A discussion of the data produced from the IoT and how organizations need to organize to extract value from it.
The Internet of Things (IoT) is top of mind for every enterprise be it 100-year-old enterprises transforming into digital companies, enterprises with brick and mortar stores or enterprises part of complex supply chains.
The ability to sense the context and environment of your users, customers or partners in which they use or interact with your enterprise and use the sensed information to change how the device, app, business behaves and adapts will drive tremendous revenue growth and user satisfaction.
However, the real value from IoT will be realized only if enterprises are able to tame the variety of data generated from their IoT spectrum and if the speed of analysis and reanalysis exceeds that of their competitors.
Deriving business value beyond operational maintenance and management will require enterprises to think about the Data of Things (DoT). Inability to get a handle on DoT will be the most significant blocker to IoT ROI. Dealing with the DoT will impose some crucial challenges for enterprises.
Data of Things will be disparate
DoT will be disparate, messy, in constant flux and inherently incomplete in nature; it will be generated in diverse forms from a plethora of devices, systems, processes, applications and users. The number of disparate streams will be equal to the number of customer touch points multiplied by the number of platforms/devices multiplied by the number of systems and processes part of the data ingestion pipeline.
DoT will be sparse, compacted and compressed. It will require being contextualized, decorated and described with data and metadata from other data sources. It will need to be blended or harmonized with data sets that can resolve and describe the entities in DoT. It will also need to be blended or harmonized with data sets that describe the event as it was recorded. It will also need to be blended or harmonized with data from other related sensors that collect the context and environment metadata about the event.
The DoT quality will be unpredictable. Because the volume and diversity of data collection and routing mechanisms that will always use the cheapest route available on the Internet, the quality will change depending on internet availability, ingest system availability; availability that can and will vary by geo region, customer tier and device type. This variance in quality will require data collection systems that can not only detect loss in quality and fidelity but also analytics designed to adapt to in flux data while maintaining quality of insights that are still accurate and meaningful.
Data of Things will need agile exploration, experimentation and fast analysis
DoT will enable micro segmentation, micro messaging and micro behavior management. That is, enterprises will be able to control the behavior of micro segments across their network of connected devices, apps and systems. Enterprises will be able to micro manage to these micros segments with messages that are targeted, personalized and contextualized for each micro segment. As these behavior adjustments are made and messages are delivered, enterprises will have an almost instant feedback loop to understand the impact of these changes and messages. Enterprises will need to react very quickly and adapt or list user attention and/or business value.
The above will put a tremendous strain on the enterprise data pipelines and processing systems. In addition to faster data generation enterprises will have to focus on much faster data analysis. Experiments that used to take weeks to run and months to plan could be implemented and completed within hours. Micro segmentation that was not possible will be a required capability. This will require enterprises to invest in fast big data processing technologies. Fast hypothesizing and experimentation will require fast exploration at the speed of thought. This will require new technology stacks designed from the ground up for DoT.
Data of Things will mandate full and complete organizational alignment
DoT will create enormous security and privacy concerns. Constant streams of events that report fine grained details about users and what they do will need to be stored appropriately. Similarly, these bidirectional communication capabilities with these devices and apps will cause major security headaches for organizations as they have to deal with the potential of malicious entities taking over control of the devices or impersonating users.
Enterprises will need to build in analytical processes to uncover and highlight such breaches of privacy and security attacks as they happen. Ability to quickly detect and react will require alignment in the enterprise through tight collaboration between the analysts that detect such attacks, the security and privacy experts that triage severity and the agents at the edge of the enterprise that take corrective or defensive steps.
DoT will enable a big brother-like profile of end users. Enterprises will be able to track what they do, how they do it, when they do it and predict why/when they will do it next. This deep profile will enable enterprises to understand the users and create a relationship with them. However, real value from this depth of insight will require that product designers and builders, the marketers, the executive decision makers align and collaborate over individual user profiles and the aggregate segment and cohorts of users. Being able to share the same insight and interpretation of the insight will kickstart the value generation process.
Similarly, enterprises in a B2B or B2B2C setting or that are part of complex supply chains will be empowered to better and deeply understand the links between them and their upstream suppliers or downstream partners. To optimize these supply chains, enterprises will not only need to harmonize the point of view of their partner with their point of view (through the blending of underlying data that is being generated on both ends) but also share the insights that they are generating with their partners at the right granularity level without losing their intellectual property. This mode of collaboration will need to be granular yet flexible and grounded in real, harmonized data and analytics.
The IoT is here. Deriving business value from the IoT will require enterprises to solve the DoT problem. This problem will be three-fold; the complete picture will require the harmonization of multiple data sources generated from a diverse set of sensors across the various customer touchpoints and points in their lifecycle. Lack of fast data analysis, hypothesizing and experimentation will also be a hurdle towards IoT value extraction and in addition, the depth and breadth of data generated will mandate that the enterprise be fully aligned and operating from the same source and point of view of the truth.
Enterprises who can get a handle of their DoT will surely be able to ride the IoT wave.