Unleashing the Strategic Sage Within: How You Can Use AI to Supercharge Annual Business Planning

As artificial intelligence continues to advance at a rapid pace, forward-thinking companies are exploring ways to leverage AI to gain a competitive edge.

One compelling application is using AI to enhance the strategic planning process.

By intelligently collecting richer data and rapidly synthesizing insights, AI can help the c-suite make higher-quality strategic decisions.

The Importance of Ground Truth

At its core, effective strategic planning relies on having an accurate understanding of ground truth—what is really happening in (and around) your business, right now.

Traditionally, this has involved manually gathering data from disparate systems like financials, CRM, aggregated (though, often incomplete) analytics dashboards, and HR databases. Some companies also conduct internal Pulse surveys to capture employee perspectives.

However, these approaches often fall short in terms of the richness, freshness, and speed of the insights generated. Important knowledge remains locked in people's heads, data quickly becomes stale, and it can take weeks of analysis to unearth key takeaways.

As a result, strategic decisions are made based on an incomplete or outdated picture.

AI-Powered Data Collection

This is where AI can be a game-changer.

Using tools like AI-enhanced surveys (see: Voiceform), and automated phone interviews (e.g., via Vapi), companies can now collect significantly richer data from employees, especially customer-facing staff who have valuable frontline insights not captured in systems.

For example, after receiving an email invitation to give an AI-powered phone line a call (at his or her convenience), a sales rep could verbally share observations from recent client meetings (among other things), which get automatically transcribed and aggregated with other fresh conversation transcripts.

If you're a software company, to complement the frontline employee–mediated insights, you might also dig into recent product usage logs, e.g., events in Mixpanel, to intelligently identify power users and their key behaviors—this can stimulate additional lines of questioning or an insightful conversation with one such power user.

Rapid Insight Synthesis

The second way AI enhances strategic planning is by compressing the time needed to extract insights from raw data.

With techniques like unsupervised learning, topic modeling, and summarization, AI engines can rapidly identify patterns and distill key takeaways from large, unstructured datasets.

Short of a sophisticated prompt-chained AI pipeline, you can simply stuff the data (especially Voiceform and/or VAPI transcripts) into a new chat with Anthropic's Claude 3 Opus and ask it to give you the:

• General shape of things (a summary) and
• Interesting anomalies that deserve the attention of the group during the goal-setting process.

Instead of an analyst spending days manually tagging, coding, and graphing survey responses, you get a concise executive summary within minutes.

Of course, business planning participants can then use natural language to interactively explore the data (i.e., asking follow-up questions via a chat interface), drilling down into items of interest.

This allows decision-makers to incorporate much fresher, more comprehensive insights into strategic plans.

Better ground truth data -> higher-fidelity "maps of the territory" -> better org-wide goals.

Piloting the Approach

For companies interested in piloting an AI-enhanced strategic planning process, a reasonable timeline would be:

• Week 1: Assess current planning practices, map key decisions, and identify insight gaps, then design and implement AI-powered data collection mechanisms (surveys, interviews, etc).

• Week 2: Conduct data collection in the lead up to quarterly/annual planning and use AI to synthesize insights, delivered to execs via a traditional executive summary + chatbot on top of the core data for them to query whenever they want.
• Week 3: Hold enhanced strategy sessions (also recorded, so you can compare key assumptions and hypotheses into the next cycle's preparation by comparing them to what actually happened).
• Week 4+: Measure improvements in strategic plan quality, alignment and execution, e.g., via a rigorous OKR process.

As with any new business process, it's important to start small, move quickly, and iterate based on feedback. But, the potential upside is significant—richer insights driving clearer priorities and better decisions.

That's an edge that every executive should be eager to harness.

The rise of AI is creating compelling new opportunities to reimagine core business activities. Strategic planning is ripe for disruption.

Forward-leaning companies would be wise to explore how AI can help them chart a clearer course in an increasingly dynamic and competitive landscape.

If you enjoyed this post, you may also enjoy the recent conversation I had with strategy & OKR expert Daniel Montgomery on the topic.

And, if it stoked your curiosity, add a question in the comments below (or find time for us to chat)!