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Companies that are struggling with labor shortages or entering the next phase of their digital transformation are exploring automated robotic solutions more than ever. The Association for Advancing Automation (A3) found that the number of robots sold in 2021 rose 28% from 2020, making last year the strongest year for robot sales to date.
Many decision-makers will be disappointed when they realize that after their initial investment, the adoption of robots into their workforce likely will not keep pace with their expectations.
These challenges are similar to the issues companies face when implementing complex enterprise technology solutions such as Salesforce, SAP or Workday.
The solution to these challenges is also similar. A successful robot adoption program must be informed by the principles of change management that are commonly applied when implementing complex enterprise technology solutions. There are a few key ways to successfully adopt, integrate and scale robotic solutions within a company.
There are many dimensions of value besides the obvious target of ROI. As a robotics company, it’s important to discuss the following with clients: Increased consistency of outcomes, proof of outcomes with data, cost of investment vs. usage, the experience of guests or residents or employees and promoting an image that is consistent with their brand.
The key is to define these objectives so that they can become the lens that showcases the value of the program. There are different people in the ecosystem who will have different values or who will prioritize the values differently. Taking this into consideration will inform how success is reported and communicated.
It’s also important to understand the physical environment before any new technology is introduced. Identify who will be operating the robots, who will manage the operators and who will care about seeing evidence the program is succeeding and delivering on its value. This is vital to a successful implementation. If the organization has prior experience with robots and data and analytics, take the “temperature” for change and try to figure out where the advocates will come from and who may be blockers.
Consider the current state of how work gets done today. Look at the time window for performing activities, days per week, how work is scheduled and other priorities in the operation. This is essential because the goal is to transform work. That means the new schedule and work priorities will be different than today. For instance, today the operations group may only perform certain activities a few hours a week. But in the future state, the robot will allow new priorities to be set, which can then allow more time for multiple activities.
This is possible because a robot transforms activity from a 1:1 relationship to a many:many relationship. In a 1:1 relationship, the activity and the human are tied together so only one activity may be performed by that person at that time. The activity is equal to the priority. The robot program can enable a ‘many:many’ relationship where many humans can manage many robots at the same time (hence the term ‘collaborative robotics’). In this desired state, the labor can be optimized based on the value of the activity.
Understand the learning styles of the people who are being trained. It’s important to translate complex robotics jargon into verbiage that’s going to make sense for the people directly managing the robots. Identify the methods of communication they will be using daily and weekly to receive information on the program and if there are language preferences.
As an example, we are finding that short videos that can be texted to a phone are becoming increasingly more impactful in getting desired results. Reading directions can be a barrier to learning, so we are choosing language-agnostic content in some scenarios. Stay flexible, as most organizations will require multiple training methods to accommodate the different learning styles.
Continuous feedback is essential to ensuring the program is successful in transitioning from the adoption to the production phase. We know that people are often the weak link in a robotic program and without the right data and reporting indicating whether things are on or off track, there is always a risk for successful programs to suddenly fail.
Also, organizations often make the mistake of believing that if they’ve invested in the training once, then they’ve successfully adopted the tech. But training is not the same thing as adoption – it’s just a step in the overall program. And since people are constantly coming into and out of organizations, training must keep pace as well. Hence, why reporting and analytics are essential to getting ahead of program risk before performance veers off track.
Leadership support takes many forms including communicating to the managing team the importance of the program and their role in reviewing the data to understand who is going off course and who is knocking it out of the park. Good data and analytics don’t waste leadership’s time and are designed for Management by Exception, so the problems are clearly identified and actionable next steps can be taken.
The successful adoption of robotic solutions will determine how much value is created for everyone in the ecosystem.
K.G. Wood-Maris is the head of customer experience at SoftBank Robotics America.
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