someone on the team already knows a lot about an API the first issues are getting setup.
- Connecting to data. Most teams used the Fitbit API only or a couple had another device they brought and then used that as a data source. Most teams spent time just getting access to the API setup, OAuth working and then dumping their data into a client for the app (if they got that far)
- Security. OAuth was a requirement for the Fitbit API which is pretty standard these days. The team I worked on had some issues that slowed us down getting this to work correctly.
- Clean data & real-time data. Given most teams had a basic scenario we were all only working with a single data set, but still getting access to the data in real-time for the client app added complexity to the solution. In the real world for most wearables to break through the basic health examples we see today they are going to need to blend multiple data sets to provide value to the end user.
A few thoughts on the solutions that were built
Most of the teams just tried to get one integration working and then add a secondary calculation or evaluation that would provide the value to the user. It’s only 3 hours and the KISS principle was generally followed by the best examples of the night.
In no order these were some of the solutions that stood out to me.
WaterGoals: Wearable integrated: Fitbit. This seemed like a very practical solution. The idea was that a lot of people are not able to read the display screen on the typical watch if they are exercising so why not integrate the data and add visuals that give them data like heart rate and water consumption. For example, the data could be integrated into the clothing they are wearing and either a single visual element or the entire garment could change color based on the person being below or above their hear rate goal range. Another example was adding a touch pad that would add a quantity of water consumed – say 1 cup – when the person pushed it while they were exercising because it’s not easy to fumble with your wearable.
Fitbeer: Wearable integrated: Fitbit. I worked on this team and the idea was just to provide an easy way for someone to track consumption of any liquid, but we used beer for the example. By tracking an activity type on a Fitbit and identifying arm movement the goal would be to track the number of times a person picked up their glass to consume and track real-time the calories being burned by the activity and the calories being consumed. In addition we planned an integration to Twitter so someone could share their results as a social component.
Where’s the damn remote: Wearable integrated: Myo armband. This team used a Myo to integrate to an Apple TV so they could do selection of shows/movies/music with hand gestures. This was interesting since they had to define the hand gestures and then do the integration to map them to get the desired action in the Apple TV. This was the most real demo of the night in terms of fully working.
My main take away from the event was that people are still searching for the way that wearables can be dead simple for the user and provide lots of value. Most of the generation 1 solutions provide some type of health measurements and now also provide access to the Internet (e.g. Google Glass) but finding ways to combine multiple data sets to provide a life changing solution are what will let us know when we are starting to see generation 2 solutions. And for the enterprise IT area it still seems wearables are a long way off as they remain very much a consumer oriented solution today with some things to work out before we see anything but very early experimentation for enterprise IT.
Data has always played a key role in informing decisions – machine generated and intuitive. In the past, much of this data came from transactional databases as well as unstructured sources, such as emails and flat files. Mobile devices appeared next on the map. We have found applications of such devices not just to make calls but also to send messages, take a picture, and update status on social media sites. As a result, new sets of data got created from user engagements and interactions. Such data started to tell a story by connecting dots at different location points and stages of user connection. “Internet of Things” or IoT is the latest technology to enter the scene that could transform how we view and use data on a massive scale.
Does IoT present a significant opportunity for companies to transform their business processes? Internet of Things probably add an important awareness veneer when it comes to data. It could bring data early in focus by connecting every step of data creation stages in any business process. It could de-couple the lagging factor in consuming data and making decisions based on it. Data generated at every stage in a business process could show an interesting trend or pattern and better yet, tell a connected story. Result could be predictive maintenance of equipment involved in any process that would further reduce cost. New product innovations would happen by leveraging the connectedness in data as generated by each step in a business process. We would soon begin to understand not only where the data is being used and how, but also what’s the intent and context behind this usage. Organizations could then connect with their customers in a one-on-one fashion like never before, whether to promote a product or offer a promotion that could be both time and place sensitive. New opportunities to tailor product and services offering for customers on an individual basis would create new growth areas for businesses. Internet of Things could make it a possibility by bringing together previously isolated sets of data.
