This blog was inspired by a web seminar created and hosted by Fast Lane's VP of Sales and Marketing, David Mantica. To view the recording of this web seminar, click here.
Internet of Things (IoT) & Digital Transformations (DX)
A common misconception on the Internet of Things (IoT) is assuming that it is a form of technology. IoT is actually a complex ecosystem with an ever growing network of physical objects that feature an IP address for internet connectivity and the communication that occurs between these objects and other Internet-enabled devices and systems.
Fundamentally, the Internet of Things (IoT) is about the transformation of any physical object into a digital footprint. As such, with all these new digital footprints, data is growing at such an exponential rate that containing and understanding this data is becoming more difficult.
Ultimately, the inherent value of this dramatic growth in IoT is that it allows enterprises the ability to listen more and more to data in the Technology Ecosystem. To take advantage of the IoT requires SDLC professionals to embrace Digital Transformation solutions (e.g., design thinking, testing, and Lean development) versus a fix-it only if it’s broken mentality.
The ecosystem that forms the IoT pulls information from disparate systems at different levels and across different situations (e.g., smart buildings, smart energy, smart health). Each of these different systems and situations has unique digital solutions that may or may not be propriety. They each provide unique and valuable solutions that companies can leverage for growth. However, for companies who are accustomed to only use proprietary software cannot leverage these tools as successfully for gathering data and knowledge. Using solely proprietary software is not sustainable for growth since technology is continuously developing and new proprietary solutions are continuously available. Many different technologies exists today that looking for a sole provider for systems that fit well together is not possible. Companies will benefit more by looking across the board at technologies that fit into their business needs. In instances today, figuring out how all the technologies will fit together is the greatest challenge that could reap many benefits if championed.
As a starter into this introduction of mixing proprietary solutions, vendors and distributors currently work together to determine how different technologies fit together prior to selling products to customers.
What DOES digital Disruption Really Mean?
As part of the IoT and its foundational ecosystem, the speed of growth in technology has decreased the length of time it takes for companies to be disrupted by environment, new technologies, and economics. The length of time has decreased from 37 years to 10-14 years today. As an example, we have moved from mortar/brick banks to online banking within the last few years. This drastic reduction in time for disruption is escalated by Digital Disruption which occurs when companies listen to the data through the IoT. By listening to this available data, companies not only automate traditional roles of human resources but also innovate improved ways for engaging customers.
IoT LoB Vision Statement
To keep up with the rate of Digital Disruption, companies must continuously innovate new technologies by using Lean transformation. The benefit of Lean is not just the associated processes but rather the mindset required for companies to consider how to build new solutions.
Lean is especially effective because it focuses on tackling Adaptive Challenges (high impact and highly innovative solutions) instead of Technical Problems (limited solutions based on issue symptoms). From a digital solutions perspective, companies must look for solutions to transform their systems with data.
For example, Netflix uses behavior of what shows people watch (e.g., binge watching 4 shows indicates user acceptance) and subsequently builds those types of shows to attract customers. In this scenario, Netflix championed an Adaptive Challenge by meeting the needs of customers that weren’t necessarily obvious. The needs were discovered through tracking behavioral data from Netflix users.
State of IoT/DX
With all the new data, systems, scenarios, and transformations of the IoT, the state of IoT today is a confusion of terms. The components that make up the state of IoT are Components, Devices, Connectivity systems, and Platforms. Ultimately, the Components and the Devices have the capability to sense data. The Connectivity systems (e.g, Internet) help maintain network and security when seeking this data. The Platform stores data as unstructured or structured data that was gathered by the Components and Devices. To properly use the Platform and stored data, SDLC professionals most know how to use query tools to access the unstructured data (e.g., social media post). Unstructured may be the most difficult data to understand, but it also the most valuable for business insights.
As such, IoT is the key driver of Digital Transformation (DX). The spectrum of DX spans the Customer Experience, Operational Process, and Business Model of every enterprise:
- Operational Processes help gather data
- Customer Experience shows how to benefit from using the data
- Business Model is changed by the use of that data.
IoT drives all this digital transformation because it enables listening to produce data. The entire story of IoT is that data is produced as structured or unstructured data which is then used for developing solutions.
Data: What Makes Data so Special?
Data drives business insights, which drives business decisions, which can ultimately drive a Digital Transformation, which causes a Digital Disruption. Because of the IoT, the available data for driving business insights keeps growing, but it is not always valuable. For example, unstructured data is more difficult to manage but can provide great Insights. Analysis of unstructured data to determine insights is one dimensional – meaning it requires human resources to discover insights and drive business decisions. As a result, analysis and interpretation of data is biased and subjective. Since data is more valuable when combined with other data situations, analytics tools help human resources analyze the data to ultimately see the value of data Insights to drive decisions. At least until machine learning has progressed to automate the data analysis process.
AI and IoT
The amount of data available has increased the complexity of data analysis, and this data along with computing power are enabling AI (machine learning). AI essentially drives the growth of IoT exponentially, because data analysis becomes second dimensional. Even in the early stages of AI where human resources currently program computers to analyze data and provide predictive results, the predictive results become more accurate the more data a machine stores. The more data means the standard deviation decreases, essentially making the machine smarter. The next level of AI is Deep Learning which is essentially a machine that runs on its own without requiring human resources to program learning capabilities. In this instance, the system itself is building the models for predictive analysis.
IoT/DX Human Capital
Even though we’re years away from machines taking over our human processing roles, it is on the horizon as machine learning improves. However, the future of machine learning doesn’t diminish the significance of the human component in IoT. To understand the swathes of hidden information in unstructured and structured data and reap their benefits, we still require Business Solution Architect, Solution Architect, and Application Developer roles. These human resources must be able to automate processes, build solutions that use that data successfully, and understand platforms as a business model.