How Businesses are Using Purpose-built AI for Change Management

According to Forrester’s Business and Technology Services Survey, change resistance is among the five most frequently selected challenges in executing digital transformation: 21% of global services decision-makers supporting their organization’s digital transformation cited implementation of new processes and capabilities as one of their greatest challenges.

We know that managing change is hard; we see it all the time while working closely with our customers to help them achieve their business goals through automation and purpose-built AI. But we also see them succeed when they when focus on creative and realistic approaches to change management that emphasize the success of all stakeholders in a process.

Here are some things that our customers have identified as important in successfully managing change in their organizations—real-world experience that can help your own transition to run smoothly.

 

Look for flexibility and responsiveness

 

Reinforce what works well.

For one transportation and logistics company, it was important that the solution they chose was sufficiently flexible to strengthen the processes that were already working well. Retention of established processes, including existing automation, in their entirety, was essential for this organization. The solution they chose offered easy-to-use, flexible business rules to reflect current best practices already in place. It also integrated easily, out of the box, with a wide variety of systems working in conjunction with document processing: ERP, ECM, CRM, BPM, LOB, and RPA systems.

 

Tailor operations to make their jobs easier.

For many organizations, the corporate benefit behind adopting intelligent document processing (IDP) is to reduce cost, increase efficiency, and better realize business goals. But workers are much more motivated by change that makes their jobs easier, like relief from tedious manual work that often needs to be redone. A high degree of straight-through or touchless processing based on business rules and integrations is not only good for the business but increases accuracy and job satisfaction (which also helps retain talent). One technology company we worked with was looking for a better user experience, especially when manual correction is necessary. Right out of the box, IDP delivered upwards of 90% accuracy. And the solution continues to get smarter and more accurate over time, learning as new document variations and statistical data is collected during human-in-the-loop review.

 

Identify and relieve points of friction that frustrate users.

One business process outsourcing (BPO) company wanted to improve their customer journey based on what the actual data from the process indicated. Process mining data shows them the most efficient and cost-effective path, and highlights existing deviations. This allows them to assess proposed improvements before spending time, effort, and cash to put them in place.

Similarly, a large healthcare provider used process intelligence to gather accurate and detailed information on what’s working in their document processing, what’s not, and why, catching and resolving deviations from best practices in real time.

 

Don’t leave staff hanging: Implement quickly.

The implementation of AI-driven automation is a critical time for change management. It needs to be as smooth and as fast as possible, in every industry and use case. What should you expect? A BPO customer of ours saw improvements in only 2 weeks. For a transportation and logistics company, software was test-ready just four days after being installed. A financial services firm was able to develop and deploy their project in record speed, under 6 weeks.

How you implement is also a factor. A large healthcare provider was successful in choosing to make process improvements one-by-one, so that as staff became familiar and comfortable with the first change, layers could be added, evolving more impactful solutions.