Recent Economist report, “The Virtuous Circle of Data: Engaging Employees in Data and Transforming Your Business” suggests that 68% of data-driven businesses outperform their competitors when it comes to profitability. 78% of those businesses foster a better culture of creativity and innovation. Report goes on to suggest that 3 areas are critical for an organization to build a data-driven business, including data supported by devices: 1) Technology & Tools, 2) Talent & Expertise, and 3) Culture & Leadership. By 2020, it’s projected that there’ll be 50B connected devices, 7x more than human beings on the planet. It is imperative for an organization to have a support structure in place for device generated data and a strategy to connect with broader enterprise-wide data initiatives.
A comprehensive Internet of Things strategy would leverage speed and context of data to the advantage of business process owners. Timely access to device generated data can open up the channels of communication to end-customers in a personalized at the moment of their readiness. It’s not enough anymore to know what customers may want or what they asked for in the past; rather anticipating what they might want by connecting dots across different stages. IoT generated data can help bridge this gap.
How to Manage IoT Generated Data
More data places more pressure on both quality and security factors – key building blocks for trust in one’s data. Trust is ideally truth over time. Consistency in data quality and availability is going to be key requirement for all organizations to introduce new products or service differentiated areas in a speedy fashion. Informatica’s Intelligent Data Platform or IDP brings together industry’s most comprehensive data management capabilities to help organizations manage all data, including device generated, both in the cloud and on premise. Informatica’s IDP enables an automated sensitive data discovery, such that data discovers users in the context where it’s needed.
Cool IoT Applications
There are a number of companies around the world that are working on interesting applications of Internet of Things related technology. Smappee from Belgium has launched an energy monitor that can itemize electricity usage and control a household full of devices by clamping a sensor around the main power cable. This single device can recognize individual signatures produced by each of the household devices and can let consumers switch off any device, such as an oven remotely via smartphone. JIBO is a IoT device that’s touted as the world’s first family robot. It automatically uploads data in the cloud of all interactions. Start-ups such as Roost and Range OI can retrofit older devices with Internet of Things capabilities. One of the really useful IoT applications could be found in Jins Meme glasses and sunglasses from Japan. They embed wearable sensors that are shaped much like Bluetooth headsets to detect drowsiness in its wearer. It observes the movement of eyes and blinking frequency to identify tiredness or bad posture and communicate via iOS and android smartphone app. Finally, Mellow is a new kind of kitchen robot that makes it easier by cooking ingredients to perfection while someone is away from home. Mellow is a sous-vide machine that takes orders through your smartphone and keeps food cold until it’s the exact time to start cooking.
Each of the application mentioned above deals with data, volumes of data, in real-time and in stored fashion. Such data needs to be properly validated, cleansed, and made available at the moment of user engagement. In addition to Informatica’s Intelligent Data Platform, newly introduced Informatica’s Rev product can truly connect data coming from all sources, including IoT devices and make it available for everyone. What opportunity does IoT present to your organization? Where are the biggest opportunities to disrupt the status quo?
I have worked with several clients in the Internet of Things space over the last year and really enjoyed all of the engagements.
First, I am not a fan of the term IoT/Internet of Things. It just seems to be a bit too much pie in the sky and marketing. It reminds me a lot of the people who put an “e” or “i” in front of everything in the late 90s and early 00s. To me this is about expanded data integration use cases (e.g. more end points that you have the choice to access), data filtering and processing (e.g. what is the data you actually care about) and work flow/bpm from an enterprise perspective. (can you automate tasks and actions based on data or analysis of data)
There are definitely advancements in technology that are making for some very interesting solutions. My Nest thermostat is really cool, but it’s not really changing the world as one might think from some of the IoT frenzy the last few years. From what I have seen I think there are three main real world solutions that fit under the concept of IoT.
