Organizations across the globe are pushing towards digital transformation to increase productivity, optimize business operations, improve marketing efforts, hire expert talent, and more. According to Statista, businesses spent $1.31 trillion globally on digital transformation technologies and services in 2020. They are projected to spend almost $2.8 trillion on digital transformation in 2025. Although digital transformation can lead to positive results for an organization, business leaders need to plan for effective change management. Without a great change management strategy in place, an organization attempting digital transformation or any kind of major change has high chances of failing. Fortunately, businesses can leverage enterprise AI solutions for change management.
Enterprise AI can help in developing efficient change management strategies that allow employees to adapt to upcoming changes. AI enables change managers to gather crucial data about employees and generate analytics to design the most suitable strategy. Using the collected employee data, organizations can train machine learning models that can predict the outcome of change learning strategies. Hence, businesses can handle the people side of change more effectively with the help of enterprise AI tools.
Enterprise AI Solutions for Change Management
Streamline Change Management in Your Organization with Machine Learning
Change managers can take a look at the following applications of enterprise AI and machine learning solutions for better change management:
Change Impact Measurement
Many organizations generally gather data regarding previous changes as well as their success and failure manually. However, this approach can be pretty ineffective as manually entered data may have biases and errors. Along with these, positive or negative incidents that occurred after the change may not be related to the change itself, but the collected data may report otherwise.
Machine learning models can accurately measure the impact of change in an organization. Enterprise AI systems can collect meta-information that gives insight into the relationship between the change and specific problems in an organization. The system generates a similarity score to identify whether a change had an unintentional impact. The similarity score will consider the following factors:
● Common entities
● Time interval between the change and an incident
● Common keywords
● Common employees reporting on the incident and working on the change
If an incident can be attributed to a certain change with high probability, then that change can be considered as the most likely source of issues in the organization. The change can be further investigated to issue an emergency fix or a rollback. This will also help change managers in understanding how a certain type of change can impact the business, leading to better deployment strategies in the future.
Incident Prediction
Enterprise AI systems can help in preventing major incidents after change by predicting them beforehand. Change management teams can then plan for prevention or mitigation measures for potential incidents. To predict possible incidents, machine learning models monitor several risk factors that may affect specific services or domains.
Machine learning models can be trained using existing data collected from services and applications in an organization. Enterprise AI can identify various risk factors that are associated with potential incidents. These risk factors include:
● Problem backlog
● Days between major incidents
● Change failure rate
● Growth rate of minor incidents
The machine learning model can correlate various metrics, performance disruptions and predicted risk to calculate factors with the best predictive value. Such models can be improved with feedback depending on accurate incident prediction. An AI solution built on this principle can accurately predict incidents and alert concerned teams, similar to a weather monitoring system.
AI systems can also help in identifying, measuring and visualizing potential risks using key performance indicators (KPIs). Enterprise AI solutions can gather data from ITSM systems, service requests, incident reports, and more to generate descriptive KPIs. AI systems can present these KPIs in a visually appealing manner to allow change managers to identify potential risks and incidents. KPIs that go beyond a specific risk threshold can be investigated by change managers. Based on the type of risk detected, they can work on creating mitigation strategies or fixing the issue pre-emptively.
Employee Support
A major part of change management is supporting and training employees. For instance, if a manufacturing business has deployed IoT solutions in the supply chain, then it needs to train employees in using IoT devices. Even after receiving the training, many employees will have queries when they start using IoT solutions themselves. All of these queries need to be answered one by one, which can introduce delays in certain business processes. Along with these, training programs introduced by the organization may not be suitable for all employees as some employees may not be as tech-savvy as the rest. Hence, organizations need a much more efficient solution for employee support.
Businesses can deploy AI-based chatbots for employee support after a major change. Such chatbots can instantly answer employee queries with animations and videos, as well as offer micro-trainings for certain topics. In case an employee isn’t satisfied with the answer, they can opt for speaking to support personnel directly from the AI-powered chatbot service. Since the chatbot is based on AI, it can gather data about the queries and offer detailed analytics on various questions. Based on these analytics, organizations can understand where employees really need support and they can design more effective training programs. Businesses can also use these analytics to create more micro-training options in the chatbot for specific queries. Rezolve.ai has already developed a similar solution for effective change management.
In an evolving business landscape, organizations that can adapt to change effortlessly will always have a competitive advantage. Hence, organizations need to adopt the best solutions for change management. Enterprise AI tools are crucial for businesses as they can predict and help mitigate potential risks as well as prepare employees for change. AI can truly augment change management by enabling the development of better strategies to adapt to change. The analytics generated by enterprise AI systems allow businesses to make data-driven decisions about an upcoming change, leading to much better deployment and implementation.
