A lot of big companies are creating “Innovation Labs” to generate IoT platforms for their enterprise. We talk to them every day. Yet we see precious few successful IoT systems ever delivered by these centralized teams. It’s not a problem of smarts or hard work. These are strong, motivated developers. But the Internet of Things is different, even more so for industrial solutions. IoT systems aren’t something you connect to your products – IoT systems *are* your product. The end-to-end experience, and (often more critically) the end-to-end business model, require much more than a central innovation group can readily deliver. Here’s why.
To produce insights and create business value, connected product solutions require data from systems across your enterprise. Customer information, BOM history, and organization details are often stored in unstructured, human-readable formats not readily available for processing across disparate or automated applications. Business units rely on these independent data silos, managed by their IT departments, for their daily operations.
Meanwhile, most innovation labs focus on architecting systems for collecting and analyzing machine data rather than solutions for optimizing your enterprise operations. When asset sensors indicate “Temperature is 100 degrees” and programmed logic includes a maximum threshold of 95 degrees, machine data is sufficient for tripping alarms and shutting down the device. But sending a message to a specific person, entering a support ticket, or initiating a parts replacement order requires data that doesn’t come from your machines at all.
How will your IoT system know who to alert and via what method, for which machines, and under what conditions? Where is each machine located, and what parts are inside them? Which are under warranty and what service agreements have been made for each particular customer? What is the process for ordering their replacement parts and tracking where and when they are installed?
In order to do much beyond enabling failing equipment to announce “NEED HELP NOW,” or if you’re lucky, “NEED HELP SOON,” your IoT solution must be integrated with your enterprise systems and able to ingest and produce data that your various enterprise systems (CRM, ERP, etc) can understand. It must then combine these previously isolated sources of data into insights for triggering specific actions that generate value for you and your customers.
Centralized innovation teams building their own “enterprise” IoT platform can’t do this on their own. They might have total control over what information is collected from your devices and how it is analyzed, but lacking easy integration with data from your other enterprise systems, their solutions are less than compelling for your lines of business, service organizations, and product sales teams for whom these centralized solutions are supposedly built for. This is why so many enterprises find themselves with an IoT platform that is ignored outside of the innovation group, and each P&L trying to build their own custom systems, each incompatible with the other, and everybody wondering how they’re going to make any money from IoT at all.
The problem is not simply the existence of a central team, but that the goals of most innovation labs are not aligned with delivering defined IoT business outcomes for the enterprise. A centrally maintained and unified IoT framework for multiple business units to leverage and build upon, rather than each team creating their own solutions from scratch, is indeed the correct path for successful digital transformation. But organizations should not expect a centralized innovation team to deliver a single central end-to-end enterprise platform meeting all of the needs of each business, on the schedule that each requires for their respective customers.
A Common IoT Core
Enterprises should adopt and support a central, flexible framework for solving the common complexities of IoT. This includes data security, user management, access control, data cleaning and transformation, and other functionality where the consistent best practices are both critical and non-specific to any particular type of machine or business context. Make these available to your teams through a common enterprise API that each line of business can leverage for delivering their unique value to their customers. Each business is still responsible for their specific customer offerings (and can proceed at their own pace), without having to worry about the challenges of collecting, processing, and securing the data in the first place – or being constrained in their ability to unlock the value in their data by a monolithic centralized system.
Consistent IT policies can be maintained across the entire enterprise, while each team remains empowered to move quickly toward creating compelling connected product scenarios for their particular markets without the cost (time, budget, and opportunity) nor the risks (security, reliability, and performance) of (re)building their own infrastructure. Everybody wins, especially your customers who care about your product, not your IoT platform, and just want business outcomes like asset management, workflow integration, predictive maintenance, and yield optimization.
It goes without saying that each line of business in your enterprise shouldn’t be responsible for building their own cloud infrastructure or machine learning tools. Likewise, your teams shouldn’t have to work out their own ways of integrating these primitives from public cloud providers like Amazon, Microsoft, and Google into their solution architectures. A centralized team (independent or virtual via representatives of each business unit) should provide consistent, well-tested APIs for individual teams to build applications on top of, rather than require each application team to work with each cloud service directly. We’ve helped Fortune 1000 brands across several industries accomplish this goal and accelerate their digital transformation journeys.
When you form a central “Innovation Lab” with the goal of generating an end-to-end enterprise IoT platform, rather than providing your business units with a common framework around data management and best practices they can leverage for creating value for their customers, the most common business outcome is just another failed experiment.