1) Passive Monitoring. This amounts to data collection and filtering. Lots of the consumer facing solutions fall into this category. Wearables, which we are told are super hot or just all the huge amount of big data collection that will then be churned and analyzed or just sit as it builds up. A big issue here is there is a lot of data to collect from an every growing set of end points but more data is not always useful if a company has not set up a process and a way to filter and identify the actual important data. I think the impact on individuals is more real than companies in this segment. I know people who swear they live better because of the data from their CPAP for example.
2) Active Monitoring. Most of these use cases fall into alerting or rule based work flow. There are examples of companies taking existing solutions or evolving existing solutions to then use real-time or near real-time data to drive work flow or alerts to make sure someone actually does something. My next write up is going to focus on an example in this space where a company has creating some really great technology to track usage of a product so they can provide real time view of inventory and then drive either automated replacement orders or work flow for people to do something like order more.
3) Automated response. To me a lot of the so called IoT use cases fall into a re-branding of solutions that have been around for years but now there is a mobile client. This is where all the security, energy (e.g. smart meters) and home automation fit.
Over the next 10 years I could see additional patterns become real, but a lot of the landscape is more hope than real when it comes to IoT from an enterprise company point of view or a how it really impacts a person’s life point of view. Of course I would expect other people would break down the use cases differently and I would love to hear your point of view.
(Note: IoT Landscape Chart is re-posted from work by First Mark Capital’s Matt Turck)
Consumer demand is driving the adoption of IoT as they embrace the new technology to improve health (Garmin Vívoactive), energy savings (NEST), safety (BeClose) and a better overall experience including shopping (beacons?). However, getting the balance between privacy, intrusion and relevance can be tricky for both the retailer and shopper.
While shoppers are willing to give up some level of privacy in return for personalization, I am not convinced most are ready of what the “Internet of Things” brings. I recently purchased a smart TV and was surprised when I was asked to accept terms and conditions before using, what are they capturing, how will it be used, will I see any benefits? Retailers need to demonstrate value and trust to the consumer.
While RFID has been around for many years the next wave of intelligent “things” bring both opportunities and challenges. Retailers need to decide which ones truly enhance the shopping experience.
“Psst! It’s Me, the Mannequin. This Would Look Great on You.” (Rachel Abrams, NY Times)
Smart Dummies (mannequins) – Last year House of Fraser started rolling out beacon-enabled mannequins to engage directly with shoppers and passers-by. Shoppers within a 50-metre range will receive information from the mannequins, which may include details about the clothes on display, with links to make a purchase from a website, or details of where the outfit can be found in the store. The next step could link customer preferences, profile and past purchases and suggest matching accessories, check customers size availability or monitor how long they browsed and offer a digital coupon.
Connected Hangers – While you browse through the racks, real-time reviews are displayed on the hanger, size availability or images & videos displayed on screens showing the garment in use. Retailers can capture how popular an item is but never purchased. Taking the clothes and hanger try on could provide personalized recommendation on shoes and accessories.
Personalized Mirrors – I recently read an article in Time (Dec 29th) about Rebecca Minkoff’s new store in Manhattan, where they installed a giant mirrored panel showing images of models walking down the runway. The panel acts as a mirror and touchscreen, where shoppers can order up a personalized fitting room, offering style tips based on their selection. This is connected to a mobile app that saves their browsing history and style preferences for their next visit. When a customer is ready to purchase a sales assistant takes payment on an iPad.
In future blog I will discuss how location based services are machine-to-machine technologies are impacting retailers and consumers.
With so many devices connected and larger volumes of data captured this raises concerns around data privacy and security. In the past year we have seen too many stores on data breaches and retailers. While shoppers are prepared to share more information for relevance they expect you to keep it safe and secure. Retailers must have a solid data governance framework and process in place or risk losing the trust and loyalty of their customers.
