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I wanted to gather all of my Internet of Things (IOT) blogs into a single blog (that I could later use with my University of San Francisco (USF) Big Data “MBA” course). However as I started to pull these blogs together, I realized that my IOT discussion lacked a vision; it lacked an end point towards which an organization could drive their IOT envisioning, proof of value, app dev, data engineering and data science efforts. And I think that the IOT end point is really quite simple… Creating “Smart” EntitiesI believe that the end point for many IOT initiatives is to create “smart” entities – smart cities, smart hospitals, smart cars, smart universities, smart schools, smart blogs, smart lawnmowers, etc. Creating a “smart” entity is an outcome of optimizing the decisions and business initiatives that support an entity’s business and operational objectives Yes, I think creating “smart” is as simple as that. But before I go any further, let me define some terms and a process that I am going to use throughout this blog (and likely in the forthcoming IOT and “smart” blog series):
Maybe the easiest way to understand the “smart” concept is with an example. For example, creating a “smart” city starts by first understanding the city’s business and operational objectives, which could include citizen quality of life, proactive business development, promoting tourism, top-quality schools and community safety. Next we need to identify the city’s 9 to 12 month business initiatives. One of the city’s business initiatives could be “improving traffic flow.” The decisions (or clusters of decisions) necessary to support the “improve traffic flow” business initiative could include (see Figure 1):
Note: decisions tend to cluster around common objectives or “themes.” We call these “clusters of decisions” around a common objective use cases. Getting Smart ExerciseLet’s see how this process of identifying the business initiatives, and ultimately the decisions, necessary to support a “smart” entity might work. I asked my University of San Francisco students to work in small groups to identify the university’s key business initiatives and to start brainstorming the decisions that the university would need to make to support those key business initiatives. The results were very impressive. The students came up with a load of different business initiatives (and associated clusters of decisions) that a “smart” university would need to cover (see Figure 1).  Figure 1: Sample of Business Initiatives and Supporting Decisions We consolidated the key business initiatives across the different teams and came up with the list in Figure 2.  Figure 2: Creating a “Smart” University of San Francisco By applying advanced analytics (yielding predictive and prescriptive insights) to the growing wealth of internal and external data sources, organizations can make better decisions and enhance the success of the organization’s key business initiatives. Ultimately, this is what helps the university become smarter. BTW, Don’t Forget The Human Component of IOTOne last point about IOT, it’s really more than just about “things.” To make the transition to smart, the discussion really needs to focus on the human component. Creating analytic or behavioral profiles on the humans involved in the operational and performance decisions – operators, mechanics, technicians, engineers – is critical if we want to optimize the decisions in support of a smart operational objectives. The IOT execution approach needs to include:
Most of the decisions that we are trying to optimize to create a smart operating entity involve humans. We’re not trying to create Skynet[1]. We’re trying to make the humans that are involved in the operations more effective with respect to the decisions that they need to make in support of their business initiatives. SummaryThe concept of “smart” should be utilized as an over-arching framework for organizations that are trying to envision the ultimate end point of their IOT journey. Integrating “Smart” into operational objectives can be a straight-forward and easy-to-grasp concept for any organization that embraces the Internet of Things. I’m excited to have the opportunity to help our clients integrate these concepts into their business models and strategies. IOT BlogsHere is a listing of the blogs that I have written on IOT, all in one place! Hope you enjoy them (as I’m sure that there will be more to come over the next several months). The Internet of Things (IoT) and Analytics at The Edge https://infocus.emc.com/william_schmarzo/internet-of-things-analytics-edge/ Big Data Business Model Maturity Index and the Internet of Things (IoT) https://infocus.emc.com/william_schmarzo/big-data-business-model-maturity-index-iot/ Internet of Things: “Connected” Does Not Equal “Smart” https://infocus.emc.com/william_schmarzo/internet-things-connected-not-equal-smart/ 5 Ways the Internet of Things Drives New $$$ Opportunities https://infocus.emc.com/william_schmarzo/5-ways-the-internet-of-things-drives-new-opportunities/ Simplifying The Internet of Things Conversation https://infocus.emc.com/william_schmarzo/simplifying-internet-things-conversation/ The Internet of Things and Its Impact on Your Privacy https://infocus.emc.com/william_schmarzo/the-internet-of-things-and-its-impact-on-your-privacy/ Understanding Skynet: Internet of Things vs. Industrial Internet Leveraging the Internet of Things for Fun and Profit https://infocus.emc.com/william_schmarzo/leveraging-the-internet-of-things-for-fun-and-profit/ GE Software Center: The Big Data Land of Oz https://infocus.emc.com/william_schmarzo/ge-software-center-the-big-data-land-of-oz/
[1] Skynet is from the Terminator movies. Skynet is a highly advanced, artificial intelligence system that saw humanity as a threat to its existence and triggered a nuclear holocaust and an army of Terminators against humanity. Not a good situation. The post Internet of Things: Getting From Connected To Smart appeared first on InFocus. |
