Launch strategy

Each phase is designed to build upon the previous one, creating a foundation for sustainable AI adoption across the enterprise. The focus remains on empowering builders, ensuring proper governance, and driving measurable business impact.

The timeline can be adjusted based on organization size and complexity, but typically spans 1-3 months for initial deployment, with ongoing optimization and expansion thereafter.

Key success factors for each phase:

Clear executive sponsorship and vision
Active builder community engagement
Regular feedback collection and iteration
Measurable success metrics and use cases ROI tracking
Continuous learning and improvement

Success planning with Dust

Crafting your Dust vision

Leadership plays a pivotal role in shaping your organization's AI journey. Here's how to build a vision that resonates:

Align with business strategy

Connect Dust's capabilities and assistants/use cases to your organization's strategic priorities:

Questions to consider:

Which workflows and teams would benefit most from AI augmentation?
How can we leverage our existing tools and data more effectively?
How can Dust help us achieve our business goals?

Empower your teams

Position Dust as a platform that enables teams to create their own AI solutions:

Questions to consider:

How can we identify and support potential builders across departments?
What resources do builders need to succeed?
How can we facilitate knowledge sharing and best practices?
How rewarding people investing time to drive efficiency with Dust?

Explore new opportunities through custom integrations

Emphasize Dust's ability to integrate deeply with existing tools and workflows:

Questions to consider:

Which integrations will deliver the most immediate value?
How can we leverage the API and Dust Apps for custom solutions?
What automation opportunities exist across our tech stack?

Ensure educated AI use

Establish clear company objectives and growth expectations for Dust use while maintaining security and compliance:

Questions to consider:

How much time do we want to save on this workflow? How to drive efficiency on identified workflows?
What data needs to be shared, restricted? What is our Dust Data Access Policy.

Build your Dust team

Measuring value

We recommend evaluating the impact of Dust throughout its deployment:

Best practices

Measure impact and team satisfaction: Assess Dust value at both the organizational, use case levels and individual level (would you be sad if you couldn’t use Dust anymore).
Align with company’s goals: Ensure every use case tested is linked to business objectives and uses metrics that stakeholders care about.
Use 80/20 estimates: Start with rough estimates focused on key impacts to build momentum quickly.
Communicate regularly: Share learnings with leadership, set clear assumptions and share progress as more data becomes available.
Iterate and improve: Treat ROI estimation as a continuous process, making adjustments over time.

Example

Scenario

Leveraging Dust to empower your Tier 2 & 3 customer support agents with assistants connected to your company's knowledge base and historical support data, with direct context of the ticket at hand.

Baseline Situation

Support tickets per month: 2000
- Current average resolution time: 30 min
- Support agent cost: €40/hour
Support resolution costs: 2000 tickets x €40 x .5 hours = €40,000 per month
Customer churn rate due to support dissatisfaction: 5% of 1000 customers/year
- Average customer lifetime value: $50,000
Annual churn cost: 5% x 1000 customers x $50,000= €2.5 million per year

With Dust

Decreased resolution time: Able to respond to tickets twice as fast (15min)
- Reduced support cost: 2000 tickets x €40 x .25 hours = €20,000 per month
- Annual Savings = €20,000 * 12 = €240,000
Increased customer satisfaction: Better answers reduces churn rate to 3%
- Reduced churn cost: 3% x 1000 customers x $50,000= €1.5 million per year

Summary

By using Dust to empower your support teams, you can simultaneously drive:

Increased savings: Potentially save €1.7 million per through better support
Employee satisfaction: Support agents deal with happier customers so are less likely to churn
Quicker onboarding: Dust assistants help decrease ramp-up time through access to all existing knowledge and policies