December 03 - 06, 2019
Hyatt Regency New Orleans

Change Management Checklist to Ensure IA Program Success

By: Katherine Byrne

Effective change management can reduce the delivery risks of implementing IA technologies such as artificial intelligence, machine learning and robotics process automation. To ensure the success of your intelligent automation program, try leveraging these tested change management strategies.

Change Management Checklist:

Is Your Organization Ready for Change?
Assess your organization's readiness for change, identify potential skills-gaps and find out what types of change management approach (i.e. big bang, tiered, etc.) have worked best for your organization in the past.

Here are some insights from our past speakers:

"[Implementing RPA] is not drastically different from other automation initiatives, but having a dedicated team in the business to deliver is what makes this different than other change management processes we have today. One of the main challenges we face is how to divide up responsibilities when it comes to our change management process. We want to utilize our IT team, as well as our automation COE, and global process owners to drive speed and efficiency in our process." Matt Gustitus, Director, Automation – Finance Shared Service Center, Eli Lilly and Company

Are You Strategically Aligned?
Work with business leaders to ensure automation strategies align with corporate objectives. Ensure leadership teams in actual agreement when it comes to RPA goals, timelines, resources and governance. Develop clear messaging around how IA benefits both the business and employees.

"The top priority when delivering complex Automation and AI solutions is foremost in preparing the business owners with a working knowledge in the proposed technologies and how such an engagement will differ from traditional improvement initiatives. For instance, the upfront data requirements for such projects are frequently considerable, consisting of gathering, cleansing and tagging large volumes of historical data. This may come as a surprise to business leaders who are typically focused on future thinking and only the most recent past performance." John Cottongim, Automation Director, Mars

Assign Change Champions
The face of your IA transformation, ensure these change leaders are set up to effectively spearhead RPA process selection, organizational design, messaging and employee training.

Leverage Multidisciplinary Implementation Committees
Develop cross-functional steering committees to help engage stakeholders, set targets, prioritize projects, create governance frameworks and ensure the “voice of the customer” is heard.

"The pace of these programs is ever quickening and with it comes its own challenges. The speed of deployment is often limited not by the technical team, but instead by governance or procedural elements (both very much required when deploying in large firms or complex spaces). Having supporting team members from the various operational areas (e.g. IT, Legal, Risk), who understand the core technologies and can ‘speak the language’, is critical to enabling the solution team to quickly deliver the solution and the business teams to receive the best possible outcome from these projects." John Cottongim, Automation Director, Mars

Re-Envision Corporate Culture
Define and communicate your vision for next generation shared services. Partner with HR to develop trainings to up-skill employees that emphasize both technical acumen and people management skills to ensure your workforce is equipped to navigate the future state of shared services.

Establish and Communicate Governance Structure
Ensure new roles and responsibilities are clearly articulated and understood. Remember, an effective governance structure enables improved standardization, decision making and prioritization across the enterprise.

“We were able to get leadership to agree that a central COE dedicated to RPA would allow us to be successful going forward. This includes internal talent as well as tapping into external talent. We are already seeing other parts of the business wanting to utilize RPA for their business areas. We have to rely on our central governance structure (in the Automation COE) to have the proper controls and support in the future." Matt Gustitus, Director, Automation – Finance Shared Service Center, Eli Lilly and Company

Organizational Design and Talent Strategy
Translate business strategies into a workforce plan that takes into account changes in the way work is done, not just changes in required employee demand.

"Another challenge seen is that with new tools, comes new terms and new ways to measure success. Meaningful time needs to be allocated to introduce the management team to the various models and associated success criteria, both of which will likely be for the first time." John Cottongim, Automation Director, Mars

Be Transparent and Open About Staff Changes
When it comes to staff transition, re-deployment, and/or release, be clear, consistent and prepared to answer the “will I lose my job” question.

Build a Long-Term, Sustainable Vision for Change
Remember, change is an ongoing process and doesn't happen overnight. A truly effective change management strategy drives innovation, continuous improvements and other transformational objectives beyond the initial implementation period. Ensure your change management frameworks are agile enough to evolve with your organization for years to come.

Interested in learning more about change management? Take a look at the event guide for a breakdown of change management sessions taking place this December 2-5 in Nashville, TN!

Here are a few of the change management sessions scheduled to take place:

With AI technologies having the ability to be more involved in your workforces’ job responsibilities, and with your employees being better educated as to what AI can do, thanks to AI going mainstream, your workforce’s fears surrounding AI are indeed justified.
In this session, topics of discussion will include:

  • How to develop a cultural tone that enable your organization to overcome a wide variety of workforce change management obstacles that relate to Artificial Intelligence technologies, their usage, and role within the dynamics of your workforces’ altered, and/or augmented job duties

Auditing internal reports is a very time-consuming, tedious, and manual process. IA technologies such as AI, ML, and deep learning can significantly improve the process and add great value to an organization’s internal audits systems. By taking away tasks that involve humans reviewing large amounts of unstructured data looking for risks and controls, the above IA technologies enables Auditors to direct their assessments towards known industry-wide issues, audit coverage completeness, report investigations better, and ensure best practices during the internal audit lifecycle.

As many have learned along their IA journeys, a “one size fits all” approach to implementing IA into an organization, and/or its various lines of business isn’t usually the best strategy – which explains why the majority of IA programs are rolled out as “siloed” Pilot Programs, and/or direct releases. In this session, topics of discussion will include:

  • The importance of sticking with a “siloed” approach when planning and rolling out your organization’s overall and Big Picture IA strategies
  • Understanding there is “no one size fits all” when it comes to IA usage
  • Determining the opportunities and benefits of utilizing a variety of IA technologies by way of close examination of program niched objectives, feasibility, and the ROI that may be realized when planned in a highly-targeted manner, and in turn, varied and target results

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