by Cary Burch*
The popular Where’s Waldo represents the art of finding that one piece of relevant data among a sea of noise. The Internet of Things (IoT) is going to continue to change all that, taking Waldo from hidden artifact to prominent installation.
Finding data among a sea of noise is tough, and particularly so when one is dealing with the sheer volume and lack of structure presented by Big Data. The Internet of Things (IoT) with its many sensors will permit us to track so much more and gain a clearer line of sight into our business process that the unstructured and mammoth data streams within our reach will only multiply. Yet this will equally present an opportunity to substantively reduce the data’s assumed complexity. More specifically, those same sensors will be the key to identifying just where each salient piece of data lies amid each wave of normative information. The Internet of Things will show us the relevant relationship(s) among the data we have at our disposal, and allow us to always know just where to find Waldo.
IoT in and of itself is not a new concept. In fact, in 2010 McKinsey published The Internet of Things as part of its McKinsey Quarterly. McKinsey had back then categorized the application types anticipated of IoT including both categories for ‘Information and Analysis’, as well as ’Automation and Control’. I find the former to be of particular interest for The Org 3.0, because the prescribed activities here covering tracking and sensory expansion are the kinds of technologies and value-added applications which present an opportunity to let Big Data shine. To elaborate we begin with the words of Chui, Loffler, & Roberts of the McKinsey article:
“As the new networks link data from products, company assets, or the operating environment, they will generate better information and analysis, which can enhance decision making significantly. Some organizations are starting to deploy these applications in targeted areas, while more radical and demanding uses are still in the conceptual or experimental stages.”
Let’s take the example of DoppelLab, which according to Paradiso and Dublon in their recent work published in Scientific American describes this as software which, “gathers data from sensors placed throughout the MIT Media Lab and depicts them visually on a translucent model of the building”. This real world, current example is quite telling of where IoT is headed, what we might gain from IoT, and how IoT will soon meld with Big Data.
IoT is not simply about placing RFID tags on our products, or sensors in cars to determine which drivers of us are at greater risk of an accident (although this is a considerable place to start). IoT gives us greater visibility into the depths of our surrounding environment, and isn’t that what Big Data is striving to do as well? Are we not the product of a quest to determine just how patterns of behavior among our vendors, our staff, and our customers can each help us run an ever-evolving enterprise more effectively? Rather than moving to a prescriptive list of ways IoT should be regarded, or to a set of bullets about the sorts of projects where IoT and Big Data can come together, I would prefer to spend this time covering some of the questions I believe deserve asking such that we may all individually forge our future assuming that both Big Data and IoT will be in them.
What’s Your Waldo? This is our chance to take what we have already previously covered about Big Data and its boundaries, as well as what we discussed concerning performance management, and bring these concepts together. Namely, in the form of an identified target or project meant to be that critical proving ground for later, bigger projects. So what’s your Waldo? Are you looking for latent production efficiencies? For foot patterns in your retail store? The relative, average wear of every jet engine in your fleet? First determining the Waldo you are searching for, will mean all the difference when you decide whether Big Data and IoT are your tools of choice.
How Will You Know When You Find Him? Social media companies do a great job of exemplifying what is possible when Big Data is sifted, used, and insights reimagined as solutions among the business process. Yet where this is less obvious is perhaps an organization where Twitter followers and Facebook likes provide only some of the ammunition when learning how to improve customer relationships. Take as one example, Cold Stone Creamery. Yes there are a great many uses for social media when frequenting the ice cream shop, yet as the owner of a franchise will you base estimates of future revenue on the number of times pictures of “Birthday Cake Remix” are uploaded to the web? Likely not. Instead, one might combine streams of social media data with the kinds of information only IoT can deliver such as traffic patterns and amount of time customers are spending at each stage of the Cold Stone Creamery experience. What matters here is not the degree to which Big Data and IoT are blended, it only matters that what is being measured is crystal clear and agreed upon in advance. The key to remember is not to seek a measurement of indisputable, exhaustive caliber. The key to determining an appropriate measurement is to identify something or a collection of something’s which give way to a noticeable reduction in uncertainty.
When Will You Ask for Help? There are a plethora of examples which exist concerning the walled-off, protective activities among corporate leadership which effectively and perhaps unintentionally also isolate these same organizations from the supplier, complementary provider, and customer collaborative networks they need to thrive in today’s operating environment. Examples of failures to elicit feedback include the much-discussed lack of awareness to customer requirement of GM as described in Sutton’s work. Not to be outdone we have the famed Microsoft Zune. The question is not whether you will reach out and expand the boundaries of your organization, the question is when. Decisions on the use of IoT, thus, are not limited to the imagination of those already employed by your business. Those decisions can also be sourced to your suppliers, your complementary businesses, and your biggest advocates – your customers – as well. Examples of this in action include Connect + Develop by P&G. Crowdsourcing such efforts as Big Data, IoT, and the combination of the two permit for a faster go-to-market, as well as the potential for an enhanced relationships with key partners along the way.
Waldo has been hiding among the crowd for over 27 years now. With a considerable history and a great many children who connect with the task of finding him and his striped shirt, the search presses on in a number of settings on the pages of his books. What cannot remain the reality for today’s organization, is a similar search continue for our team’s Waldo. This, when we now have the scale, speed, and technology to bring our Waldo quickly to the surface.
* About the Author: Cary Burch is the Senior Vice President for Innovation at Thomson Reuters. He has logged more than two decades in the eBusiness and information technology industry, and is known in the technology industry for his keen business acumen and strong management expertise. In 2003, Burch was acknowledged as one of the TOP 20 IT Executives in the financial services industry by the Financial Services Executive Forum. https://www.linkedin.com/in/caryburch
Hyperlinks for the Above
The Internet of Things
Sensors in Cars
Cold Stone Creamery
Noticeable Reduction in Uncertainty
Connect + Develop
by Cary Burch*