Sensor Driven Analytics
The Internet of Things presents retailers with a wonderfully opportunity to understand and engage the customer like never before. However, retailers need to manage the explosion of data available through smarter devices to gain insight into shopper behaviours and preferences and turn into a more rewarding experience for the consumer.
However, before loading an analytics engine they need to ensure the data is clean, connected and safe. Without this any decisions made are flawed and will impact their brand and ultimately the bottom line.
Marketers, Are You Ready? The Impending Data Explosion from the New Gizmos and Gadgets Unveiled at CES
This is the first year in a very long time that I wasn’t in Las Vegas during CES. Although it’s not quite as exciting as actually being there, I love that the Twitter-verse and industry news sites kept us all up to date about the latest and greatest announcements. Now that CES2015 is all wrapped up, I find myself thinking about the potential of some very interesting announcements – from the wild to the wonderful to the leave-you-wondering! What strikes me isn’t how useful these new gizmos and gadgets will likely be to myself and my consumer counterparts, but instead what incredible new data sources they will offer to my fellow marketers.
One thing is for sure… the connected “Internet of Things” is indeed here. It’s no longer just a vision. Sure, we’re just seeing the early stages, but it’s becoming more and more main stream by the day. And as marketers, we have so much opportunity ahead of us!
I ran across an interesting video interview on the CES show floor with Jack Smith from GroupM on Adweek.com. Jack says that “data from sensors will have a bigger impact, longer term, than the Internet itself.” That is a lofty statement, and I’m not sure I’ll go quite that far yet, but I absolutely agree with his premise… this new world of connectivity is already shifting marketing, and it will almost certainly radically change the way we market in the near future.
Riding the Data Explosion (Literally)
The Connected Cycle is one of the announcements that I find intriguing as a marketer. In short, it’s a bike pedal equipped with GPS and GPRS sensors that “monitor your movements and act as a basic fitness tracker.” It’s being positioned as a way to track stolen bicycles, which is a massive problem in Europe particularly, with the side benefit of being a powerful fitness tracker. It may not be as sexy as some other announcements, but I think there is buried treasure in devices like these.
Imagine how powerful that data would be to a sporting goods retailer? What if the rider of that bicycle had opted into a program that allowed the retailer to track their activity in exchange for highly targeted offers?
Let’s say that the rider is nearing one of your stores and it’s a colder than usual day. Perhaps you could push them an offer to their smart phone for some neoprene booties. Or let’s say that, based on their activity patterns, the rider appears to be stepping up their activity and is riding more frequently suggesting they may be ready for a race you are sponsoring in a few months in the area. Perhaps you could push them an inspirational message saying how great they’re progressing and had they thought about signing up for the big race, with a special incentive of course.
The segmentation possibilities are endless, and the analytics that could be done on the data leaves the data-driven marketer salivating!
Home Automation Meets Business Automation
There were numerous announcements about the connected “house of the future”, and it’s clear that we are just beginning of the home automation wave. Several of the big dogs like Samsung, Google, and Apple are building or buying automation hub platforms, so it’s going to be easier and easier to connect appliances and other home devices to one another, and also to mobile technology and wearables. As marketers, there is incredible potential to really tap into this. Imagine the possibility of interconnecting your customers’ home automation systems with your own marketing automation systems? Marketers will soon be able literally serve up offers based upon things that are occurring in the home in real time.
Oh no, your teenage son finished off all but the last drop of milk (and put the almost-empty jug back in the fridge without a second thought)! Not to worry, you’ve linked your refrigerator’s sensor data with your favorite grocery store. An alert is sent asking if you want more milk, and oh by the way, your shopping patterns indicate you may be running out of your son’s favorite cereal too, so it offers you a special discount if you add a box to your order. Oh yeah, of course he was complaining about being out just yesterday! And whala, a gallon of milk and some Cinnamon Toast Crunch magically arrives at your door by the end of the day. Heck, it will probably arrive within an hour via a drone if Amazon has anything to say about it! No manual business processes whatsoever. It’s your appliance’s sensors talking to your customer data warehouse, which is talking to your marketing automation system, which is talking to a mobile app, which is talking to an ordering system, which is talking to a payment system, which is talking to a logistics/delivery system. That is, of course, if your internal processes are ready!
