Fast and Furious Technology: From HFT to IoT

Think about technical features beyond the first initial use cases, which are often internal, and take the time to investigate the features that would be required if the use case were to become customer-facing. It would probably mean that functionality not only has to be re-brandable but it should also be able to comply with new laws such as EU’s General Data Protection Regulation (GDPR) (meaning that you have to understand if multi-tenancy and data separation through private instances are required for your organization).

Consider the Maturity Curve

Once you understand the technology better, it is time to come to grips with use cases that adhere to the maturity curve. The use case complexity has to be aligned with the maturity of the organization. If any use case is too advanced for the organization, then the learning curve becomes too steep and adoption becomes too expensive.

An easy way to think about this is to view your organization’s competency on a scale of three stages.

1. The data-centric stage: This stage means that your organization can handle data volumes generated by devices at a large scale, along with connectivity and device management issues. It can store the data generated by those devices continuously in a reliable way. On top of that, parts of your organization understand how to get access to this data and how to visualize it in one form or another.
2. The process-centric stage: Once the data stage is passed, you might want to alter existing processes to take advantage of the insights generated by the data, or even create new processes. A relevant example might be how an automatic replenishment process can take advantage of real-time inventory data feeds, ensuring that customers are never out of stock.
3. The analytics-centric stage: In this phase, data scientists are analyzing the data and creating new advanced analytic models such as machine learning and artificial intelligence models to create predictions and actions that automatically optimize decisions and processes. Here, the biggest gains can be made in terms of customer experience but also in optimization of the workforce—and in reducing spare parts inventory levels.

What’s Ahead

If you are thinking of going after a use case that requires advanced analytics, consider the fact that Rome wasn’t built in one day, and neither will your IoT infrastructure. Take the time for your organization to adopt the stages and start reaping benefits from day one. Apply a methodology that introduces the technology step by step, allowing the organization to adopt and benefit from it.

We need to make sure we don’t make the same mistakes as the financial world, which created a house of cards based upon a technology that allowed for products no one understood, bringing the world into a severe economic crisis.

Google understood it years ago and hence its credo “Don’t be Evil.” (However, it seems to have dropped that, which is a shame. It is now reportedly, “Do the right thing.”)

To me, having witnessed the HFT phenomenon from up close, every company that goes digital should take this motto to heart—and especially remember “Don’t be evil with IoT!” If we do that and make sure that we apply IoT and the new technologies that come with it, such as advanced analytics and machine learning, in a sensible and understandable way, economies may prosper in the years ahead. Fast technology is a good thing, but only if you understand what it is doing for you.