The Discovery phase of any large-scale ERP rollout is critical. It sets the stage for the entire project by defining the strategy, identifying key outcomes, and ensuring stakeholder alignment. However, this phase can also be daunting due to the sheer volume of information and the diverse needs of various audiences. Enter AI – a powerful tool that can transform how we approach Discovery, making it more efficient, insightful, and tailored to the unique needs of every stakeholder. Today, although I suspect this will change over the next couple of years, nearly 60% of a project cost in billable resource time is spent either reading documentation, talking about documentation to understand it, writing documentation, regurgitating documentation for various audiences, summarizing it, categorizing it, and even archiving it for later. Let's look at ways AI can help recoup some of this cost, if not significantly.
Challenging Strategy and Focusing on Positive Business Outcomes
One of the primary roles of leadership during the Discovery phase is to challenge and refine the project strategy. AI can play a crucial role here by analyzing historical data, project trends, and internal metrics to provide insights that might not be immediately apparent. It's dangerous for leadership to become "task" blind. A situation where the leadership becomes more vested in the outcome or achievement of the task than the Outcome of the Key Result. For instance, if a legacy application's licensing costs were targeted as an outcome for savings against the project's overall costs, "savings" in this context is the key result and outcome we're looking for. It would not be great for leadership to force the "task" of eliminating the legacy application at all costs, especially if the cost significantly exceeded the licensing savings. This is an example of becoming "task" blind, and leadership has lost sight of the strategic objective, which was to look for ways to reduce the cost impact of the project. AI can be an excellent tool for looking at things from a different perspective without the biases usually associated with "task" blindness.
AI can also do the same for the project team and help keep them focused on Positive Business Outcomes (PBOs) and agreed-upon Target Outcomes rather than getting lost in tasks. By continuously analyzing project progress and outcomes, AI can provide real-time feedback and suggestions, ensuring the team remains aligned with the overall objectives and key results (OKRs).
Tailoring Documentation for Diverse Audiences
A common challenge in any large project is effectively communicating with different audiences—from project sponsors and C-level executives to operational staff. AI can be a game-changer in this aspect. By leveraging tools like Microsoft 365 Copilot, teams can write technical requirements and documentation once and then use AI to rewrite and tailor these documents based on the audience's needs.
For example, a detailed technical specification can be transformed into an executive summary for C-level stakeholders, highlighting critical points without overwhelming them with technical jargon. Similarly, the same document can be restructured into a more detailed and operational-focused format for the implementation team, ensuring everyone has the information they need in the most helpful format. There is a tremendous opportunity for project savings here, in addition to customized end-customer training documentation that considers the AS-IS state, which employees might be familiar with, and the TO-BE state, which is coming in the future, providing both a less expensive approach to managing this type of boutique documentation and having it auto-generated even in the face of changes during the project. Updating training documentation when new product versions are released during a project rollout is often costly. But, with AI, this cost can be easily mitigated.
Simplifying Access to Project Documentation
Large-scale projects generate a vast amount of documentation and artifacts. Sifting through this information can be time-consuming and distracting. AI tools like Microsoft 365 Copilot can easily reference these documents, allowing team members to focus on tasks rather than searching for information. For instance, team members can ask broad questions and get precise answers, such as locating specific test scripts, historical project decisions, or open tasks. This also streamlines internal chatter between team members, reducing interruptions and questions that new team members depend on seasoned team members to provide to be productive.
Creating Visuals and Diagrams
AI can also assist in creating visuals and diagrams, essential for communicating complex information clearly and effectively. Using declarative markup languages or metadata languages like HTML or XML, AI can generate visual mind maps or technical workflow diagrams based on the provided data. This saves time and ensures consistency and accuracy in the visual representation of information, even as things change throughout the project's lifespan. While AI is not perfect at this task today, it gets close enough to cut the design time for these critical project visuals in half and even more the maintenance of them over time.
AI as a Thought Partner
One of the most exciting uses of AI during the Discovery phase is as a thought partner. When projects introduce new elements to a customer's solution enterprise, there are often unknowns and uncertainties. AI can help project teams think through these unknowns by providing insights and suggesting scenarios that might not have been considered.
For instance, if a new integration is being added to the ERP system, AI can analyze the existing environment and provide potential interaction scenarios, highlighting possible conflicts or synergies. This allows the project team to address issues and optimize the integration process proactively.
A final thought
Incorporating AI into the Discovery phase of a large-scale ERP rollout can significantly enhance the efficiency and effectiveness of the process. From challenging strategy and focusing on positive business outcomes to tailoring documentation and simplifying access to information, AI provides a multitude of benefits. By leveraging AI as a thought partner and its capabilities to create visuals and analyze unknowns, project teams can ensure a smoother and more successful ERP rollout. The key is to embrace these technologies and integrate them into the project workflow, allowing AI to augment human capabilities and drive better outcomes.
By effectively leveraging AI, we can transform the Discovery phase into a more strategic, insightful, and streamlined process, ultimately leading to more successful ERP implementations and significant business value.
As we progress on this journey, we'll find more and more that allowing humans to focus on the value they bring and less on the busy work produces an exponential untapped value that we're only beginning to realize.
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