Smart machines are one of the most widespread and transformative disruptions to ever influence industries. According to Gartner, smart machine technology will hit mainstream adoption as early as 2021, and 30% of that adoption will be by large organizations. There’s a good chance that all businesses, both large and small, will incorporate smart machines into their operations by then (or soon after).
The value of integrating smart machines can already be seen in nearly every industry, and in a wide variety of ways — consider the range of smart machines from air, land, and underwater to robots in factories, warehouses, and even kitchens. Collaborative machines, from robotic arms to life-size robots, work alongside humans to streamline operations and create smart factories and workplaces.
Even industries like hospitality and healthcare are benefiting from highly intuitive social machines like virtual assistants and intelligent medical devices, respectively. Thanks to smart technology, organizations across industries are enjoying higher productivity through increased operations and uptime. They’re also benefiting from improved safety and security for their workers and facilities.
However, with all of the benefits smart machinery has to offer, implementing new technology is a significant change. Like all significant changes, it may be difficult for everyone on the team to stay in sync. By making the value of the switch clear and by strategically implementing the most beneficial solutions, companies have a much better chance at seeing a smooth transition.
Why There’s Resistance
Reskilling is one of the many challenges companies face while adopting smart machines. The costs of implementation is another concern, and those costs are often amplified by large and unwieldy form factors or a lack of standards across various interfaces.
When smart technology isn’t implemented in a well thought-out manner, it may lead to legal implications and concerns regarding privacy and security. Combined with the challenges mentioned above, these concerns can make integrating smart machines seem difficult at best and impossible at worst.
How to Manage the Change to Smart Machines
Effectively implementing smart machines is similar to managing any other large-scale change in operations. For smart technology, specifically, the most important thing to remember is that its purpose is not to replace employees, but to help make their workflows faster and more efficient. With that focus in mind, the following tips can help make managing the transition to smart machines easier and more valuable in the long run:
1. Design backwards from the process
Look at the existing processes, evaluate the areas that need improvement and potential areas that will benefit from the disruption, and then seek the best solution. In order to succeed, it's imperative to avoid the tendency to force-fit new innovations on a point-solution approach without considering the larger picture.
2. Choose employee-centric solutions
We can never stress enough the fact that smart machines are designed to aid employees, not replace them. For optimal results, choose solutions that manage repetitive tasks to free up time and identify process hiccups that need to be addressed. Remember: Human input is still required to prioritize which tasks should be delegated to smart machines as well as which issues are dealt with and in what order.
3. Focus on great user experience
The focus of smart machines isn’t just what they can do, but also how easy they are to use, so choose technology with man-machine interfaces that are usable and user-friendly. For instance, machine learning can make smart machines hyperaware, self-organized, and adaptive so users can evolve how they interact with them and become increasingly more efficient.
4. Learn from pilots and prototypes
Much of the hesitation about implementing smart machines stems from uncertainty about whether they will be worth the investment. Test the waters by implementing prototypes in select areas of the organization. Such pilot programs will provide a clear idea of how smart machines can be best utilized throughout the rest of the company. They will also give the machines a sampling of data to begin learning from. Additionally important is that the pilot addresses uncertainties and risks in implementation rather than being designed to succeed.
5. Keep track of success factors
Throughout pilot phases (and continuously afterward), measure success by keeping track of two factors: engagement and effectiveness. Measure engagement by how many solutions have been integrated, how many employees are using them, how often they use them, and how many processes are affected. Effectiveness should be gauged by increased productivity, shortened cycle times, and reduced overall costs of operations.
Smart machines may not begin saturating the market for another few years, but the field is already advanced enough to make it inevitable. It is time to start initiatives and build teams to focus on areas where smart machines can and should be introduced. By defining engagement targets and identifying the most beneficial investment areas early, companies can be ahead of the learning curve when smart machines finally become mainstream.