Advancements in AI technology, especially Decision Intelligence, are reshaping the ways teams work. More leaders are realizing AI’s value in helping overcome the biases inherent in decision making, not to mention helping employees deal with the growing volume of decisions that must be made, quickly, to remain competitive.
Decision Intelligence allows teams to make better decisions at the point of impact, while automating many routine and repetitive decisions that have typically consumed much of their time. These capabilities are changing how employees work by improving the quality of work and by increasing employees’ level of satisfaction.
Adopting Decision Intelligence offers many opportunities and benefits, but achieving success requires careful planning and coordinated execution. Based on our team’s years of experience in guiding companies through these transformations, here's a roadmap to finding success in your Decision Intelligence and AI journey.
1. Secure buy-in from leadership across your organization
Every business decision impacts multiple teams and processes across an organization. Even when teams collaborate well, that collaboration often leads to conflicting decisions whose cross-functional impacts can be lost due to a lack of organizational transparency. Yet many teams lack real-time collaboration and visibility – growing organizational challenges that Decision Intelligence addresses.
For that reason, it’s crucial to get buy-in and support across business units. Involving cross-functional leaders early in the process of adopting Decision Intelligence, your IT, supply chain, procurement, finance, and other teams can understand the benefits of AI for decision making, and move forward with the best outcomes for the company in mind. Without this pre-implementation alignment, companies can still achieve success, but that success will not be optimized if it results in decisions without end-to-end visibility and data (as we’ll discuss further below).
This approach differs significantly from the process of implementing supply chain planning or inventory management solutions, or other niche technologies which maintain siloed approaches to decision making – i.e., leveraging a limited set of data and addressing a subset of functions and questions.
The transformative impact of an end-to-end, holistic approach to decision making can’t be understated. Research shows that digital transformations are twice as likely to succeed when the executive team shares a common vision and strategy, especially in the context of the evolving future of work. With a platform like Aera Decision Cloud™, scenarios such as raw materials shortages that impact multiple teams can be solved in ways that balance service levels, cost, environmental impact, logistics, and other factors with a few simple clicks in a skill.
Our recent Halloween-themed webinar on running successful AI implementations dives into the principles of successful change management efforts, with examples to help you make your case to leadership.
2. Take enough time to prepare your digital transformation project plan
Your AI project’s scoping phase should include an initiative to document critical steps, especially as they pertain to the changing nature of how employees work and make decisions:
- Identify specific Decision Intelligence and AI use cases and prioritize them, considering their role in shaping the future of work.
- Scope the implementation details in your roadmap, ensuring that this roadmap aligns with the evolving work landscape.
- Select vendors and partners who understand the significance of AI in the future of work.
- Ensure your internal IT team understands why this is a business priority and is ready to support this transformation, especially when it comes to addressing the changing needs of your workforce.
- Launch a pilot program to test and refine selected use cases, while keeping an eye on how your teams are embracing change.
Remember, Decision Intelligence has the most significant and positive impact when it is deployed beyond a single business unit, embracing a diverse range of opportunities to digitize and automate decisions across your organization.
3. Ensure full access to data across your ecosystem
As you collaborate with IT to ensure the requirements for Decision Intelligence deployment are met, it’s best to ensure access to data across your systems of record and data sources – including areas that might seem out of scope for your initial deployment. This is important because, as mentioned above, decisions may have unforeseen impacts beyond a single business unit or function.
This process is simpler than you might expect. Our AI platform for Decision Intelligence includes predefined data crawlers that connect to hundreds of existing solutions and sources. In addition, AI skills can address master data management and other concerns over data quality, helping streamline processes for IT and digital teams.
4. Focus on managing talent as well as change
Technology is just one piece of the Decision Intelligence and automation transformation. The success of any business initiative rests on effective talent and change management.
Identifying and cultivating the right talent pool is crucial, and new positions and job descriptions will evolve rapidly as organizations recalibrate their teams to capitalize on the benefits of AI. As you consider your own digital transformation effort, focus on employee engagement and upskilling, and explore internal recruitment and retraining as strategies for adapting to new ways of working.
The change management aspect of your digital transformation effort is crucial to the project's overall success – particularly when you’re evolving the way teams use technology, collaborate, and make and execute critical decisions. A proven, reliable technology platform is crucial, but good communication, employee engagement, and celebrating milestones are all key to garnering support and ensuring you gain the full benefits of AI in the workplace. These important aspects can be overlooked, yet they’re essential for achieving buy-in across the organization – especially as organizational processes change in response to changing market conditions and customer needs.
For more details and examples of how to successfully deploy Decision Intelligence and evolve to maximize the benefits of new ways of working, watch our Future Now series webinar on AI deployment and change management.