Nov 26, 2021

Enterprise IoT solutions: making the POC scale

Alexis Leibbrandt

This article analyzes what it means to scale a POC to a higher degree of complexity. It explores the challenges an organization faces during the implementation of a large-scale IoT enterprise solution.

In a previous article, we spoke about how complex IoT solutions are and how a specific IoT platform can help in making your project successful. This is even more true when it comes to enterprise solutions.

In a typical enterprise use case you always start from something small to evaluate the technology and the solution you would like to put in place, a so-called “Proof of Concept” (POC). This very first step is fundamental to understanding technology’s potential and limits, checking the feasibility of the project itself, and making an estimation of the potential Return on Investment (ROI).

Within this article, we will analyze what it means to scale a POC to a higher degree of complexity. We will focus on the typical problems an organization faces during the implementation of an IoT solution and how the particular functionalities of akenza support enterprise-grade solutions. One of these features is the Microsoft Azure integration: a no-code “output connector” that dramatically reduces complexity in IoT projects while allowing more flexibility in creating advanced IoT solutions.

Not only quantity matters!

One may think that scaling the POC is just about adding more devices to the solution. This is only partially true, as more devices may lead to numerous other problems that you may not have considered during the project's initial phase.

The data problem

As reported in the book Analytics for the Internet of Things: “A company can easily have thousands to millions of IoT devices with several sensors on each unit, each sensor reporting values on a regular basis. The inflow of data can grow quite large very quickly. Since IoT devices send data on an ongoing basis, the volume of data in total can increase much faster than many companies are used to” (Minteer, Andrew Analytics for the Internet of Things Packt, July 2017).

The chart below shows how the amount of IoT data can grow faster than expected in comparison with production data. This is absolutely a critical factor to be considered while planning the scalability of a solution.

Storage capacity could, therefore, quickly become a problem. But more data is not only a storage problem. All this data must be managed, organized, and aggregated for further analysis through high-demanding computational power operations.

The connectivity problem

Increasing the number of devices leads as well to problems strictly correlated to connectivity. For IoT devices, the bandwidth may not be a big issue, but coverage and connectivity management can be a real problem.

The conditions encountered in a POC are hardly replicable on a larger scale. One particular network may not work in each location of the scaled solution. Similarly, a device could be perfect for indoor but not suitable for outdoor or industrial environments. To respond to all these challenges, flexibility is key, as explained in our article Going digital with IoT: do I need an IoT platform? This is even more important when it comes to scaling your solution: because managing 10 devices is easy, 100 a problem, 1'000 possibly a nightmare. A POC can quickly become a multi-connectivity solution with different devices that have to coexist in a shared environment and cooperate to merge their data to enable normalization and, therefore, cross-use-cases analysis.

The organizational problem

When a company grows, the biggest challenge is finding for each employee a place to work and organizing them to work together. In business, this most likely means hierarchization and subdivision into teams that cooperate to achieve a common goal.

As a matter of fact, for IoT devices, this works more or less in the same way. When the number of connections, devices, and outputs to third-party systems grows, organization matters: clustering use cases into different workspaces, grouping sensors to easily manage information, decoders and data processing enables scalability on a solid basis.

ROI means success

IoT is fantastic, it is one of the current technological trends, but without a decent return on investment, it is not worth the effort. That is why connecting devices is just the very beginning of the journey.

World Sensing correctly describes the 7 benefits IoT can bring to your business and why you should invest now in IoT, but the critical factor is: how can you transform data into value?

Data visualization, data analysis, AI, and digital processes are all added values to raw data. In our article about how to integrate IoT into your business process, we have explained what it means to put a digital process in place to support the digital transformation many companies aim to achieve. What was not mentioned in the previous article is the complexity behind the development of a project like this.

The point is that for an enterprise, the complexity derived from the problems we have just mentioned can grow as the project scales and, most of the time, even at a non-linear pace. Complexity leads to costs that could be so high as to affect the expected ROI negatively.

The bad news is that complexity is here to stay. You cannot avoid it, but you can face it in the right way to minimize effort and costs. If you have to screw in a screw, the tool you use makes all the difference. You cannot wholly avoid the effort, but you can dramatically reduce it by using a screwdriver that performs part of the job for you.

akenza: scale with the power and flexibility of a multi-tool

Let’s say you have to work with screws, but you can take with you just one screwdriver. Not knowing in advance what kind of shape the screws have, will you choose a single type of screwdriver hoping that it will work for all screws, or would you go for one with interchangeable heads? We built akenza with just this purpose in mind: being the multitool of choice for every IoT project.

To achieve this result, we worked on both sides of the data path: input and output.

If you follow akenza, you may already know that on the input side, you can choose between several connectivity options and integrations, a constantly growing Device Type Library, and a no-code data processing engine to build your own business logic.

But the output is as important as input, especially when scaling a project from the POC phase to a large-scale rollout. Therefore, besides our standard output connectors for further data analytic or notification services, we provide Azure IoT Hub as a new output connector that takes akenza to the next level as a tool for enterprise-level solutions.

This direct integration to Azure IoT Hub opens endless possibilities in terms of applications integration and data analysis. Together with a flexible pricing model that adapts as your project scales, these functionalities grant a concern-free IoT journey where the focus is your business.

Follow us in the next articles to discover why the combination of akenza and Azure is a game-changer for your next IoT project.

Enterprise IoT solutions: get the best of Azure

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