Part 4 in 8 part series - Separating the Wheat from the Chaff
Turning Questions Into Predictions
Part 4 in 8 part series - Separating the Wheat from the Chaff
Author
Jonathan Neitzell
Jonathan Neitzell
Founder, Managing Partner, Anduril Partners

Part 4 of 8

Peeling Back the Veil In a moment of stark honesty, most organizations will admit they have never actually drawn out their decision process, and the few that have will tell us with some flowchart they have a process.

However, if the inputs are not touching software and creating a time series of quantified changes, the effort is incredibly prone to narrative shift, hindsight bias, and lack of objectivity. Consequently, the ability for feedback loops or incremental learning will be severely compromised. It has been said, if software is eating the world, models will run the world. For those humble, confident, and willing to be held accountable, the tailwinds of technology can harness this tremendous potential in transparency, scale, and continued improvement on behalf of your stakeholders.

Turning Questions into Predictions

One of the largest shifts we are likely to see in team discussions during the next five years is toward analytics and data-influenced decisions. To do this, we must take our qualitative, thematic questions and turn them into key performance indicators – hypotheses which can be quantified, tested, and predicted. This process entails integrating the personal experiences of business users and operators and attaching their primary metrics to data consistently available.

For the financial industry, analysts might answer questions about a company’s equity value by inferring revenue growth based on KPIs such as new customer growth, average spend per transaction, share of industry sales, and cohorts changing purchasing locations between physical and virtual storefronts. These may be seen within transaction records, email receipts, web traffic, or natural language processing queries of customer social media comments.

These discussions are often the same across corporate, private equity, and public equity uses, making a focus on defining, tracking, and predicting KPIs an increasingly universal language. Corporate intelligence and investor relations groups are likely to be a vital bridge between planning for resource allocation and explaining these key components to stakeholders.

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