Inflection point of a curve is the point where the curve takes a considerable change in trajectory. The change in trajectory can be either positive or negative. The same is true with business growth.
An inflection point for a business occurs due to convergence of multiple events. These events could be related to market structure, competition, policy framework, advent of new technologies, and so on. In order to move towards a positive growth trajectory from an inflection point, organizations need to make strategic, decisive choices.
In today’s world, adopting disruptive[1] technologies is a preferred strategic choice.
Progressive organizations have made this choice of adopting disruptive technologies to come up with new business models, enhance customer experience, build smart products and services, and optimize business operations.
IIoT or Industrial internet of things is one such disruptive technology that has significant potential to propel organizations into a positive growth trajectory. Many organizations are realizing this and have started moving from IIoT proof of concepts to large scale deployments. However, designing, developing, deploying, and realizing business value from IIoT solutions is inherently complex and poses several difficult questions.
Designing and developing IIoT solutions - Any IIoT solution requires expertise on multiple technologies; Sensors, Field protocols, Edge processing, Device management, Data ingestion and storage, Stream processing, Analytics, Visualization. How to design and develop an IIoT solution covering these many technologies?
Acquiring Data – Large IIoT solutions invariably involve collecting data from a number of equipment and machinery of different types, makes, models, and vintages. How to extract required data from these equipment? How to “IoT enable” these different assets?
Leveraging the Edge - What functionalities should be at the edge? What functionalities should be in the cloud? What should be the level of intelligence at the Edge?
Choosing IoT Platforms – A plethora of IoT platforms are available in the market from various vendors. How to go about choosing a suitable platform? What are the strategic and operational considerations?
Security by design – IIoT security has to cover a wide canvas starting with sensors, field protocols, gateway, data transmission, data ingestion, storage, IoT platform, infrastructure and more. How to do a comprehensive threat modelling of the complete system and ensure that security is built in during the design stage?
Implementation at Scale – Once IIoT solutions are designed and developed, implementing these solutions at scale presents several challenges in the areas of Implementation planning, field force management, skill management, monitoring data quality, and sustenance. How to manage these challenges effectively?
Data, Analysis, and Insights – How to effectively ingest and store asynchronous data streams originating from different types of industrial assets? How to meaningfully analyse these large data sets and provide relevant insights to the right stakeholders?
Realizing Business value - What is required to realize business value from these insights? How to ensure that the insights are consumed and acted upon by the right people? How to drive change management?
Well, quite a lot of questions ...
As an Industry practitioner, i have had the opportunity to work hands-on in large scale Industrial IoT programs from inception to sustenance. I had the chance to work with great teams to define road-maps, build business cases, conceptualize and develop scalable and robust IIoT solutions to achieve specific business objectives, deploy these solutions at scale, and drive business value realization programs.
In the business world, the rear view mirror is always clearer than the windshield
- Warren Buffett
Beloved Readers, this blog is my attempt to organize and share my experience, learning, and insights that i have gained by looking at the rear view mirror throughout my Industrial IoT journey. I sincerely hope that this blog will help you effectively navigate your Industrial IoT journey by making your windshield clearer.
[1] To disrupt is to change the traditional way that an industry operates, especially in a new and effective way - dictionary.camridge.org
Excellent articulation Balaji. Add domain expertise requirement in IIoT
Awesome Balaji. Very well captured the typical challenges , queries , decision points for arriving at an IIoT solution.