5 steps to get ready for for data-driven decision making with AI
Strategic leaders are guided by data.
Traditionally, decisions were made based on personal interactions, customer anecdotes or surveys. This data was shared in meetings and (sometimes) recorded to help inform the next steps to take on a project or partnership. This was all that was really needed – leaders shared what they’ve heard with their teams and actions would follow.
But business has become more complex. Departments can no longer work effectively in silos and quick decisions often make the difference between success and a missed opportunity.
Strategic leaders are now turning to AI for help.
The key to using AI for decision making, is good data. CRMs have been used for years to store corporate knowledge, record interactions and drive insights. The data in your CRM has the ability to feed your AI and quickly generate results that would have previously taken days, weeks or even months to find….or does it?
Do you know what is in your CRM? Is your data complete? Are you collecting information that aligns with your goals? What are you missing?
If you are considering investing in AI, you need to have a strong data foundation in place. AI-generated insights are useless and potentially harmful if not based on clean and factual data. Before you take the leap, consider the following steps to help you strengthen your data-driven decision making.
(And if you aren’t ready for AI to play this role in your organization, these tips should still be helpful. After all human decision-making needs good data too!)
Organizational strategy must guide your data strategy, helping you (and AI) focus on what actually matters, rather than collecting blindly. As your goals evolve, make sure your data strategy stays in alignment!
Identify the data needed to support your strategy. Group your data into broad categories to allow for better reporting on trends and gaps.
Create a data map to illustrate how, why and where you get your data. You will better understand your clients’ journey and ultimately be able to optimize your collection methods.
Clean up data that no longer serves you. Incomplete or stale data creates clutter in your system, making the information you need hard to find. It also confuses reporting and data analysis tools!
Train your staff. If you really want to use data to help guide your decision making, the people working in the system, not just the IT team, need to understand its significance and their role to keep it running well.
