Crafting a Successful AI/Automation Roadmap
In today's digital age, AI and automation have emerged as a cornerstone for businesses seeking efficiency and innovation. However, blindly jumping into the AI/Automation bandwagon can lead to wasted resources and missed opportunities. When your company feels ready to take the plunge and start implementing automation use cases into its operations, structure and a thoughtfully crafted automation roadmap are key. While each roadmap will be unique to the company where it will be deployed, the steps to crafting a transformation roadmap will be similar:
1. Aligning with Corporate Strategy
Automation should not operate in a vacuum. It needs to be a part of the broader corporate narrative. What is your company’s long-term goals and appetite? Will you hire a full team to perform the full transformation? Hire management consultants to help with the strategy and last mile automation? Hire an outside firm to provide AI-as-a-Service / Automation-as-a-Service and maintain the automation? How will these technologies give your company a definite edge on its competitors? Those, and many more, are the critical questions on which your executive team needs to align prior to starting your roadmap.
2. Selecting an Area and Understanding its Processes
You can’t automate everything at once. Start by selecting a department where processes are very labor intensive, capacity constrained or are directly client facing. Starting with a function where the impact will be felt quickly and at scale. Those first few use cases will make or break your transformation, so make sure they are positioned in an area that matters. Also, make sure the decision makers of the selected department(s) are fully on board with the transformation and eager to infuse their processes with AI and automation.
3. Selecting the Right Use Cases
Nobody just "does AI" or "does automation". They are technologies that are used as tools for a specific purpose. They are specific back office processes being automated to reduce labor costs, they are classification models flagging a customer as in the right state to receive a specific upsell at a specific time. They are not magic wands. When planning for a transformation, the selection of use cases will go through 4 phases:
3.1 Identifying Use Cases
Brainstorm all potential areas where AI and automation can be applied. This involves understanding existing challenges, studying data availability, and discussing with team members. Here, using process mapping techniques will go a long way to identify where AI and Automation can have a significant impact on performance.
3.2 Qualifying Use Cases
Once listed, validate each use case. Do they align with the business objectives? Can they be technically implemented? Is the data available and of good quality? Can they create a measurable lift in performance on metrics that are core to the company's definition of performance?
3.3 Assessing Use Case Potential Impact
How much of a lift in performance can we really believe this use case will generate? Is it building on other use cases or datasets / automations from other use cases? Will its impact be monetary or other (such as compliance or goodwill)?
3.4 Use Case - Business Case
How much will developing and deploying each use case cost? How much risk is there that we start developing it and realize it can't be done? Can we make a business case that will make the finance department smile or will they look at us like a deer in the headlights?
4. Prioritizing & sequencing
Not all use cases will be implemented immediately. Prioritize them based on business impact, feasibility, and resource availability. Starting with low hanging fruits and quick wins allow for the transformation to gain momentum. It's much easier to ask for additional resources when the program is already paying for itself and more!
5. Resource allocation & building a timeline
Each use case will require development time and potentially specialized resources (database expert, machine learning engineer, cybersecurity expert). Depending on the appetite to invest, the scope of the transformation both in terms of number of use cases and duration will vary.
6. Planning for implementation and change management
Implementation is more than just the technical side of things. People are at the heart of any change. Plan for training sessions, create awareness about the benefits of AI, address concerns, and ensure a smooth transition. Change management ensures that the team is onboard and the technology is utilized to its full potential.
7. Planning for long-term maintenance
AI and automation are not a one-time setup. They require consistent monitoring and maintenance. Regularly review the systems, update algorithms, and ensure they’re in sync with the evolving business needs. Moreover, anticipate potential challenges and be ready with solutions.
Conclusion
Crafting a successful AI/automation roadmap is a blend of strategic planning, understanding of your business processes, and human-centric change management. With the right approach, AI and automation can become powerful tools, transforming your business operations and achieving unparalleled growth.
If you’re seeking assistance in your journey to AI integration, Red Fox Solutions is here to guide you. From coaching and strategic planning to seamless implementation, our team of experts will ensure your transition to AI and automation is smooth and successful. Contact us and let’s craft a roadmap tailored for your business's success.