Some of the More Weird and Wacky, But There May Just Be Something…
Panasonic’s Smart Mirror allows you to analyze your skin and allows you to visualize yourself with different makeup or even a different haircut. Cosmetics and hair care companies should be all over this. Imagine the possibilities of visualizing yourself looking absolutely stunning – if only virtually – with perfect makeup and hair. Who wouldn’t want to rush right out and capture the look for real? What if a store front could virtually put the passer-byer in their products, and once the customer is inside the store, point them to the products that were featured? Take it a step further and send them a special offer the next week to come back buy the hat that just goes perfectly with the rest of the outfit. It all sounds a little bit “Minority Report-esque”, but it’s closer to becoming true every day. The power of the interconnected world is endless for the marketer.
And then there’s Belty… it’s definitely garnered a lot of news (and snarky comments too!). Belty is a smart belt that slims or expands based upon your waist size at that very moment – whether you’re sitting, standing, or just had a too-large meal. I don’t see Belty taking off, but you never know! If it does however, can’t you just see Belty sending a message to your Weight Watchers app about needing to get back on diet? Or better yet, pointing you to the Half Yearly Sale at Nordstrom because you’re getting too skinny for your pants?
The “Internet of Things” is Becoming Reality… Is Your Marketing Team Ready?
The internet of things is already changing the way consumers live, and it’s beginning to change the way marketers market. With the It is critical that marketers are thinking about how they can leverage the new devices and the data they provide. Connecting the dots between devices can become a marketer’s best friend (if they’re ready), or worst enemy (if they’re not).
Are you ready? Ask yourself these 6 questions:
- Are your existing business applications connected to one another? Do your marketing systems “talk” to your finance systems and your sales systems and your customer support systems?
- Do you have fist-class data quality and validation technology and practices in place? Real-time, automated processes will only amplify data quality problems.
- Can you connect easily to any new data source as it becomes available, no matter where it lives and no matter what format it is in? The only constant in this new world is the speed of change, so if you’re not building processes and leveraging technologies that can keep up, you’re already missing the boat!
- Are you building real time capabilities into your processes and technologies? You systems are going to have to handle real-time sensor data, and make real-time decisions based on the data they provide.
- Are your marketing analytics capabilities leading the pack or just getting out of the gate? Are they harnessing all of the rich data available within your organization today? Are you ready to analyze all of the new data sources to determine trends and segment for maximum effect?
- Are you talking to your counterparts in IT, logistics, finance, etc. about the business processes and technologies you are going to need to harness the data that the interconnected world of today, and of the near future? If not, don’t wait! Begin that conversation ASAP!
Informatica is ready to help you embark on this new and exciting data journey. For some additional perspectives from Informatica on the technologies announced at CES2015, I encourage you to read some of my colleagues’ recent blog posts:
There is a new “Band Wagon” out there and it’s not Big Data. If you were at this year’s CES Show this past week, it would have been impossible even with a “Las Vegas-size” hangover not to have heard the hype around the Internet of Things (IoT). The Internet of Things includes anything and everything that is connected to the Internet and able to communicate and share information with other “smart” devices. This year as well as last it was about home appliances, fitness and health monitors, home security systems, Bluetooth enabled toothbrushes, sensors in shoes to monitor weight and mileage, thermostats that monitor humidity and sound, to kitchen utensils that can track and monitor the type of food you cook and eat.
