Is your company creating an “innovation lab” to build a new IoT platform for your enterprise? We’ve worked with Fortune 1000 brands across several industries to accelerate their digital transformation journeys, and have seen only a handful of these centralized teams ever successfully deliver revenue-generating IoT systems. 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 the end-to-end business model, require much more than a central innovation group can readily deliver. Here’s why.
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Machine data is useful to, well, machines. Not humans. Or your business operations. When the data from the sensors on your asset reports “Temperature is 100 degrees” and your programmed logic includes a maximum threshold of 95 degrees, machine-only data is sufficient for turning on a flashing light or wailing siren, or to initiate a system shutdown. But what if you want to send a text or email message to a specific person about the problem, or enter a support ticket, or initiate a parts replacement order? That takes data that does not come from machines at all. How does your IoT solution know who to alert and via what method, for which machines and under which conditions? Where is this machine installed, and what parts are inside it? Is it under warranty and what service agreements have been made for this particular customer? For replacement parts, who are the approved purchasers for automatic ordering? In order to do much beyond announcing “SEND HELP,” your IoT technology must be integrated with your enterprise systems and be able to ingest and produce data that your various systems (CRM, ERP, etc.) can understand, and combine these disparate sources of data into actions that provide value to you and your customers.
Centralized enterprise innovation teams building their own IoT platform can’t do this on their own. They may have total control over what information is collected from your devices and how it is analyzed, but without integration with data from your other enterprise systems, their technologies will be less than compelling for the various lines of business, service organizations and product sales teams for whom these the products are supposedly built for. These enterprises often find themselves with an IoT platform that is ignored outside of the innovation group, and each P&L trying to build its own custom systems, each incompatible with the other, and everybody wondering how they’re going to make any money from IoT at all.
Successful adoption and deployment of revenue-generating connected products require your central IoT champions to work directly with your IT teams and business unit leaders. Together they must create a flexible system for integrating data from systems across your enterprise to produce insights that create business value. Customer data, BOM history and organization details are often unstructured and exist in human-readable formats not readily processed across disparate or automated systems. These silos (and the data inside them) are frequently maintained by IT departments for the business units. To transform this information into useful context for enriching machine data (i.e., notifying the technician responsible for a specific machine under warranty for a particular client that it is having issues with a certain part that is available in what storeroom and where that machine is currently installed), your IT team and your business units will have to work together to structure their data appropriately for integrating with any IoT system.
Enterprises should not seek to build a new all-encompassing IoT platform, but instead adopt and support a central, flexible framework for solving the common complexities of IoT. 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. These should be made available through a common enterprise API that each line of business can use to deliver their unique value to their customers. Each business is still responsible for its specific customer offerings (and can proceed at its 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 infrastructure. This approach delivers not only more efficient use of resources, a faster route to production and higher-quality technologies, but is also much more likely to deliver value to your customers who care about your product, not your IoT platform. They just want business outcomes like asset management, workflow integration, predictive maintenance and yield optimization.
Few organizations would expect each line of business in their enterprise to be responsible for building its own cloud infrastructure, storage 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 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. When central teams are instead created as “innovation labs” with the goal of building not a common framework of best practices, but a new company-wide IoT platform, the most common business outcome is simply failure.
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