Practical Playbook for Copilots in Discovery

Discovery is often the most critical phase in managing projects or devising strategies, typically taking around 2 to 4 weeks on average to gather insights and define goals effectively. But what if your team had a copilot, an AI-driven assistant that could analyze vast swaths of data and deliver precise and actionable insights almost instantly?

Copilots, particularly in discovery phases, are transforming the way teams gather, analyze, and synthesize information. By tapping into their capabilities, businesses can not only save time but also ensure their decisions are data-driven and precise.

This playbook explores how copilots’ function in discovery, their key benefits, tips for building an effective copilot, a real-world example from Bridgenext, and actionable steps to get started.

Understanding Copilots and Their Role in Discovery

Think of a copilot as your AI-powered assistant, here to help your team process information and generate insights faster. Unlike simple automation tools, copilots take it further by synthesizing unorganized and multifaceted inputs – like documents, meeting transcripts, and presentations – into clear, actionable insights.

When applied within a discovery process, copilots help organizations address the most challenging aspect of early-phase project work: gathering and analyzing extensive data in a short timeframe.

The Key Benefits of Copilots in Discovery

Copilots offer clear and measurable benefits in discovery, from increased operational efficiency to enhancing the quality of insights. Here’s why organizations are incorporating them into their processes:

1. Accelerated data analysis
   Copilots can rapidly analyze large datasets from multiple sources (such as videos, reports, or spreadsheets), cutting down weeks of manual processing to minutes.
2. Centralized “source of truth”
   With copilots, your team gets a single, reliable repository for synthesizing information. They ensure all interpretations and insights come directly from the input data you’ve provided, so outdated or irrelevant information from external sources is excluded. This ensures your teams work with the most relevant and up-to-date data.
3. Insights without bias
   Unlike human analysts, copilots provide objective interpretations. They analyze the data as it is, eliminating the risk of human bias that can often skew findings or recommendations.
4. Continuous learning
   The more you use your copilot, the better it becomes! Copilots continually adapt, providing increasingly targeted and refined results as you engage with them.
5. Better strategies for greater impact
   With access to actionable insights generated in record time, teams can spend less time sifting through data and more time on thoughtful analysis to create impactful strategies.
6. Streamlined collaboration for more effective execution
   This shift helps teams execute projects more efficiently with smaller cross-functional teams who can collaborate seamlessly. With a shared co-pilot facilitating idea exchange, the need for lengthy presentations or summaries to share knowledge is eliminated.

Tips for Building a Highly Effective Copilot

To fully unlock the value of a copilot for discovery, you need to design your AI assistant with care. Here are some tips for creating a copilot that delivers maximum value:

1. Define clear use cases
   Start by identifying specific areas where a copilot can add value. Whether analyzing customer feedback or streamlining supply chain inefficiencies, focus on high-impact tasks.
2. Ensure input diversity
   For a copilot to provide meaningful insights, its input must reflect a variety of data formats and sources, including reports, meeting transcriptions, or operational metrics.
3. Invest in training
   Equip your copilot to understand your organization’s unique nuances, including industry-specific language, challenges, and priorities. Allow time for initial customization to align the copilot with your business requirements.
4. Regularly update data sources
   To maintain reliability, keep the copilot’s inputs current. Ensure it pulls from the latest reports, feedback, and documentation to avoid outdated recommendations.
5. Promote team collaboration
   Think of your copilot as a true team member! Keep the interaction flowing, and watch it learn, adapt, and become an essential part of your team, supercharging your discovery process.

By following these tips, you can lay the foundation for a copilot that not only supports your team but also drives meaningful results across your organization.

Real-World Success Story: Bridgenext’s Copilot for Discovery

Bridgenext recently transformed its discovery process with the implementation of a Microsoft Teams Copilot.

The copilot was tasked with analyzing a client’s vast trove of materials, including over 20 hours of meeting transcripts, reports from ERP systems, and long-term business plans. The results? It provided instantaneous insights, like pinpointing inefficiencies and identifying manual processes suitable for automation.

Key outcomes from Bridgenext’s use of copilot in discovery included:

• Accelerated analysis: The initial analysis phase was cut by 60%, giving consultants more time to focus on solution design.
• Optimized operations: The copilot identified inefficiencies in data flows and recommended automation opportunities, cutting the client’s business planning cycle from 90 days to just 45.
• Data-driven solutions: By centralizing all discovery inputs into a single source of truth, Bridgenext ensured our recommendations were backed by comprehensive and accurate data.

This case study highlights not only the efficiency gained but also the strategic advantage of adopting a copilot for early-stage processes like discovery.

How to Get Started with Your Own Copilot

Now that you’ve seen the benefits and possibilities, it’s time to take action. Here’s how you can launch your own copilot for discovery:

1. Identify your goals
   What tasks do you want your AI copilot to streamline or improve? Start small, targeting a specific process like analyzing customer feedback or synthesizing operational reports, before scaling up.
2. Choose the right platform
   Evaluate AI tools that integrate easily into your existing workflows and systems.
3. Work with experts
   Partner with consultants or AI specialists who can guide you through the setup, training, and fine-tuning to ensure your copilot aligns with your needs.
4. Train your team
   Bring everyone onboard by educating your team about the copilot’s capabilities and how to use it effectively.
5. Monitor and iterate
   Set key performance indicators (KPIs) and continuously evaluate the copilot’s performance. Use feedback to improve and refine results over time.

From Discovery to Delivery with Your AI Copilot

By leveraging AI as an always-available assistant, organizations can deliver faster, more robust insights while focusing their energy on creating impactful strategies.

At Bridgenext, we’ve seen firsthand how integrating Microsoft Teams Copilot can revolutionize the way businesses operate. From managing data to streamlining workflows, a copilot can reshape your organization and take efficiency to the next level.

Ready to explore how this could work for your team? Let’s make it happen—connect with our experts today!