If you ask me, all these devices and the IoT movement is both cool and creepy. Cool in the sense that networking technology has both matured and become affordable for devices to transmit data for companies to turn into actionable intelligence. IoT is creepy in the sense where do I really want someone monitoring what I cook or how many times I wake up and night? Like other hype cycles or band wagons, there are different opinions as to the size of the IoT market. Gartner expects it to include nearly 26 billion devices, with a “global economic value-add” of $1.9 trillion by 2020. The question is whether the Internet of Things is truly transformational to our daily lives? The answer to that really depends on being able to harness all that data into information. Just because my new IoT toothbrush can monitor and send data on how many times I brush my teeth, it doesn’t provide any color whether that makes me healthier or have a prettier smile :).
To help answer these questions, here are examples and potential use cases of leveraging all that Big Data from Small devices of the IoT world:
- Mimo’s Smart Baby Monitor is aimed at helping to prevent SIDS, the Mimo monitor is a new kind of infant monitor that provides parents with real-time information about their baby’s breathing, skin temperature, body position, and activity level on their smartphones.
- GlowCaps fit prescription bottles and via a wireless chip provide services that help people stick with their prescription regimen; from reminder messages, all the way to refill and doctor coordination.
- BeClose offers a wearable alarm button and other discrete wireless sensors placed around the home, the BeClose system can track your loved one’s daily routine and give you peace of mind for their safety by alerting you to any serious disruptions detected in their normal schedule.
- Postscapes provides technology a suite of sensors and web connectivity help save you time and resources by keeping plants fed based on their actual growing needs and conditions while automating much of the labor processes.
- OnFarm solution combines real-time sensor data from soil moisture levels, weather forecasts, and pesticide usage from farming sites into a consolidated web dashboard. Farmers can use this data with advanced imaging and mapping information to spot crop issues and remotely monitor all of the farms assets and resource usage levels.
- Banks and auto lenders are using cellular GPS units that report location and usage of financed cars in addition to locking the ignitions to prevent further movement in the case of default.
- Sensors on farm equipment now provides real-time intelligence on how many hours trackers are used, the weather conditions to predict mechanical problems, and measuring the productivity of the farmer to predict trends in the commodity market.
I can see a number of other potential use cases for IoT including:
- Health devices not only sending data but receiving data from other IoT devices to provide real time recommendations on workout routines based on weather data received from real-time weather sensors, food intake from kitchen devices, to nutritional information based on vitamins and medications consumed by the wearer.
- Credit card banks leveraging their GPS tracking device data from auto loan customers to combine it with credit card data to deliver real-time offers on merchant promotions while on the road.
- GPS tracking devices on hotel card keys to track where you go, eat, entertain to deliver more customized services and offers while one is on a business trip or vacation.
- Boxing gloves transmitting the impact and force of a punch to monitor for athlete concussions.
What does this all mean?
The Internet of Things has changed the way we live and do business and will continue to shape the future hopefully in a positive way. Harnessing all of that Big Data from Small devices does not come easily. Every device that generates data sends it to some central system through WiFi or cellular network. Once in that central system, it needs to be access, translated, transformed, cleansed, and standardized for business use with data from other systems that run the business. For example:
- Access, transform, and validate data from IoT with data generated from other business applications. Formats and values will be often different and change over time and needs to be rationalized and standardized for downstream business use. Otherwise, you end up with a bunch of Alphas and Numerics that make no sense.
- Data quality and validation: Just because a sensor can send data, it does not mean it will send the right data or data that is right for a business user trying to make sense of it. GPS data requires accurate coordinate data. If any value is transmitted incorrectly, it is important to identify those errors; more importantly correct it so the business can take action. This is especially important when combining like values (e.g. Weather status = Cold, Wet, Hot however the device is sending A,B, C)
- Shared with other systems: Once your data is ready to be consumed by new and existing analytic applications, marketing systems, CRM, or your fraud surveillance systems, it needs to be available in in real-time if required, in the right format, and structure as required by those applications and doing it in a way that is seamless, automated, and does not require heavy IT lifting.
In closing, IoT’s future is bright along with the additional insights gained from all that data. Consider it Cool or Creepy one thing is for sure, the IoT band wagon is in full swing!