Solving the Biggest Challenge of Enterprise IoT: UX

In Digital Innovation, Enterprise Mobility, Internet of Things, User Research by Rachel Nitschke

James Bond is driving a BMW 750i, expertly maneuvering through a difficult parking garage and evading a rocket launcher, a steel wire trap and quite a few barrages of gunfire. He’s doing all this from an Ericsson mobile phone track pad— from the backseat of the vehicle, often just relying on the phone’s screen for a visual as gunshots fly through the windshield. Despite only receiving one warning of an obstruction, Bond is able to drive the car with a certain ease, never cursing the poor vantage point from the phone or the numerous tumbles he takes while navigating the car around tight corners from the back seat.

Completely improbable.

This scene from Tomorrow Never Dies epitomizes the James Bond mystique: cool gadgets and super human abilities. The filmmakers dreaming up these gadgets can relate to the many enterprises deploying IoT and M2M integrations to their workforce. Neither start with the idea of what works for the user and instead use the technology as the foundation for the project, hoping users will adapt. These technologies (RFID tags, embedded controllers, BLE sensors) are still relatively new to the industry, and despite their potential to deliver transformative changes to many industries, they are unlikely to have a dramatic effect on ROI or efficiency. Products that ignore the user get ignored by the user.

The crucial point where the filmmakers and the enterprise IT and Innovation groups creating projects is that the enterprise users are not special agents in fiction movies. They are working with a real workforce that has real issues with their environment. Digital products with Industrial Internet of Things and Machine-to-Machine integrations need to especially take these issues into account. These products often include a degree of interaction with multiple environments.

Consider this: you run a manufacturing factory floor. Your workers are having issues with monitoring the operations of the assets as they move through the production line, leading to a lot of confusion, idle worker time and asset downtime. Factory floor employees don’t know when the product will be ready for their stage, and end up waiting or, end up becoming preoccupied with a separate task and production halts. How could an IoT-integrated digital product manage this? One idea may be to give tablets to each worker with a dashboard that integrates with the sensors on the production line, but this could also lead to unintended consequences and more frustration for employees.

If the team is required to have a lot of gear on, where will they store the iPad when not in use? Will they be constantly picking it up and setting it down? Chances are that most workers would opt out of using them at all if it meant additional trips over to a storage area. OK, so another idea: what about a kiosk? The kiosk would provide the dashboard of each part’s stage of production. Will that create a “traffic jam” of your workers trying to look at the kiosk? How will the workers flow between the kiosk and their task area?

These are the types of questions that are often not considered in developing these crucial products. The answers can be found in ethnographic research.

What is ethnographic research?

Here’s what ethnographic research is not: user interviews, market research, or employee manuals. Too often, companies rely on those for guidance on how to develop crucial products. For user interviews, the easiest way to demonstrate where these go wrong is by example. Think of how you would explain to someone how you brush your teeth. How do you grab the toothbrush— by the handle or the head? What area of the tube do you apply force to push out the paste? These are the crucial details that enterprises miss when only relying on what users say their process is. Market research presents the same issues. The data that market research presents will help you understand how to market the product to users, but not how to make a successful product. The data, which presents patterns of consumer behavior, is simply not detailed enough for a fine-grained understanding of users. In a similar vein, employee manuals rarely tell the whole or accurate story of how an employee completes his or her work. They often reflect the “ideal,” rather than the “real.”

Ethnographic research, according to the National Park Service, is the “study of people in their own environment.” It strives to provide meaning to their interactions with their environment and peers. It’s more than just quantifying interactions from observations; it’s also backing up those observations with insights from the user about their choices. Although traditionally employed by anthropologists and social scientists, it’s emerging as a serious tool for companies who are looking to digital products as a future revenue-generator.

Yet, IoT-enabled consumer products are accompanied by a poor user experience. In late 2013, the U.K. government commissioned a study on the usability of smart heating controls. None of the five major products on the market offered a good user experience. The systems required multiple, confusing steps to set up the schedules, and did not provide confirmatory feedback that the actions had been registered. Some also allowed users to enter errors into their heating system schedules. In addition, users did not understand the metaphors, labels or icons used in the systems.

Internet of Things-enabled products have a long way to go for enabling a better user experience. The products that succeed with consumers and employees are those that use a robust ethnographic research engagement to drive the product’s development.

Learn more about how IoT will transform industries in 2016 with our ebook, covering the most ROI-generating uses of IoT-enabled products in the utilities industry.
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